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Transcript
Advances in Genetics
and Breeding of Capsicum and Eggplant
Advances in Genetics and
Breeding of Capsicum and Eggplant
Proceedings of the XIVth EUCARPIA Meeting on
Genetics and Breeding of Capsicum & Eggplant
30 August - 1 September 2010
Valencia - Spain
Editors
Jaime Prohens and Adrián Rodríguez-Burruezo
The publication of this book has been funded by Ministerio de Ciencia
e Innovación (grant reference: AGL2009-07831-E/AGR) and by Conselleria d’Educació de la Generalitat Valenciana (grant reference:
AORG/2010/014).
Editors
Jaime Prohens and Adrián Rodríguez-Burruezo
Title
Advances in Genetics and Breeding of Capsicum and Eggplant
Sub-title
Proceedings of the XIVth EUCARPIA Meeting on Genetics and Breeding of
Capsicum & Eggplant, 30 August - 1 September 2010, Valencia, Spain
Publisher
Editorial de la Universitat Politècnica de València
Camino de Vera s/n, 46022 Valencia, Spain
Tel. 96 387 70 12. Fax 96 387 79 12
Ref. 2010.2354
© Jaime Prohens and Adrián Rodríguez-Burruezo
Printed by
LAIMPRENTA CG
ISBN: 978-84-693-4139-1
Depósito Legal: V-2687-2010
XIVth EUCARPIA
Meeting on Genetics
and Breeding of
Capsicum & Eggplant
30 August - 1 September 2010
Valencia - Spain
Advances in Genetics
and Breeding of Capsicum and Eggplant
International Scientific Committee
Local Organizing Committee
Marisol Arnedo (Spain)
Paul Bosland (USA)
Marie-Christine Daunay (France)
Maria J. Díez (Spain)
Anne Frary (Turkey)
Sergio Lanteri (Italy)
Katarzyna Niemirowicz-Szczytt (Poland)
Alain Palloix (France)
Jaime Prohens (Spain)
Adrian Rodríguez-Burruezo (Spain)
Giuseppe Leonardo Rotino (Italy)
John Stommel (USA)
Roeland Voorrips (The Netherlands)
Carlos Baixauli
Jaime Cebolla
María José Díez
Álvaro Gil
Carmina Gisbert
María del Carmen González-Mas
Fernando Hernández
Francisco Javier Herraiz
Estela Moreno
Mariola Plazas
Jaime Prohens
María Dolores Raigón
Adrian Rodríguez-Burruezo
Salvador Soler
Santiago Vilanova
Major Sponsors of the XIVth EUCARPIA
Meeting on Genetics and Breeding of Capsicum & Eggplant
Ministerio de Ciencia e Innovación, Gobierno de España
Conselleria d’Educació, Generalitat Valenciana
Universitat Politècnica de València
European Association for Research on Plant Breeding
Fundación Ruralcaja
SPICY FP7 Project
Enza Zaden España
Semillas Fitó
Semillas Ramiro Arnedo
Zeta Seeds
Fundación Agroalimed
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana
28th International Horticultural Congress
Surinver
Asociación para la Promoción de la Indicación Geográfica Protegida “Berenjena de Almagro”
Sociedad Española de Ciencias Hortícolas
Sociedad Española de Genética
TABLE OF CONTENTS
Foreword ............................................................................................................... 17
INVITED CONFERENCE
An American in Spain ............................................................................................ 21
P.W. Bosland
SESSION I. DIVERSITY, CONSERVATION, AND ENHANCEMENT
OF GENETIC RESOURCES
Collection, conservation and breeding of Iranian eggplant landraces ................ 29
M. Bagheri
A MS Excel implementation of the seed viability equation for
managing gene bank collections of Solanum melongena and
Capsicum annuum ................................................................................................. 37
I.O. Daniel, M. Kruse, G. Muller, A. Börner
Phylogenetic relationships and diversity of Capsicum species in Ecuador .............. 49
V.P. Ibiza, J. Blanca, J. Cañizares, F. Nuez
Evaluation of the National collection of eggplant (Solanum
melongena L.) in Bulgarian conditions ................................................................. 51
L. Krasteva, N. Velcheva, K. Uzundzhalieva
Taxonomy and ethno-botanical study of Indonesian’s eggplants
and their wild relatives ........................................................................................ 57
H. Kurniawan, Hartati, Asadi, C. Mariani, G. van der Weerden
Morphological and molecular characterization for the conservation
and protection of Listada de Gandía eggplant .................................................... 59
J.E. Muñoz-Falcón, J. Prohens, S. Vilanova, F. Nuez
9
Use of Capsicum and eggplant resources for practical classes
of Genetics and Plant Breeding courses ............................................................... 67
J. Prohens, A. Rodríguez-Burruezo, C. Gisbert, S. Soler, F.J. Herraiz,
M. Plazas, A. Fita
Public and commercial collections of heirloom eggplant and pepper:
a case study ........................................................................................................... 77
G. Roch, J.P. Bouchet, A.M. Sage-Palloix, M.C. Daunay
Taxonomic relationships of eggplant wild relatives in series
Incaniformia Bitter ............................................................................................... 89
John Samuels
Use of morphological description and DNA analysis for the detection
of duplicities within the Czech germplasm collection of pepper ....................... 97
H. Stavělíková, P. Hanáček, T. Vyhnánek
Determination of genetic variation among Turkish eggplant
(Solanum melongena L.) varieties by AFLP analysis ............................................ 107
Y. Tumbilen, A. Frary, S. Doganlar
SESSION II. BREEDING FOR RESISTANCE TO BIOTIC
AND ABIOTIC STRESSES
CMS-Rf genotype of newly-discovered sources of resistance to
bacterial spot in pepper (Capsicum annuum L.) .................................................. 111
J.H. Ahn, B.S. Kim
Epistasis and aggressiveness in resistance of pepper (Capsicum
annuum L.) to Phytophthora nicotianae .............................................................. 115
F. Bnejdi, S. Morad, A.M. Bechir, M. El Gazzah
Introgression of Phytophthora capsici root rot resistance from
Capsicum annuum into C. chinense ...................................................................... 121
C.S. da Costa Ribeiro, P.W. Bosland
Durable management of root-knot nematodes Meloidogyne spp.
in pepper (Capsicum annuum) using resistant genotypes ................................... 125
C. Djian-Caporalino, A. Palloix, A. Fazari, N. Marteu, M. Bongiovanni,
M., A.M. Sage-Palloix, G. Nemouchi, P. Castagnone-Sereno
Evaluation of root knot nematode resistance in Capsicum annuum L.
and related species ............................................................................................... 127
C. Gisbert, A. Rodríguez-Burruezo, F. Nuez
10
Compatibility assessment in tomato and common eggplant grafted
onto gboma and scarlet eggplants ........................................................................ 129
C. Gisbert, J. Prohens, C. Trujillo, F. Nuez
Genetics of resistance of the Kahramanmaraş pepper KM2-11
genotype to Phytophthora capsici isolates ......................................................... 135
M. Gocmen, K. Abak
Development of sweet pepper grafting in Brazil ................................................. 143
R. Goto, H. S. Santos, R.K. Kobori, R. Braga
Resistance of Indonesian Solanum melongena and wild relatives
to Ralstonia solanacearum . ................................................................................. 145
Hartati, H. Kurniawan, E. Sudarmonowati, G. van der Weerden, T. Mariani
Molecular mapping of a CMV resistance gene in peppers
(Capsicum annuum L.) .......................................................................................... 147
W.H. Kang, H. N. Huy, H.-B. Yang, S.H. Jo, D. Choi, B.C. Kang
Gall insects damaging eggplant and bell peppers in South India ......................... 153
N.K. Krishna Kumar, D.K. Nagaraju, C.A. Virakthamath, R. Ashokan,
H.R. Ranganath, K.N. Chandrashekara, K.B. Rebijith, T.H. Singh
Economics of management of eggplant shoot and fruit borer (ESFB),
Leucinodes orbonalis Guenee raised under low cost net house ......................... 171
N.K. Krishna Kumar, D. Sreenivasa Murthy, H.R. Ranganath,
P.N. Krishnamoorthy, S. Saroja
Evaluation of resistance of pepper varieties from the Basque
Country to Phytophthora cryptogea .................................................................... 179
S. Larregla, E. Pérez, B. Juaristi, M. Nuñez
Development of test methods and screening for resistance to thrips
in Capsicum species .............................................................................................. 181
A. Maharijaya, B. Vosman, G. Steenhuis-Broers, R.G.F. Visser, R.E. Voorrips
Breeding for resistance and pathogenicity of chili anthracnose ......................... 189
O. Mongkolporn, P.W.J. Taylor, P. Temiyakul
New source of resistance to Thai isolate of Cucumber mosaic virus
and Chilli veinal mottle virus in Capsicum germplasm collection ...................... 191
S. Patarapuwadol, W. Sompratoom, K. Sitadhani, S. Wasee
Response of pepper rootstocks for resistance to Meloidogyne
incognita populations in greenhouses of Southeast Spanish . ............................. 199
C. Ros, C. Martínez, M.M. Guerrero, C.M. Lacasa, V. Martínez, J.L. Cenis,
A. Cano, A. Bello, A. Lacasa
11
CM334 rootstock improves the resistance of grafted chili pepper to
root necrosis and plant wilting caused by Phytophthora nicotianae ................. 211
M. Saadoun, M.B. Allagui
Aggressiveness and genetic diversity of Phytophthora capsici
isolates infecting pepper ...................................................................................... 213
P. Sánchez-Torres, C. Gisbert, F. Nuez
New resistant source to viruses, particularly Tomato leaf curl Joydebpur
virus, infecting chilli in India and its utilization in hybrid development ........... 221
D. Singh, R.K. Dhall
Viruses on Capsicum plants in the Czech Republic-challenge
to resistance breeders .......................................................................................... 225
J. Svoboda
Interaction of the gds and Bs-2 gene during the defense against
the pepper pathogen Xanthomonas vesicatoria bacterium ............................... 231
E. Szarka, G. Csillery, and J. Szarka
Relationship between pepper flower abortion and enzymes activity
under low night temperature ............................................................................... 233
N. Tarchoun, S. Ben Mansour, S. Rezgui, A. Mougou
Biochemical and molecular analyses of Rfo-sa1 resistant eggplant
interaction with Fusarium oxysporum f. sp. melongenae and/or
Verticillium dahliae .............................................................................................. 241
L. Toppino, G.L. Rotino, G. Francese, A. D’Alessandro, G.P. Vale’, N. Acciarri,
V. Barbierato, P. Rinaldi, G. Caponetto, G. Mennella
SESSION III. BREEDING FOR QUALITY
Characterization of volatile and non-volatile compounds of fresh
pepper (Capsicum annuum) .................................................................................. 251
P.M. Eggink, J.P.W. Haanstra, Y. Tikunov, A.G. Bovy, R.G.F. Visser
The assessment of variability in fruits of local pepper
(Capsicum annuum L.) from individual plants ..................................................... 261
K. Lahbib, M. El Gazzah
Effect of storage on stability of capsaicin and colour content in chilli
(Capsicum annuum L.) .......................................................................................... 267
J. Pandey, J. Singh, R. Kumar, K. Srivastava, S. Kumar, M. Singh, B. Singh
QTLs for capsaicinoids content in Capsicum . ...................................................... 273
I. Paran, T. Akler, Y. Borovsky
12
Occurrence and genotypic differences of flavour-active volatile
3-isobutyl-2-methoxypyrazine among accessions of Jalapeno pepper ............... 279
A. Rodríguez-Burruezo, A. Fita, O. Holguin, M. O´Connell, P.W. Bosland
A versatile PCR marker for pungency trait in Capsicum spp. .............................. 281
M.J. Rodríguez-Maza, A. Garcés-Claver, M.S. Arnedo-Andrés
Traditional eggplant varieties and their hybrids:
Vitamin C characterization ................................................................................... 289
R. San José, M.C. Sánchez, M. Cámara, J. Prohens, F. Nuez
Exploring the variation of health-related compounds in pepper ........................ 291
Wahyuni, A.R. Ballester, E. Sudarmonowati, R.J. Bino, A.G. Bovy
SESSION IV. BREEDING FOR YIELD
1. SPICY PROJECT SYMPOSIUM
Exploratory QTL analyses of some pepper physiological traits
in two environments ............................................................................................. 295
N.A. Alimi, M.C.A.M. Bink, A. Dieleman, A.M. Sage-Palloix, R.E. Voorrips,
V. Lefebvre, A. Palloix , F.A. van Eeuwijk
Providing genomic tools to increase the efficiency of molecular
breeding for complex traits in pepper ................................................................. 307
M. Nicolaï, A.M. Sage-Palloix, G. Nemouchi, B. Savio, A. Vercauteren,
M. Vuylsteke, V. Lefebvre, A. Palloix
Crop growth models for the -omics era: the EU-SPICY project ........................... 315
R.E. Voorrips, A. Palloix, A. Dieleman, M. Bink, E. Heuvelink, G. van der Heijden,
M. Vuylsteke, C. Glasbey, A. Barócsi, J. Magán, F. van Eeuwijk
2. GENERAL CONTRIBUTIONS
Heterosis in relation to multivariate genetic divergence in eggplant
(Solanum melongena) . .......................................................................................... 325
P. Hazra, P.K. Sahu, U. Roy, R. Dutta, T. Roy, A. Chattopadhyay
Per se performance for fruit yield of green chilli varieties ................................ 335
R.M. Hosamani, B.C. Patil, P.S. Ajjapplavar
Genetic and phenotypic correlations between productivity
components of sweet pepper ............................................................................... 337
L. Khotyleva, L. Tarutina, L. Mishin, M. Shapturenko
13
Assessing genetic variation by thermogravimetric analysis to
predict heterosis of sweet pepper lines .............................................................. 339
M. Shapturenko, L. Tarutina, L. Mishin, L. Shostak, L. Khotyleva
Reconstruction of regulatory feedback of global gene network
of economically valuable characters of Capsicum annuum L. ............................. 349
O.O. Timina, A.S. Ryabova, O.Yu. Timin
SESSION V. DEVELOPMENT OF MOLECULAR AND OTHER
BIOTECHNOLOGICAL TOOLS
Construction of an intra-specific linkage map in eggplant
(Solanum melongena L.) ....................................................................................... 359
L. Barchi, S. Lanteri, E. Portis, A. Stagel, L. Toppino, G.P. Valè, N. Acciarri,
G.L. Rotino
Identification of molecular markers linked to ms8 gene in sweet
pepper (Capsicum annuum L.) .............................................................................. 367
G. Bartoszewski, I. Stepien, P. Gawronski, C. Waszczak, V. Lefebvre, A. Palloix,
A. Kilian, K. Niemirowicz-Szczytt
Improvement in doubled haploids production through in vitro
culture of isolated eggplant microspores ............................................................. 369
P. Corral-Martínez, J.M. Seguí-Simarro
Development of an integrated linkage map using genomic SSR
and gene-based SNPs markers in eggplant ........................................................... 375
H. Fukuoka, K. Miyatake, T. Nunome, S. Negoro, H. Yamaguchi, A. Ohyama
New perspective: microspore culture as new tool in paprika breeding ............. 377
A. Gémes Juhász, Cs. Lantos, J. Pauk
SSR Markers Derived from EST Database in Capsicum spp. ................................. 383
H. Huang, Z. Zhang, S. Mao, L. Wang, B. Zhang
Graft-induced genetic variation of fruit color in the progenies
derived from interspecific-grafting in chili pepper ............................................. 391
M. Ishimori, C. Yamaguchi, M. Khalaj Amirhosseini, H. Miyazawa,
L. Yu, C.R. Zhao, Y. Hirata
Evaluation of response to in vitro embryo rescue in Capsicum spp. ................. 397
J.P. Manzur, J. Herraiz, A. Rodríguez-Burruezo, F. Nuez
CDKA gene expression related to anatomical events during in vitro
regeneration from pepper (Capsicum annuum L.) cotyledon explants . ............. 403
N. Mezghani, R. Gargouri-Bouzid, J.F. Laliberté, N. Tarchoun, A. Jemmali
14
Confirmation of detected QTLs for parthenocarpy in eggplant using
chromosome segment substitution lines .............................................................. 409
K. Miyatake, T. Saito, S. Negoro, H. Yamaguchi, T. Nunome, A. Ohyama, H. Fukuoka
Establishment of isolated microspore cultures in pepper of the
California and Lamuyo types ................................................................................ 411
V. Parra-Vega, N. Palacios, P. Corral-Martínez, J.M. Seguí-Simarro
In vitro regeneration in chilli (Capsicum annuum L.) and biohardening of plantlets using arbuscular mycorrhizal fungi (AMF) ...................... 417
J.K. Ranjan, A.K. Chakrabarti, S.K. Singh, Pragya
Production and analysis of interspecific hybrids among four
species of the genus Capsicum ............................................................................. 427
T.P. Suprunova, E.A. Dzhos, O.N. Pishnaya, N.A. Shmikova, M.I. Mamedov
Development of a linkage map of eggplant based on a S. incanum x
S. melongena backcross generation ..................................................................... 435
S. Vilanova, M. Blasco, M. Hurtado, J.E. Muñoz-Falcón, J. Prohens, F. Nuez
Graft transformation mechanism in eggplant and chili pepper plants ................ 441
L. Yu, Y. Hirata, M. Ishimori, C. Yamaguchi, M. Khalaj Amirhosseini,
C.R. Zhao, N. Yagishita
SESSION VI. NEW BREEDING OBJECTIVES, EVALUATION AND RELEASE OF
BREEDING MATERIALS AND CULTIVARS, AND SEED PRODUCTION
Assessment of new Italian-type pepper cultivars and evaluation
of TSWV tolerant cultivars .................................................................................... 449
C. Baixauli, A. Giner, J. M. Aguilar, A. Núñez, I. Nájera, F. Juan
‘NuMex Heritage 6-4’ and ‘NuMex Heritage Big Jim’:
Reviving Traditional Flavors ................................................................................. 459
D. Coon, P.W. Bosland
Status of male sterility in chilli for hybrid development in India ....................... 463
R.K. Dhall, D. Singh
Studies on the effect of extended pollination time on fruit set and
seed quality and storage temperature on viability and storability
of pollen of eggplant (Solanum melongena L.) .................................................... 473
H.H. Fonseka, K. Warnakulasooriya, Ramya Fonseka, G. Senanayake
Evaluation of male-sterile lines for breeding sweet pepper
hybrid cultivars ..................................................................................................... 483
E. Horodecka, K. Tkacz, J. Borowiak
15
Byadagi chilli improvement: status, challenges and future ................................ 485
R.M. Hosamani
Fruit and seed development in aubergine cv. Tsakoniki in relation
to the fruit load on the plant ............................................................................... 487
E.M. Khah, S.A. Petropoulos, L. Myzithras, H.C. Passam
Trait stability of sweet pepper inbred lines in three different
environments ........................................................................................................ 493
A. Korzeniewska, M. Romac, K. Niemirowicz-Szczytt
Rootstocks for pepper cultivars in greenhouses of Southeast Spain .................. 501
C.M. Lacasa, C. Ros, M.M. Guerrero, V. Martínez, M.A. Martínez, A. Lacasa
Development and characterization of a Capsicum rootstock cultivar,
‘Dai-Power’, that is resistant to Phytophthora blight, bacterial wilt,
and the pepper mild mottle virus ........................................................................ 503
H. Matsunaga, A. Saito, T. Saito
New uses for an old landrace: potential for the fresh market
of the pickling “Almagro” eggplant ...................................................................... 511
J. Prohens, J.E. Muñoz-Falcón, M. Blasco, F. Ribas, A. Castro, F. Nuez
Development of Solanum melongena breeding lines as resistant
rootstocks to Verticillium, bacterial, and Fusarium wilts ................................... 513
T. Saito, H. Matsunaga, A. Saito
Ornamental peppers: breeding for a high value market ..................................... 521
J.R. Stommel
Breeding of multiple disease resistant rootstock variety to
Phytophthora blight and bacterial wilt in pepper (Capsicum annuum) .............. 529
E.Y. Yang, M.C. Cho, S.Y. Chae, Y.A. Jang, H.J. Lee, H.S. Choi,
H.B. Jeong, S.R. Cheong
INDEX OF AUTHORS ............................................................................................... 537
16
FOREWORD
This book contains the contributions presented at the XIVth EUCARPIA Meeting on Genetics
and Breeding of Capsicum & Eggplant, held in Valencia at Universidad Politécnica de
Valencia from August 30 to September 1, 2010. The full papers and abstracts included
in the book cover a wide range of topics related to the genetics and breeding of peppers
and eggplant. For the purposes of organization, they have been divided into six sessions
(I. Diversity, conservation, and enhancement of genetic resources; II. Breeding for re­
sistance to biotic and abiotic stresses; III. Breeding for quality; IV. Breeding for yield;
V. Development of molecular and other biotechnological tools; and, VI. New breeding
objectives, evaluation and release of breeding material and cultivars, and seed production)
plus an invited conference. Within each session, contributions have been alphabetically
ordered by the surname of the first author.
We thank contributing authors for preparing and submitting manuscripts to this Meeting.
We also wish to give thanks to the members of the scientific committee for the work
and time devoted to review the manuscripts in order to ensure a standard of scientific
quality. Members of the organizing committee have also done an outstanding work in
order to editing contributions into a uniform format.
Thanks are also given to all institutions and companies that have sponsored this Meeting.
We hope that this book, which contains relevant information on the genetics and bree­­
ding of peppers and eggplant, will contribute to future advances in this subject. We look
forward to meeting you again in the next EUCARPIA Meeting on Genetics and Breeding
of Capsicum and Eggplant.
Valencia, 2010
Jaime Prohens and Adrian Rodríguez Burruezo
Conveners of the XIVth EUCARPIA Meeting on
Genetics and Breeding of Capsicum and Eggplant
17
INVITED
CONFERENCE
////////////////////////////////////////////////////////
///////////////////////////////////////
/////////////////////
Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
An American in Spain
P.W. Bosland
Department of Plant and Environmental Science, New Mexico State University,
Las Cruces, NM 88003-8003, USA. Contact: [email protected]
Abstract
Spain and Capsicum have been closely associated with one another ever since Christopher
Columbus’ first voyage to the Western Hemisphere. On that voyage he brought to Spain the
“pepper more pungent than that of the Caucasus”. He could never have imagined the impact
this plant would have on markets around the world. Capsicum is one of the most versatile
spices/vegetables used in today’s cooking. Historians believe capsicums have been a stable
diet of humans since 7,500 B.C. In 1699, the bell pepper was first mentioned and continues
to be an important vegetable. In the 21st century, wild species of Capsicum are still being
discovered, while at the same time great progress in Capsicum genomics is occurring. Most
cultures throughout the world have dishes that include capsicums as an ingredient, and the
capsicums of Spain are valued among chefs internationally for supplying a robust flavor to
their dishes.
Keywords: disease resistance, genome, landrace, no-heat, ornamental, spice, vegetable,
wild species.
Introduction
Supported by a fleet of Spanish ships, Christopher Columbus found a land with “Indians”
and spices in 1492. Not only did Columbus misname the Indians, he also mistook Capsicum
for black pepper (Piper), thus giving Capsicum the inaccurate name “pimiento”, from the
Spanish term for black pepper “pimienta”. Columbus’ introduction of this American (spice)
to Spain changed the world forever. Within a hundred years after Columbus brought it to
Spain, Capsicum had circumnavigated the globe and spiced up numerous cuisines along the
way. Often mistakenly thought to be of African or Indian origin, chile peppers are absolutely
American and are among one of the earliest plants domesticated by humans in the Western
Hemisphere. Today, it is hard to imagine modern world cuisines without chile peppers.
They have come to dominate the world hot spice trade and are grown everywhere from
the tropics to the temperate regions of the globe. The genetic recessive no-heat forms
have become an important international vegetable crop. Capsicums continue to be a
vibrant and dynamic crop, adapting and changing as humans envision new uses for it.
21
Advances in Genetics and Breeding of Capsicum and Eggplant
Origin
The exact mouth-burning moment when chile peppers first spiced up the palates of
early Americans is a matter of speculation. The American botanist H. Eshbaugh speculates
that Bolivia is the nuclear center of Capsicum and the origin of the domesticated taxa
can ultimately be traced back to this area. However, he does not imply that each of the
domesticated species arose in Bolivia. Evidence supports a Mexican/Central America
origin of domesticated C. annuum while the other domesticated species may have arisen
in South America. Currently, 32 species are recognized in the genus Capsicum. These
undomesticated species can still be found growing wild in various locations in South
America, with the highest species diversity in Brazil. In fact, three new species, Capsi­
cum pereirae, C. friburgense, and C. hunzikerianum, were described in 2005 from
eastern coastal Brazil. This area of Brazil, known as the Atlantic rainforest, is one of the
most threatened regions in the world with less than seven percent of the original forest
area remaining. It is still among one of the most biologically rich and diverse forests in
the world, containing a high number of endangered species that can be found nowhere
else including these three Capsicum species. Collecting all varieties of Capsicum may
sound easy but it is proving to be increasingly difficult because its natural habitat is
seriously threatened by tropical deforestation. While collecting genetic diversity is an
ongoing task, it may be impossible for a complete collection of all Capsicum species
ever to be gathered.
Birds dispersed the wild chile peppers from South America all the way to the southern
regions of the U.S.A. It was the ancient humans of the Western Hemisphere who took the
wild chile pepper and domesticated five different species, C. annuum, C. baccatum, C.
chinense, C. frutescens, and C. pubescens. From those five domesticated species, humans
have selected for thousands of various cultivated types seen around the world today,
including vegetable, spice, and colorful ornamental peppers.
Scientists at Smithsonian’s National Museum of Natural History have discovered evidence
in the form of microscopic starch grains that when linked with archaeological stone
tools, revealed chile pepper was being commonly used 6,500 years ago. Prehistoric
people, from the Bahamas to Peru, were using chile peppers in a variety of foods as a
way to enhance the flavor of maize and manioc. This discovery is revealing evidence of
a complex cuisine at a very early time in the Americas.
The spread of chile peppers throughout the world during the 500 years since Columbus’
discovery is truly a phenomenon. Food historians believe that monks at the Monastery of
Guadalupe in Extremadura, Spain, were the first Europeans to discover the flavor and
heat of chile peppers by crushing them and adding them to their soups. They also believe
that chile peppers were initially grown in monasteries and the seeds were spread
throughout Spain and Europe first by traveling monks and then by Spanish and Portuguese
traders, who introduced them into Africa, India, and Asia in the 16th century via trade
routes. In the 16th century the celebrated Indian musician Purandarasa described chile
peppers in lyrics as a comfort to the poor and as a great flavor enhancer. Chile peppers
are known to have reached Szechuan and Hunan in China by the middle of the 16th
century, probably via caravan routes from India through Burma. It is assumed that chile
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Advances in Genetics and Breeding of Capsicum and Eggplant
peppers were readily incorporated into many of these international cuisines because
people were already familiar with hot and spicy flavors.
Domestication
Domestication of Capsicum probably occurred much like the domestication of other crops.
Ancient people grew wild plants, and then selected seeds from preferred plants to sow the
next season. Over many years, this gave rise to plants with bigger fruit and a variety of
different colors, shapes, and flavors. Today’s plant breeders are using similar techniques
to create new cultivars. The most widely utilized and the most important commercial
domesticated species on a global level is C. annuum var. annuum. It is used fresh or dried,
whole or ground, and alone or in combination with other flavoring agents.
Recently, crop landraces have become more important as regional foods garner greater
attention in the media. Landraces are domesticated plants adapted to the natural and
cultural environment in which they live or originate. Local climate and soil conditions
favor specifically adapted accessions. These landraces are important genetic resources
because they have unique gene pools and serve as important reservoirs of genetic diversity
for breeding and conserving biodiversity. Landraces are often more tasty, having been
selected by local farmers for flavor as well as adaptability, and have become culinary
delights to chile pepper connoisseurs all over the world. There are some very well known
examples of Capsicum landraces. Spanish examples include the “pimientos de Padron”
and the “pimientos del piquillo.” Italy has the “Cuneo” and “Peperone di Senise” from
the Piedmont and Basilicata regions, respectively, and in northern New Mexico, in the
U.S.A, “Chimayo” is famous. The world’s most famous landrace may well be the Bhut
Jolokia from Assam, India, and its close sister the Naga Jolokia from Nagaland, India. The
Bhut Jolokia is recognized as the world’s hottest chile pepper measuring more than one
million Scoville Heat Units. This landrace chile pepper was found to be an interspecific
hybrid through DNA testing. The molecular markers indicated that at some point the
mainly C. chinense landrace had hybridized with C. frutescens. From my own travels and
genetic studies, I have found such species mixes are not uncommon. Many “kitchen
gardens” in South America have interspecific hybrids among the species, C. annuum, C.
frutescens, and C. chinense. Insects cross-pollinate the plants in the garden, and when
the seeds are saved and planted, the “cooks” select the chile peppers that are perfect
for their dishes. In Assam, plants of C. chinense and C. frutescens have been grown near
each other for decades, allowing for possible hybridization between them. Quite possibly,
local farmers knowingly selected for a higher heat chile pepper, eventually leading to the
ultra-hot Bhut Jolokia.
Plant breeders are always looking for ways to improve capsicums to meet user preferences,
and new varieties are bred all the time. For a classic example, look at the common bell
pepper. Starting with the wild chiltepin no larger than a garden pea, humans have selected
for mutations that have made the fruit bigger, square shaped, heat-less, and in a variety
of colors. In the United States, the consumption of high-quality red, orange, and yellow
bell peppers has been increasing dramatically during the past two decades. To satisfy this
demand, Spanish and Dutch greenhouse operations export high-quality colored bell pe­
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Advances in Genetics and Breeding of Capsicum and Eggplant
ppers to the U.S.A. Greenhouses help to provide a quality and controlled environment for
the production of colored bell peppers. Greenhouse production system differs greatly
from the traditional field pepper cultivation system. In greenhouses, the Capsicum plants
need to be adapted to grow hydroponically in a soilless medium with fertigation. Instead
of bushy compact plants as is grown in the open field, these greenhouse cultivars have
indeterminate growth allowing them to be trained to grow upwards toward the greenhouse
roof along a string. To meet these novel conditions, plant breeders have been very busy.
Ornamental chile plants are saved by humans for their unusual fruit shapes, colored
foliage and bright colorful fruits. ‘NuMex Twilight,’ an ornamental plant with four different
colored fruits on a single plant at the same time, was originally a landrace from Mexico.
After selection for a more compact plant habit, the ornamental cultivar was released.
Ornamental chile peppers are normally thought of as a pot plant or garden shrub, but a
new class of ornamental chile peppers appearing in the marketplace is for florist use.
These cultivars are selected for long strong stems and fruit that is retained after maturing.
These cultivars are used as a “cut flower” would be used in the floral industry.
An ongoing challenge in chile pepper breeding is disease resistance. The continuous battle
to provide resistant cultivars to growers is an arduous task with new pathogens occurring,
and new strains of current pathogens constantly forming. One of the most destructive
pathogens on a global basis is Phytophthora capsici. Phytophthora blight has become one
of the most serious threats to production of Capsicum worldwide. Since first described by
Leonian on chile peppers in New Mexico in 1922, it has become a pathogen of international
economic importance. To date, the best source of resistance to P. capsici is Criollo de
Morelos-334, a landrace from Morelos, Mexico. It has shown resistance when challenged
by every known isolate in the world.
Capsicum genetics and breeding are evolving toward a genomics approach, whether it is
marker-assisted selection, comparative plant genomics, sequencing the complete
genome, or genetic transformation. These tools will enable faster and more effective
breeding and/or evaluation of genetic diversity within the Capsicum genus. Capsicum is
an extremely difficult recalcitrant species with respect to in-vitro regeneration and
genetic transformation. Sporadically, there are reports of success with transformation,
but a standard and efficient procedure is still lacking. It is likely that sequencing of the
Capsicum genome will be a major activity in the very near future. With the tomato
genome already sequenced, it can be used to facilitate the sequencing of the Capsicum
genome. The tomato and Capsicum genomes share 35 conserved syntenic segments
within which gene/marker order are well preserved, providing a reference for anchoring
the genomic information of Capsicum. Once genes underlying individual traits are known,
the basis for disease resistance and stress tolerance is likely to emerge as it has in model
organisms, allowing more precise diagnosis in breeding programs as well as genetic
modification. The sequence can also be used to detect epigenetic, as well as genetic
variation. Although genomics can provide a roadmap for the next generation of Capsicum
breeding, it cannot replace the geneticist or the plant breeder. What it can do is open
new areas of research untouchable by classical plant breeding.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Conclusion
Our host country, Spain, has a wonderful history and culinary use associated with
Capsicum. As mentioned earlier several famous landraces including pimientos del
piquillo, pimientos de padrón, and pimientos morrones are quite popular and continue
to be grown in Spain. Capsicum’s sister Solanaceae, eggplant, has its own international
pedigree, and it is appropriate that eggplant shares the stage with Capsicum. The 14th
EUCARPIA Meeting on Genetics and Breeding of Capsicum and Eggplant promises to be
much more than just a meeting. The knowledge shared with our colleagues and the
opportunity to learn about the latest research from some of the most highly respected
experts in Capsicum and eggplant genetics and breeding is invaluable. The possibility for
exchanging ideas and networking is incomparable. So, for this American in Spain I look
forward to the talks, tours, and comradery this meeting will provide.
25
SESSION I.
DIVERSITY, CONSERVATION,
AND ENHANCEMENT OF GENETIC
RESOURCES
/////////////////////////////////////
/////////////////////////////////////////////
////////////////
Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Collection, conservation and breeding of Iranian eggplant landraces
M. Bagheri
Vegetable & Irrigated Pulses Research Department, Seed & Plant Improvement Institute (SPII),
Fahmideh Blvd., Karaj, Tehran, Iran. Contact: [email protected],[email protected]
Abstract
Eggplant (Solanum melongena L.) is an important vegetable in Iran. The first diversity
center of eggplant is India and the second center is China. Iran is located in the diversity
zone of eggplant and there are some eggplant landraces in Iran. Study on breeding of
Iranian eggplant isn’t very old and have been started since 2006 by collecting of landraces
from different locals of Iran. 11 major landraces (e.g. Varamin, Neishabur, Mazandaran,
Dezful, Yazd, Shendabad, Jahrom, Esfahan, Lorestan, Borazjan and Bandarabas) have been
collected by author already. We have conserved these landraces by planting in isolated
plots, extracting seeds, and storing the seeds in cold room annually. There is a big genetic
diversity within and among these landraces, that’s why we could extract good lines of
them. Breeding of these landraces was conducted via pure line selection method in 3 years.
In the first year, 500 plants of each landrace were planted in the field and some plants of
every landrace were selected with respect to quantitative and qualtitative traits. In year
two, selected plants of the first year (as treatment) and their landraces (as control) were
planted in an augment design and we selected 35 better lines base on the yield and quality
of fruits. In third year, selected lines of 2nd year along a control were planted in a randomized
complete block design with 3 replications. Finally, 23 better lines with best quality and
highest yield were selected from aforesaid landraces.
Keywords: Solanum melongena, Landrace, breeding, improvement, line, yield, qualitative
traits, quantitative traits
Introduction
Eggplant (Solanum melongena L.) is an important vegetable in Iran. The first diversity
center of eggplant is India and the second center is China (Kallo and Bergh, 1993). Iran
is located in the diversity zone of eggplant and there are some eggplant landraces in Iran
(Hari, 2003). According to FAO (2007) Iran by production of 125,000 ton is the 13th country
in world in eggplant production. Study on breeding of Iranian eggplant isn’t very old and
have been started since 2006 by collecting of landraces from different localities of Iran
(Bagheri, 2009). According to IBPGR (1985), various complexes of eggplant landraces
were collected from Nepal, Syria, Sudan, and Spain and so on, and it seems that some
countries as Iran, Pakistan and Iraq can be in this geographic chain, and existence of
local landraces in these areas is possible. Eggplant landraces are similar to landraces of
other partially self pollinated crops and can be submitted to selection by choosing better
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Advances in Genetics and Breeding of Capsicum and Eggplant
plants within the available diversity. According to Harlan (1975), a landrace is the
complex of different genotypes that produced by natural and artificial selection in an
environment. Hari (2003) advised pure line selection method to get good lines in the
eggplant landraces collected from farmers’ fields.
Material and methods
This work was conducted in agriculture center of Varamin, Vegetable and Irrigated
Pulses Research Department, Seed and Plant Improvement Institute (SPII) of Iran since
2006 to 2010.
Eleven eggplant landraces were collected from farmers’ fields across Iran. These
landraces have being planted by farmers for a long time. For this purpose, we traveled
to different locals of Iran and visited each area personally. Every landrace is as popular
cultivar in its region. These landraces are: Varamin, Neishabur, Mazandaran, Dezful,
Yazd, Shendabad, Jahrom, Esfahan, Lorestan, Borazjan and Bandarabas. We have conser­
ved these germplasms by planting 500 plant of each landrace in the isolated plots,
extracting seeds, and storing the seeds in cold room annually. The isolation distance
between every planting is 200 meters. To have good quality seeds, the first setting fruit
were harvested and discarded. We allowed the next fruits to get mature completely and
their color changed to yellow and brown. Then we harvested the fruits and after about
2 weeks we extracted seeds, dried them and stored them in cold rooms.
Genetic diversity of these landraces was evaluated in a randomized complete block
design with 3 replications. Each plot had 30 plants, planted in three rows of 10 m length.
Ten random plants of each plot (in total, 30 plants of each treatment) were studied
about diversity.
Breeding of these landraces was conducted via pure line selection method throughout 3
years. In the first year, we sowed enough seeds of each landrace in plastic greenhouse
and about two months later, when ready, 500 plants of every landrace were transplanted
to the major field. For the next step, 60 good figure plants of each landrace were
selected and some traits of these single plants were recorded during the cultivation
season such as: plant height at the time of flowering, fruit number, fruit length, fruit
diameter, fruit shape, fruit skin color, fruit weight, marketable fruit yield of each plant,
amount of seed per fruit, and days to fruit setting. Finally, with respect to the afore
mentioned traits, the best plants were selected and we extracted their seeds and stored
them for next years.
In year 2, the progenies (lines) of the first year selected plants (treatment) and their
landraces (control) were planted in two separate trials in two aside fields; in one trial
we planted the selected material of 5 landraces (Varamin, Neishabur, Mazandaran,
Dezful and Bandarabas) in an augmented design (Federer, 1956; Yazdi Samadi et al.,
1988) with 6 replications (controls were replicated and there is no replication for
treatments in the augmented design). Each plot had 10 plants, planted in one row of 10
m length. In the other one, we planted the selected material plants of the other landraces
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Advances in Genetics and Breeding of Capsicum and Eggplant
(Yazd, Shendabad, Jahrom, Borazjan, Lorestan and Esfahan) in another augmented
design with 4 replications. Similar to the first trial, there is no replication for lines and
each plot had 10 plants, planted in one row of 10 m length. We selected the better
progenies on the basis of the yield and quality of fruits. Yield of each progeny was
recorded at each harvest. Furthermore, we ranked the progenies along a scale of 1 to 9
on the basis of the quality of fruits and plants appearance. At the end of second year, we
selected the better progenies.
All selected progenies of the 2 trials, as well as the control treatment (Varamin landrace
as popular cultivar of study region) were planted in a randomized complete block design
with 3 replications in the third year of the experiment. Each plot consisted of 3 rows of
10 meter length. Distances between plants along the row, between plots and between
blocks were 1.5, 3, and 3 m respectively. We recorded the marketable yield of the plots
throughout the harvest period and analyzed it by using MSTATC software.
Results and discussion
Study of genetic diversity showed a big variation within and between these landraces,
that’s why, we could extract good lines of them. Amount of genetic diversity in each
landrace was different from others (results not published). As for the results, we started
breeding program on the landraces via pure line selection for 3 years.
Year 1
At the end of the first year, with respect to quantitative and qualitative traits of single
plants, 85 plants were selected from all landraces. Number of selected plants from each
landrace is 16, 8, 13, 7, 4, 8, 8, 8, 6, 4, and 2 from Varamin, Neishabur, Dezful, Mazan­da­
ran, Bandarabas, Esfahan, Lorestan, Shendabad, Yazd, Borazjan and Jahrom, respectively,
i.e. 84 plants in total. The difference of the number of selected plants from one landrace
to another is due to the differences of genetic diversity in each landrace and the variation
of the landraces for quantitative and qualitative traits. The landraces which have more
selected plants have more diversity and better traits than the others. Selected plants of
the landraces are as follows:
—Varamin (V): V9, V10, V17, V23, V24, V26, V35, V36, V38, V44, V46, V48, V50, V56,
V57, V61
—Neishabur (N): N2, N12, N19, N29, N46, N53, N60, N61
—Dezful (D): D1, D7, D8, D11, D13, D15, D22, D23, D35, D40, D46, D53, D61
—Mazandaran (M): M9, M15, M18, M24, M45, M60, M61
—Bandarabas (B); B5, B29, B60, B61
—Esfahan (E): E2, E6, E8, E15, E17, E28, E29, E30
—Lorestan (L): L1, L2, L3, L14, L18, L27, L29, L30
—Shendabad (SH): SH2. SH5, SH9, SH10, SH12, SH16, SH21, SH26
—Yazd (Y): Y1, Y3, Y6, Y9, Y22, Y23
—Borazjan (BJ): BJ1, BJ7, BJ19, BJ30
—Jahrom (J): J10, J11
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Advances in Genetics and Breeding of Capsicum and Eggplant
Year 2
As can be seen in table 1 and 2, there are high significant differences among controls in
trials 1 and 2.
Table 1. Analysis of variance of yield for the controls in trial 1.
S.O.V.
Rep
D.F.
SS
MS
F
5
204.67
40.93
4.27 **
25.76 **
Treat
4
985.82
246.45
Error
20
191.31
9.56
Total
29
1381.8
C.V. = 16.05%, ** significant at P<0.01
Table 2. Analysis of variance of yield for the controls in trial 2.
S.O.V.
D.F.
SS
MS
F
3
818
27.3
5.83**
Treat
5
981.8
196.4
41.97**
Error
15
70.2
4.68
23
1133.8
Rep
Total
C.V. = 7.89%,
**
significant at P<0.01
We evaluated the Rj (effect of incomplete block) and corrected the yield of every line
(Yij). Then we evaluate the
and LSD for comparison of each line yield with the mean
yield of its respective landrace (control treatment).
Effect of incomplete block
Block mean
Total mean
Corrected yield of each line
Original yield of each line
Trial 1; =
Trial 2; =
Standard error
r; number of replications
Mean Square (variance) of error c; number of controls
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Advances in Genetics and Breeding of Capsicum and Eggplant
For selecting the better progenies, each one was compared with its respective control
and furthermore, we recorded it’s the quality according to the 1 to 9 scale. Finally, 16
lines from trial 1 and 19 lines from trial 2, i.e. 35 lines in total, were selected with
respect to their yield and also their quality. By above two trials, we reduced 84 initially
selected plants to 35 selected lines. These lines are:
—V44, V50, V61, D1, D7, D13,D35, D53, M45, M60, N12, N46, N61, B5, B29, B60, BJ1,
BJ30, L18, L27, L30, J10, J11, Y3, Y6, Y9, Y23, SH2, SH5, SH12, SH16, SH21, E17,
E28, E29
Year 3
According to table 3 the selected progenies showed very high significant differences for
the yield. This is in accordance with our expectance, because these lines are from
different landraces with different properties.
Table 3. Analysis of variance of yield for the selected progenies in year 3.
S.O.V.
D.F.
SS
MS
F
Rep
2
1192.3
596.2
124.33***
Treat
35
4025.2
115
23.98
Error
70
335.6
4.8
107
5553.2
Total
C.V. = 9.79%
, ***
significant at P<0.001
We compared the means of the progenies by using two methods; Duncan’s and LSD. Table
4 shows the comparison of means by Duncan’s method. Line Yazd 6 ranks first with the
highest yield (39 t/ha), and next progeny is line L29 with a yield of 31 t/ha. The rank of
the other lines is displayed in table 4. As can be seen, most lines have a higher yield than
the control “Varamin” and 15 of them have a significant higher yield.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Table 4. Comparison of means in third year experiment by Duncan’s method at P<1%.
Treatment
Yield Mean
(t/ha)
Grouping
Treatment
Yield Mean
(t/ha)
Grouping
Y6
39
A
SH2
22.1
DEFGH
L29
31.3
B
BJ30
22
EFGHI
E17
29.7
BC
J10
21.7
FGHIJ
L27
29.6
BC
V44
21.5
FGHIJ
Y9
29.3
BC
SH12
21.2
GHIJ
N61
28.7
BC
SH21
20
GHIJ
L18
28
BCD
D53
18.3
GHIJK
D1
27.7
BCD
D35
18
GHIJK
E28
27.6
BCD
BJ1
17.7
GHIJKL
Y23
26
BCDE
Control
17.5
HIJKL
Y3
26
BCDE
V61
17.3
HIJKL
IJKL
D13
25.4
CDEF
J11
17
D7
25.2
CDEF
SH5
16.7
IJKL
N12
25.1
CDEF
N46
16.6
IJKL
E29
25
CDEF
V50
15.6
JKL
M60
23
DEFG
B29
13
KLM
M45
23
DEFG
B5
12
LM
L30
22.7
DEFGH
B60
8.3
M
Sx̄ = 1.265
We compared the means of the selected progenies via LSD method also. In this way we
compared each line only with the control. Table 5 displays the result of this comparison.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Table 5. Comparison of the selected progenies with control by LSD method at P<5% & 1%.
Treatment
Yield Mean (t/ha)
Treatment
Yield Mean (t/ha)
Y6
39**
SH2
22.1*
L29
31.3**
BJ30
22*
E17
29.7**
J10
21.7*
L27
29.6**
V44
21.5*
Y9
29.3**
SH12
21.2*
N61
28.7**
SH21
20 ns
L18
28**
D53
18.3 ns
D1
27.7**
D35
18 ns
E28
27.6**
BJ1
17.7 ns
Y23
26**
Control
17.5
Y3
26**
V61
17.3 ns
D13
25.4**
J11
17 ns
D7
25.2**
SH5
16.7 ns
N12
25.1**
N46
16.6 ns
E29
25**
V50
15.6 ns
M60
23**
B29
13*
M45
23**
B5
12**
L30
22.7**
B60
8.3**
Non-significant or significant at P<0.05 or 0.01, respectively.
LSD1%= 4.734, LSD5%= 3.658
ns, *, **,
According to table 5, 18 lines showed significant higher yield at P<1%, and 5 other lines
showed significant higher yield at P<5%. As a result, 23 lines of all 35 lines had higher
yield than the control. For the 3 lines, V44, V61 and V50, issued from Varamin landrace
(control), only Line V44 had a significant difference with its respective landrace and
the two other lines had a similar yield of a better quality score. All lines that are
issued from Bandarabas landrace, i.e. B5, B29 and B60, despite of their good quality
grade, had significant lower yields than the control and they had the lowest yields
among all lines. In total, we selected 23 lines as better lines. We can use these lines
for our next breeding programs and for releasing new cultivars of eggplant. These lines
are as follows:
—V44, D1, D7, D13, M45, M60, N12, N61, BJ30, L18, L27, L30, J10, Y3, Y6, Y9, Y23,
SH2, SH12, SH16, E17, E28, E29
Acknowledgements
This research has been financed by SPII (Seed & Plant Improvement Institute). Author
thanks R. Chogan and M. Abedi for their help in this study.
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Advances in Genetics and Breeding of Capsicum and Eggplant
References
Bagheri, M. 2009. The Line Selection from 5 Iranian Eggplant (Solanum melongena L.)
Lan­drace Genotypes. SPII Publication. Register No. 87.1404. 40 p.
FAO. 2007. FAO STAT. http://faostat.fao.org
Federer, W. T. 1956. Augmented (or hoonuiaku) designs. Hawaiian Planters’ Record LV
(2): 191-208.
Hari, H.K. 2003. Vegetable breeding, principles and practices. Oscar publication, 188.
Harlan, J.R. 1975. Crop and man. Amer, Soc, Agronien Madison, Wi, USA, 150-189.
International Board for Plant Genetic Resource. 1985.IBPGR Annual report. IBPGR, Rome, 27.
Kalloo, G. 1988. Vegetable breeding, CRC press, Inc, USA, 587-598.
Kalloo, G.; Bergh, B. O. 1993. Genetic Improvement of Vegetable Crops. Oxford Pub. 833 p.
Yazdi Samadi B., Rezaie A. and Valizadeh M. 1998. Statistical Designs in Agricultural Re­
search. Tehran University Pub, Tehran, Iran, 576-579.
36
Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
A MS Excel implementation of the seed viability equation for managing
gene bank collections of Solanum melongena and Capsicum annuum
I.O. Daniel1, M. Kruse2, G. Muller3, A. Börner4
Department of Plant Breeding & Seed Technology, University of Agriculture, PMB 2240, Abeokuta, Ni­geria.
Contact: [email protected]
2
Institute of Plant Breeding, Seed Science & Population Genetics, University of Hohenheim,
Fruwirthstr. 21, 70593 Stuttgart, Germany.
3
Institut für Mikrobiologie und Genetik. Abteilung für Bioinformatik. Universität Göttingen.
Goldsch­midtstr. 1. 37077 Göttingen. Germany.
4
Gene bank Department, Leibniz-Institute for Plant Genetics and Crop Plant Research (IPK),
Corrensstr. 3, 06466 Gatersleben, Germany.
1
Abstract
The Nigerian National Center for Genetic Resources and Biotechnology (NACGRAB) gene
bank holds seed collections of over 4000 accessions of indigenous tropical plant species
including 7 and 40 accessions of Solanum melongena and Capsicum annuum respectively.
Since maintaining viability of the seed collections is the goal of the gene bank, computer
applications for seed viability prediction will form vital gene bank decision support tools.
The Ellis-Roberts’ seed viability equations are accepted as a predictor of viability under
experimented conditions of storage temperatures and seed moisture contents. We con­
ducted controlled deterioration tests on seeds of Solanum melongena and Capsicum
annuum and viability constants were estimated which were implemented as a Microsoft
Excel application using source codes written with Visual Basic macros. A unique feature of
the application is the possibility of predicting viability of a large number of accessions by
a click of a command button taking advantage of MS Excel spreadsheet capabilities. A user
can also load viability constants estimates for new species on the spreadsheet, thus
extending its use to as many species as possible. Performance of the application is
illustrated and the potential uses of the application in gene bank and seed inventory
management will be discussed.
Keywords: eggplant, pepper, plant genetic resources, seed viability, viability equations.
Introduction
The recommended FAO/IPGRI, (1994) protocol requires that the viability of seeds of crop
germplasm stored in gene banks as base collections at sub-zero temperature be retested every ten years. But for many seed gene banks especially in developing countries
operating merely at above-zero temperatures, precise information on seed deterioration
rates is required for scheduling seed viability testing, rejuvenation or recollection. An
example is the National Center for Genetic Resources and Biotechnology (NACGRAB)
gene bank in Nigeria which holds over 4,000 accessions of over 20 indigenous species in
37
Advances in Genetics and Breeding of Capsicum and Eggplant
5C cold store facility. In this situation, seed viability prediction tools are invaluable for
gene bank management.
The viability equation developed at Reading University in the 1980’s has been widely
used to predict seed longevity for many plant species with orthodox seed storage biology
(Ellis and Roberts, 1980a; Daniel et al., 2003; Chaves and Usberti, 2004; Hay et al.,
2006; Ellis and Hong, 2007; Muthoka et al., 2009). The equation was derived from
empirical data during controlled seed deterioration tests at a wide range of conditions
of seed moisture content and storage temperature, thus the equation relates the viability
of a seed lot to seed moisture content and storage temperature as follows:
V = Ki – p / 10 exp KE – CW log10 m – CHt – CQt
²
(1)
V is viability expressed as normal equivalent deviates (NED) after p days of storage at
temperature t (°C) and moisture content m (% fresh weight basis). Ki, KE, CW, CH, and CQ
are the viability constants (Ellis and Roberts, 1980a, b). Ki, is the theoretical initial
viability of the seed lot (NED) prior to storage. The value of Ki varies between seed-lots
due to the effects of genotype and post-harvesting handling but is constant for a single
seed-lot under different conditions of storage. KE is the constant that indicates inherent
seed longevity of a species. CW describes the relative effect of change in moisture con­
tent on longevity and is species specific. CH and CQ are constants describing the relative
effect of change in temperature on longevity.
To implement this equation for the management of seed viability in gene banks, Roberts
(1960) and Ellis and Roberts (1980b) developed the use of seed viability nomographs to
trace and chart viability of seeds stored under known conditions of temperatures and
seed moisture. However with the availability of personal computers, it has become
relatively easier to estimate seed viability using computer programmes to run the
equation. Kraak (1992), developed a programme with Pascal that runs on IBM compatible
computers to calculate initial seed viability, resultant seed viability after storage,
storage period, moisture content or temperature during storage. The Millennium Seed
Bank Project (MSBP) also launched a web-based application that estimates seed viability
using published estimates of the seed viability equation for about 70 plant species (Flynn
and Turner 2004, Flynn et al., 2006). In these implementations, only estimates of a sin­
gle seed lot sample can be derived at a time. However, for gene bank management,
viability estimation of a large number of accessions is required, thus we investigated a
spreadsheet-based implementation of the seed viability equation.
For personal computers, spreadsheets are more common and are good applications for
preparation, plotting and analysis of data. One of such spreadsheet software is Microsoft
Excel (MSExcel) which is part of the Microsoft office Suite, preloaded with new PCs that
run on Windows platform. Hence there is no additional cost to the user. Moreover, the
MSExcel spreadsheet has capabilities for application development using Macros that runs
object oriented Visual Basic (VB) codes. The objectives of this study were therefore to
estimate viability constants and implement a MSExcel application for calculating the
seed viability equation for 2 tropical vegetable species Capsicum annuum and Solanum
melongena.
38
Advances in Genetics and Breeding of Capsicum and Eggplant
Materials and methods
The NACGRAB gene bank holds 7 and 40 accessions of Solanum melongena and Capsicum
annum, respectively. The seeds were equilibrated to various moisture content levels by
relative humidity (RH) adjustment to between 26% to 93% over various salt solutions in
3-liter capacity plastic desiccators (Exicator™, Italy) (Table 1). The seeds were packed in
net bags and placed in the upper chamber of the desiccators with a digital thermohy­
grometer (Tf™, Germany) to indicate temperature and %RH values in the chamber, which
can be easily seen through the transparent top lid of the desiccator. The loaded
desiccators were stored at 10, 20, and 45°C at the Institute of Plant Genetics and Crop
Plant Research, Gatersleben, Germany. Seed samples were drawn for germination tests
at predetermined intervals for 17 months. Seed germination tests were done on moist
blotter paper for 3 replicates of 45 seeds. Probit analysis of seed survival data was done
using SAS 8.1 version to fit the Ellis and Roberts (1980a) viability equation:
V = Ki - p /σ
(2)
which is similar to fitting seed survival curves constructed on NED equivalent values of
percentage seed germination data. Where V is germination in NED after storage for p
days, Ki is the seed-lot constant equivalent to the y-intercept of seed survival curves
transformed into NED, and σ is the standard deviation of the frequency distribution of
seed deaths in time and relates to storage conditions as:
log σ = KE – CW log10 m – CH t – CQ t
²
(3)
PROC NLIN SAS statements were used to model viability as a linear function of initial
germination, storage period, and exponential function of seed moisture content and storage
temperature as in equation 1. Viability constants KE, Cw, CH and CQ were thus estimated.
39
Advances in Genetics and Breeding of Capsicum and Eggplant
Table 1. Storage experimental conditions of Capsicum and Solanum seeds used in the study.
Species
Capsicum
Temperature
10
20
45
Solanum
10
20
45
40
% Seed moisture
content
Saturated salt solution
% RH
Lithium Bromide (LiBr) + silica gel
26.6
8.45
Calcium Chloride (CaCl2)
27.4
6.08
Lithium Chloride (LiCl)
34.3
7.12
Sodium Bromide (NaBr)
40.3
8.41
Sodium Chloride (NaCl)
75.6
10.16
Potassium Chloride (KCl)
87.5
13.60
ZnCl2
20.9
3.01
CaCl2
36.3
7.09
LiCl
44.7
7.84
NaBr
57.4
8.59
Ammonium chloride (NH4Cl)
68.0
14.52
KCl
88.8
11.40
CaCl2
11.5
3.66
ZnCl2
7.0
3.17
LiCl
21.3
4.13
NaBr
37.5
7.14
NH4Cl
60.9
10.31
KCl
73.2
9.8
CaCl2
27.4
4.28
KCl
87.5
11.30
LiCl
34.3
5.05
NaBr
40.3
7.61
NaCl
75.6
8.95
LiBr + Silica gel
26.6
2.76
CaCl2
36.3
5.73
KCl
88.8
11.18
LiCl
44.7
6.38
NaBr
57.4
7.85
NH4Cl
68
8.31
ZnCl2
20.9
3.30
CaCl2
11.5
5.33
KCl
73.2
8.90
LiCl
21.3
4.86
NaBr
37.5
6.21
NaCl
60.9
6.87
NH4Cl
66
7.58
ZnCl2
7.0
2.56
Advances in Genetics and Breeding of Capsicum and Eggplant
MS Excel implementation
The MS excel implementation of the seed viability equation was done with the Visual basic
(VB) editor on the tools menu of the spreadsheet. Macros were created in the VB to create
buttons on column heads of the cells that runs the seed viability equation. The VB formulas
written as MS Excel macros for the computation of equation 1 are shown in Table 2.
Table 2. Formulas for seed viability model (Equation 1)
computation in form of VB macros.
Model parameter
Cell
Formula
Temperature
F1
Private Sub tempquadrate_Click()
Dim i As Integer Let i = 2
For i = 2 To rowcounter() - 1
Cells(i, 6) = Cells(i, 4) ^ 2
Next i End Sub
Seed moisture
content
G1
Private Sub logmoisture_Click()
Dim i As Integer Let i = 2
For i = 2 To rowcounter() - 1
Cells(i, 7) = LogCells(i, 5) / Log(10))
Next i End Sub
Initial germination
(in proportion)
H1
Private Sub germination_Click()
Dim i As Integer Let i = 2
For i = 2 To rowcounter() - 1
Cells(i, 8) = (Cells(i, 2) / 100)
Next i End Sub
Initial germination
(Ki in NED value)
I1
Private Sub Ki_Click()
Dim i As Integer Let i = 2
For i = 2 To rowcounter() - 1
Cells(i,9)=NormSInv(Cells(i, 8))
Next i End Sub
σ (as in equation 3)
J1
Private Sub sigma_Click()
Dim i As Integer Let i = 2
For i = 2 To rowcounter() - 1
Cells(i, 10) = Cells(2, 14) - Cells(2, 15) * Cells(i, 7)) Cells(2, 16)*Cells(i, 4)) - Cells(2, 17) *Cells(i, 6)))
Next i End Sub
Viability
K1
Private Sub Viability_Click()
Dim i As Integer Let i = 2
For i = 2 To rowcounter() - 1
Cells(i, 11)=Cells(i, 9 ) - Cells(i, 3)/(10 ^ Cells(i, 10)))
Next i End Sub
% Viability
L1
Private Sub Viability_Click()
Dim i As Integer Let i = 2
For i = 2 To rowcounter() - 1
Cells(i, 12)=NormSdist (Cells(i, 11))
Next i End Sub
41
Advances in Genetics and Breeding of Capsicum and Eggplant
Results and discussion
The results of the seed survival data for the 2 species under the different storage treat­
ments were presented for review elsewhere. However, fits of the seed survival data to
the seed viability equations were used to estimate seed viability constants for the two
species which are used to make viability calculations and predictions for the two species
in the MS Excel spreadsheet implementation of the equation.
Table 3 shows the estimates of the seed viability constants KE, CW, CH and CQ for Capsicum
annuum and Solanum melongena from the SAS NLIN procedure of the seed survival data.
The difference in the estimates between the 2 species was not significant but higher
values of KE, and CW in Solanum melongena seeds suggests better longevity than Capsicum
annuum seeds (Daniel et al., 2008) in response to changes in seed moisture content. The
relatively smaller estimate for the temperature terms CH and CQ than the seed moisture
terms corroborates expectations that the species respond to moisture conditioning like
drying than storage temperature as reported for a wide range of species (Dickie et al.,
1990; Ellis and Hong, 2007).
Table 3. Estimates of seed viability constants for Capsicum annuum and Solanum melongena.
Capsicum annum
Viability constants
KE,
CW
CH
CQ
Estimates
4.9449
2.0877
0.0334
0.00013
Standard error
0.4548
0.3553
0.0250
0.000430
Solanum melongena
Viability constants
KE,
CW
CH
CQ
Estimates
5.7047
2.6957
0.00100
0.000332
Standard error
1.6320
1.7854
-
0.000453
MS Excel implementation
The seed viability equation was implemented on a single spreadsheet template of MS
Excel 2003 version. The template contained a total of 15 active columns divided into
3 parts: the data entry columns, the viability calculation columns and the equation
parameter columns. The public domains on the spreadsheet are the columns A to E
where attributes of seed lots can be declared by users according to column labels in
cells A1 to E1 (Fig. 1). The data entry columns A to E are where a user can declare
characteristics of seed lots including accession number, percentage germination
before storage, the period of time for which seed viability forecast is required,
temperature of storage and seed moisture content (Fig. 1). Cells A1 to E1 bear the
title headers to identify seed lot characteristics that users can declare and are
referenced for calculations. The headers are accession number which serves as
accession identifier, % germination of seed lot before storage to be used for calculating
Ki, storage period required to predict viability according to equation 1, temperature
of storage and seed moisture content in column A, B, C, D and E respectively. Though
a user may change the titles, deleting any of the columns will affect calculations with
the spreadsheet application.
42
Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 1. Seed lot data entry columns for accessions of any particular species.
Columns F to K are the programmed template linking VB macros through header cells F1
to K1 (Fig. 2). Command buttons were created on the cells F1 to K1 to run formulas
written as MS Excel macros in VB editor. Table 2 shows the VB macros run by the command
buttons in cells F1 to K1 of the spreadsheet. The programmed template columns are
essentially the components of equation 1. Clicking the command button temp^2 in Cell
F1 references data in column D to compute the square of storage temperature for the
whole column. Clicking log moisture command button in cell G1 computes the logarithm
of equilibrium moisture content referencing column E. The command button Germination
in cell H1 transforms the initial percentage germination data in column B in preparation
for calculation of Ki in column I which estimates the NED of the germination data in
column H, which uses an algorithm that computes the inverse normal cumulative
distribution as a replacement for the Microsoft Excel Worksheet function NORMSINV. The
command button in cell J1 computes σ estimates as in equation 3 referencing the
viability constant values placed in cells N2 to Q2 for the species as well as the temperature
and seed moisture data in columns D, E, F and G. Cell K1 computes viability as in equa­
tion 1 and retransforms the NED viability value to percentage.
43
Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 2. Programmed columns for computation of viability based on
declared values in columns A to E using equation 1.
To run the seed viability equation 1, the viability constants calculated in equation 1 are
stored in columns N to Q of the spreadsheet (Fig. 3). The value of KE is stored in cell N2,
Cw in cell O2, CH in cell P2 and CQ in cell Q2. The cells holding the viability constants’
estimates are referenced by the seed viability calculation columns in the VB program
used by the application.
Figure 3. Estimates of seed viability constants calculated for
Capsicum annuum seeds.
The viability equations were used to make predictions of seed longevity for the two
species. As expected, there was a considerable variation in the predicted longevity of
seeds depending on the storage environment (Figs. 4 and 5). In the implementation
mode of the spreadsheet, the viability constant values in cells N2 to Q2 are interchangeable
with estimated values of any species in question for example, figure 4 shows example of
calculations for Capsicum annuum and figure 5 for calculations for Solanum melongena
to demonstrate how to run viability prediction calculations for the 2 species.
44
Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 4. MS Excel implementation of the seed viability equation for Capsicum annum seeds.
The implementation was done by writing the estimated viability constants for Capsicum annuum
in cells N2 to Q2 of the spreadsheet having the macros for calculating the seed viability equation.
Figure 5. MS Excel implementation of the seed viability equation for Solanum melongena seeds.
45
Advances in Genetics and Breeding of Capsicum and Eggplant
Uses for gene bank management
A spreadsheet program, such as Excel, processes information that is set up in tables. With
a spreadsheet program, you can: i) place numbers and text in easy-to-read rows and
columns, ii) perform calculations on data and show the results, iii) automatically recalculate
results when data is changed. These features make spreadsheets perfect for tracking
information that involves numbers. The implementation of the seed viability equation being
examined in the present study takes advantage of some of these MS Excel features.
The application is useful in providing information very rapidly, for example, the effects
of seed moisture content and storage temperature on seed longevity can be easily
determined from germination tests. Moreover, it can be helpful to select storage
conditions for individual seed lot. Furthermore, it can be used to choose controlled
deterioration tests conditions as a vigour test (Kraak, 1992). Seed viability estimation
capabilities will help gene bank managers to be able to assess the viability of accessions
in collections of several species. This capability will help gene bank managers to make
decisions on accessions and seed lots that need to be rejuvenated at specific times of
storage. To make such selections, colour constraints can be place on cells on the viability
column to show a certain colour when viability estimates are below specified thresholds
according to gene bank standards.
Secondly, the application explores the capacity of MS Excel to compute viability for
more than 10,000 accessions at a click on the viability button. Since each seed lot and/
or accessions occupy a row in the application, it would be possible to run the seed
viability equation on a large number of accessions at a time once the storage conditions
and the initial seed viability can be provided in the data entry columns. This capability
enhances the use of the application in gene bank management than the previously
reported implementation of the seed viability equation (Kraak, 1992, Flynn et al., 2006).
Nonetheless, the web-based seed viability calculation application of MSBP currently
provides seed viability constants for about 70 species, thus making the MS Excel
spreadsheet application applicable for those species and provides a complementary
platform for the use of both implementations of the seed viability equation.
Thirdly, the low cost of the application will enhance the concept of low-input genebanking
suggested by FAO/IPGRI (2004). This will benefit gene banks particularly the ones operating
at sub optimal condition or with very limited budgets. Since MS excel is part of the Microsoft
office Suite, preloaded with new PCs that run on Windows platform, no additional costs are
necessary. Moreover, the application does not require technically sophisticated procedures
for usage, only that viability constants need to be changed for different species. Since
NACGRAB already run all her systems on Microsoft office, the application will be most
suitable for seed inventory management at the gene bank. By extension, other gene bank
and seed store operators can use the application as a decision support tool.
Acknowledgements
Funding and logistic supports for this project came from the Alexander von Humboldt
Foundation, Germany. The authors also acknowledge contributions of scientific and
46
Advances in Genetics and Breeding of Capsicum and Eggplant
technical staff of the Genebank Department, IPK, Gatersleben and Seed Science labo­
ratory, University of Hohenheim, Stuttgart, Germany. Prof. Hans Peipffer and his team
are also acknowledged for assistance in statistical programming.
References
Chaves, M.M.F.; Usberti, R. 2004. Controlled seed deterioration in Dalbergia nigra and Di­
morpphandramollis, endangered Brazilian forest species. Seed Science and Techno­
logy 32:813-823.
Daniel I.O.; Kruse, M.; Börner, A. 2008. Comparative seed longevity among five tropical
vegetable species. In: A Book of Abstracts 9th International Seed Biology Conference
University of Warmia and Mazury, Olsztyn, Poland. Polish Journal of Natural
Sciences. (Supplement 5), 90.
Daniel, I.O.; Ng, N.Q.; Tayo, T.O.; Togun, A.O. 2003. Storage of West African yam (Dioscorea
spp.) seeds: modelling seed survival under controlled storage environments. Seed
Science and Technology 31:139-147.
Dickie, J.B.; Ellis, R.H.; Kraak, H.L.; Ryder, K.; Tompsett, P.B. 1990. Estimation of provisio­
nal seed viability constants for apple (Malus domestica Borkh. cv. Greensleeves).
Annals of Botany 56:271-275.
Ellis, R.H.; Hong, T.D. 2007. Quantitative response of the longevity of seed of twelve crops
to temperature and moisture in hermetic storage. Seed Science and Technology
35:432-444.
Ellis, R.H; Roberts, E.H. 1980a. Improved equations for the prediction of seed longevity.
Annals of Botany 45:13-30.
Ellis, R.H.; Roberts, E.H. 1980b. The influence of temperature and moisture on seed via­
bility period in barley (Hordeum distichum L.). Annals of Botany 45:31-37.
FAO/IPGRI. 1994. Gene bank Standards. Food and Agriculture Organization of the United
Nations, Rome, International Plant Genetic Resources Institute, Rome, Italy.
FAO/IPGRI. 2004. Low cost technologies for seed conservation. IPGRI Annual Report 2004,
International Plant Genetic Resources Institute, Rome, Italy, pp. 19-21.
Flynn, S.; Turner, R.M. 2004. Seed Viability Equation: Viability Utility (release 1.0, Sep­
tember 2004) http://data.kew.org/sid/viability/index.html
Flynn S.; Turner, R.M.; Stuppy, W.H. 2006. Seed Information Database (release 7.0, October
2006) http://www.kew.org/data/sid/
Hay, F.; Klin, J.; Probert, R. 2006. Can a post-harvest ripening treatment extend the lon­
gevity of Rhododendron L. seeds? Scientia Horticulturae 111:80-83.
Kraak, H.L. 1992. A computer programme to predict seed storage behaviour. Seed Science
and Technology 20:337-338.
Muthoka, P.N.; Hay, F.R.; Dida, M.M.; Nyabundi, J.O.; Probert, R.J. 2009. Moisture content
and the longevity of six Euphorbia species in open storage. Seed Science and
Technology 37:383-397.
Roberts, E.H. 1960. The viability of cereal seed in relation to temperature and moisture.
Annals of Botany 24:12-31.
47
Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Phylogenetic relationships and diversity of Capsicum species
in Ecuador
V.P. Ibiza, J. Blanca, J. Cañizares, F. Nuez
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universidad Politécnica de Valencia,
Camino de Vera 14, 46022 Valencia, Spain. Contact: [email protected]
Abstract
A wide study about the variability of cultivated Capsicum species from Ecuador has been
done. A total of 138 accessions, belonging to five species from COMAV genebank (C. annuum,
C. chinense, C. frutescens, C. pubescens and C. baccatum) were analyzed. These species
belong to C.annuum, C. pubescens and C. baccatum complexes. The genetic diversity and
relationships among species were determined using four AFLP primer pairs and ten
microsatellites markers. The AFLPs tree showed that there were clear differences between
the three complexes. Moreover inside of C. annuum complex, C. chinense, C. frutescens
and C. annuum were well defined, although C. chinense and C. frutescens are sister species
and showed the smallest genetic distance. The C. chinense, C. pubescens and C. baccatum
accessions from Bolivia were differentiated to the Ecuador accessions in the PCA analysis.
In spite of Bolivia is their nuclear area, these species showed a high variability in Ecuador.
This high variability and its study will allow to maximize the usefulness of the genebank
collections and the EcoTilling platforms to improve the plant breeding of Capsicum sp.
Acknowledgements
V. P. I. received of a F.P.U fellowship from the Ministerio de Educación y Ciencia.
49
Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Evaluation of the National collection of eggplant (Solanum
melongena L.) in Bulgarian conditions
L. Krasteva, N. Velcheva, K. Uzundzhalieva
Insitute of Plant Genetic Resources – Sadovo, Bulgaria. Contact: [email protected]
Abstract
Plant genetic diversity can be efficiently used only if evaluated and improved. The results
from the evaluation made by curators, phytopathologists, biochemists and other research
scientists are stored in databases. They are of great interest to breeders, growers and
genebanks. The objective of the present study, conducted at the IPGR-Sadovo, was to
create an evaluation database in eggplants with a view to accelerating the process of
breeding and meeting the practical needs. To realize this task, we conducted in the period
1985-2008 an inventory of the eggplant collection available, a study by descriptors and a
complex study by breeding-important criteria. Based on computer programs developed
previously at the IPGR in Sadovo, statistical treatment was made for all accessions involved
in the collection. Using the software packages VISITREND, VIVIPLOT, AIDA /Apple Interactive
Data Analysis/ and CCADMS /The Creative Computer Applications Data Management
System/, the data for each crop were stored according to international descriptors.
Information storage and processing is helpful for specialists in the field of plant resources
for giving them full access to data for analysis. Thus, the whole available information is at
the disposal of every specialist who shows interest in eggplant genetic resources.
Keywords: plant genetic resources, evaluation, databases, eggplant.
Introduction
Eggplant (S. melongena L.) is a traditional vegetable crop in Bulgaria. It was introduced
in the country at the time of the Turkish invasion of the Balkan Peninsula. The creation
of the national eggplant collection dates back to 1982. Through exchanges between the
Institute of Plant Genetic Resources (IPGR) in Sadovo and related foreign institutes, a
collection of 143 eggplant accessions of foreign origin was established. The major sources
of acquisition of new accessions are contacts with other institutes, genebanks and
botanical gardens. The successful selection of eggplant depends to a great extent on the
use of the whole potential in productivity, resistance to diseases. On the other hand it
depends on the study of the mathematical variance of the measured plant characteristics
and the correlations between them (Krasteva at al. 2004, Krasteva et al., 2008).
The aim of the present investigation is to analyze the basic morphological and economical
characteristics of eggplant collection and to determine the variability in the groups of
local and foreign origin (Krasteva at al. 1994, Krasteva et al., 2002).
51
Advances in Genetics and Breeding of Capsicum and Eggplant
Material and methods
Based on computer programs developed previously at the IPGR in Sadovo, statistical
treatment was made on all accessions involved in the collection. Using the software
packages VISITREND, VIVIPLOT, AIDA /Apple Interactive Data Analysis/ and CCADMS /The
Creative Computer Applications Data Management System/, the data for each crop were
acquired and stored according to international descriptors.
This package gives the opportunity to add, delete and refresh the data, as well as
search and sort by definite indices. The average value and average error were determined
for 17 basic descriptors indices. The coefficient of variation was also determined (CV
%). The mathematical treatment was made according to Draiper et al. (1973). The
average values for one year period for each accession were calculated. The investigation
was made at certain stages during the period 1985-2008 in the experimental field of
IPGR - Sadovo.
The collection comprises 219 accessions from more than 16 countries, 143 of them
introduced and 76 of local origin. Most accessions originate from Europe and Asia. Part
of the material was collected during expeditions in various regions of Bulgaria, resulting
in the collecting of 76 local accessions. This was the first step in the introduction process.
Efficient planning and organization of these expeditions was essential. The IBPGR
methodology for collecting local genetic resources was adapted for Bulgarian conditions.
(Krasteva, 1989)
The national collection consists of foreign and local cultivars and populations, predo­
minance of foreign cultivars (143) over local cultivars (76) (Figure 1).
Figure 1. Geographic origin of the eggplant accessions.
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Advances in Genetics and Breeding of Capsicum and Eggplant
The international Comecon descriptors for Solanum melongena were adapted to Bulgarian
conditions for the description, evaluation and analysis of the genetic material used.
Results and discussion
The results for the morphological, phenological and biological characteristics of the
accessions with foreign and local origin are shown in table 1. The mean, standard deviation
and coefficient of variation of 17 important morphological traits were calculated. For
both foreign and local groups coefficients of variation were high whatever the descriptors
and the geographical origin of accessions. For introduced material, moderate variation
was observed for flowering earliness – CV – 18,8%, leaf length - CV – 13.6%, leaf width –
CV-12,9%, flower diameter – 10,5%, fruit width – 14,7%, total sugars (%) – VC- 14,2%,Crude
protein (%)- VC- 13,7%. Plant descriptors with considerable varia­tion in that group were:
emergence –fruit formation – VC-21.8%, stem height (cm) – VC-26.8%,fruit length (cm) –
VC-29.7%,fruit shape– VC-23.7%, fruit weight (g) – VC- 32.4%, fruit number per plant– VC25.6%, productivity per plant (g) – VC- 32.3%, dry matter (%)– VC- 21.3%, resistance to
Verticillium wilt – VC- 24.7%.
In the group of the local accessions plant descriptors with medium and considerable
variation are the same than for the group of foreign accessions.
Table 1. Variation in the principal quantitative traits of eggplant accession.
№
Traits
1 Emergence flowering (days)
Introduced accession
x
Sx
VC
Local accession
x
Sx
VC
91.30
1.30
18.8
97.14
1.18
19.6
115.40
2.16
21.8
120.40
1.93
23.1
3 Stem height (cm)
56.90
4.80
26.8
57.83
4.10
27.8
4 Branching number
3.69
0.04
11.5
4.18
0.06
12.9
5 Leaf length (cm)
17.05
0.58
13.6
18.07
0.63
14.2
6 Leaf width (cm)
12.90
0.44
12.9
13.70
0.61
14.7
4.18
0.28
10.5
4.30
0.32
12.4
8 Fruit length (cm)
13.60
0.36
29.7
15.10
0.43
30.5
9 Fruit width (cm)
6.70
0.14
14.7
7.50
0.18
16.3
2.13
0.04
23.7
2.70
0.09
25.1
264.00
13.65
32.4
280.15
15.10
34.1
29.7
2 Emergence–fruit formation (days)
7 Flower diameter (cm)
10 Fruit shape
11 Fruit weight (g)
12 Fruit number per plant
12.00
0.52
25.6
13.15
0.60
2018.00
98.40
32.3
2263.00
99.60
34.2
14 Dry matter (%)
7.80
0.11
21.3
8.16
0.15
24.2
15 Total sugars (%)
2.10
0.04
14.2
2.40
0.08
16.3
13 Productivity per plant (g)
16 Crude protein (%)
17 Resistance to Verticillium wilt
13.10
0.37
13.7
15.70
0.43
15.7
39.6
0.83
24.7
39.60
0.97
26.7
53
Advances in Genetics and Breeding of Capsicum and Eggplant
High yield and good quality are much affected by some economically important diseases.
The most severe of these diseases are Phytophthora parasitica and Verticillium dahliae.
In a number of countries this problem has been solved for the local ecological conditions
by breeding resistant cultivars. A study was made on the susceptibility of introduced S.
melongena L. accessions to Phytophthora capsici Leon.: most of them displayed mo­
derate susceptibility to Phytophthora rot, and a relatively resistant accession was
identified. Concerning Verticillium dahliae Kleb., the 81 eggplant accessions tested,
whatever introduced or local, were all very susceptible according to the scale used:
immune - i=0; highly resistant – i =0.1-10% wilting; slightly resistant – i =10.1–25% wil­
ting; slightly susceptible i = 25.1-50% wilting; highly susceptible i > 50.1% wilting
(Neshev at al. 1999).
The variation of the traits measured is determined by the variation factor (CV %). The
variation is considered as low if the coefficient of variation is less than 10%, as medium
if the coefficient of variation is comprised between 10 – 20%, and as large if the coefficient
of variation is more than 20% (Dospehov, 1985). Table 2 displays the number of measured
traits having low, medium or large coefficients of variation, for the introduced and local
accessions. For both varieties groups, there are no traits with a low coefficient of
variation, and only a slight difference between the number of traits, respectively 8 and
9, with a medium or a large coefficient of variation .
Table 2. Distribution of the number of accessions for low, medium
and large coefficients of variation.
Coefficent of variation
(CV %)
Accessions
Introduced accessions
Local accessions
< 10 % - low
0
0
10 % - 20 % - medium
8
8
> 20 % - large
9
9
According to Merezhko (1984), the first step in research for breeding purposes is the
constitution of working collections for each valuable breeding trait. These collections
can be classified by trait or by source. Further to the thorough evaluation of the collection
and according to breeding needs, the accessions were grouped according to the degree
of expression of each trait and sub collections, one per trait, were created (Table 3).
Accessions surpassing the standard for earliness, productivity and fruit morphology were
selected and included in each matching sub collection –or trait collection.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Table 3. Eggplant accessions selected for several traits.
Traits
Accessions cat. №
Number of
accessions
Earliness
A2006, 90603010, A2000147, A200146,
90603003, 94603004
6
Productivity
98603001, 87603001, 90603001,
94603005, 946030004, A8E0534
6
Egg-shaped fruits
A200006, A7E0431, A7E0313,
A200005, A8E0344
5
Cylindrical fruits
94004, 94005, 97001, A7E0430, A8E534,
A7E0430, 98603002
7
High sugar content
A8E0657, A8E0536, A2000145, A200005,
93603002, 90603010
6
High dry matter content
94603004, 93603001, 93603003, 87603001,
90603011, A7E0431
6
High raw protein
8560307, 85603021, 85603024, 85603030,
85603033, A4000269, A7E0431, A2000146
8
Resistance to Phytophthora
capsici (Leon.)
A7E0313, A7E0262, A7E0525, A7E0430,
A8E0344
5
Resistance to Verticilium
dahliae (Kleb)
A200006, A7E313, 98603002, 91603004
4
Conclusions
1.An eggplant collection comprising a total of 219, including 143 foreign and 76 local
cultivars, was constituted and characterized for 17 traits of agronomic interest,
2.The collection exhibited large coefficients of variation for all traits measured
(phenological phases, morphological characters and plant productivity
3.The coefficients of variation were medium or large, whatever the foreign or local
origin of the accessions,
4.Traits with large variation are slightly predominant in both groups. Whatever the
traits, the coefficients of variation were larger in the group of local accessions than
in the group of foreign accessions.
5.Traits collections were created for earliness, productivity, fruit shape, high sugar and
dry matter contents, and disease resistance.
6.A database recording 17 quantitative and qualitative traits was created; it will con­
tribute to more effective utilization of the germplasm for breeding.
55
Advances in Genetics and Breeding of Capsicum and Eggplant
References
Dospehov, B.A. 1985. Biometrics. Moscow.
Draiper, N.; Smit, G. 1973. Regression analyzes. Moscow.
Krasteva, L. 1989. Collecting and utilization of plant genetic resources in vegetable. Pro­
tected plant wealth in Bulgaria, Sofia, p. 75-90.
Krasteva, L.; Lozanov, I.; Petrov, H.; Nakov, B.; Jordanov, M. 1994. Genetic Resources of
eggplant in Bulgaria and its utilization in breeding. Symposium with international
participation New technologies in vegetable and flower production. Ohrid.
Krasteva, L.; Sevov, V.; Kitcheva, P.; Shamov, D.; Sabeva, M.; Neykov, S.; Popova, Z.;
Lozanov, I. 2002. Local Genetic Resources in Bulgaria on farm conservation. Scientific
Session of Jubilee, IPGR, Sadovo, 1, 57-63.
Krasteva, L. 2004. Collection and evaluation of the local vegetable genetic resources in
Bulgaria, Proceedings of the 3rd Balkan symposium on vegetables and potatoes, 6-10
September, Bursa, Turkey, Acta horticulturae 729, ISHS, 73-76.
Krasteva, L.; Neshev, G.; Vassileva, M. 2004. Some results on evaluation of Bulgarian
Eggplant [S. melongena L.] germplasm collection. Proceedings of the 3rd Balkan
symposium on vegetables and potatoes, 6-10 September, Bursa, Turkey, Acta horti­
culturae 729, ISHS, 81-84.
Krasteva, L.; Angelova, S.; Antonova, N.; Popova, Z.; Neykov, S. 2008. Plant Genetic Re­
sour­­ces Utilization. Proceedings of 7th scientific – technical conference with
international participation, Plovdiv, Bulgaria p.109-115.
Merezhko, A.F. 1984. A system of genetic investigation of source breeding material. VIR,
leningrad.
Neshev, G.; Krasteva, L.; Ivanova, I. 1999. Response of introduced eggplant (S. melongena
L.) accession to Verticillium wilt (V. dahliae Kleb.). Scientific Works of the Agricultural
University in Plovdiv 11 (3): 109-112.
The International Comecon list of descriptors for genus (Solanum melongena). 1986.
Leningrad.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Taxonomy and ethno-botanical study of Indonesian’s eggplants
and their wild relatives
H. Kurniawan1,3,4, Hartati2,3, Asadi1, C. Mariani3, G. van der Weerden4
1
Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development
(ICABIOGRAD), Bogor Indonesia.
2
Biotechnology Research Center, The Indonesian Institute of Science (LIPI), Cibinong-Bogor, Indonesia.
3
Dept. Plant Cell Biology, IWWR, Radboud University Nijmegen, The Netherlands.
4
Experimental Garden and Genebank, IWWR, Radboud University Nijmegen, The Netherlands.
Abstract
Many species of Solanum subgenus Leptostemonum are known to be used as food and for
medicinal purposes. In Indonesia, the cultivated eggplant (Solanum melongena) has been
widely used as food and can be found in some areas by their local names. A collecting
mission has been carried out in Indonesia to make an inventory of the eggplant and wild
relatives distribution, and to describe their habitat and the popular use in various regions.
Furthermore, the collection of eggplants and wild relatives also will be used to study their
taxonomy. From the collection activities in Java, Sumatera, Kalimantan, Sulawesi, Lombok,
and Sumbawa islands, 380 accessions of Solanum subgenus Leptostemonum have been
collected. This collection comprises 250 accessions of cultivated eggplant (S. melongena),
49 accessions of hairy eggplant (S. ferox; S. quitoense), 19 accessions of torvum (S. torvum),
10 accessions of gboma eggplant (S. macrocarpon), 9 accessions of scarlet eggplant (S.
aethiopicum), 8 accessions of nipple eggplant (S. mammosum), 5 accessions of S. capsi­
coides, 4 accessions of S. sanitwongsei, 2 accessions of S. jamaicense, 2 accessions of S.
mauritianum, and 22 accessions of other Solanum species. Passport and morphological data
as well as characterization data were recorded. The results of this study will be useful for
breeding purposes of eggplant, in particular for the introgression of interesting traits from
the wild species into the cultivated one.
57
Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Morphological and molecular characterization for the conservation
and protection of Listada de Gandía eggplant
J.E. Muñoz-Falcón, J. Prohens, S. Vilanova, F. Nuez
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universidad Politécnica de Valencia,
Camino de Vera 14, 46022 Valencia, Spain. Contact: [email protected]
Abstract
Listada de Gandía is an internationally known Spanish eggplant (Solanum melongena)
heirloom. We have studied the Listada de Gandía diversity and its relationships with other
striped materials either from Spanish or from other countries with morphological and
agronomic traits and molecular (AFLP and SSR) markers. The results show that although the
Listada de Gandía accessions are morphologically distinct to the other materials studied,
no individual traits could unambiguously distinguish the Listada de Gandía accessions from
other similar materials. AFLPs and SSRs showed that Listada de Gandía accessions share a
common genetic background and that are differentiated from the rest of striped materials.
In addition, two SSR alleles specific and universal to Listada de Gandía accessions were
found, which may be useful for identifying Listada de Gandía materials. The results obtained
show that Listada de Gandía heirloom is genetically diverse although clearly distinct to
other striped eggplants. The information obtained may be useful for the conservation and
enhancement of this heirloom.
Keywords: AFLPs, eggplant, Listada de Gandía, characterization, Solanum melongena, SSRs
Introduction
Listada de Gandía is an eggplant (Solanum melongena L.) heirloom native to the area
around the city of Gandía (Safor county, province of Valencia, Spain). This local heirloom
has large fruits with obovate to oblong shape and with a characteristic shiny skin with
white background and purple stripes (Prohens et al., 2005; Muñoz-Falcón et al., 2008a).
Listada de Gandía heirloom is widely known, both in Spain and abroad, for its white flesh
and excellent flavour and texture after cooked. Because of this, Listada de Gandía
eggplant might be a candidate for protection through either a conservation variety
status (Commision of the European Communities, 2008) or, like the pickling Almagro
eggplant (Muñoz-Falcón et al., 2009), a Protected Designation of Origin (PDO) status
(Commision of the European Communities, 2006). However, there are many cultivars and
local varieties of striped eggplants, and on occasion some of these are labeled and
marketed as Listada de Gandía, although they do not correspond to the Listada de
Gandía characteristics. In consequence, development of tools that allow distinguishing
this heirloom from related materials is necessary.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Morphological characterization is essential for the description of distinctive characteristics
of cultivars and local varieties (UPOV, 1991). However, environmental conditions may
affect the expression of some traits, and molecular markers, like amplified fragment
length polymorphisms (AFLPs) or simple sequence repeats (SSRs) may represent an
additional tool for the protection of vegetable heirlooms (Rao et al., 2006; Muñoz-Falcón
et al., 2008b; Mazzucato et al., 2010). In a previous work (Muñoz-Falcón et al., 2008a)
we studied the morphological and AFLP diversity and relationships of Listada de Gandía
eggplant. In subsequent experiments we studied Listada de Gandía materials with SSR
markers. Here, we present the integration of the results of morphological, AFLP and SSR
characterization for the conservation, protection and development of a specific genetic
fingerprint of this heirloom.
Materials and methods
Plant material
Nineteen accessions of striped eggplants, of which five correspond to the Listada de
Gandía local heirloom, five to Other Spanish Listada (i.e., Spanish varieties similar to
the Listada de Gandía, although from other origins), five to Non-Spanish Listada (i.e.,
Non-Spanish varieties similar or marketed as Listada de Gandía), and five to Other NonSpanish Striped (i.e., Non-Spanish striped varieties with few morphological similarities
with the Listada de Gandía) were used for this study (Table 1). Further details on the
materials studied can be found in Muñoz-Falcón et al. (2008a).
Table 1. Accessions used for the morphological, AFLP, and SSR characterization, grouped
according to the four categories established.
Accesion name
Code
Origin
IVIA-25
I25
Moncada,Valencia, Spain
Listada de Gandía
IVIA-371
I371
Moncada, Valencia, Spain
Listada de Gandía
LDG
Valencia, Valencia, Spain
V-S-1
VS1
Alzira, Valencia, Spain
V-S-8
VS8
La Punta, Valencia, Spain
Other Spanish Listada
AN-S-4
ANS4
Castro del Río, Cordoba, Spain
C-S-10
CS10
Barcelona, Barcelona, Spain
C-S-23
CS23
Gavá, Barcelona, Spain
C-S-7
CS7
Villabertrán, Gerona, Spain
V-S-22
VS22
Orihuela, Valencia, Spain
Listada de Gandíaa
LBCS
Italy (Baker Creek Seeds, USA)
Non-Spanish Listada
60
Listada de Gandíaa
LRS
Italy (Reimer Seeds, USA)
Listada de Gandíaa
LTGS
Italy (Tomato Growers Seeds, USA)
Advances in Genetics and Breeding of Capsicum and Eggplant
Accesion name
Code
Origin
Pandora Striped Rose
PAN
Italy (Baker Creek Seeds, USA)
Zebra
ZEB
Unknown (Tomato Growers Seeds, USA)
Other Non-Spanish Striped
Little Purple Tiger
LPT
Unknown (Reimer Seeds, USA)
Manjri Gota
MAN
India (Reimer Seeds, USA)
PI-169659
P169
Edirme, Turkey
RNL-580
R580
Homs, Syria
Accesions labeled as Listada de Gandía but which do not fit the typical characteristics
of the Listada de Gandía heirloom.
a
Morphological, agronomic and molecular characterization
Six plants per accession were grown in an open field plot in a completely randomized
design in Valencia, Spain. Accessions were characterized with the primary descriptors
developed by the European Genetic Resources Network (EGGNET) as well as with some
additional descriptors considered as important by the authors. Details on the
morphological and agronomic characterization can be found in Muñoz-Falcón et al.
(2008a). For the AFLP characterization we used three combinations of primers and for
the SSR characterization we evaluated nineteen SSR markers. Methodologies used for
the molecular characterization can be consulted in Muñoz-Falcón et al (2008a) for AFLPs
and in Muñoz-Falcón et al. (2009) for SSRs.
Data analysis
The mean and standard deviation for each considered trait was calculated for each of
the groups of accessions. For the AFLP and SSR data we calculated the Dice (Sorensen)
coefficient of genetic similarity, which was used to generate UPGMA phenograms. The
reliability and robustness of the phenograms were tested by bootstrap analysis with 1000
replications to assess branch support.
Results and discussion
Morphological and agronomic characterization
A considerable variation has been found for morphological and agronomic traits. For
most traits, the ranges of variation of the groups of accessions overlapped. However, we
found that for a number of traits the Other Non-Spanish Striped group was clearly
distinct to the rest of Listada groups. In this respect, the Other Non-Spanish Striped
accessions presented, as a mean, a greater earliness (measured as first fruit harvest), a
higher number of fruits and a lower fruit weight than the other three Listada groups
(Table 2). As is usual with local varieties (Lanteri et al., 2003; Muñoz-Falcón et al., 2009;
Mazzucato et al., 2010), some variation was present among the Listada de Gandía
accessions. Altough, the Listada de Gandía accessions did not present many differences
in vegetative traits with respect to the other Listada groups, they had a lower plant
height, shorter leaf blade length, and longer leaf pedicel length than either the Other
Spanish Listada and the Non-Spanish Listada. When considering fruit traits, Listada de
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Advances in Genetics and Breeding of Capsicum and Eggplant
Gandía accessions were characterized by a greater fruit size, higher fruit weight, and
yield than the rest of Listada groups. However, these morphological traits are subjected
to environmental variation (Prohens et al., 2004), and this may difficult its use for es­
tablishing absolute ranges of values for discriminating Listada de Gandía accessions from
other closely related materials.
Table 2. Mean (± standard deviation) for some of the most relevant traits studied
for the four groups considered in this study.
Listada
de Gandía
Other Spanish
Listada
Non Spanish
Listada
Other NonSpanish Striped
No. of accessions
5
5
5
4
Plant heigth (cm)
82.3 ± 23.1
88.5 ± 15.0
94.4 ± 8.8
88.2 ± 8.2
Leaf blade breadth (cm)
10.5 ± 0.9
11.4 ± 1.4
11.5 ± 2.0
8.2 ± 1.5
Leaf blade length (cm)
14.9 ± 1.2
15.7 ± 5.4
16.5 ± 1.9
13.5 ± 1.9
3.8 ± 0.7
Leaf pedicel length (cm)
6.3 ± 1.5
5.4 ± 1.5
5.7 ± 1.3
Fruit breadth (cm)
7.9 ± 0.5
7.7 ± 0.8
7.1 ± 0.8
6.8± 1.1
Fruit length (cm)
14.7 ± 2.7
13.5 ± 2.8
12.2 ± 1.3
10.8± 2.3
Fruit length/breadth ratio
1.9 ± 0.5
1.8 ± 0.3
1.8 ± 0.4
1.7 ± 0.7
Flowering time (d)
36.7 ± 2.3
30.9 ± 5.2
33.6 ± 2.6
29.8 ± 2.0
First fruit harvest (d)
58.8 ± 4.4
53.9 ± 7.9
50.0 ± 5.7
45.0 ± 2.9
Number of fruits per plant
14.2 ± 2.5
13.5 ± 3.0
18.1 ± 0.7
19.6 ± 8.2
425.4 ± 13.4
390.4 ± 26.9
300.0 ± 39.9
207.9 ± 48.6
6.1 ± 1.1
5.5 ± 1.4
5.6 ± 0.7
4.5 ± 2.6
Fruit weight (g)
Yield (kg/m2)
AFLP characterization
All the Listada de Gandía accessions cluster together in a branch supported by a 91.3%
of bootstrap value in the the UPGMA phenogram performed with the AFLP data (Figure
1). These data also show that, as occurs with other heirlooms (Lanteri et al., 2003;
Muñoz-Falcón et al., 2009; Mazzucato et al., 2010), the Listada de Gandía is not gene­
tically uniform. The accessions of Other Spanish Listada also cluster together in a single
branch of the phenogram, although, in this case, the bootstrap value for this branch is
below 50%. Remarkably, the accessions marketed as Listada de Gandía and which belong
to the Non-Spanish Listada accessions do not cluster together with the Listada de Gandía
accessions, indicating that, although they are marketed as Listada de Gandía, they are
genetically distinct to the authentic Listada de Gandía. Also, the other accessions of the
Non-Spanish Listada and of the Other Non-Spanish Striped accessions plot in different
clusters. AFLP markers, which have been proved useful to study overall variation in
eggplant (e.g., see Daunay, 2008), indicate that the Listada de Gandía accessions share
a common genetic background and that this heirloom is genetically distinct to other
closely related materials. However, no specific and universal AFLP band has been found
for the Listada de Gandía accessions.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 1. Unrooted UPGMA tree corresponding to 19 striped eggplant accessions based on
AFLP markers. Bootstrap values greater than 50% are indicated at each node.
The branch where the Listada de Gandía accessions are found is indicated.
SSR characterization
As occurred with the AFLP data all the Listada de Gandía accessions cluster together in
a single branch of the UPGMA phenogram with a bootstrap value of 73.3% (Figure 2).
Also, the SSR data confirm the existence of genetic diversity within the Listada de Gandía
heirloom. The Other Spanish Listada together with the Non-Spanish Listada accessions
marketed as Listada de Gandía cluster together in the same branch, although the
bootstrap value of this cluster of accessions is below 50%. SSR markers have been able,
like AFLPs, to distinguish the Listada de Gandía heirloom from closely related materials.
Furthermore, we have found two SSR alleles specific and universal to all Listada de
Gandía accessions, which shows that SSR markers may be more efficient than AFLP
markers in establishing genetic fingerprints in closely related materials of eggplant, as
has been found in other reports dealing with local materials of eggplant (Muñoz et al.
2008a, 2008b).
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Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 2. Unrooted UPGMA tree corresponding to 19 striped eggplant accesions based on
SSR markers. Bootstrap values greater tan 50% are indicated at each node.
The branch where the Listada de Gandía accessions are found is indicated.
Conclusions
The results obtained show that the Listada de Gandía heirloom is clearly distinct from
other similar materials, including some striped eggplants erroneously labeled and sold
as Listada de Gandía. Molecular markers have shown that the different accessions of this
variety cluster together and share a common genetic background. Furthermore, we have
found two SSRs that are present in all Listada de Gandía materials and are absent in the
rest of striped accessions. This information may be useful for the conservation and
protection of the Listada de Gandía heirloom.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Acknowledgements
This work was partially financed by the Ministerio de Ciencia y Tecnología (AGL200907257 and RF-2008-00008-00-00) and Generalitat Valenciana (ACOMP/2010/033).
References
Commision of the European Communities. 2006. Council Regulation (EC) No. 509/2006 of
20 March 2006 on the protection of geographical indications and designations of
origin for agricultural products and foodstuffs as traditional specialities guaranteed.
Official Journal of the European Union L93:12-25.
Commision of the European Communities. 2008. Commision Directive 2008/62/EC of 21
June 2008 providing for certain derogations for acceptance of agricultural landraces
and varieties which are naturally adapted to the local and regional conditions and
threatened by genetic erosion and for marketing of seed and seed potatoes of
those landraces and varieties. Official Journal of the European Union L162:13-19.
Daunay, M.C. 2008. Eggplant. pp. 163-220. In: J. Prohens y F. Nuez (eds.), Handbook of
Plant Breeding: Vegetables II. Springer, New York, USA.
Lanteri, S.; Acquadro, A.; Quagliotti, L.; Portis, E. 2003. RAPD and AFLP assessment of
genetic variation in a landrace of pepper (Capsicum annuum L.) grown in NorthWest Italy. Genetic Resources and Crop Evolution 50:723-735.
Mazzucato, A.; Ficcadenti, N.; Caioni, M.; Mosconi, P.; Piccinini, E.; Sanampudi, V.R.R.;
Sestili, S.; Ferrari, V. 2010. Genetic diversity and distinctiveness in tomato (Solanum
lycopersicum L.) landraces: the Italian case of ‘A pera Abruzzese’. Scientia Horticul­
turae: in press.
Muñoz-Falcón, J.E.; Prohens, J.; Vilanova, S.; Nuez, F. 2008a. Characterization, diversity,
and relationships of the Spanish striped (Listada) eggplants: a model for the
enhancement and protection of local heirlooms. Euphytica 164:405-419.
Muñoz-Falcón, J.E.; Prohens, J.; Vilanova, S.; Ribas, F.; Castro, A.; Nuez, F. 2008b. Distin­
gui­shing a protected geographical indication vegetable (Almagro eggplant) from
closely related materials with selected morphological traits and molecular markers.
Journal of the Science Food and Agriculture 89:320-328.
Muñoz-Falcón, J.E.;, Prohens, J.; Vilanova, S.; Nuez, F. 2009. Diversity in commercial
varieties and landraces of black eggplants and implications for broadening the
breeders gene pool. Annals of Aplied Biology 154:453-465.
Prohens, J.; Blanca, J.M.; Rodríguez-Burruezo, A.; Nuez, F. 2004. Spanish traditional
varieties of eggplant: diversity and interest for breeding. Proceedings XIIth EUCARPIA
Meeting on Genetics and Breeding of Capsicum and Eggplant:38-43.
Prohens, J., Blanca, J.M., Nuez, F. 2005. Morphological and molecular variation in a collec­
tion of eggplant from a secondary center of diversity: implications for conservation
and breeding. Journal of the American Society for Horticultural Science 130:54-63.
Rao, R.; Corrado, G.; Bianchi, M.; Di Mauro, A. 2006. (GATA)4 DNA fingerprinting iden­
tifies morphologically characterized ‘San Marzano’ tomato plants. Plant Bree­ding
125:173-176.
UPOV. 1991. International convention for the protection of new varieties of plants.
Publication No. 221 (E), March 19, UPOV, Geneva, Switzerland.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Use of Capsicum and eggplant resources for practical classes of
Genetics and Plant Breeding courses
J. Prohens, A. Rodríguez-Burruezo, C. Gisbert, S. Soler, F.J. Herraiz, M. Plazas, A. Fita
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universidad Politécnica de Valencia,
Camino de Vera 14, 46022 Valencia, Spain. Contact: [email protected]
Abstract
General courses on “Genetics and Plant Breeding” are common in the syllabi of Agriculture
and Horticulture University degrees. Frequently, practical classes constitute an important
part of these courses. In this respect, given the diversity, existing knowledge, and
characteristics of Capsicum and eggplant materials, we consider that they may represent
a useful resource for use in the practical classes of “Genetics and Plant Breeding” courses.
Here, we study the applicability of Capsicum and eggplant materials in the practical
sessions of a “Genetics and Plant Breeding” course at the Universidad Politécnica de
Valencia. Our study shows that for most of the 15 practical sessions of the course, peppers
and eggplants can make an effective contribution to the learning and acquisition of skills
in “Genetics and Plant Breeding” courses. We describe how Capsicum and eggplant
materials could be used in each of the practical classes and how they could contribute to
the improvement of the present practical classes in the modules of fundamentals of
genetics, genetic resources and variation, reproductive biology, evaluation of traits of
agronomic interest, and biotechnolo­gical tools in plant breeding. In conclusion, the use of
peppers and eggplants in courses of “Genetics and Plant Breeding” is not only of utility for
those lecturers having experience in these crops, but also for lecturers that use or want to
introduce vegetable crops in the practical sessions in courses of “Genetics and Plant
Breeding” in Agriculture and Horticulture Faculties.
Keywords: Capsicum, genetic resources, Genetics and Plant Breeding, Horticulture and Agri­
culture degrees, practical classes, Solanum, teaching.
Introduction
The degrees imparted in Faculties of Agriculture and Horticulture usually include in their
syllabi general courses on “Genetics and Plant Breeding”. In our University (Uni­versidad
Politécnica de Valencia; UPV), the “Genetics and Plant Breeding” subject is included in the
degrees of Technical Engineer in Horticulture and Gardening (three-academic years degree)
and of Engineer in Agronomy (five-academic years degree). These courses are imparted in
the second and third academic years, respectively, when the students have already had
basic courses on Biology and Botany. Students of Engineer in Agronomy who take a major
in “Biotechnology and Plant Breeding” or “Plant Production” have further specialized and
widening courses related to Plant Genetics and Plant Breeding.
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Advances in Genetics and Breeding of Capsicum and Eggplant
The “Genetics and Plant Breeding” general courses are essential for knowledge of the
fundamentals of developing new improved cultivars, as well as to develop skills for the
optimization of the utilization of different types of cultivars in horticultural production
(Acquaah, 2007; Rodríguez-Burruezo et al., 2009a). In order to achieve these objectives,
in the UPV, the “Genetics and Plant Breeding” course includes units essential for
understanding the principles and practices of Plant Breeding, like fundamentals of
genetics; importance of variation, conservation and utilization of genetic resources;
genetic structure of plant populations; types of cultivars; elementary conventional
breeding methods for autogamous, allogamous, and asexually reproduced plants; as well
as an introduction to the application of the new biotechnologies to plant breeding
(Rodríguez-Burruezo et al., 2009a).
In the degrees of Technical Engineer in Horticulture and Gardening and Engineer in
Agronomy of the UPV, the “Genetics and Plant Breeding” subject has assigned 6 ECTS
(European Credits Transfer System) credits, of which 3 ECTS credits correspond to
lectures and 3 ECTS credits to practical classes (Rodríguez-Burruezo et al., 2009b).
This distribution of credits shows that practical sessions are considered as very
important for successful and efficient teaching of these “Genetics and Plant Breeding”
courses. Laboratory and greenhouse practical classes, including contact with and
utilization of plant material are essential for adequate teaching and understanding of
this subject. Given that during the last years the “Genetics and Plant Breeding”
subject has around 60-100 students for the degree ofTechnical Engineer in Horticulture
and Gardening and around 100-150 students for the degree of Engineer in Agronomy,
there are several groups of practical classes, each of which has a maximum of 25-30
students. Therefore, planning of practical classes must take into account that
lecturers have to deal with a considerable number of students in these classes and
that the degree of expertise of students in laboratory techniques and management of
plants is still limited.
The materials used in these practical classes have to be chosen adequately so that they
allow the objective of facilitating the learning process and acquiring skills. In addition,
research work done by the academic staff provides feedback for the practical and
provides the lecturers with first hand examples as well as with plant material that can
be used in these practical classes. In this respect, lecturers who are involved in research
on Capsicum and/or eggplant genetics and breeding have interesting material that can
be used as support for their practical classes. Peppers and eggplants can be grown easily
both in greenhouse and open field, present a wide diversity of materials with an ample
variation for many morphological and agronomic traits, and are amenable to the
application of in vitro culture and to the use of molecular markers for plant breeding
programmes. Here, we evaluate the applicability of Capsicum and eggplant materials in
the practical classes of the courses on “Genetics and Plant Breeding” at the UPV. Our
aim is to provide information to lecturers teaching courses of “Genetics and Plant
Breeding” on possible uses of Capsicum and eggplant materials in the practical classes,
as well as to stimulate further development of the use of these resources ps in such of
University courses.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Capsicum and eggplant materials for “Genetics and Breeding” practical classes
In the UPV, the 3 ECTS credits of practical classes of the “Genetics and Plant Breeding”
subject are divided into 15 two-hour sessions which take place either in the laboratory,
or in the greenhouse. In addition, students can also be required by the lecturers to
monitor some of the activities done (e.g., results of crossings, development of in vitro
cultures, etc.) as part of autonomous work to be done by themselves. The 15 practical
classes are divided into five modules, each of which consists of three practical classes:
1) fundamentals of genetics; 2) genetic resources and variation; 3) reproductive biology;
4) evaluation of traits of agronomic interest; 5) biotechnological tools in plant breeding
(Table 1). An evaluation of the potential suitability of Capsicum and eggplant materials,
based on the experience of the authors, to each of these five practical classes modules
has been performed (Table 1) and is presented and discussed.
Table 1. Practical classes imparted in the “Genetics and Plant Breeding” subject at the UPV,
materials currently used, and potential suitability of Capsicum and eggplant materials
for being used in each class as assessed by the authors.
Practical class
Materials currently used
Potential suitability of
Capsicum and eggplant
materials
Mitosis
Meiosis
Mendelian genetics
Fundamentals of Genetics
Onion
Tradescantia pallida
Maize
Genetic resources and variation
Low
Low
High
Genetic resources
characterization
Different species of vegetables
High
Wild relatives and
domestication traits
New crops
Floral biology
Pollen fertility
Hybridization
Resistance to pests
Resistance to diseases
Quality traits
Micropropagation
DNA extraction
Molecular markers
Different species of field and horticultural
crops
New World Solanaceae horticultural crops
Reproductive biology
Different species of field, horticultural and
ornamental crops
Hibiscus, maize, Cucurbitaceae, Solanaceae,
Tradescantia pallida, beans
Solanaceae and Cucurbitaceae species
Evaluation of traits of agronomic interest
Cultivated and wild species of Solanaceae
Virus susceptible and hypersensitive resistant
materials of Solanaceae crops
Different species of vegetables
Biotechnological tools in Plant Breeding
Coleus blumei and pepino (Solanum muricatum)
Solanaceae and Cucurbitaceae crops
Virus susceptible and hypersensitive resistant
materials of Solanaceae crops
High
Medium
High
High
High
High
Medium
High
Medium
High
Medium
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Advances in Genetics and Breeding of Capsicum and Eggplant
Fundamentals of Genetics module
Two of the practical classes include the study of the genetic material during cell division
in somatic cells (mitosis) and in reproductive cells (meiosis). Mitosis is studied in actively
growing onion roots, which through a simple and well established procedure, allows
observing all the phases of mitosis under the microscope (Helms et al., 1997). Observation
of mitosis in Capsicum and eggplant is possible, but requires actively dividing tissues
(Shopova, 1986; Bletsos et al., 2000), and the use of these plant materials does not seem
to provide advantages over the present use of onion roots, as chromosomes in onion
roots are large and very dark when stained. Also, a highly efficient protocol exists for the
observation of the different phases of the two divisions of meiosis in developing anthers
of Tradescantia pallida (Hammersmith and Mertens, 1997). As with mitosis, observation
of meiosis in Capsicum and eggplant is also possible (Shopova, 1986; Traas et al., 1989),
but again, the use of these materials do not provide advantages to the established
protocol with Tradescantia pallida.
Finally, the Mendelian genetics practical class is performed using maize cobs in which
the phenotype of the zygote is observed for the colour grain (purple vs. yellow) and
grain texture (smooth vs. wrinkled). In this way, by counting the number of individual
grains in cobs corresponding to the parents, F1, F2, and backcross generations it is
possible to study the inheritance of traits in monohybrid and dihybrid crosses. Use of
Capsicum and eggplant materials in this practical session requires the use of a high
number of individuals in which the unambiguous classification of individuals in different
classes. In this respect, in the case of peppers, inheritance of fruit colour-related traits
like “yellow vs. red” and “red vs. brown” might be utilized in practical lessons. Yellowfruited colour is recessive to red-fruited colour, as yellow colour is conferred by a
recessive mutant allele (Hurtado-Hernández and Smith, 1985). In the same way, brownfruited genotypes have the red carotenoid pigments typical of red fruits, but they also
carry a recessive mutation which avoids chlorophyll degradation during ripening (Dewitt
and Bosland, 1996). Consequently, the combination of typical red/yellow/orange
carotenoids with green chlorophyls results in its characteristic brown/chocolate colour
at the ripening stage. In this way, complete families (P1, P2, F1, F2, BC1, and BC2) can
be used to analyse the inheritance of these fruit colour types. In the case of eggplant,
the use of parental, F1, F2, and backcrosses generations in which the parents differ for
the genetic constitution for genes that affect the content in anthocyanins in the
hypocotyl could be of interest (Tigchelaar et al., 1968). This could allow the study of the
inheritance of the anthocyanin content in the hypocotyl in crosses in which this trait is
controlled by a single gene with dominance of the allele for content in anthocyanins (3:1
ratio in the F2) and in crosses in which the genetic control is by duplicate recessive
epistasis (9:7 ratio in F2). This has the advantage that this practical classes would use
real plants, instead of grains, and would also have the advantage that the students
would have to sow the seeds and take care of the plants, which complements their
formation in plant production.
Genetic resources and variation module
The first practical class in this module consists in the characterization of genetic
resources, in which students observe the variation in different materials of vegetable
crops and use descriptors for the characterization of genetic resources. Use of Capsicum
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Advances in Genetics and Breeding of Capsicum and Eggplant
and eggplant materials is highly applicable to this practical class, as a high diversity
exists for morphological traits in the plants and fruits of peppers and eggplants, which
include five cultivated species for pepper (C. annuum, C. baccatum, C. chinense, C.
frutescens, and C. pubescens) and three for eggplant (S. aethiopicum, S. macrocarpon,
and S. melongena) (Pickersgill, 1997; Daunay, 2008). Also, well established and easily
applicable descriptors exist for both crops (IBPGR, 1990; IPGRI et al., 1995).
The second practical class in this module deals with the study of wild relatives of crops
and the changes associated with domestication. In the case of Capsicum, differences in
plant and fruit traits can be observed between pungent (wild trait) and sweet peppers
(mutant trait) (Bosland and Votava, 2000), as well as between domesticated peppers, like
C. annuum var. annuum, C. baccatum var. pendulum, C. chinense, C. pubescens, and wild
relatives (e.g. C. annuum var. glabriusculum, C. baccatum var. praetermissum, C.
chacoense, C. eximium). For eggplant, the study of the differences between the common
eggplant (S. melongena) and its wild ancestor (Solanum incanum) allows studying an
important number of traits modified as a result of the domestication process, including
prickliness, number of flowers per inflorescence, fruit size, fruit colour, or bitterness
(Frary et al., 2003).
This module finishes with a practical class on introduction and improvement of new
crops, which consists in describing the characteristics of several potential new crops
and the challenges for breeders for a successful introduction under our conditions.
This practical class is mostly focused on Solanaceae species from the New World with
potential for introduction under our conditions, like the pepino (Solanum muricatum),
cape gooseberry (Physalis peruviana), tree tomato (Solanum betaceum) and naranjilla
(Solanum quitoense) (Prohens et al., 2004). An addition to these Solanaceae, potential
new crops could include the aji (C. baccatum) and rocoto (C. pubescens), profusely
utilized in the Andean cuisine and whose demand has increased in Spain due to the
increase in the immigrant population from South America and the increasing interest
in ethnic foods (Rodríguez-Burruezo et al., 2009c). Other potential new crops include
the scarlet (S. aethiopicum) and gboma (S. macrocarpon) eggplants, which are of
African origin and might be interesting as new crops for Mediterranean regions (Dau­
nay, 1996). In fact, scarlet eggplant is a traditional crop in the South of Italy (Sunseri
et al., 2007). Problems of adaptation, variation, types of cultivars, and objectives of
breeding programmes for the introduction of these potential new crops, as well as the
observation of plants in the greenhouse can be introduced in this practical class about
new crops.
Reproductive biology module
Study of floral biology is done through the observation of the floral morphology and the
reproduction system of different species. Materials studied include systems that favour
allogamy, like dioecy in date palm and asparagus, monoecy in maize, monoecy and
andromonoecy in cucurbits, pollination by hummingbirds (ornithophily) in Hibiscus and by
bumblebees (entomophily) in Iris, and mechanisms that favour self-pollination, like
cleistogamy in beans and wheat. Capsicum and eggplant flowers can be studied as examples
of hermaphroditic flowers in materials that are self-compatible but that may have a
certain degree of allogamy when the conditions are favourable for pollination (Pickersgill,
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Advances in Genetics and Breeding of Capsicum and Eggplant
1997; Daunay, 2008). Furthermore, local varieties or wild relatives of eggplant, with
multiple inflorescences can be used as an example of functional andromonoecy, in which
the basal flower of the inflorescence is a functional hermaphrodite with exserted stigma
and large ovary and protected by prickles, while the other flowers are more exposed and
mostly behave as functional male flowers with inserted stigma, small ovary, and without
protective prickles (Anderson and Symon, 1989).
The pollen fertility practical class consists in estimating pollen viability through two
different staining techniques: one of them estimates viability by staining the pollen
grains with acetocarmine, which allows observing morphology and degree of staining of
viable and non-viable pollen grains; the other is staining with 3-(4,5-dimethylthiazol-2yl)-2,5-diphenyltetrazolium bromide (MTT) which allows distinguishing pollen grains
having enzymatic activity (stained) from those having no or low activity (not stained)
(Shivanna and Tangaswamy, 1992). Different species are observed, which allows
comparing the two methodologies for estimating viability and also comparing the
morphology of different species as well as the pollen viability of different materials.
Pepper and eggplant flowers have an abundance of pollen which is easy to extract from
anthers, and therefore is suitable material for being included in this practical class.
Furthermore, male sterile materials, like interspecific hybrids with a high degree of
sterility, such ashybrids between S. melongena and S. aethiopicum or S. macrocarpon
(Daunay, 2008) or materials of the cultivated species having cytoplasmic or nuclear male
sterility (Shifriss, 1997; Isshiki and Kawajiri, 2002) can be used to observe low levels of
pollen viability.
In the practical class on hybridization students learn how to make crosses in different
plants and observe the development of the crosses performed. Materials conventionally
used are Solanaceae and Cucurbitaceae crops, on which students make self-pollinations
and hybridizations. Capsicum and eggplant materials are especially well suited for this
practical session, as they provide an abundant and continuous supply of flowers and the
size and morphology of the flowers allow easy emasculation and pollination as well as
the tagging and bagging of the pollinated flowers. Thus, students can make self-polli­na­
tions, cross-pollinations, and interspecific hybridizations between different species of
Capsicum and eggplants (Crosby, 2008; Daunay, 2008).
Evaluation of traits of agronomic interest module
In the practical class for evaluation of resistance to pests and diseases, the students
observe different levels of tolerance or resistance response in cultivated plants and
related species. Some eggplant materials could also be very well suited to the practical
class on resistance to pests. For example, comparison of different levels of infestation of
spider mites can be done by comparing S. melongena (susceptible) and S. macrocarpon
(resistant) plantlets grown in the same tray and artificially infested with Tetranychus
urticae mites (Schaff et al., 1982). In the case of resistance to diseases, normally, this
practical class is done by observing hypersensitive resistance and symptoms after
inoculation with viruses that are easy to manipulate and inoculate, like the Tomato
Mosaic Virus (ToMV) in segregating generations for the Tm22 gene of tomato. These
materials are subsequently used for the practical session on molecular markers. In
peppers, this practical lesson could be based on the Tsw gene identified in the C. chinense
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Advances in Genetics and Breeding of Capsicum and Eggplant
accession PI-152225, which provides resistance to some Tomato Spotted Wilt Virus (TSWV)
strains which affect peppers (Black et al., 1991). Although the use of easy and reliable
protocols of virus inoculation, observation of symptoms, classification of individuals to be
used in a classroom are not fully developed for eggplant, an interesting addition to the
practical session would be the observation of resistance to Meloidogyne nematodes
previously inoculated in susceptible materials of S. melongena and in resistant materials
of S. torvum (Daunay and Dalmasso, 1985). This would also allow the introduction of
breeding techniques for the selection of rootstocks when no resistance is found in the
cultivated species.
Finally, a practical class on quality traits is performed. In this practical class, the
evaluation of some internal and apparent quality traits is made by the students. In this
case, peppers and eggplants seem especially suited. For example, evaluation of
different levels of pungency of peppers can be evaluated by means of the Scoville
scale, which is based on an easy to perform organoleptic test (Scoville, 1912). In the
case of eggplant, browning of different materials can be evaluated with a colourimeter
using the protocols devised by Prohens et al. (2007). Similarly, the bitterness of
cultivated species with different levels of saponins (S. melongena, S. aethiopicum, and
S. macrocarpon) and wild related materials can be evaluated by using the froth index,
in which fruits are quartered, frozen and thawed, and then 10 ml of the juice is poured
in a test-tube, shaken vigorously, and the heigth of froth measured in milimeters
(Polignano et al., 2010).
Biotechnological tools in Plant Breeding module
Micropropagation is used to introduce the students to in vitro culture procedures. At
present, in vitro culture is done by cultivating explants of the ornamental plant Coleus
blumei and of pepino (Solanum muricatum). Both plants root easily and develop quickly
in basal MS medium, and are vegetatively propagated in agricultural practice, and
therefore this practical class is useful to introduce the students to highly efficient
techniques for vegetative propagation of selected clones. Peppers and eggplants can
also be micropropagated in vitro (Kamat and Rao, 1978; Christopher and Rajam, 1994),
but the growing media require growth regulators and plantlets take more time to develop
than Coleus blumei or pepino. Therefore Capsicum and eggplants do not represent a
significant contribution over presently used materials.
The DNA extraction practical class consists in isolating DNA from fresh leaf tissue of
Solanaceae and Cucurbitaceae materials using a modification of the Doyle and Doyle
(1987) method. In this respect, peppers and eggplants can be used for this practical
session, as the procedure for DNA extraction in these species using this method provides
significant amounts of good quality DNA.
Finally, the molecular markers practical class makes use of tomato plants from segregating
generations tested for resistance to ToMV and screened with a SCAR marker linked to the
gene of resistance Tm22 (Dax et al., 1998). In the case of peppers, molecular markers
linked to L4 (PMMoV) and Tsw (TSWV) resistance genes (Moury et al., 2000; Matsunaga et
al., 2003) exist and could be used in these practical lessons. This would allow de­
monstration of the utility of marker assisted selection in breeding programmes.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Conclusions
Capsicum and eggplant materials represent resources of interest for most of the practical
sessions for a basic course on “Genetics and Plant Breeding” in Faculties of Horticulture
and Agriculture. These materials are not only of interest to lecturers who research or
have experience with peppers and eggplants, but are also suitable material for those
lecturers who want to use vegetable crops materials in their practical sessions.
Acknowledgements
This research has been partially financed by the Ministerio de Ciencia e Innovación
(grants RF2008-00008-00-00 and AGL2009-07257).
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Public and commercial collections of heirloom eggplant and pepper: a case study
G. Roch, J.P. Bouchet, A.M. Sage-Palloix, M.C. Daunay
INRA, Génétique et Amélioration des Fruits et Légumes, UR 1052, BP 94, 84143 Montfavet cedex, France.
Contact: [email protected]
Abstract
An analytical and comparative study of public and commercially available heirloom
germplasm was carried out for eggplant and pepper in a public institution (INRA) collection
and in two commercial catalogues of heirloom varieties (Garden Seed Inventory, and
Kokopelli). A methodology was set up for selecting, gathering, and formatting the data
within a single file for each crop and source. Although the geographical origin was better
known for INRA accessions than for commercial heirloom varieties, and although INRA
material was better characterized for traits of agronomic interest in this case study, it was
possible to approximate the level of duplication between the three sets. For all germplasm
sets the distribution of the accessions for their geographical provenance reflects the origin
and diversity centres of each crop. INRA germplasm was characterized for some agronomic
traits, but comparison with the other germplasm was limited because of insufficient
common descriptive data. Nonetheless, for the case studied public and commercial
collections of heirloom eggplant and pepper each have their own value and uniqueness.
This indicates complementarities between public and private efforts of safeguarding and
conserving eggplant and pepper genetic diversity.
Keywords: Solanum melongena, Capsicum spp., genetic resources, descriptors, duplication,
comparison.
Introduction
The availability of well characterized plant genetic resources is an important pre­
requisite for crop improvement and genetic research. Public collections of germplasm
are kept in Europe by official entities, including gene banks and research institutes.
However, various seed companies and associations also maintain genetic resources,
independent of public initiatives. The European Cooperative Programme for Plant
Genetic Resources (ECPGR), created in 1980, facilitates collaboration between public
institutions and Non Governmental Organisations (NGOs) in over 40 European countries.
The ECPGR Solanaceae working group (http://www.ecpgr.cgiar.org/Workgroups/
solanaceae/solanaceae.htm) in charge of eggplant (Solanum melongena L.), pepper
(Capsicum spp.), and other genetic resources of the Solanaceae, created an accessible
on line database for eggplant (http://www.bgard.science.ru.nl/WWW-IPGRI/eggplant.
htm) and pepper (http://www.ecpgr.cgiar.org/Databases/Crops/Pepper.htm). These
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include passport data and sets of plant descriptors on germplasm held by an increasing
number of European countries.
The case study presented here aimed at developing a methodology for investigating and
comparing, for the first time, the eggplant and pepper germplasm held by the public and
private sectors. The INRA collection was chosen as representative of a public collection.
The heirloom varieties commercialized in North America and gathered within a catalogue
edited by Seed Savers Exchange (SSE), as well as the online French catalogue of Kokopelli
(KK) were chosen to represent germplasm in the private sector.
Material and Methods
Collections
INRA eggplant and pepper collections were created in the 1960s as a basis for genetic
research and crop improvement programmes. They include hundreds of accessions from
far-flung corners of the world (landraces, traditional varieties, contemporary varieties,
wild forms, all conserved as pure lines, and cultivated and wild relatives), as well as
accessions with specific genetic characteristics, such as a resistance towards a given
pathogen or a given race or pathotype of a given pathogen. We chose 473 unique eggplant
accessions and 1176 unique pepper accessions for the purposes of this study.
NGOs, including some seed companies and associations, also hold plant germplasm,
often advertised as “heirloom varieties.” These heirloom varieties include domestic and
foreign landraces, traditional as well as contemporary varieties, often noted for their
exceptional flavor. This material is mostly intended for exchange or sale to gardeners
and small farmers. There are several NGOs in Europe dealing with vegetable genetic
resources such as Arche Noah, Henry Double Day Research Association, and Kokopelli; as
well as seed companies such as Graines Baumaux, Ferme de Ste Marthe, and Graines
Voltz that feature open pollinated varieties. However, the number of eggplant and
pepper varieties held by these European bodies is much lower than INRA’s. In order to
obtain a better cross section of the material held by the private sector, and to optimize
the number of accessions from both types of collections, we choose to use the much
larger list of heirloom varieties contained in the Garden Seed Inventory (GSI) published
by Seed Savers Exchange (SSE), a non profit organization founded in 1975 and committed
to saving heirloom garden seeds from extinction (http://www.seedsavers.org/). The GSI
compiles all non hybrid varieties, mostly heirloom varieties, available through commercial
mail order catalogues in North America. We used the sixth edition of this “catalogue of
catalogues” (published in 2004) which lists 102 eggplant and 669 pepper varieties from
more than 200 commercial sources. SSE has an extensive germplasm collection which is
far more inclusive, but we did not have access to that data at the time of this study. We
also used Kokopelli’s (KK) 2008 on line list of varieties to represent a European NGO,
even though it had only 30 eggplants and 149 peppers.
Data used
For the INRA collections, passport, descriptive, and evaluation data, are managed in
homemade databases, and run with DBASE3 software for eggplant and Microsoft ACCESS
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Advances in Genetics and Breeding of Capsicum and Eggplant
for pepper. The INRA passport data are derived from the Multicrop Passport Descriptors
(http://www.bioversityinternational.org/publications/publications/publication/issue/
multicrop_passport_descriptors.html) and were restricted for this study to the accession
number, accession name, and geographical origin. The INRA morphological descriptors are
derived from IPGRI descriptors for eggplant (http://www.bioversityinternational.org/
publications/publications/publication/issue/eggplantaubergine.html) and for pepper
(http://www.bioversityinternational.org/publications/publications/publication/issue/
emvapsicumen.html); but for our purposes only a subset was used. INRA data relevant for
our analytical and comparative purposes were transferred to two Microsoft EXCEL files,
one for each of eggplant and pepper.
The GSI and KK on line catalogue provide informal workaday information about each
variety, for example, its name, geographical origin, and brief descriptions of fruit
characteristics. This information, if sufficient for farmers and gardeners, is much less
detailed and structured than that contained in INRA databases tailored for research
purposes. However, it is likely that the private stakeholders possess more information on
the varieties than the ones published in their catalogues. In order to harmonize the
available data of GSI and KK heirloom varieties with those of INRA, we acquired and
formatted them within two EXCEL files (one file for eggplant and one for pepper) similar
to the EXCEL files of INRA material. Unfortunately, much data were missing and that
limited comparisons between collections.
Organization of a virtual electronic collection and identification of duplicates
In order to be able to detect the duplication within and between the INRA, GSI and
KK collections (i.e. the repeated presence of same accessions), the data from the
three collections were merged and re-organized within a single file for each crop.
Each file constituted the virtual collection of eggplant and pepper. Three new columns
were created:
—Column (a), for hosting the code number identifying each collection,
—Column (b), for hosting a sequential code number of each accession within each
co­llection,
—Column (c), for hosting a sequential code number of each accession within the vir­
tual collection.
• Identification of the duplicates WITHIN each collection:
Column (b) was filled in for each accession simultaneously with the identification of
duplicates within each collection. The identification of duplicates was done via a stepby-step process using a combination of three successive criteria. We searched first for
the existence of identical or similar variety names such as ‘Fing Yuon Purple’ and
‘Fengyuan Purple’; or ‘Udmalbet’ and ‘Udumalapet’. Such literally and phonetically
related names generally originate from typing errors or approximate phonetic
interpretation and transliteration of foreign names. The similarity for names can also
originate from the translation of a same name in different languages such as ‘Red Bull
Horn’ and ‘Corno di Toro Rosso’. The next step was the comparison of the geographical
origin of the varieties bearing identical or similar names. When the geographical origin
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Advances in Genetics and Breeding of Capsicum and Eggplant
was identical or proximate (e.g. India and Sri Lanka), the descriptions (mostly fruit
traits) of varieties of the same name and geographical origin were compared. If the
description matched, they were considered probable duplicates of each other. The final
decision for evaluating duplication was made by expert INRA curators of eggplant and
pepper collections. When two or more varieties were found to be identical, we labelled
each one a duplicate. Whatever their number, identical varieties form a group of
duplicates. Several groups of duplicates may exist. For a given collection, when duplicate
varieties were found, they were allocated the same sequential code number in column
(b), instead of an incremented (augmented) one as was the case for distinct varieties.
Duplicates were searched for only in GSI and KK lists, since the INRA list contained only
unique accessions.
• Identification of duplicates BETWEEN collections:
Column (c) was filled in for each accession simultaneously with the identification of
duplicates between the three collections of INRA, GSI and KK assembled in the
electronic virtual collection, each being duly identified by its code number in column
(a). The identification of duplicates was done, as before, by using the combination of
{accession name + geographical origin + description}. When duplicate varieties were
found within the file of the virtual collection, they were allocated the same sequential
code number in column (c), instead of an incremented one as was the case for distinct
(unique) varieties.
Calculation of the level of duplication WITHIN each collection
The number of duplicates within a given collection was calculated on the basis of the
information contained in columns (a) and (b), and of the total number of accessions. The
formalisation of the calculation is:
Given x is the number of duplicates within collection I,
Given NI is the total number of varieties of collection I,
The level of duplication within collection I is: Dwc = 100 * (x / NI).
Calculation of the relative level of duplication of one collection related to another one
The number of duplicates between collections was counted on the basis of the information
contained in columns (a) and (c). The formalisation of the calculation is:
Given NI, nd is the total number of non duplicated (i.e. unique) varieties of collection I,
Given NJ, nd is the total number of non duplicated (i.e. unique) varieties of collection J,
Given y is the number of varieties common to collection I and J, i.e. the number of
duplicates,
The relative duplication rate of collection I related to collection J is: RD I/J = 100 * (y /
NI, nd).
When collections I and J are reciprocally compared (I to J, and J to I), their relative
duplication rates are different (RD I/J ≠ RDJ/I) when their sizes differ (NI, nd ≠ NJ, nd).
The relative level of duplication was calculated for the six combinations of the collections
of INRA, GSI and KK taken two by two (INRA/GSI, INRA/KK, GSI/ INRA, GSI/ KK, KK/ INRA,
KK/ GSI).
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Results and Discussion
Level of duplication WITHIN and BETWEEN collections
There were no duplicates within INRA material used for this study, since the accessions
were chosen in that manner. The level of duplication within GSI material and within KK
material, was respectively 2% and 7% for eggplant, and 6% and 3% for pepper. These low
intra collection duplication rates are probably under-estimated, because geographical
origin was often unknown and descriptive information was limited (see further down).
With either eggplant or pepper, the level of duplication between INRA and the two other
collections (Table 1) was low, with a maximum of 4% for INRA pepper accessions that are
also found in the lists of GSI. This means that INRA collection includes mostly unique
varieties that are absent from either of the two other collections.
Table 1. Levels of duplication between the collections (RD I/J) of INRA,
Garden Seed Inventory and Kokopelli.
Collections compared (I/J)
RDI/J for eggplant
RDI/J for pepper
INRA / Garden Seed Inventory
3%
4%
INRA / Kokopelli
1%
2%
Garden Seed Inventory / INRA
15%
7%
Garden Seed Inventory / KK
22%
17%
Kokopelli / INRA
21%
18%
Kokopelli / Garden Seed Inventory
76%
77%
Although there is some duplication of the varieties of GSI with regard to those of INRA
(15% and 7% respectively for eggplant and pepper accessions), and to those of KK (22%
and 17%), it is relatively low. This indicates that GSI contains many unique varieties that
are not found either in INRA or KK collections.
There is a higher level of duplication of the varieties of KK with regard to those of INRA
(21% for eggplant and 18% for pepper); and a striking high level of duplication of the
varieties of KK with regard to those of GSI with 76% of eggplant and 77% of pepper KK
varieties that are also listed in the GSI. This result suggests a dependency between
private collections, at least for KK towards GSI.
The concept of duplication in germplasm is quite complex (Engels & Visser, 2006). It has
been theorized (e.g. van Hintum & Knüpffer, 1995; van Hintum, 2000; Germeir et al.,
2003) within the general framework of genebank management, and different categories
of duplicated material have been defined. The quality and detail level of the passport,
phenotypic and genetic information available for each accession has of course a direct
influence on the identification of duplicates, and hence on the level of duplication
determined within or between collections. However, the useful level of detail at which
duplicates are identified depends on the end user, such as geneticists or gardeners who
have different views of what traits should distinguish two accessions. The method of
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Advances in Genetics and Breeding of Capsicum and Eggplant
detection of duplicates that we used here, though poorly technical, was adapted to the
information at our disposal and on the whole, we can conclude that each of the three
collections compared has its own value and that the conservation efforts of INRA and
GSI, and to a lesser extent of KK, are complementary. Because of the high level of
duplication between the varieties of GSI and KK, we exclude this latter from the next
results presented.
Distribution of the geographical origin of the accessions of INRA and Garden Seed
Inventory
The countries of origin of the accessions roughly corresponded to the geographical origin
and diversification areas of eggplant (Fig. 1A) and pepper (Fig. 1B). The origin noted as
“mixed” for eggplant is for material issued from crosses between accessions of various
geographical origins. The most numerous eggplant accessions of INRA (43%) originate
from Asia, where the centres of origin (Indochina), of domestication (Indo-Burma region,
and probably also South West China) and primary diversification (India, China) of eggplant
are located, and from the secondary diversity centre, the Mediterranean basin (21%),
Fig. 1A. The rest is of diverse origins. This general geographical profile is also observed
for GSI material which is however characterized by a high frequency (66%) of varieties
of unknown geographical origin.
The high proportion of material of unknown origin is also observed for GSI peppers (52%),
Fig. 1B. Material from the American continent, which is the centre of origin of Capsicum
species, is clearly dominant (29% of the varieties) in the GSI germplasm when compared
to material of other origins (next is 10% of the varieties originating from Europe). The
INRA pepper collection includes also many American accessions (32%), but the proportion
of material from Europe, which is a secondary centre of diversification, is slightly higher
(36%). Asian and African pepper varieties are better represented in INRA collection (17%
and 10%) than by GSI (6% and 1%).
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A.
Advances in Genetics and Breeding of Capsicum and Eggplant
B.
Figure 1. Geographical origin of INRA and Garden Seed Inventory accessions
A. Eggplant (S. melongena); B. Pepper (Capsicum spp.).
INRA eggplant collection: some major traits
Since this collection includes material of worldwide origin, some general conclusions can
be drawn. Whatever the geographical origin (data not shown), the absence of prickles/
spines on stems and leaves is much more frequent (85% of accessions) than their presence.
The opposite is observed for the fruit calyx since 67% of the accessions have a prickly
calyx. Solitary fruits are much more frequent (83% of accessions) than fruits in clusters.
Fruit shape, which displays a continuum of variation between round and long fruits, was
simplified to three classes: round, intermediate and long. Globally, fruits of intermediate
shape (43% of accessions) are more frequent than round (31%) and long (26%) shapes.
However, the relative proportion of these three fruit types varies with the geographical
origin of the accessions (data not shown). For instance, the Mediterranean material
tends to be more frequently long (37% of accessions) than round (34%) or intermediate
(29%). Globally, glossy fruited varieties are more frequent (65%) than dull fruited ones,
but this proportion varies also with the geographical origin of the accessions. Eighty
percent of the Mediterranean accessions, for example, were glossy for only 55% of the
Asian accessions. However these differences may be skewed because glossiness is
measured when the fruits have reached their full size, whereas Far Eastern varieties, in
particular Japanese ones, have very young fruits that are very glossy but rapidly turn
dull when their size increases.
Eggplant fruit colour depends on the presence and distribution of two pigments,
anthocyanins and chlorophylls (Daunay et al., 2004). We analyzed the presence or
absence of each of these pigments for the whole INRA collection. The simultaneous
presence of anthocyanins and chlorophylls is found for the wide majority (61%) of
accessions; this means that dark violet, dark purple, or black fruit is the most frequent.
Light violet or light purple fruit colour, resulting from the presence of anthocyanins and
absence of chlorophylls comes next, with 22% of accessions. This means that globally,
83% of the varieties have fruit epidermis with anthocyanins. Green fruits (12%), the
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result of the sole presence of chlorophylls, and white fruits (5%), the result of the
absence of both pigments, are much less frequent.
The higher frequency of intermediate fruit shapes as compared to round and long ones,
the higher frequency of purple fruit epidermis colour as compared to green, as well as
the low frequency of white fruits, were also found in a set of 622 Asian accessions,
originating mainly from India and characterized by Kumar et al. (2008). These trends,
as evidenced in two large and different sets of germplasm, are indicators of the
selection pressure applied to the species since its domestication from round and green
netted fruits. Kumar et al. (2008) also showed that the relative proportions of varieties
with different fruits shapes and colours vary with the Indian region or Asian countries
they originate. These geographical variations are also illustrated by the results of
Prohens et al. (2003) who found, for 67 traditional Spanish varieties, 37% round, 21%
intermediate and 42% long fruited varieties; and 96% of varieties with violet or purple
fruits. These authors also indicate a variation of these proportions from one Spanish
region to another. For Laos, an area of South East Asia where primitive (and wild)
eggplant types are common (Daunay et al, 2001), Plewa (2007) found that 40% of the
local varieties displayed round fruits and 43% displayed intermediate fruits. Long fruited
ones were less in evidence (16%) and the proportion of varieties with green fruits (63%)
was much higher than those with purplish (26%) or white (11%) fruits. These data from
Laotian varieties are interestingly skewed towards more ancestral traits (round and
green fruits), suggesting a weaker effectiveness of the selection pressure there for
these traits.
The higher frequency of accessions found in the INRA collection with prickle-less
vegetation, prickly calyces, and solitary fruits vs. clustered ones need to be compared
to other sets of germplasm in the future. These trends can be interpreted as the result
of a long lasting selection pressure for prickle-lessness which was more successful on
stems and leaves than on calyces; and of a strong selection pressure for single fruits,
probably because singleness favours an increase of fruit size.
INRA pepper collection: some major traits
The INRA pepper collection includes material garnered from many continents of which a
majority (78%) are C. annuum accessions. The rest consists of other cultivated species
(C. baccatum, C. chinense, C. frutescens, C. pubescens) and a few wild species. A large
sample of this collection was already characterized for several traits (Sage-Palloix et al.,
2007). We provide here further descriptive statistics based on a smaller sample of
accessions.
For C. annuum, fruit shape is diversified and the proportion of each shape type is
heterogeneous from one geographical area to another. For all geographical origins taken
together in order to get a global picture, the dominant type is elongated, sharp pointed,
and of various lengths (44% of accessions); followed by the triangular-horn shaped (22%),
square (16%), and rectangular (10%); with the remainder (8%) displaying other shapes
such as spherical, heart shaped, or bell shaped. These shapes are illustrated in SagePalloix et al. (2007).
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Pepper colour is diverse and we simplified its description into four states for immature
as well as for mature fruits. Green is by far the most frequent colour of unripe fruits
(90% of accessions), as compared to white (5%), yellow (4%) and black-violet (2%). At
maturity, red is the most frequent colour (90% of the accessions), when compared to
yellow (5%), orange (3%) and brown (2%). The correspondence between the percentages
of green and red fruits is an artifact, since red can originate from any immature colour.
INRA records for pungency include three levels: hot, moderately hot, and sweet.
However, since the number of moderately hot accessions was negligible, we combined
them with the hot accessions. Sweetness is more frequent (56% of the accessions) than
pungency (44%) in the INRA collection of C. annuum whereas it is rare in the other
Capsicum species (Fig. 2). These results are in line with those published on a larger set
of accessions by Sage-Palloix et al. (2007).
Figure 2. Distribution of INRA accessions of Capsicum species (C. annuum, C. baccatum,
C. chinense, C. frutescens, and other species) for pungency classified as hot or sweet.
If we assume that the INRA collection is a representative sample of the genetic diversity
of cultivated Capsicum species, these results indicate that C. annuum underwent a
longer or stronger selection pressure for sweetness than the other Capsicum species.
Comparison between INRA and GSI material
Given the many missing data for GSI eggplant and pepper material, we could only carry
out a comparison of pepper pungency (Fig. 3). We present this comparison between INRA
and GSI material only for C. annuum because GSI varieties belong mostly to this species
as do INRA accessions (respectively 85% and 78%), and because the vast majority of GSI
accessions of other Capsicum species are pungent (results not shown), as observed for
INRA material (Fig. 2).
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Figure 3. Distribution of varieties of INRA and Garden Seed Inventory
Capsicum annuum accessions for pungency.
Interestingly, the proportion of pungent vs. sweet varieties is reversed between INRA
and GSI collections: the INRA collection includes more sweet C. annuum accessions (56%)
than pungent ones, and GSI material includes more pungent varieties (61%) than sweet
ones. Perhaps this difference reflects the fact that GSI varieties are intended for North
American gardeners who may prefer more pungency.
Conclusions
The characterization and comparison of the collections of INRA (public) and GSI and KK
(commercial) were investigated for the duplication levels within and between
collections, as well as for a sample of agronomic traits. The method of detection of
duplicates used, based on accession name, geographical origin and plant description,
was adapted to the available information and makes horticultural and practical sense.
The level of duplication within and between collections that we obtained might be an
underestimate given the limited information at our disposal for geographical origin
and morphological description of the heirloom varieties held in the private sector,
since the less information, the less probability of detecting duplicates. However, even
if it is underestimated, the low duplication levels we detected between the material
of INRA and GSI provide a first indication of the complementarities of public –ex situ–
and commercially available –in situ– germplasm, which are both important for the
preservation of crop germplasm. It is however possible that commercial germplasm
collections are sometimes dependent to each other, as suggested by the fact that
three quarters of the varieties held by KK are duplicates of GSI material. The renewed
interest in home gardening, in particular in North America and Europe, stimulates
private companies commercializing heirloom varieties, and enhances the important
role of these cultivated collections of germplasm for the preservation of the genetic
diversity of cultivated plants.
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Our results also underline the importance of accurate passport and descriptive information
for effective comparisons between collections. Although the interaction between public
and private stakeholders has been limited, the evidence for low duplication of germplasm
strongly suggests that a dialogue between the two sectors, in particular for upgrading
passport and characterization data in commercial collections, would be beneficial.
Improved communication and collaboration between germplasm stakeholders, and
improved availability of the germplasm, are some of the goals of the ongoing European
effort, developed within the frame of ECPGR. This collaborative project aims in particular
to improve the quantity and quality of the data present in the European crop databases
in order to establish a centralized international, all-inclusive, public and private database.
The ECPGR AEGIS project (A European Genebank Integrated System) (http://aegis.cgiar.
org/about_aegis/objectives.html) will use these databases for a large scale analysis of
the duplication between public and private or commercial collections.
Acknowledgments
The authors thank A. Goldman, Seed Savers Exchange, for fruitful discussions, exchange of
information and critical review of this paper; Dr Jules Janick, Purdue University, USA and Dr
Jan Engels, Bioversity International, Rome, Italy, for their critical review of this paper, as
well as L. Maggioni, ECPGR, Bioversity International, Rome, Italy and Th. van Hintum, CGN,
The Netherlands, for providing references and articles on the concept of duplication.
References
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Daunay M.C.; Lester R.N.; Ano G., 2001: Eggplant. pp. 199-222 in Tropical Plant Breeding.
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collections. IPGRI Handbooks for Genebanks No. 6. IPGRI, Rome, Italy.
Germeir C.U.; Frese L.; Bücken S., 2003. Concepts and data models for treatment of
duplicate groups and sharing of responsibilities in genetic resources information
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Kumar G.; Meena B.L.; Ranjan Kar; Tiwari S.K.; Gangopadhyay K.K.; Bisht I.S.;
Mahajan R.K. 2008. Morphological diversity in brinjal (Solanum melongena L.)
germplasm accessions. Plant Genetic Resources: Characterization and Utilization
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Plewa M. 2007. Eggplant (Solanum melongena L.) –an example for a biodiversity hot spot
in Lao People’s Democratic republic (PDR) in South East Asia. pp 23-31 In:
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Prohens J.; Valcárcel J.V.; Fernández de Córdova P.; Nuez F. 2003. Characterization and
typification of Spanish eggplant landraces. Capsicum and Eggplant Newsletter 22:
135-138.
Sage-Palloix A.M.; Jourdan F.; Phaly T.; Nemouchi G.; Lefebvre V.,2007. Analysis of diver­
sity in pepper genetic resources: distribution of horticultural and resistance traits
in the INRA pepper germplasm. Pp 33-42. In: Niemirowicz-Szczytt K. (Ed.), Progress
in research on Capsicum & Eggplant. Warsaw University of Life Sciences Press,
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Van Hintum Th.J.L. 2000. Duplication within and between germplasm collections. III. A
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Taxonomic relationships of eggplant wild relatives in series
Incaniformia Bitter
John Samuels
Trezelah Barn, Trezelah, Gulval, Penzance, TR20 8XD, UK. Contact: [email protected]
Abstract
Solanum incanum L., and its allies in series Incaniformia Bitter are collectively known as S.
incanum sensu lato, and are wild relatives of the brinjal eggplant, S. melongena L. They
have been the subject of extensive taxonomic, plant breeding and genomic studies in
eggplant improvement over the last fifty years. There have been many difficulties in
ascertaining the precise taxonomic status, diagnostic characteristics and distribution of the
individual members of this group. In order to progress more consistently with eggplant prebreeding studies using these wild relatives, it is first necessary to provide a reliable
taxonomic framework upon which to base identification, characterisation and nomenclature
of taxa in this difficult group. The taxonomy of S. incanum s.l. is described, along with a
key for identification and information on distribution in Africa and the Middle East. Other
information suggests that S. campylacanthum is closely related to a common ancestor of
the S. incanum s.l. group. S. campylacanthum subsp. panduriforme and S. incanum seem
to have diverged away from S. campylacanthum-type predecessors in tropical E. Africa,
moving southwards or towards the Middle East, respectively. S. lichtensteinii probably
evolved from an even earlier ancestor in its migration towards southern Africa.
Keywords: Solanum incanum, Solanum melongena, species concept, variation, interfertility,
morphometrics.
Introduction
The taxonomy of species related to the eggplant remains a challenge (Daunay, 2008)-it is
complex and in need of clarification. In particular, the eggplant wild relatives known as
bitter tomatoes (Burkill, 2000; Matu, 2008; Tindall, 1983) have caused taxonomic difficulty
for a considerable time. S. incanum L. is the best known and consequently this group is
collectively referred to as S. incanum sensu lato (Lester and Hasan, 1991; Samuels, 1996),
or S. incanum L. agg. (Daunay et al., 2001a; Jaeger, 1985). They are classified as part of
series Incaniformia Bitter (1923) in subgenus Leptostemonum, the “spiny solanums.”
The various species are to be found across much of eastern and southern Africa, and
parts of western Africa and south-west Asia. The bitter tomatoes are typically ruderal
shrubs or sub-shrubs with yellow berries, and often have a dense tomentum and prickles
(see Fig. 1). They may colonise roadsides and recently disturbed land, and sometimes
become invasive weeds in cultivated fields (Samuels, 2009).
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The highly variable nature of the bitter tomatoes has caused many problems with
identification (Samuels, 2009) and species delimitations within the group have been
difficult to establish. They also exhibit considerable interfertility (Jaeger, 1985; Lester
and Daunay, 2003; Lester and Hasan, 1990, 1991; Pearce, 1975; Samuels, 1996, in press).
Furthermore, S. incanum L. s. str. has been confused with the closely related S.
melongena L., brinjal eggplant (Samuels, unpubl.) and the more distantly related S.
aethiopicum L., scarlet eggplant and S. macrocarpon L., Gboma eggplant (Lester and
Hasan, 1991). The taxonomy of the bitter tomatoes has consequently challenged many
authors (eg Furini and Wunder, 2004; Karihaloo et al., 2002; Lester and Daunay, 2003;
Lester and Hasan, 1991; Mace et al., 1999; Olet and Bukenya-Ziraba, 2001).
Figure 1. S. incanum L. s. str. (photo: courtesy of Radboud University
Botanical and Experimental Garden, Netherlands).
S. incanum L. is believed to be the wild ancestor of the brinjal eggplant (Daunay et al.,
2001b; Lester and Daunay, 2003; Lester and Hasan, 1991; Samuels, 1996; Weese and
Bohs, 2010) and along with its close relatives continues to be the subject of research
associated with eggplant improvement (eg. Behera and Singh 2002; Behera et al., 2006;
Furini and Wunder, 2004; Isshiki et al., 2008; Lester and Daunay, 2003; Singh et al.,
2006). In this light, the definitive taxonomy of the bitter tomato group would enable
consistency in programmes of pre-breeding research.
Taxonomy of S. incanum s.l.
Since the 1920s the tendency has been to classify the numerous taxa associated with S.
incanum into informal groups without precise nomenclatural designations (eg Bitter,
1923; Jaeger, 1985; Lester and Hasan, 1991; Whalen, 1984). Further taxonomic progress
on the bitter tomatoes was only made possible by the much-needed typification of S.
incanum L. s. str. and S. insanum L. (Hepper and Jaeger, 1985), and S. campylacanthum
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Advances in Genetics and Breeding of Capsicum and Eggplant
Hochst. ex A. Rich and S. panduriforme E. Meyer ex Dunal (Lester, 1997). However, some
researchers in Asia believe that the identity and affinities of S. insanum are still in
dispute. There also remains a lack of clarity over synonymy and species identities of
some taxa associated with S. panduriforme (Lester, unpubl.). In spite of such
discrepancies, the present paper attempts to clarify the taxonomy of S. incanum s.l. as
we understand it according to information published to date. In addition, recent studies
on S. incanum s.l. (eg. Mace et al., 1999; Samuels, 1996, in press) have tended towards
a broader species concept and a reduction in the number of recognised species. This has
made up-to-date taxonomic keys and descriptions easier to prepare.
Historically, taxa associated with S. campylacanthum and S. panduriforme have been
allocated a diversity of names. Many of these are synonyms (Samuels, unpubl.).
Furthermore, most taxa exhibiting variation beyond that expected for such highly
variable plants might best be conferred with infra-specific status, as for many of Bitter’s
(1923) recombinations of Dammer’s taxa (Samuels, in preparation). Samuels (in press)
performed an investigation into the taxonomic relationships within S. incanum s.l.,
which he considered to consist of just four species. This involved a study of interfertility
between S. campylacanthum, S. panduriforme, S, incanum and S. lichtensteinii Willd.
from Africa and the Middle East, and the morphometric analysis of African S.
campylacanthum and S. panduriforme. The findings of Samuels’ study confirmed several
of those of Lester and Hasan (1991) and also showed that S. panduriforme is a subspecies
of S. campylacanthum, and that S. incanum and S. lichtensteinii are distinct species.
Distribution and spread of S.incanum from Africa to the Middle East
The common ancestor of S. incanum s.l. may have originated in tropical East Africa and
resembled S. campylacanthum (Samuels, in press) which is probably a more ancient
bitter tomato taxon (Mace et al., 1999; Sakata and Lester, 1994; Samuels, 1996, in
press). Diversification possibly commenced around one million years ago (Samuels, 1996)
and the information in Fig. 2 may give an insight into this process of evolution and
spread through Africa and S.W. Asia.
Subspecies campylacanthum has a distribution (“camp”) which is centred in eastern Africa,
and it is therefore based largely in the ancestral zone. The distribution of subspecies
panduriforme (“pand”) covers the ancestral zone and extends into southern and southwestern Africa. The distribution patterns of the two subspecies are consistent with divergence
away from the common ancestor, although both taxa still partly occupy the ancestral zone.
S. incanum and S. lichtensteinii distributions (“inc” & “licht”) extend further out from the
ancestral zone. The evolving S. incanum seems to have migrated away from East Africa,
moving north-eastwards to the Middle East. The distribution of S. lichtensteinii lies solely in
the southern hemisphere with little obvious connection to the ancestral zone in eastern
Africa. This is an indication that the evolving S. lichtensteinii moved away from the ancestral
zone and migrated towards southern Africa at an even earlier stage. The distinctive DNA
found in S. lichtensteinii compared with other bitter tomatoes (Mace et al., 1999; Sakata
and Lester, 1994, 1997; Weese and Bohs, 2010), and reproductive isolation from S. campy­
lacanthum (Samuels, in press) support an earlier divergence.
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inc
camp
licht
pand
Figure 2. Distribution of S. incanum s.l. in Africa and the Middle East
(after Samuels, in press; Samuels and Lester, in preparation; for key see text).
Key to the species and subspecies
Shrubs or sub-shrubs, always less than 2m high; branches robust, up to 7mm diam.,
densely tomentose with stellate hairs; always armed on shoots, leaves, inflorescence
axes, and calyces and pedicels of hermaphrodite flowers; leaf lamina ovate; corolla
violet, purple, or white.
Leaf lamina narrowly ovate, margin always lobed, sub-repand; inflorescence 1-5flowered; corolla white (rarely violet), 2.5-3.0cm across; fruiting calyx manifestly
robust, heavily armed, lobes strongly reflexed; berry 3.5-4.5cm diam.
... S. lichtensteinii
Leaf lamina broadly ovate, margin subentire to lobed, strongly repand; inflorescence
1-15-flowered; corolla violet to purple, 2.5-3.0cm across; fruiting calyx enlarged, ±
armed, lobes slightly reflexed; berry 3.0-3.5cm diam.
... S. incanum
Shrubs, sub-shrubs or herbaceous perennials up to 2m or more high; branches up to 4mm
diam., sparsely tomentose with stellate hairs; armed or unarmed; leaf lamina lanceolate
to elliptic; corolla violet or purple.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Leaf lamina ovate-lanceolate or lanceolate, margin subentire to lobed, base rounded or
oblique; inflorescence 3-15 (-50)-flowered; corolla violet or purple, 2.0-3.5cm across;
berry 2.5-3.5cm diam.
... S. campylacanthum subsp. campylacanthum
Leaf lamina elliptic, margin entire to subentire, base ± attenuate; inflorescence 3-12flowered; corolla violet, 1.5-3.0cm across; berry 2.0-2.5cm diam.
... S. campylacanthum subsp. panduriforme
The species and subspecies
S. campylacanthum A. Rich. subsp. campylacanthum subsp. nov.. Highly variable group
of ± tomentose, ± armed shrubs, up to 2m or more high, with lanceolate, ± lobed leaves.
Inflorescence with up to 50 violet or purple flowers, up to 15 or more hermaphrodite,
producing yellow fruits up to 3.5cm diameter. Distribution across tropical eastern Africa,
tropical savanna regions.
S. campylacanthum A. Rich. subsp. panduriforme comb. nov.. Uniform group of finely
tomentose, sparsely armed or unarmed shrubs, sub-shrubs or herbaceous perennials, up
to 2m high, with elliptic, entire to sub-entire leaves. Inflorescence with up to 12 violet
flowers, up to 3 hermaphrodite, producing yellow fruits, up to 2.5cm diameter. Distribution
across eastern and south-eastern Africa, tropical savanna and hot semi-arid regions.
S. incanum L. (Fig. 1). Densely tomentose, strongly armed, shrubs, less than 2m high,
with broadly ovate, sub-entire to lobed leaves. Inflorescence with up to 15 purple or
violet flowers, up to 3 hermaphrodite, producing yellow fruits, up to 3.5cm diameter.
Distribution across north-east Africa and Middle East to south-east Iran, possibly further,
hot semi-arid regions.
S. lichtensteinii Willd.. Densely tomentose, strongly armed shrubs or sub-shrubs, usually
0.5-1m high, with narrowly ovate, lobed leaves. Inflorescences with up to 5 white (rarely
violet) flowers, up to 3 hermaphrodite, producing yellow fruits, up to 4.5cm diameter.
Distribution across much of southern Africa, tropical savanna and hot semi-arid
regions.
Further study
The proposed evolutionary and geographical divergence of S. incanum s. str. from its
African ancestor were formative events which would eventually have led to the
evolution and domestication of the brinjal eggplant. The precise taxonomy of this crop
and its wild and weedy relatives in Asia remains unclear. Further studies (Samuels, in
preparation) on their taxonomy, distribution and phylogeny will enable a better
understanding of this group.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Acknowledgements
I would like to record my gratitude for expert advice and guidance given by the late Dr.
Richard Lester, my mentor for nine years at Birmingham University.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Use of morphological description and DNA analysis for the detection
of duplicities within the Czech germplasm collection of pepper
H. Stavělíková, P. Hanáček, T. Vyhnánek
Department of Vegetables and Special Crops Olomouc, Crop Research Institute, Šlechtitelů 11,
783 71 Olomouc - Holice, the Czech Republic. Contact: [email protected]
Abstract
The Crop Research Institute, Department of Vegetable and Special Crops, Olomouc, the
Czech Republic is holding the collection of pepper (Capsicum annuum L.) genetic resources.
The collection has very long tradition. The collection of pepper consists of 504 accessions
(acc.), currently. New accessions are obtained from seeds companies and other genebanks.
Many accessions have the same name, and this is why we chose 41 accessions for DNA
analysis. They were divided into ten groups according to the name. These accessions were
described according to Descriptors for Capsicum (Capsicum spp.) of IPGRI (1995) with 27
characters and with thedescriptor list by International Union for the Protection of New
Varieties of Plants (UPOV) (44 characters). Some characters are both in Descriptor and in
UPOV (plant habit, pedicel attitude, fruit colour etc.). Finally 54 characters were used for
pepper description. Photodocumentation was performed twice in the growing season– in
phase of flowering and in phase plants with the ripe fruits. We took photo of the detail of
fruit sideways look, top point of view, cross section, too. The polymorphism of DNA in
pepper was analysed using the SSR (Simple Sequence Repeats) method. We analysed 8 SSR
markers chosen in accordance with literature (SSR markers are localised on different
chromosomes). The dendrogram of similarity was constructed on based of statistical
evaluation. The possible duplications were found in 4 groups. The detection of duplications
leads to effective work with genetics resources. In future we would like to continue with
the determinative of duplications on the basis of molecular markers and morphological
description.
Keywords: pepper, Capsicum spp., genetic resources, microsatellites, SSRs, variability, morpho­
logical descriptors.
Introduction
Pepper is a very popular, widespread in the world, annual vegetable, to produce high
amounts of vitamin C, provitamin A, E, P (citrin), B1 (thiamine), B2 (riboflavin) and B3
(niacin) (Valšíková, 1987; Bosland & Votava, 2000). Various authors describe 25 species
to the genus Capsicum. (Basu & De, 2003). The oldest known records of pepper come
from the desert valley of Tehuacán, in Southern Mexico. It is known that the indigenes
were eating peppers as early 7000 B.C. Now we do know that peppers were among the
first plants to be domesticated in the Americas (Smith, 1984). Christopher Columbus
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Advances in Genetics and Breeding of Capsicum and Eggplant
brought the pepper to the Europe (Bosland & Votava, 2000). The pepper was known as
spice plant in 16th century in Bohemia (Müller, 1959). The intense growing of pepper in
the Czechoslovakia started after the First World War (Valšíková, 1987). It is necessary to
find duplications within collection for effective and rational work with genetics resources
on the national and international level (Dotlačil, 2007; ECPGR, 2008). At present, a
number of methods are used to evaluate the genetic diversity and variability in the
collections of genetic resources; e.g. morphological characteristics, analysis of the
genealogy, biochemical markers (in particular proteins and their various iso-enzyme
variants) and the dynamically developing molecular (DNA) markers (Zhang et al. 2007).
Within the DNA markers, the microsatellite markers (SSRs – Simple Sequence Repeats),
are especially useful due to their high degree of polymorphism and co-dominant character
of heredity. The use of microsatellite polymorphisms to study the genetic diversity and
variability was described for a number of plant species, e.g. in pea (Haghnazari et al.
2005), tomato (Wang et al. 2006) and rape (Li et al. 2007). The main aim of present
study was to evaluate the variability of SSR markers and morphological description in
selected accessions of pepper in the collection of the Crop Research Institute, Department
of Vegetables and Special Crops in Olomouc.
Material and methods
Plant material and characterization
The collection of pepper held by CRI consists of 504 accessions (acc.), currently (Sta­
vělíková et al. 2009). All accessions of pepper have been described for 27 characters
taken from Descriptors for Capsicum (Capsisum spp.)(Descriptor) [IPGRI, (1995)].
Documentation photos of all accessions have been taken. The passport data of the
collection are fully recorded, computerized and entered in EVIGEZ (Czech Information
System of Genetic Resources). http://genbank.vurv.cz/genetic/resources/) and in the
ECPGR (The European Cooperative Programme for Plant Genetic Resources) Pepper
Database http://www.ecpgr.cgiar.org/Databases/Crops/Pepper.htm. Main part of this
collection presents the old open pollinated varieties from Hungary, Soviet Union,
Czechoslovakia, USA, Bulgaria and Czech Republic (Stavělíková et al. 2009).
We chose 41 acc. pepper from the collection of pepper genetic resources to DNA analysis.
Twenty plants per accession were grown in isolation cages. The samples for DNA analysis
from three plants were taken in 17th July.
The accessions were split into ten groups according name (Table 1). These acc. were
described according Descriptor [IPGRI (1995)] – 27 characters and descriptor list by
International union for the protection of new varieties of plants (UPOV) (UPOV 2006) – 44
characters. Some characters are both in Descriptor and in UPOV (plant habit, pedicule
attitude, fruit colour etc.). Finally 54 characters were used for pepper description – 1
character in seedlings, 8 characters in the plants, 10 characters in leaves, 10 characters
in flowers and 25 characters in fruits. We took photo of the acc. twice per growing
season at phase of flowering and at phase plants with the ripe fruits. We took detailed
photo of fruits, too.
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Table 1. Analysed pepper accessions.
Order
Accession
number
Name
Country of origin
Order
Accession
number
Name
Country of origin
1. group Astrachanskij - former Soviet Union
6. group Japan Madarszem - Hungary
7
09H3100055
Astrachanskij
14
09H3100350
Japan Madarszem
8
09H3100056
Astrachanskij
28
09H3100351
Japan Madarszem
9
09H3100057
Astrachanskij
29
09H3100503
Japan Madarszen
10
09H3100058
Astrachanskij
30
09H3100504
Japan madarszen
12
09H3100059
Astrachanskij 147
31
09H3100505
Japan madarszen
11
09H3100541
Astrachanskij
7. group Kalocsai Fuszer (Edes) - Hungary
2. group Aufrechte Cayenne - France
2
09H3100243
Kalocsai Fuszer (Edes)
20
09H3100137
Aufrechte Cayenne
3
09H3100244
Kalocsai Fuszer (Edes)
21
09H3100138
Aufrechte Cayenne
4
09H3100245
Kalocsai Fuszer (Edes)
22
09H3100139
Aufrechte Cayenne
8. group Konservnyj Belyj 289 - former Soviet Union
23
09H3100140
Aufrechte Cayenne
3. group Bogyisloi - Hungary
18
09H3100354
Konservnyj Belyj 289
24
09H3100111
Bogyisloi
40
09H3100352
Konservnyj Belyj 289
25
09H3100112
Bogyiszloi
41
09H3100353
Konservnyj Belyj 289
26
09H3100113
Bogyiszloi
9. group Tetenyi - Hungary
27
09H3100114
Bogyiszloi Vastaghusu
32
09H3100067
Tetenyi
33
09H3100068
Tetenyi
4. group Hatvani - Hungary
13
09H3100416
Hatvani
34
09H3100069
Tetenyi
17
09H3100417
Hatvani
35
09H3100070
Tetenyi
16
09H3100418
Hatvani
1
09H3100071
Tetenyi
15
09H3100419
Hatvani Csemege
10.group Vinedale - Canada
5. group Japan Hontakka - Hungary
5
09H3100290
Vinedale
37
09H3100349
Japan Hontakka
6
09H3100291
Vinedale
38
09H3400501
Japan Hontakka
19
09H3100292
Vinedale
39
09H3100502
Japan Hontakka
36
09H3100288
Vinedale
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Methods
DNA polymorphism, detected by the SSR method, was used as genetic marker. The
genomic DNA was isolated using the Invisorb Spin Plant Mini Kit (INVITEK, Germany) from
leaves collected from plants at the beginning of flowering. Three plants of each accession
were sampled by collecting four leaf discs from each plant (approximately 80 mg). The
DNA concentration was measured fluorimetrically. Eight SSR markers described previously
for pepper were used (Lee et al. 2004; Minamiyama et al. 2006). The 25 μl-reaction
mixture for PCR contained: 30 ng template DNA, 1 U Taq polymerase (PROMEGA, USA),
1× concentrated reaction buffer, 0.2 μM of fluorescence-labelled forward primer, 0.2 μM
of reverse primer, and 0.1 mM dNTPs. The PCR program consisted of initial denaturation
for 3 min at 94 °C, followed by 35 cycles per 1 min at 94 °C, 1 min at 50–55 °C (subject
to the used pair of primers), 2 min at 72°C, and 1 cycle 10 min at 72°C. The PCR
amplification was verified by agar- ose electrophoresis before loading the samples on
capillary electrophoresis ABI Prism 3100 (Applied Biosystems , USA). The number and size
of the amplicons were evaluated by the Gene Marker 1.3 software. The amplicons at
polymorphic loci were scored as presence (1) or absence (0) of an allele and used to
construct a binary matrix. These values were statistically evaluated using UPGMA
(Jaccard coefficient) by the FreeTree programme (Hampl et al. 2001) and a dendrogram
was constructed by the TreeView programme (Page 1996). Following values were assessed
for each SSR marker: diversity index (DI), probability of identity (PI) and polymorphous
information content (PIC) (Russell et al. 1997).
Results and discussion
Out of eight analyzed SSR markers three had a uniform spectrum (Hpms 1-1, Hpms
1-168, and Hpms 1-274) in all plants of the whole set analyzed. In the other microsatellites
two to eight alleles were detected (total 28), i.e. average 3.5 alleles per locus (Table
2.). The highest number of alleles was detected in microsatellites Hpms 1-5 (8 alleles)
and Hpms 2-21 (7 alleles). Minamiyama et al. (2006) detected a high number of alleles
in the SSR markers Cams 163 (9 alleles) and Cams 647 (10 alleles) which, in our case, had
a lower number of alleles, i.e. Cams 647 (6 alleles) and Cams 163 (2 alleles). The obtained
number of alleles per locus is comparable with other authors who found average values
of 2.9 (Minamiyama et al. 2006) and 3.0 (Kwon et al. 2007). The average DI (diversity
index) value was 0.33 (0.00–0.74), average of PI (probability of identity) 0.55 (0.04–1.00)
and for PIC (polymorphous information content) average value was 0.32 (0.00–0.73)
(Table 2). The average value of PIC was lower than the value of 0.76 described by Lee et
al. (2004) when studying various members of the genus Capsicum. Minamiyama et al.
(2006) quoted a similar value of 0.46 in their studies of dihaploid pepper lines (C.
annuum). The low value of PIC implies a higher level of genetic similarity within the
pepper genotypes analyzed.
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Table 2. Characteristics of the analyzed SSR markers.
SSR marker
Linkage
group
Number of
alleles
DI*
PI**
PIC***
Hpms 1-1
1
1
0.00
1.00
0.00
Hpms 1-5
6
8
0.73
0.04
0.72
Hpms 1-168
16
1
0.00
1.00
0.00
Hpms 1-172
11
2
0.18
0.69
0.16
Hpms 1-274
7
1
0.00
1.00
0.00
Hpms 2-21
10
7
0.68
0.09
0.67
Cams 163
5
2
0.31
0.52
0.26
Cams 647
3
6
0.75
0.03
0.74
3.5
0.33
0.55
0.32
Average
*DI – diversity index; **PI – probabilities of identity;
***PIC – polymorphic information content.
Based on statistical evaluation we constructed a similarity dendrogram of the analyzed
pepper genotypes (Jaccard coefficient) (Hanáček et al. 2009)(Fig.1). Four accessions
were significantly (Hatvani (No. 13), Japan Madarszen (No. 29, 30 and 31)) different the
other 37 analyzed accessions. These four accessions differed not only in their SSR markers
but also according to descriptive morphological data (No. 29 – chilli pepper; No. 30
and 31 – spice pepper). The distribution of the analyzed genotypes in the dendrogram
indicated a high level of similarity within some items of the same or similar name, e.g.
Kalocsai Furzer (Edes) (Nos. 3 and 4), Hatvani and Hatvani Csemege (Nos. 15 and 16);
Bogyiszloi (No. 26) and Bogyiszloi Vastaghusu (No. 27).
1. group Astrachanskij – according morphological characterization 09H3100059
Astrachanskij 147 was different from others acc. in plant height and fruit colour at
intermediate developmental stage. The acc. 09H3100059 and 09H3100057 were different
from others acc., according DNA analysis.
2. group Aufrechte Cayenne – within group the genotype 09H3100140 was different in
length of blade, width of blade and shape of fruit according morphological charac­te­
rization. DNA analysis presented the small differences in all accessions but big differences
were between acc. 09H3100137, 09H3100138, 09H3100139 and 09H3100140.
3. group Bogyisloi – the fundamental morphological differences were not found within
group. According DNA analysis, acc. 09H3100113 and 09H3100114 were very similar. The
small differences were between acc. 09H3100111 and acc. 09H3100112. All these acc.
were in one subgroup.
4. group Hatvani – the morphological differences were not among acc. 09H3100417,
09H3100418 and 09H3100419. The plants of acc. 09H3100416 had heterogeneous
phenotype expression. 09H3100416 was dissimilar to the rest of group, according to
DNA analysis.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 1. Dendrogram of similarity of the analysed pepper plants.
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Advances in Genetics and Breeding of Capsicum and Eggplant
5. group Japan Hontakka – the acc. 09H3100502 was different from 09H3100349 and
09H3400501 in the position, shape and size of fruits. The results of DNA analysis
corresponded with to morphological traits assesment
6. group Japan Madarszem – the individual accessions were differed in the size of leafs,
size and shape of fruits. The biggest differences were between acc. 09H3100350 and
09H3100351 and among the acc. 09H3100503, 09H3100504 and 09H3100505 according
DNA analysis. These groups were put in different cluster.
7. group Kalocsai Fuszer (Edes) – the genotype 09H3100243 was different from
09H3100244 and 09H3100245 in the shape and position of fruits on plants. The result of
DNA analysis is identical with morphological description.
8. group Konservnyj Belyj 289 – the morphological differences were not found within
group. According to DNA analysis acc. 09H3100354 and 09H3100352 were the same. The
small differences were found between acc. 09H3100353 and acc. 09H3100354 and
09H3100352.
9. group Tetenyi – according to morphological description it is possible to split up two
parts this group. 09H3100068 and 09H3100071 form the first subgroup. These acc. have
low plants, erect and triangular fruits, the fruit colour at intermediate stage is yellowish
and light red at stage of maturity. The acc. 09H3100067, 09H3100069 and 09H3100070
form the second subgroup have elongate and drooping fruits. The fruits of this group are
green at intermediate developmental stage and red at stage of maturity. The result of
DNA analysis is the same. Small variability was found within the second subgroup.
10. group Vinedale – identical accessions were not found neither after morphological
description nor by DNA analysis. Within this group the accessions were different in all
important morphological characters.
Conclusions
This work was the first step for detection of duplicitions in the Czech germplasm
collection of pepper (Capsicum annuum L.) In future we would like to continue in the
determination of duplications on the basis of increase number of SSR markers and
morphological description. Higher number of SSR markers gives results with higher
predicative ability an variability within collection and in the scope of individual
accessions.
Acknwledgements
The study was funded by the National programme for the preservation and use of genetic
resources of plants and agro-biodiversity of the Ministry of Agriculture, CR Nor.:
20139/2006-13020 and by the project Internal Grant Agency of Mendel University of
Agriculture and Forestry in Brno No. DP1/AF/2008.
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References
Basu, S.K.; De, A.K. 2003. Capsicum: historical and botanical perspectives. 1– 15; In: De,
A.K. (ed.) Capsicum: the genus Capsicum. London: Taylor & Francis: 275 s. ISBN
0-415-29991-8.
Bosland, P.W.; Votava, E. 2000. Peppers Vegetable and Spice Capsicums. New York: Cabi
Publishing: 204 s. ISBN 0-85199-335-4.
Dotlačil, L. 2007. Projekt integrace evropských genových bank (AEGIS). Sborník referátů
ze seminářů Aktuální problém práce s genofondy rostlin v ČR, Kostelany: 79-83. ISBN
92-9043-319-1.
ECPGR 2008. A Strategic Framework for the Implementation of a European Genebank
Integrated System (AEGIS). Discussion paper. European Cooperative Programme for
Plant Genetic Resources (ECPGR). Bioversity International, Rome, Italy:24.ISBN:97892-9043-774-1
Haghnazari, A.; Samimifard, R.; Najafi, J.; Mardi, M. 2005. Genetic diversity in pea (Pisum
sativum L.) accessions detected by sequence tagged microsatellite markers. Journal
of Genetics and Breeding, 59: 145-152.
Hanáček, P.; Vyhnánek, T., Rohrer, M.; Cieslarová, J.; Stavělíková, H. 2009. DNA poly­
morphism in genetic resources of red pepper using microsatellite markers. Hort.
Sci. (Prague), 36, 2009 (4): 127-132
Hampl, V.; Pavlíček, A.; Flegr, J. 2001. Construction and bootstrap analysis of DNA finger­
printing-based phylogenetic trees with a freeware program FreeTree: Application to
Trichomonad parasites. International Journal of Systematic and Evolutionary
Microbiology, 51: 731-735.
IPGRI; AVRDC; CATIE. 1995. Descriptors for Capsicum (Capsicum spp.). International Plant
Genetic Resources Institute, Rome, Italy; the Asian Vegetable Research and Deve­
lopment Center, Taipei, Taiwan, and the Centro Agronómico Tropical de Investigación
y Enseñanza, Turrialba, Costa Rica.
Kwon, Y.S.; Moon, J.Y.; Yi, S.I.; Bae, K.M.; Son, E.H.; Cho, I.H.; Kim, B.D. 2007. Comparative
analysis of pepper (Capsicum annuum L.) varieties using morphological characters,
AFLP and SSR markers. Korean Journal of Genetics, 29: 11-20.
Lee, J.M.; Nahm, S.H.; Kim, Y.M.; Kim, D.D. 2004. Characterisation and molecular genetic
mapping of microsatellite loci in pepper. Theoretical and Applied Genetics, 108:
619-27.
Li, M.; Zhang, C.; Qian, W.; Meng, J. 2007. Genetic diversity of Brassica species revealed
by amplified fragment length polymorphism and simple sequence repeat markers.
Horticulture, Environment, and Biotechnology, 48: 9-15.
Minamiyama, Y.; Tsuro, M.; Hirai, M. 2006. An SSR-based linkage map of Capsicum annuum.
Molecular Breeding, 18: 157-169.
Müller, S. 1959. Paprika roční. 257-277; In: Podešva, J. (ed.) Encyklopedie zelinářství Vol.
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Page, R.D.M. 1996. TREEVIEW: An application to display phylogenetic trees on personal
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Russell, J.; Fuller, J.; Young, G.; Thomas, B.; Taramino, G.; Macaulay, M.; Waugh, R.; Po­
well, W. 1997. Discriminating between barley genotypes using microsatellite markers.
Genome, 40: 442-450.
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Smith, J.A. 1984. Peppers, the domesticated Capsicums. 1 vyd. Austin: University of Te­
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on SSR and morphological markers among tomato cultivars. Journal of Tropical and
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Pepper, Hot Pepper, Paprika, Chili. 1-47. http://www.upov.int/en/publications/tgrom/tg076/tg_76_8.pdf.
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drace Mazhamai as revealed by morphological characteristics, seed storage proteins,
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Determination of genetic variation among Turkish eggplant
(Solanum melongena L.) varieties by AFLP analysis
Y. Tumbilen, A. Frary, S. Doganlar
Department of Molecular Biology and Genetics, Izmir Institute of Technology, Urla 35430, Izmir, Turkey.
Contact: [email protected]
Abstract
In Turkey, local varieties of eggplant (Solanum melongena) have many forms and are a
staple ingredient of the cuisine. Although Turkish eggplant varieties are morphologically
distinct, little is known about their molecular genetic variation. In this study, the genetic
variability of 67 Turkish eggplant accessions from the national germplasm collection was
assessed with AFLP markers. In addition, accessions of S. macrocarpon, S. aethiopicum and
S. linnaeanum were included as outgroups. Ten primer combinations were used and yielded
488 polymorphic fragments with PIC values ranging from 0.03 to 0.50. Of the polymorphic
fragments, 144 (29%) were specific to S. melongena accessions while 73, 49 and 16 fragments
were specific to S. macrocarpon, S. aethiopicum and S. linnaeanum, respectively. UPGMA
cluster analysis of the AFLP data resulted in a dendrogram which had a very high correlation
(r=0.97) with the similarity matrix data. Genetic similarity in the dendrogram ranged from
0.30 to 0.95 with the related Solanum species located outside the S. melongena clusters,
as expected. Genetic similarity of the S. melongena accessions ranged from 0.68 to 0.95
indicating good genetic diversity present in the Turkish national collection. It is hoped that
this information, together with morphological data, will help guide future germplasm
collection and eggplant breeding efforts.
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SESSION II.
BREEDING FOR RESISTANCE TO BIOTIC
AND ABIOTIC STRESSES
/////////////////////////////////////////////////////
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
CMS-Rf genotype of newly-discovered sources of resistance to
bacterial spot in pepper (Capsicum annuum L.)
J.H. Ahn, B.S. Kim
Department of Horticulture, Graduate School, Kyungpook National University,
Daegu 702-701, Korea. Contact:[email protected]
Abstract
Of the new sources of resistance to bacterial spot found in Vietnam, Laos, and Nepal,
KC00897, KC00995 and KC01015 were restorers of cytoplasmic genic male sterility (CGMS)
with N(S)RfRf genotype and KC00939, KC01006, KC01327 and KC01328 were maintainers
with Nrfrf genotype.
Keywords: Capsicum annuum, Xanthomnas campestris pv. vesicatoria, cytoplasmic male
sterility.
Introduction
Bacterial spot caused by Xanthomonas campestris pv. vesicatoria is causing a significant
damage on chile pepper in Korea, particularly in the years when typoon hits the country
during the growing season. Breeders are interested in breeding for resistance to the
disease. Most commercial varieties of chile pepper grown in Korea are hybrids and the
hybrid cultivars are produced by utilization of cytoplasmic genic male sterility (CGMS).
Therefore, any male fertile accessions can be classified into the maintainer class with
Nrfrf genotype or restorer with N(S)RfRf genotype for cytoplasmic male sterility (Shifriss,
1997). Cytoplasmic male sterile lines, their maintainers, and restorers are often referred
to as A, B, and C lines of CGMS, respectively. Resistance to bacterial spot was first found
in US PI’s (Sowell, 1960; Sowell and Depmsey, 1977) and their CMS-Rf genotype was
reported to be all restorers (NRfRf) (Kim and Hwang, 1998). New sources of resistance
to bacterial spot were reported lately in accessions originating in Vietnam, Laos and
Nepal (Kim et al., 2009; Tran and Kim, 2007). The new sources of resistance were crossed
to a cytplasmic male sterile line with Srfrf genotype. Nuclear genotype with respect to
the gene restoring cytoplasmic male sterility, CMS-Rf genotype, of the genetic resources
was identified on the basis of male fertility of the F1 plants obtained by crossing the
sources of resistance to a cytoplasmic male sterile line, Chilbok-A.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Materials and methods
New sources of resistance to bacterial spot found in Vietnam, Laos and Nepal collections
were crossed to a cytoplasmic male sterile line (Srfrf), Chilbok-A, which has been bred
by incorporation of Phytophthora resistance of CM334 into a local cultivar in Youngyang
in Korea, to identify their nuclear genotype interacting with male sterile cytoplasm in
the first half of 2009. The sources of resistance and the F1 hybrids between the Chilbok-A
were tested for resistance to bacterial spot. One month old seedlings were inoculated
by spraying bacterial suspension and incubated for two days in a hot bed by wetting the
bottom of the bed and covering the tunnel with plastic film. Humid condition for disease
development was induced by covering hot bed tunnel with a plastic film and blanket and
heating the wet bottom by electric heat cable every night thereafter. Disease was scored
4 weeks after inoculation on the basis of spot type and degree of spot and defoliation.
Fertility of the F1 hybrids was determined by visual observation and quantification of
pollen on an anther. Quantification of pollen per anther was done as previously described
(Kim and Hwang, 1998).
Results and discussion
The results of testing the sources of resistance to bacterial spot and their F1’s with a
susceptible male sterile line, male fertility of the F1’s and quantity of pollen on an
anther are given in Table 1.
The new sources of resistance originating in Vietnam, Laos and Nepal showed similar to
or higher level of resistance to bacterial spot than those originating in US PI’s. However,
none of them was hypersensitive but very limited spots were formed on them. Their F1’s
with a susceptible male sterile line, Chilbok-A, developed more disease than their
resistant parents but less than the susceptible parents. As regards of resistance of F1’s,
KC00939 and KC01015 appeared to carry more genes or higher level of resistance than
the other accessions. Commercial hybrid cultivars, Geumtap and Nokgwang, were
susceptible with severe spots.
In nuclear genotype with regard to cytoplasmic male sterility, KC00897, KC00995, and
KC01015 produced male fertile F1 plants in a cross with a cytoplasmic male sterile line,
Chilbok-A, therefore, were restorers with N(S)RfRf genotype. In contrast, KC0939,
KC01006, KC01327 and KC01328 resulted in male sterile F1 plants with the Chilbok-A
indicating that they are maintainers with Nrfrf genotype. All of the resistant US PI’s
were restorers (Kim and Hwang, 1998) and maintainers were not found but this time
both restorers and maintainers were found in the sources of resistance to bacterial spot
found in Vietnam, Laos and Nepal. Therefore, breeders can choose any sources of
resistance with restorer or maintainer genotype depending on their objective of
breeding, resistant maintainer or restorer, in hybrid breeding system. Pollen on an anther
was quantified. Abundant pollen was produced on the F1 plants between the male sterile
Chilbok-A and restorer resistance sources except one cross, Chilbok-A x KC00995-3.
Further observation for the cross is being continued.
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Table 1. Reaction to bacterial spot of sources of resistance and their respective F1’s with a
susceptible male sterile line, and nuclear genotype interacting with male sterile cytoplasm.
Accession
Origin
Bacterial spotz
F1
BSR line
(CBA*BSRL)
Fertility
of F1
KC00043
PI241670
1.4 ab
-
-
KC00047
PI244670
1.7 a-d
-
-
KC00079
PI271322
1.2 a
-
KC00127-1
PI369994
2.3 c-f
KC00127-2
PI369994
KC00127-3
Pollen
per
anther
Genotype
of pollen
parent
Remark
(N(S)RfRf)
Kim & Hwang, 1998
-
(N(S)RfRf)
Kim & Hwang, 1998
-
-
(N(S)RfRf)
Kim & Hwang, 1998
-
-
-
(N(S)RfRf)
Kim & Hwang, 1998
2.4 d-g
-
-
-
(N(S)RfRf)
Kim & Hwang, 1998
PI369994
3.4 h-j
-
-
-
(N(S)RfRf)
Kim & Hwang, 1998
KC00131
PI369998
3.3 g-k
-
-
-
(N(S)RfRf)
Kim & Hwang, 1998
KC00177
PI163192
1.9 a-e
-
-
-
(N(S)RfRf)
Kim & Hwang, 1998
KC00897
Nepal
1.9 a-e
2.4 d-g
MF
16160
KC00939
Korea
1.5 a-c
1.2 a
MS
-
KC00995-1
Vietnam
2.3 c-f
2.6 d-h
MF
14960
N(S)RfRf
KC00995-2
Vietnam
2.4 d-g
2.2 b-f
MF
14360
N(S)RfRf
KC00995-3
Vietnam
1.3 a
2.6 d-h
MF
4120
N(S)RfRf
KC01006-1
Vietnam
1.4 ab
2.4 d-g
MS
-
Nrfrf
KC01006-2
Vietnam
1.2 a
2.9 f-j
MS
-
Nrfrf
KC01006-3
Vietnam
1.5 a-c
2.9 f-j
MS
-
Nrfrf
KC01015
Vietnam
2.7 e-i
1.8 a-d
MF
11200
KC01327
Laos
1.3 ab
3.4 h-j
MS
-
Nrfrf
KC01328
Laos
1.4 a-d
3.4 i-k
MS
-
Nrfrf
Chilbok
Korea
3.7 i-k
-
-
-
Nrfrf
PR NIL of Chilseong
Chilbok-A
Korea
3.7 i-k
-
-
-
Srfrf
CMS Chilbok
Chilseong
Korea
4.0 k
-
-
-
Nrfrf
Kim & Hwang, 1998
Geumtap
Korea
4.8 l
-
-
-
-
Comm. Hybrid
Nokgwang
Korea
3.4 i-k
-
-
-
-
Comm. Hybrid
N(S)RfRf
Nrfrf
N(S)RfRf
1= 1=No spot; 2=Trace of arrested spots; 3=Spots with oil-soaked edge; 4=Water-soaked spots; 5=Defoliated
with water-soaked spots.
y
Mean separation by Duncan’s multiple range test at P ≤ 0,05.
z
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References
Kim, B.S.; Hwang, H.S. 1998. Testing bacterial spot resistant lines of Capsicum pepper for
nuclear genotype interacting with male sterile cytoplasm. Korean J. Plant Pathol.
14:212-216.
Kim, B.S.; Souvinmonh, B.; Son, K.; Ahn, J.H.; Lee, S.M. 2009. New additions to sources
of resistance to bacterial spot and field performance of HR gene NILs in Capsicum
pepper. Hort. Environ. Biotechnol. 50:566-570.
Shifriss, C. 1997. Male sterility in pepper (Capsicum annuum L.). Euphytica 93:83-88.
Sowell, G. Jr. 1960. Bacterial spot resistance of introduced peppers. Plant Dis. Rep. 44:
587-590.
Sowell, G. Jr.; Dempsey, A.H. 1977. Additional sources of resistance to bacterial spot of
pepper. Plant Dis, Reptr. 61:684-686.
Tran, N.H.; Kim, B.S. 2007. Search for sources of resistance to bacterial spot (Xanthomonas
campestris pv. vesicatoria) in Capsicum pepper. Acta Hort. 760:323-328.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Epistasis and aggressiveness in resistance of pepper
(Capsicum annuum L.) to Phytophthora nicotianae
F. Bnejdi1, S. Morad2, A.M. Bechir2, M. El Gazzah1
Laboratoire de Génétique et Biométrie Faculté des Sciences de Tunis, Université Tunis El Manar 2092,
Tunisia. Contact : [email protected]
2
Institut National de la Recherche Agronomique de Tunisie (INRAT), Tunisia
1
Abstract
This study evaluated the types of gene action governing the inheritance of resistance to
Phytophthora nicotianae necrosis in populations derived from two crosses involving two
susceptible (Beldi and Nabeul II) and one resistant (CM334) cultivars of pepper (Capsicum
annuum L.). Populations, composed of Pr, Ps, F1, F2, BC1Pr, and BC1Ps generations, were
inoculated with six P. nicotianae isolates. Generation means analysis indicated that an
additive-dominance model was appropriate for P. nicotianae isolates PnKo1, PnKo2 and PnKr1,
which had low aggressiveness in the two crosses. For more aggressive isolates PnBz1, PnBz2
and PnKr2, epistasis was an integral component in resistance in the two crosses. The presence
of epistasis in resistance of pepper to P. nicotianae was dependent on the isolates’ level of
aggressiveness. Selection in pepper with less aggressive isolates was efficient, but not for
more aggressive isolates; selection with more aggressive isolates was more stable.
Keywords: additive model, best fit model, gene effect, heredity.
Introduction
Although epistasis is common in gene systems that determine quantitative traits, it is
also a major problem in studies of quantitative traits because it complicates interpretation
of genetics experiments and makes predictions difficult. The importance of epistasis is
not well understood, and it was once considered to make a small contribution to
quantitative variation (Crow, 1987). Epistasis effects commonly occur in plant resistance
to pests or diseases. Examples are pepper and P. nicotianae (Bnejdi et al., 2009), pepper
and P. capsici (Bartual et al., 1993), common bean and anthracnose (Marcial and Pastor,
1994), barley and Fusarium head blight (Flavio et al., 2003). There is a lack of knowledge
on the contribution of pathogen aggressiveness in determining the mode of gene action.
Several studies have reported that the nature and magnitude of gene action in resistance
to pest and disease were determined by pathogen aggressiveness. Bartual et al. (1991,
1993) reported that the relative importance of higher order epistasis in additive ×
additive epistasis seemed correlated with the aggressiveness of the P. capsici isolate.
Bnejdi et al. (2009) reported that the probability of goodness-of-fit of models was
negatively correlated with the aggressiveness of the P. nicotianae. Both types of
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resistance for different isolates of P. palmivora were reported by Surujdeo-Maharaj et
al. (2001). Generation mean analysis is the methodology generally used to study
quantitative trait inheritance, including interaction between non-allelic genes (Mather
and Jinks, 1974). The objective of the present study was to investigate the types of gene
action governing the inheritance of resistance to different aggressiveness of P. nicotianae
isolates in pepper.
Materials and methods
Pepper (C. annuum L.) parental lines were selected based on their resistance to P.
nicotianae. The resistant parent (Pr) used was cv. CM334 and the susceptible parents
(Ps) were cvs. Beldi and Nabeul II. Crosses were made as follows: CM334 x Beldi, and
CM334x Nabeul II. Generation means analysis was performed using each of Pr and Ps, F1
and F2 generations, and backcrosses of the F1 to each parent (BC1 Pr and BC2 Ps). Six P.
nicotianae isolates were collected from infected pepper plants from different regions in
Tunisia: PnKo1 and PnKo2 from Korba, PnBz1 and PnBz2 from Bizert, and PnKr1 and PnKr2 from
Kairown. These isolates were identified as P. nicotianae according to morphological and
biological characteristics reported by Allagui et al. (1995) and Allagui and Lepoivre
(2000). Two weeks after sowing, the seedlings (two-cotyledon stage) were transplanted
into alveolated plates containing the same substrate disinfected by heat. Plants were
grown in a randomized complete block design with two replications. Two weeks after
transplantation, seedlings (two-leaf stage) from each replication were inoculated by
different isolates, by dripping a suspension of 280,000 zoospores (in 3.5 mL) onto the
collar of each plant. After three weeks of incubation, the root system of each seedling
was delicately detached from substratum by washing in a water bowl. The root necrosis
intensity was evaluated with the following scale: 0 (healthy plant), 0.5 (necrosis limited
to the extremity of radicles), 1 (necrosis only on the lower half of primary roots), 2
(necrosis on all the primary roots), 3 (necrosis reaching the crown and the lateral roots),
4 (hypocotyl rotten), and 5 (whole plant dead).
Gene effects and best model
Weighted least squares regression analyses were used to solve for mid-parent [m] pooled
additive [d], pooled dominance [h] and pooled digenic epistatic ([i], [l] and [j]) genetic
effects, following the models and assumptions described in Mather and Jinks (1982). A
simple additive-dominance genetic model containing only m, d and h effects was first
tested using the joint scaling test described in Rowe and Alexander (1980). Adequacy of the
genetic model was assessed using a chi-square goodness-of-fit statistic derived from
deviations from this model. If statistically significant at P < 0.05, genetic models containing
digenic epistatic effects were then tested until the chi-square statistic was nonsignificant.
Results and Discussion
There were significant differences among generation means in all cases, revealing
genetic diversity for this attribute in the materials, thus validating the genetic analysis
of the traits following the technique of Mather and Jinks (1982).
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Advances in Genetics and Breeding of Capsicum and Eggplant
Although varying with the cross and isolates’ class of aggressiveness, the variation in the
generation means fitted an additive dominance model for PnKo1, PnKo2 and PnKr1 in the two
crosses. The additive effect was significant and greater than the dominance effect. The
fact that the additive and dominance effects were negative indicated that they con­
tributed more to resistance than to susceptibility (Table 1).
Table 1. Estimates of gene effects ± SE (× 100) for pepper resistance to six P. nicotianae
isolates in two crosses of susceptible (s) × resistant (r) parents.
Modela
PnKo1
PnKo2
PnBz1
PnBz2
PnKr1
PnKr2
Beldi (s) × CM 334 (r)
m
1.87
± 10**
1.13
± 7**
2.31
± 9**
2.68
± 9**
1.16
± 9**
2.12
± 10**
d
–1.36
± 9**
–1.08
± 6**
–1.85
± 8**
–1.80
± 8**
–1.00
± 8**
–1.60
± 10**
–1.25
± 11**
–0.14
± 13
–0.97
± 19**
–0.50
± 17**
0.03
± 16**
–1.2
0± 14**
h
(P)
0.36
b
0.29
< 0.001
< 0.001
0.58
< 0.001
Best fit model
m
2.50
± 10**
15.50
± 49**
1.95
± 22**
d
–2.05
± 10**
–2.00
± 10**
–1.70
± 22**
h
–2.46
± 44**
–9.70
± 125**
–0.08
± 70**
–4.00
± 48**
1.38
± 52**
l
1.77
± 0.52**
4.95
± 83**
–1.22
± 51**
j
1.26
± 0.39**
2.59
± 38**
-
i
0.14
(P)
0.92
-
Nabeul II (s) × CM 334 (r)
Three-parameter model
m
1.80
± 9**
1.39
± 10**
1.76
± 10**
2.05
± 11**
1.57
± 12**
2.26
± 9**
d
–1.36
± 9**
–1.31
± 9**
–0.88
± 8**
–0.96
± 10**
–1.41
± 11**
–1.7
± 9**
h
–0.93
± 7**
0.13
± 17
–0.39
± 19**
0.13
± 22
0.21
± 19
–1.27
± 13**
(P)
0.96
0.59
< 0.001
< 0.001
0.56
< 0.001
Best fit model
m
17.58
± 58**
6.46
± 50**
3.94
± 21**
d
–1.80
± 12**
–1.80
± 13**
–1.79
± 18**
h
–8.13
± 134**
–5.92
± 123**
–3.16
± 25**
i
–2.89
± 57**
–2.55
± 49**
–1.89
± 30**
l
4.2
± 83**
2.63
± 83**
-
j
3.72
± 35**
3.44
± 38**
2.17
(P)
-
-
± 51**
0.25
Mean (m), additive (d), dominance (h), additive × additive (i), additive × dominance (j) dominance ×
dominance (l) genetic effects for the model. y = m + d + h + i + j + l, where y is the generation mean.
b
(P): Probability of adequateness of model.
*,** indicates means and gene effects are statistically different from zero at P < 0.05 and P < 0.01,
respectively.
a
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Epistasis
Advances in Genetics and Breeding of Capsicum and Eggplant
Aggressiveness
Figure 1. Mean of aggressiveness of six P. nicotianae isolates revealed in cv. Beldi and absolute
total of epistasis in cross Beldi × CM344. Column of aggressiveness followed by the same
letter not significantly different at P < 0.05.
■ Epistasis (measured as follows: epistasis = /i/+/l/+/j/)
□ Aggressiveness (means of necrosis revealed in the susceptible parent Beldi).
Epistasis
For PnBz1, PnBz2 and PnKr2 the digenic epistatic model was adequate in three cases. In the
other cases none of the models explained variation between generations, indicating
more complex mechanisms of genetic control. To identify whether the model failure was
due to higher order interactions or linkage effects there should be further analyses of
sufficient generations to fit a full trigenic interaction and linkage model. Generation
mean analysis indicated that the comportment of the two crosses for resistance to
different isolates was similar. For the isolates with aggressiveness levels of 2.05–3.16 an
additive-dominance model was fitted. For the isolates with level of aggressiveness ≥
3.63, the epistatic effect was an integral component in resistance to P. nicotianae and
the aggressiveness level determined the epistasis.
Aggressiveness
Figure 2. Mean of aggressiveness of six P. nicotianae isolates revealed in cv. Nabeul II and
absolute total of epistasis in cross Nabeul II × CM344. Column of aggressiveness
followed by the same letter not significantly different at P < 0.05.
■ Epistasis (measured as follows: epistasis = /i/+/l/+/j/)
□ Aggressiveness (means of necrosis revealed in susceptible parent Nabeul II).
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Bartual et al. (1991) found that epistasis was a principal source of variation in resistance
of pepper to Phytophthora stem blight, and was correlated with the level of pathogen
aggressiveness. In the present study, for the less aggressive isolates only additive and
dominance models were applied and found sufficient. With high levels of aggressiveness,
additive and dominance effects were not sufficient to explain variation in generation
means and epistasis was an integral component in the mechanism of genetic control of
resistance to Phytophthora nicotianae. When epistasis was detected, the total of
absolute of epistasis effects increased when aggressiveness increase (Figures I and II).
Recurrent selection with less aggressive isolates was efficient to fix the part of resistance
controlled by additive effect. Selection with more aggressive isolates was complicated
but more stable than for less aggressive isolates.
References
Allagui, M.B.; Lepoivre, P. 2000. Molecular and pathogenicity characteristics of Phy­
tophthora nicotianae responsible for root necrosis and wilting of pepper (Capsicum
annuum L.) in Tunisia. European Journal of Plant Pathology 106: 887–894.
Allagui, M.B.; Marquina, J.T.; Mlaiki, A. 1995. Phytophthora nicotianae var. parasitica
pathogène du piment en Tunisie. Agronomie 15: 171–179.
Bartual, R.; Carbonell, E.A.; Marsal, J.I.; Tello, J.C.; Campos, T. 1991. Gene action in the
resistance of peppers (Capsicum annuum) to Phytophthora stem blight (Phytophthora
capsici L.). Euphytica 54: 195–200.
Bartual, R.; Lacasa, A.; Marsal, J.I.; Tello, J.C. 1993. Epistasis in the resistance of pepper
to phytophthora stem blight (Phytophthora capsici L.) and its significance in the
prediction of double cross performances. Euphytica 72: 149–152.
Bnejdi, F.; El Gazzah, M. 2008. Inheritance of resistance to yellowberry in durum wheat.
Euphytica 163: 225–230.
Bnejdi, F.; Saadoun, M.; Allagui, M.B.; El Gazzah, M. 2009. Epistasis and heritability of
resistance to Phytophthora nicotianae in pepper (Capsicum annuum L). Euphytica
167: 39–42.
Crow, J.F. 1987. Population genetics history: a personal view. Annual Review of Genetics
21: 1–22.
Flavio, C.; Donald, C.R.; Ruth, D.M.; Edward, S.; Amar, E. 2003. Inheritance of resistance
to fusarium head blight in four populations of barley. Crop Science 43: 1960–1966.
Marcial, A.; Pastor, C. 1994. Inheritance of anthracnose resistance in common bean
accession G 2333. Plant Disease 78: 959–962.
Mather, K.; Jinks, J.L. 1974. Biometrical Genetics. Ithaca, New York: Cornell University
Press.
Mather, K.; Jinks, J.L. 1982. Biometrical Genetics. The study of continuous variation.
Ithaca, New York: Cornell University Press.
Rowe, K.E.; Alexander, W.L. 1980. Computations for estimating the genetic parameter in
joint-scaling tests. Crop Science 20: 109–110.
Surujdeo-Maharaj, S.; Umaharan, P.; Iwaro, A.D. 2001. A study of genotype-isolate
interaction in cacao (Theobroma cacao L.): resistance of cacao genotypes to isolates
of Phytophthora palmivora. Euphytica 118: 295–303.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Introgression of Phytophthora capsici root rot resistance from
Capsicum annuum into C. chinense
C.S. da Costa Ribeiro, P.W. Bosland
Department of Plant and Environmental Science, New Mexico State University, Las Cruces,
NM 88003-8003, USA. Contact: [email protected]
Abstract
Phytophthora capsici is a soilborne fungal pathogen that can cause four different disease
syndromes in Capsicum known as root rot, foliar blight, stem blight, and pod rot. The
accession “Criollo de Morelos 334” (Capsicum annuum) is the most stable resistance source
to root rot disease used in breeding programs around the world. The main objective of this
research is to incorporate P. capsici root rot resistance from “CM 334” to the “Orange
Habanero” accession (C. chinense) with the backcross breeding method. The F1 generation
was only obtained when “CM 334” was used as female parent and “Orange Habanero” as the
male parent. The F1 plants were selfed to obtain the F2 generation, and backcrossed to
“Orange Habanero” to recover plant and fruit characteristics of the “Orange Habanero.” The
F1 plants presented intermediate fruit and plant characteristics between “CM 334” and
“Orange Habanero.” The F2 population segregated for plant characteristics such as shape
and size of leaves, stem and leave pubescence, presence or absence of anthocyanin in leaves
and stems. From 40 F2 plants evaluated only three produced fruits by selfing. The F2 plants
were inoculated with a P. capsici isolate from Brazil (Pcp 106), and approximately 50% of the
plants showed resistance. Backcrossing and screening for resistance will continue.
Keywords: Interspecific hybridization, chile, pepper, root rot, backcrossing, habanero.
Introduction
Among different chile peppers, habanero (C. chinense) pod type is described as very hot.
Habanero fruits are used fresh in salsas, cooked directly in dishes, or fermented to make
a hot sauce. Processing companies have a great interest for this kind of chile pepper.
Habanero pepper production is limited due to Phytophthora capsici, particularly
destructive under high humidity and high temperature (Sy and Bosland, 2005; Walker
and Bosland, 1999). P. capsici is a soil borne fungal pathogen and causes four different
disease syndromes in pepper known as root rot, foliar blight, stem blight, and pod rot
(Walker and Bosland, 1999). Chemical control of P. capsici is limited and the development
of resistant cultivar is crucial to the future success of the chile crop (Oelke and Bosland,
2003). All habanero cultivars and hybrids available are susceptible to Phytophthora
capsici and resistance to phytophthora wilt is important for Capsicum breeding programs.
The use of resistant cultivars is the most effective method of disease control (Bosland &
Lindsey, 1991).
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Advances in Genetics and Breeding of Capsicum and Eggplant
The main objective of this work is to incorporate P. capsici root rot resistance from
“Criollo de Morelos 334 - CM 334” to the “Orange Habanero” accession (C. chinense)
with the backcross breeding method.
Material and methods
Plant material and growing conditions
Plants of “CM 334” (source of resistance) and “Orange Habanero” (recurrent parent)
were grown in 5-liter pots that were filled with commercially soil mixture (SunGro Rediearth plug & seedling mix, Sum Gro Horticulture, WA, USA).
Backcrossing
The F1 hybridizations were made using “Orange Habanero” as female parent and “CM334”
as male parent, and the reciprocal cross using “CM 334” as female parent. Only two F1
plants from the hybridization CM334 x Orange Habanero were obtained, and none were
obtained from the reciprocal hybridization. A BC1 to “Orange Habanero” (female parent)
was obtained, and the F2 population was obtained from selfing of F1 plants.
Evaluation of F2 generation
Morphological characteristics: A total of 40 F2 plants were cultivated in 5-liter pots to
confirm the hybridization between C. annuum and C. chinense. To confirm the F2 plants
were from an interspecific hybridization, plant traits such as shape and size of leaves,
stem and leave pubescence, presence or absence of anthocyanin in leaves and stems
were evaluated.
Phytophthora capsici resistance: Seedlings were grown in planting trays composed of 72
cells (#TOD 1804, T. O. Plastics, Clearwater, MN). Cells were filled with commercial soil
mixture (SunGro Redi-earth plug & seedling mix, Sum Gro Horticulture, WA, USA). The
trays were placed on heated propagation pads and soil kept at 28ºC. Two seeds were
sown per cell. Plants were inoculated at the four to six-true-leaf stage.
Brazilian P. capsici isolate Pcp106 was grown at 25 oC for 5-7 days on V8 juice agar media.
Using a spatula, the V8 plates were sliced into a grid. Each slice was transferred into a
150 x 150 mm petri plate with distilled water (35 ml) to induce formation of sporangia.
The plates were incubated for two days before inoculation. Then, the water plates were
placed in the refrigerator for exactly one hour. After removing from the refrigerator, the
plates were placed in the incubator (25 oC) for one hour for zoospores release. Inoculum
was adjusted with a hemacytometer to 2,000 zoospores per milliliter. Plant trays with
drainage holes were placed into trays filled with water to saturate the root zone. Each
cell received 5 ml of the prepared inoculum with a concentration of 2,000 zoospores/
ml. The water-satured root zone condition was maintained until susceptible controls
have showed disease symptoms. Approximately ten days after inoculation, when the
susceptible control exhibited extreme root rot symptoms, plants were scored for
resistance or susceptibility.
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Results and discussion
When “CM-334” (C. annuum) was used as female parent and “Orange Habanero” as
male parent few F1 fruits and seeds were obtained. Two F1 plants were grown and were
used as pollen donor to the recurrent parental “Orange Habanero” for obtaining BC1
generation. The BC1 germination was 12.5%, and 14 plants were grown and used as
pollen donor to recurrent parent “Orange Habanero” (Table1). Because of the low
germination of BC1 seeds, the BC2 generation was advanced without screening of BC1 for
P. capsici resistance. Tanksley and Iglesias-Olivas (1984) obtained seeds from
hybridizations between C. annuum x C. chinense with normal size, while seed from
reciprocal crossing were few and lower in size, and unilateral incompatibility between
C. annuum and C. chinense was documented by Pickersgill, (1991). Only 1% of these
seeds germinated and resulted in vigorous hybrids with intermediate characteristics
between C. annuum and C. chinense. Fruits of BC2 generation were recently harvested,
and a new cycle of backcrossing has been initiated. Backcrossing and screening for
resistance will continue.
Table 1. Total number of fruits and seeds, and percentage of seed germination
of F1, F2, and BC1 from C. annuum x C. chinense cross.
Total number fruits
Total number seeds
% germination
F1
12
72
5.55
F2
25
230
47.6
BC1
16
134
12.5
The F1 plants presented intermediate fruit and plant characteristics between “CM 334”
and “Orange Habanero.” The interspecific hybridization was confirmed through
evaluation of F2 population, which segregated for some plant characteristics such as
shape and size of leaves, stem and leaf pubescence, presence or absence of anthocyanin
in leaves and stems. F2 plants presented different combinations of “CM334” and “Orange
Habanero” (Table 2). Unfortunately, from 40 F2 plants evaluated only three produced
fruits by selfing, but these fruits did not develop well and did not form seeds.
Table 2. Some plant characteristics of “CM 334” and “Orange Habanero.”
Accessions
Trait
CM334
Shape leaves
Ovate
Orange Habanero
Deltoid
Corolla color
White
Light yellow
Flowers per axil
1
2-3
Anthocyanin
+
-
Leaves pubescence
Abundant
Sparse
Stem pubescence
Abundant
Sparse
(+): presence; (-): absence
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Advances in Genetics and Breeding of Capsicum and Eggplant
A total of forty-eight F2 plants were inoculated with a Phytophthora capsici isolate from
Brazil (Pcp 106), and 23 plants showed resistance (47.9%). Six F2 resistant plants were
saved and will be also backcrossed with “Orange Habanero.”
References
Bosland, P.W.; Lindsey, D.L. 1991. A seedling screen for Phytophthora root-rot pepper,
Capsicum annuum. Plant Disease 75:1048-1050.
Bosland, P.W.; Votova, E. J. 2000. Peppers: Vegetable and spice Capsicums. CABI Publishing,
New York, USA.
Oelke, L.M.; Bosland, P.W. 2003. Differentiation of race specific resistance to Phytophthora
root rot and foliar blight in Capsicum annuum. Journal of the American Society for
Horticultural Science 128:213-218.
Pickersgill, B., 1991. Cytogenetics and evolution of Capsicum L., In, T. Tsuchiya and P. K.
Gupta (Eds.), Chromosome engineering in plants. Genetics, Breeding and Evolution,
Elsevier, Amsterdam, Part B, 139.
Sy, O.; Bosland, P.W. 2005. Inheritance of Phytophthora stem blight resistance as compared
to Phytophthora root rot and Phytophthora foliar blight resistance in Capsicum
annuum L. Journal of the American Society for Horticultural Science 130:75-78.
Tanksley, S.D.; Iglesias-Olivas, J. 1984. Inheritance and transfer ol multiple-flower character
from Capsicum chinense into Capsicum annuum. Euphytica 33:769-777.
Walker, S. J.; Bosland, P.W. 1999. Inheritance of Phytophthora root rot and foliar blight
resistance in pepper. Journal of the American Society for Horticultural Science
124:14-18.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Durable management of root-knot nematodes Meloidogyne spp.
in pepper (Capsicum annuum) using resistant genotypes
C. Djian-Caporalino1, A. Palloix2, A. Fazari1, N. Marteu1, M. Bongiovanni M.1,
A.M. Sage-Palloix2, G. Nemouchi2, P. Castagnone-Sereno1
INRA, UMR 1301 Interactions Biotiques et Santé Végétale, 400 Route des Chappes, BP 167,
F-06903 Sophia Antipolis, France. Contact: [email protected]
2
INRA, UR1052 Génétique et Amélioration des Fruits et Légumes, BP 94,
F-84143 Montfavet, France. Contact: [email protected]
1
Abstract
Breeding for root-knot nematode (RKN) resistance is a major challenge for pepper
breeders. The diversity of RKN species infecting pepper plants in several major production
areas is a threat to the use of single R genes. In Capsicum annuum, resistance to
Meloidogyne spp. is controlled by several linked dominant genes - the Me genes. Three
of them are effective against a wide range of RKN species, including the most common
species in tropical areas. Several molecular markers useful for marker assisted selection
have been developed. Studies to determine the durability of the R-genes (alone or
pyramided) in different genetic backgrounds are now underway to implement better
management of the R-cultivars under agricultural conditions. First, we showed that
these genes direct different response patterns in root cells depending on the pepper line
and nematode species and that these different response patterns are linked to the
frequency of emergence of virulent nematode genotypes. So, the pyramiding of Me
genes based on the complementarity of their mode of action may make it possible to
prevent the breakdown of RKN resistance. Then, comparing heterozygous or homozygous
R-lines in susceptible or partially resistant genetic backgrounds, we showed that both
allelic status and genetic background influence the selection pressure exerted by the
R-genes on the RKN populations. Finally, experiments are in progress under 3-years-field
agronomic conditions comparing i) the alternance of single R-genes in rotation, ii) the
mixture of lines bearing single R-genes sown in the same plot, iii) the pyramiding of two
R-genes in one line and iiii) the genetic background in which the R gene was introgressed.
Results will allow the identification of conditions lowering the emergence of virulent
biotypes of RKN in the field, and to assess the time required for the improvement of soil
health (reduction of parasites under their damage threshold) using the R-plants as RKN
“traps”. This transfer from the laboratory to the field will constitute the ultimate
validation of the previous observations.
Acknowledgements
This research is supported at the national level by 1/ the Agriculture Ministry with a
CTPS (permanent technical committee of the selection of the crop plants) project on the
durability of resistance to RKN in Solanaceae (2007-2010), 2/ INRA with a project on
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Advances in Genetics and Breeding of Capsicum and Eggplant
integrated production of vegetable crops (PIClég™), acronym Neoleg2 (2008-2012), and
3/ the French National Research Agency with a project on Ecosystems, living resources,
landscapes and agriculture (Systerra), acronym Sysbiotel (2009-2013). At the European
level, this research is supported by 1/ the European network for the durable exploitation
of crop protection strategies, acronym ENDURE (2008-2010), and 2/ the INTERREG Al­
cotra cross-border cooperation France-Italy project, acronym Valort– Valorization of
cross-border vegetable crops (2010-2013).
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Evaluation of root knot nematode resistance in Capsicum annuum L.
and related species
C. Gisbert, A. Rodríguez-Burruezo, F. Nuez
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universidad Politécnica de Valencia,
Camino de Vera 14, 46022 Valencia, Spain. Contact: [email protected]
Root-knot nematodes (RKN) Meloidogyne spp., cause important crop losses in pepper (Capsicum
annuum) worldwide. The withdrawal in Europe of the efficient nematicide methyl bromide
has increased interest in finding new sources of variation for RKN resistance. Landraces of C.
annuum and other related Capsicum species represent a potential under­exploited material for
Capsicum breeding. In this work, we performed an evaluation for testing RKN tolerance in a
collection of Capsicum accessions from the COMAV Institute. Forty landraces of Capsicum
annuum and ten accessions of C. chacoense, C. frutescens and C. chinense were grown in a
natural infested field. Three C. annuum varieties, two of them previously reported as RKN
resistant and one sensitive, were used as controls. The percentage of plants with galled roots
varied among the tested germplasm from 0-100%. In general, a high galling index (3-5) was
observed in infected roots. Variability in RNK concentrations in the soil could be the cause of
infection rates lower than 100% in those accessions which were not tolerant. Accessions
considered as tolerant (with any plant with galled roots) or those which presented infection
rates lower than 40% were selected for subsequent RKN tolerance assays. If these preliminary
tolerances are confirmed, these materials, which belong mostly to C. annuum, could be of
great interest for pepper breeding or for direct utilization as rootstocks.
127
Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Compatibility assessment in tomato and common eggplant grafted
onto gboma and scarlet eggplants
C. Gisbert, J. Prohens, C. Trujillo, F. Nuez
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universidad Politécnica de Valencia,
Camino de Vera 14, 46022 Valencia, Spain. Contact: [email protected]
Abstract
Graft compatibility was investigated using the cultivar of tomato (Solanum lycopersicum
L.) UC82 and the common eggplant (Solanum melongena) cultivar Black Beauty (BB) as
scions, and the gboma eggplant (Solanum macrocarpon; accessions BBS117 and BBS168)
and scarlet eggplant (Solanum aethiopicum; accessions BBS107 and BBS116) as rootstocks.
Evaluations of the extent of graft (in)compatibility were made by examining survival
percentages 30 days after grafting. High survival rate was obtained after grafting eggplant
(BB) onto S. macrocarpon and S. aethiopicum (from 90 to 100%). With respect to tomato
(UC82) grafted plants, grafting success rates of 80% and 90% were obtained using S.
macrocarpon BBS168 and S. aethiopicum BBS116 as rootstocks. Tomato and eggplant plants
grafted onto S. macrocarpon BBS168 (combinations with lower grafting success) were
grown until complete development and a similar growth and development were observed
in these plants and their respective controls. A decrease in S. macrocarpon rootstock
diameter and overgrowth just over the healing stem zone were observed in tomato plants
grafted onto S. macrocarpon BBS 168. However, despite these symptoms of incompatibility
we have not observed other symptoms of delayed graft-incompatibility such as dwarfism,
sudden wilting, high chorophyll content, or small fruits. Other changes in tomato plants
grafted onto BBS168 have been earliness and a slight modification of tomato fruit shape.
A reduction of leaf length and a lower number of flowers was observed in both tomato and
eggplant plants grafted onto BBS168. These preliminary results are indicative of the
moderate incompatibility reported in eggplant-tomato rootstock combinations, which was
expressed in tomato grafted onto S. macrocarpon BBS168. The hight graft union in eggplant
grafted onto S. aethiopicum and S. macrocarpon rootstocks and the good growth
performance of eggplant-S. macrocarpon grafted plants indicates that these rootstocks
might be useful for grafting eggplant.
Keywords: S. lycopersicum, S. melongena, S. macrocarpon, S. aethiopicum, grafting,
compatibility.
Introduction
The primary purpose of grafting vegetables worldwide has been to provide resistance to
soil borne diseases. Subsequently, grafting has been used to enhance vigour, water or
nutrient uptake as well as for avoiding abiotic stresses such as low temperatures or
salinity (Lee, 1994; Oda 1995; Rivero et al., 2003; Davis et al., 2008). Worldwide interest
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Advances in Genetics and Breeding of Capsicum and Eggplant
in vegetable grafting has risen because of the increase in sustainable practices and the
withdrawal of methyl bromide.
The eggplant (Solanum melongena L.) is widely cultivated in tropical and temperate
regions around the world (Daunay, 2008) and grafting is a common practice in some
countries, like Japan (Oda, 2008). Eggplant is commonly grafted onto Solanum torvum
Sw. (Singh and Gopalakrishnan 1997, Bletsos et al., 2003, Daunay 2008), tomato hybrids
and interspecific hybrids S. lycopersicum L. x S. habrochaites (Bletsos et al., 2003;
Leonardi and Giuffrida 2006). Other wild species that have been tested for grafting
eggplant have been Solanum sisymbriifolium Lam. (Rahman et al., 2002, and Solanum
integrifolium Poir. (Suzuki and Morishita, 2002; Yoshida et al., 2004). Eggplant rootstocks
have also been used for grafting tomato (Oda, 1995). Nevertheless, tomato-eggplant
rootstock-scion combinations have been reported as moderately incompatible (Kawaguchi
et al., 2008) and deleterious effects may appear as consequence of grafting (Oda et al.,
1996, Leonardi and Giuffrida 2006, Kawaguchi et al., 2008). Thus, it is of interest to
increase the spectrum of compatible rootstocks for increasing tomato or eggplant yield
under different stress conditions. In this work we assess the compatibility of two varieties
of gboma eggplant (Solanum macrocarpon L.) and two of scarlet eggplant (Solanum
aethiopicum L.) as rootstocks of eggplant and tomato. S. aethiopicum has been described
as tolerant to Fusarium oxysporum and Ralstonia solanacearum (Hébert 1985; Daunay et
al., 1991; Cappellii et al., 1995). Fusarium wilt resistance was also found in S. macrocarpon
(Monma et al., 1996). These characteristics and their good germination ability, compared
to wild species may make them good candidates as rootstocks.
Material and Methods
Plant material
Two varieties of S. macrocarpon (BBS-117, BBS-168) and two of S. aethiopicum (BBS-107,
BBS-116) were used for the present study as rootstocks. The eggplant cultivar ‘Black
Beauty’ (BB; B and T World Seeds, Aiguesvives, France) and the tomato cultivar UC82
(Intersemillas, Valencia, Spain) were used as the scions. Ungrafted plants were used as
controls.
Grafting and cultivation conditions
Eggplant and tomato were grafted onto S. aethiopicum and S. macrocarpon rootstocks
using the cleft approach procedure described by Lee (1994). Rootstock seeds were
germinated 10 days before of those of scions. Grafting was made when plants used as
rootstocks and scion showed five to six and three to four leaves, respectively resulting
in 20 plants per rootstock-scion combination. Ten days after grafting all grafted plants
were transplanted to pots (16 cm diameter) with a fertilized peat and they were cultured
during 20 days in order to observe grafting success rates. Also, in order to study the
effects of grafting on plant and fruit characteristics, ten tomato and ten eggplant plants
grafted onto S. macrocarpon BBS168 (combinations with lower grafting success), as well
as their respective non-grafted controls were transplanted to pots (40 cm diameter)
filled with non-fertilized coconut fibre substrate (Horticoco and Valimex, Valencia,
Spain) and grown in an hydroponic system as detailed in Gisbert et al. (2010) in a
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greenhouse that had average maximum and minimum temperatures of 20 ºC and 12 ºC,
respectively. At 50 days after transplant, height, stem diameter of scion and rootstock
(measured 3 cm below the junction and 10 cm above), leaf morphology (lobes, lenght,
width) and the number of flowers and fruits were measured. Also, a sample of the first
tomato mature fruits (10 fruits for each treatment) were weighted.
Statistical analysis
Data for each of the traits evaluated was subjected to a one-factor analysis of variance
(ANOVA). Significance of the treatment effects was obtained from the ANOVAs, and
where the F-test proved significant (p =0.05), means were compared using the Duncan
multiple-range test.
Results and discussions
Grafting success
Grafting success was high (from 90 to 100%) in all combinations of S. melongena grafted
plants (Table 1). With respect to tomato grafting success, 95% and 90% of survival were
observed 3 days after grafting onto S. aethiopicum BBS116 and S. macrocarpon BBS168,
respectively. These percentages decreased subsequently to 90 and 80 %, respectively,
due to the graft union opening.
Table 1. Grafting success at 3 and 30 days after grafting Black Beauty (BB) eggplant
and UC82 tomato onto S. aethiopicum (BBS107, BBS116) and onto
S. macrocarpon (BBS117; BBS168) rootstocks.
a
Scion
Grafting success (%) Grafting success (%)
at 3 daysa
at 30 daysa
Rootstock
Species
BBS117
S. macrocarpon
Eggplant BB
95
95
BBS168
S. macrocarpon
Eggplant BB
90
90
BBS107
S. aethiopicum
Eggplant BB
95
95
BBS116
S. aethiopicum
Eggplant BB
100
100
BBS168
S. macrocarpon
Tomato UC82
90
80
BBS116
S. macrocarpon
Tomato UC82
95
90
Twenty plants for each rootstock-scion combination
Growth performance
The growth performance of tomato and eggplant plants grafted onto S. macrocarpon
BBS168 and non-grafted plants was compared. In appearance, eggplant and tomato
plants grafted onto this rootstock developed like their respective controls (non-grafted
plants) showing similar height (Table 2). However, a decrease in S. macrocarpon rootstock
diameter was observed in tomato grafted plants (Table 2). Also a marked overgrowth
just over the stem graft union point was observed in these plants (Figure 1A). This
effect, has been described as common in tomato grafted onto S. integrifolium (Oda et
al., 1996). Other symptoms of delayed graft-incompatibility such as dwarfism, sudden
wilting, high chlorophyll content or small fruits were not observed in our case. Despite
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the decrease of S. macrocarpon stem, grafted plants grew till maturity and fructified
like the control. This indicates that the translocation of assimilates, mineral nutrients,
and water between scions and rootstocks was correct. Other changes observed in tomato
grafted plants in respect to the control were a reduction of leaf length and number of
leaf lobes, whereas a higher fruit number was obtained (Table 2). A reduction of leaf
length was also observed for eggplant grafted onto the same rootstock (Table 2).
Table 2. Growth characteristics of S. macrocarpon BBS168 and tomato UC82 and BB eggplant
plants (controls) and of UC82 and BB plants grafted onto S. macrocarpon BBS 168 (BBS168-UC82
and BBS168-BB, respectively) at 50 days after transplant in an hydroponic system.
Plant
material
BBS168
Tomato
UC 82
Eggplant
BB
Graft BBS
168-UC82
Graft BBS
168-BB
Plant
height
(cm)a
Rootstock
stem
diameter
(cm) a
Scion
stem
diameter
(cm) a
Leaf
width
(cm)a
Leaf
length
(cm)a
Number
of leaf
lobesa
Number of
Number
opened
of fruits /
flowers /
planta
planta
132.b
3.60 b
3.08 b
28.c
43.2 e
10.8 b
3.7 a
0.8 a
91.7 a
3.61 b
2.90 ab
6.5 a
15.3 b
12.9 c
4.5 a
4.2 b
138.4 b
3.7 b
3.03 b
22.1 b
33.5 d
6.8 a
30.8 c
0.0 a
80.3 a
2.93 a
2.64 a
5.4 a
12 a
10.9 b
6.9 a
5.7 c
138.2 b
3.8 b
2.77 ab
21.4 b
29.8 c
6.7 a
22.5 b
0.0 a
Mean values separated by different letters are significantly different (P<0.05) according to
Duncan’s multiple range test.
a
The first mature fruits were observed for tomato grafted plants. This fact, and the
higher number of fruits observed in tomato grafted plants indicate increased earliness in
this rootstock-scion combination. Earliness in grafted plants has been reported in several
works (Yasinok et al., 2009; Gisbert et al., 2010) and may be related to a greater vigour
or nutrient uptake of the rootstock or to a modification of the internal growth regulator
balance. On average, the number of flowers was lower for grafted eggplant than for the
control, but in tomato grafting had not effect on flower number (Table 2). Other changes
that have been observed in tomato fruits of grafted plants was a slight modification of
fruit shape. That is, fruits from tomato variety UC82 showed a round shape and those
from grafted plants presented a heart shape (Figure 1C). Modification of shape in one
pepper hybrid grafted onto a pepper rootstock was also reported by Gisbert et al. (2010).
Fruit size decrease of grafted plants has been reported in several works (Oda et al.,
1996; Morra and Bilotto, 2006; Mohamed et al., 2009). In our work, tomato fruits from
ungrafted and grafted plants presented similar average weights respectively of 60.5 ±
3.5 g and 57.2 ± 2.1 g.
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Advances in Genetics and Breeding of Capsicum and Eggplant
A
B
C
Figure 1. A and B: Junction area of a tomato (A) and an eggplant (B) plant grafted ontos
S. macrocarpon BBS168 rootstock. C. Tomato fruits from non-grafted (on the left)
and grafted plants (on the right).
Conclusions
The results showed a moderate incompatibility in the S. macrocarpon-tomato rootstock
combination that was expressed by a lower percentage of grafting success when compared
with grafted eggplant an overgrowth just over the graft union zone in plants of tomato
grafted onto S. macrocarpon BBS168 and a reduction of the S. macrocarpon rootstock dia­
meter. Grafting has produced a reduction of leaf length and number of leaf lobes in tomato
scion. Earliness, an increase in fruit number, and a slight modification of fruit shape were
also observed in tomato grafted plants. When eggplant was used as scion only a reduction
of leaf length was observed. The better graft union was observed for eggplant grafted onto
S. aethiopicum and S. macrocarpon rootstocks and the good growth performance of eggplant
-S. macrocarpon grafted plants indicate that this species can be used as eggplant rootstock.
Acknowledgements
The excellent technical assistance of Mrs. Nuria Palacios is gratefully acknowledged.
References
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Genetics of resistance of the Kahramanmaraş pepper KM2-11
genotype to Phytophthora capsici isolates
M. Gocmen1, K. Abak2
Antalya Tarim Production, Consulting and Marketing Co., Antalya, Turkey.
Contact: [email protected]
2
Çukurova University, Faculty of Agriculture, Department of Horticultural, Adana, Turkey
1
Abstract
Phytophthora capsici is a major disease of pepper in the fields of Kahramanmaraş region in
Turkey. KM2 genotype which was selected in Kahramanmaraş region pepper population is
partially resistant to P.capsici. In this study, three experiments were conducted including
KM2-11, the susceptible genotype ‘KMAE-12 and its F1, F2, and backcrosses. Three P.capsici
isolates , i.e., Top-1; virulent, M-26; mildly virulent and M-56; avirulent were isolated from
pepper plants and pathogens with different virulence levels were inoculated to (6-week
old) plants. Three different criteria were used to evaluate the resistance, corresponding to
different steps of the host-pathogen interaction: receptivity, inducibility and stability. The
F1 F2 and BC1 generations of KM2-11 line which were inoculated by three isolates showed
that resistance is polygenic
Keywords: Capsicum annuum, partially resistant pepper, Phytophthora root rot, disease
resistance
Introduction
In Turkey, pepper is grown mainly for both their red fruits for being used as dried powder/
spices and for their green pods for fresh consumption. The best material for spices is
grown in spring and summer in open fields in Kahramanmaraş region. Growing pepper for
dried powder and sauce in southern part of Turkey is very intensive and continuous
cropping is a common practice. Therefore, growers often face severe soil borne disease
problems. The most severe one of them is Phytophthora blight caused by Phytophthora
capsici L. In order to minimize the yield losses of pepper caused by Phytophthora blight,
fungicides, crop rotation, drip irrigation, and resistant cultivars have been employed
widely during the cultivation of pepper plants (Hartman and Wang 1992). However,
because of difficulties in effectively controlling the disease with soil and foliar fungicides,
the use of resistant cultivars, crop rotation and drip irrigation would be a valuable
contribution to growers. Tolerant or resistant commercial pepper variety to Phytophthora
blight is absent in Turkey.
Several resistance sources were found in local populations of the cultivated species
Capsicum annuum. Two of four main sources of resistance to Phytophthora capsici are
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“PI201232” and “PI201234”, which come from Central America (Kimble and Grogan, 1960)
and the other two, “Line 29” and “Serrano Criollo de Morelos 334” (SCM334), originated
from Mexico (Guerrero and Laborde, 1980). Genetic analysis of resistance to P.capsici has
been undertaken for each of these four sources by different authors. Several factors have
been reported to affect host plant resistance, such as plant age, inoculation method,
fungal isolate/pathotype, and zoospore concentration (Hartman and Wang, 1992, Kim et
al., 1989, Palloix et al., 1988). One additional factor, such as virulence levels of pathogens
(avirulent, mildly virulent and virulent), also affects the host plant resistance (Black and
Berket, 1998). Breeding for P.capsici resistance is facilitated if the type of inheritance of
the resistance is known. Numerous researchers have reported conflicting results regarding
the inheritance of resistance to P.capsici, likely due to the above factors (Guerrero and
Laborde, 1980, Ortega et al., 1991, Walker, 1999).
The objective of this experiment was to investigate the inheritance of resistance to
Phytophthora capsici isolates in the local pepper KM2-11 genotype as resistance sources
to P.capsici. Three isolates of P.capsici originating from different geographical regions in
Turkey were selected to evaluate the genetics of resistance in KM2-11.
Material and Methods
Plant materials
Two lines were used in this study; KM2-11 and KMAE-12.
KM2-11 was selected in the Kahramanmaraş pepper population by Abak. It was selfed for
four generations. This line is characterised by having dark red fruits with “kapya” type
with 10,5 cm. fruit length, 2.8 cm. fruit width, 1.8 mm. pericarp thickness and 13.6 g
fresh fruit weight, and is suitable for dried red pepper production as spices. KM2-11 line
was used as a male parent and resistant source for P.capsici in this study.
The other line KMAE-12, also selected from Kahramanmaraş pepper population by
Kahramanmaraş Agricultural Research Institute. Because of its fruit red colour, pericarp
thickness and dry yield, KMAE-12 line is better than KM2-11. This line was used as a
female parent and susceptible for P.capsici
Susceptible parent, “KMAE-12” was crossed with the resistant “KM2-11” to obtain F1
progeny. Self-pollinated fruits were harvested at the ripe stage from F1 plants to obtain
the F2 generations. F1 plants were also backcrossed to their respective resistant parent
(KM2-11) to obtain testcross plants.
Fungal materials
Three P.capsici isolates were used in this experiment. A highly virulent P.capsici isolate
(Top-1) was isolated from an infected pepper plant in greenhouse in Antalya provinces of
Turkey. M-26 isolate (mildly virulent) and M-56 (avirulent) were isolated from the
diseased pepper stems in fields of Kahramanmaraş province. These three isolates were
inoculated to different pepper genotypes to confirm the differences for the virulence of
isolates in an other work (Gocmen and Abak, unpublished data).
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Inoculation and resistance evaluation
Stem artificial inoculation method was used to evaluate the P.capsici resistance in this
study. The stem inoculations were performed as described by Pochard et. al. (1976). Test
pepper plants were grown in peat moss-:perlite soil mixture (6:2; v/v) in black plastic
containers (7 x 9 cm). The resistance tests were conducted in a controlled growth
chamber at 24±2°C with 12 h of light.
Parental lines (KMAE-12 and KM2-11), F1, F2, and testcross plants were artificially ino­
culated. Top-1, M-26 and M-56 isolates were tested in three different experiments. The
number of plants in parents, F1, F2 and testcross in the each experiment were 10, 10,
50, and 25 respectively. The stem inoculation procedure was as follows. Plants at the
first flowering stage (from 6- to 8-week-old plants) were cut off below the first flower.
A P.capsici mycelia plug was placed on the fresh section of the main stem and wrapped
with aluminium sheet for 3 days period. Typically, the disease symptom in pepper tissue
was brownish tissue resulting of necrosis. The progression of necrosis toward the bottom
of the stem was measured every 3-4 days and the speed of fungal invasion (mm/day) was
calculated (Lefebvre and Palloix, 1996). Three quantitative criteria were used to
evaluate the resistance according to Pochard and Daubeze (1980) and Pochard et. al.
(1983). The quantitative criteria of resistance were receptivity, which included over the
first 3 days after inoculation (mm/day), inductibility, which was the decrease of speed
necrosis between the 3rd and 10th day after inoculation (mm/day2), and stability
respectively. The stability period covered the mean speed of stem necrosis between 14th
and 21st day after inoculation (mm/day). Receptivity, inducibility and stability correspond
to distinct resistance components were observed in KM2-11 genotype against three P.
capsici isolates.
Results and discussion
Parents and isolates interaction
In this study, susceptible parent KMAE-12 pepper line and KM2-11 partially resistant to
P.capsici were crossed and F1, F2 and backcross (BCKM2-11) were developed as the
populations for genetic studies. These populations were used to determine the inheritance
of resistance in KM2-11 genotype against three different P.capsici isolates. Parents x
isolates interactions in receptivity and inducibility periods were non significant (p=0.22
and p=0.41) but was significant in stability period. However, KMAE-12 and KM2-11
genotypes resistance level and three isolates virulence level were significantly different
in the three resistance criteria (Table 1).
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Table 1. Mean speed of stem necrosis of parents and isolates interaction for receptivity,
inducibility, and stability resistance criteria.
Receptivity period
Parents
KMAE-12
Top-1
M-26
19.06
11.46
M-56
6.3
Mean
12.38 A
Inductibility period
Top-1
M-26
2.03
1.15
M-56
0.72
Mean
1.30 A
KM2-11
18.66
8.90
5.79
11.12 B
1.88
0.87
0.54
1.10 B
Mean
18.86 a
10.18 b
6.21 c
11.75
1.95 a
0.01 b
0.63 c
1.20
Parents
Stability period
Top-1
M-26
M-56
Mean
KMAE-12
14.35 a
12.81 a
8.04 b
11.73 A
KM2-11
13.03 a
4.54 c
3.77 c
7.11 B
Mean
13.69 A
8.67 B
5.90 C
9.42
Means followed by different letter are significantly different (P<0.05).
Receptivity resistance component
The mean speed of stem necrosis of parents and F1, F2 and BC1 populations ranged
between 12.0 mm in KMAE-11 variety for Top-1 isolate and 2.9 mm in KM2-11 resistance
parent for M-56 isolate. The mean speed of stem necrosis of the F1 and F2 populations
was closer to the susceptible parent (respectively 10.1 and 11.3 mm) for Top-1 virulent
isolate, predictably to be between resistance to susceptible parents in the M-26 and
M-56 isolates (F1, 6.6 and F2, 8.4 mm in M-26 isolate; F1, 4.3 and F2, 4.9 mm in M-56
isolate) (Table 2). Regarding receptivity period, the resistance of plants against M-26 and
M-56 isolates in testcross population was high toward to resistance parent, contrary to
expectation; it was low in Top-1 virulent isolate.
Table 2. Mean speed (±SE) of stem necrosis of parents and F1, F2, and BC1 populations in
receptivity (mm/day-), inducibility (mm/day2) and stability (mm/day).
Parents and
population
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Receptivity period
Top-1
M-26
M-56
Inducibility period
Top-1
M-26
M-56
Stability period
Top-1
M-26
M-56
KM2-11
5.4±1.4
4.2±0.8
2.9±1.6
0.6±0.2
0.6±0.1
0.2±0.1
4.5±2.4
4.1±1.3
2.1±0.9
KMAE-12
12.0±.5
9.6±1.1
6.8±1.2
2.0±0.2
1.2±0.2
0.3±0.1
12.0±2.9
4.5±1.3
3.8±1.1
F1
10.1±0.5
6.6±1.3
4.3±0.7
1.6±0.1
0.7±0.1
0.4±0.1
10.0±1.5
7.3±1.3
1.6±0.3
F2
11.3±1.3
8.4±1.3
4.9±1.0
1.7±0.4
0.7±0.2
0.3±0.1
8.5±2.4
4.8±1.4
2.0±0.9
BC1 (F1 x KM2-11)
9.6±1.3
7.2±1.0
3.1±0.6
1.3±0.3
0.6±0.2
0.3±0.1
9.3±2.5
3.4±1.0
2.0±0.7
Number of BC1 populations plants
Number of F2 populations plants
Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 1. Frequency distribution of receptivity, inducibility and stability in the F2 and BC1
population. Note: KM2-11, resistance variety; KMAE-12, susceptibily variety; Top-1,
highly virulent, M-26, mildly virulent; M-56, avirulent isolate.
Figure 1 shows the frequency distribution of receptivity criteria in F2 and BC1 population.
The F1 plants were partially resistant to three isolates but not completely resistant. This
indicates that inheritance of resistance was not dominant in receptivity resistance
criteria. This hypothesis was supported by the segregation ration of the F2 population.
Some plants in tested plants with three isolates in F2 population were observed as
resistant and susceptible, similarly to KMAE-12 and KM2-11 parents. Besides, the majority
of plants reacted as partially resistant to three isolates as F1 plants. The evaluation of
F1, F2 and BC1 data show that, the inheritance of receptivity resistance criteria to three
isolates fits with the hypothesis of polygenic inheritance.
Inducibility resistance component
The second resistance criteria to P. capsici was inducibility, which was the induction of
fungi static activity in infected stems that would be brake or stop the fungal progression
in resistant genotypes (Lefebvre and Palloix, 1996). The parent plants were inoculated
with Top-1 virulent and M-26 mildly virulent isolates. The results indicated that KMAE-12
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Advances in Genetics and Breeding of Capsicum and Eggplant
was susceptible and KM2-11 was resistant. For two isolates, genetic segregation was
observed in F2 and BC1 populations. Nevertheless, when KMAE-12 and KM2-11 parents,
F2 and BC1 population plants were inoculated with M-56 non-virulent isolate there was
no genetic segregation. All plants were resistant or partially resistant (Table 2).
The frequency distribution for inducibility resistance criteria in KM2-11 line as the
resistance parent in the F2 and BC1 population is shown in Figure 1. These distributions
suggested that this resistance criterium was controlled by an oligogenic/polygenic system.
However, some resistant alleles were present in resistant parent KM2-11 and these could
control the fungal progression in tissue even different isolates virulent level. The F1 plants
derived from KMAE-12 and KM2-11 were partially resistant to Top-1 virulent isolate, and
were completely resistant to M-26 mildly isolate. In the F2 population, some plants (34%)
were more resistant than the resistant parent. These data observed from F1 and F2
population to M-26 mildly isolate indicated that there was heterosis in F1 generation and
also transgressive segregation in F2 population. The F1 population against Top-1 virulent
isolate has shown partial dominance effects. In F2 and BC1 population, segregation was
not observed when inoculated with M-56 avirulent isolate. This data indicated that
susceptible parent KMAE-12 has some resistant alleles to avirulent isolate M-56. Several
authors have reported that the susceptible parent has a minor effect on P.capsici resistance
(Young et al., 1993, Black and Berket, 1998, Lefebvre and Palloix, 1996). The frequency
distribution for Top-1 virulent isolate in the F2 population showed a very wide range which
indicated that additive effect was shown to control a part of the resistance of KM2-11
genotype to aggressive isolate as Top-1. Additive and epistasis effects in resistance to P.
capsici have been reported by Bartual et al. (1994) and Lefebvre and Palloix, (1996).
Stability resistance component
Stability resistance criteria can give us the important information about resistance to
P.capsici that it expresses the ability of the genotype to maintain the fungi static activity
over a long time period (Lefebvre and Palloix, 1996). The mean speed of stem necrosis
(mm) of parents and F1, F2, and BC1 populations in stability is shown at Table 2. As
shown Table 2, the mean speeds of stem necrosis of KMAE-12 and KM2-11 parents against
M-26 mildly virulent were respectively 4,5 mm and 4,1 mm and very similar. However,
the genetic segregation for M-26 isolate in F2 and BC1 populations observed (figure 1).
The mean speed of stem necrosis of F1 generation indicated that the resistant to the
virulent isolate Top-1, was respectively controlled by the partial dominance gene system.
F1 population screening against M-26 mildly virulent showed a response of negative
heterosis, in despite of heterosis effect to M-56 avirulent isolate. Negative heterosis to
M-26 isolate indicated that there were gene/genes affecting susceptibility to both
parents. The frequency distribution in the F2 population to M-26 and M-56 isolates shown
at figure 1 that there were higher resistant plants than resistant parent and more
vulnerable plants from susceptible parent. The F2 population segregation to M-26 and
M-56 isolates indicates that plants resistance and susceptible were affected by
complementary and epistasis gene system. These results, in particular, showed the
polygenic/oligogenic gene system in the KM2-11 against three isolates to stability
resistant period. In addition, plant resistance in the susceptible parent could affect the
stability resistant criteria. Effects in the susceptible parent against Top-1 virulent isolate
were lower level than when infected with M-26 mildly and M-56 avirulent isolates.
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Conclusions
This study focused in the understanding of the inheritance of resistance of KM2-11 local
genotype to the different P. capsici isolates. Three different criteria were used to evaluate
the resistance, corresponding to different steps of the host-pathogen interaction;
receptivity, inductibility and stability. The frequency distribution of three resistance
criteria in F1, F2 and BC1 population derived from KMAE-12 and KM2-11 indicated that
these three criteria against three isolates were controlled by a polygenic/oligogenic
resistance system.
References
Allard, R.W. 1999. Priciples of plant breeding. 2nd Edition In: Inheritance of Continuously
varying characters: Biometrical Genetics.
Black, L.L. Berket, T. 1998. Breeding for Phytophthora resistance in pepper. Xth Eucarpia
meeting on genetics and breeding of Capsicum and Eggplant, France, p. 115-119.
Guerrero-Moreno, A. Laborde, J.A. 1980. Current status of pepper breeding for resistance
to Phytophthora capsici in Mexico. IV. Meeting Eucarpian Capsicum Working Group.
Wageningen: 52-56.
Hartman, G.L. Wang, T.C. 1992. Phytophthora blight of pepper: screening for disease
resistance. Trop. Pest. Manage. 38:319-322.
Kim, Yj., Hwang, Bk. Park, Kw. 1989. Expression of age-related resistance in pepper
plants infected with Phytophthora capsici. Plant Dis. 73: 745-747.
Kimble, K.A. Grogan, R.G. 1960. Resistance to Phytophthora Root Rot in Pepper. Plant
Disease Reporter 44 (11): 872-873.
Lefebvre, V. Palloix A. 1996. Both additive and Epistatic Effects of QTLs are Involved in
Polygenic Induced Resistance to Diseases: A Case Study, the Interaction PepperPhytophthora capsici Leon. Theor. Appl. Genet. 93: 503-511.
Ortega,R.G., Palazon-Espanol, C. And Cuartero-Zueco, J. 1991. Genetics of resistance to
Phytophthora capsici in the pepper line SCM 334. Plant Breeding 107:50-55.
Palloix, A., Daubeze, A.M. Pochard, E. 1988. Phytophthora root rot of pepper. Influence
of host genotype and pathogen strain on the inoculum density- disease severity
relationships. J.Phytopathology.123:25-33.
Pochard, E., Clerjeau, M. Pitrat, M. 1976. La Resistance du piment, Capsicum annuum L.a
P.capsici Leon.I. Mise en evidence d’une ınduction progressive de la resistance. Ann.
Amelior.Plantes. 26(1):35-50.
Pochard, E. Daubezea, M. 1980. Recherches et evalution des composantes d’une resistance
polygenique:la resistance du piment a Phytophthora capsici. Ann. Amelior. Plantes,
30(4): 377-398
Pochard, E., Molot, P,M. Domınguez, G. 1983. Etude de deux nouvelles sources de resistance
a P.capsici chez le piment:confirmation de existence trois composantes distinctes
dans la resistance. Agronomie. 3:333-342.
Walker, J.S. Bosland, P.W. 1999. Inheritance of Phytophthora root rot and foliar blight
resistance in pepper. J. Amer. Soc. Hort.Sci.124 (1):14-18.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Development of sweet pepper grafting in Brazil
R. Goto1, H.S. Santos2, R.K. Kobori3, R. Braga3
1
Universidade Estadual Paulista/Fac.Ciências Agronômicas-C.Botucatu; CP 237, CEP 18603-970 Botucatu,
SP, Brazil Contact: [email protected]
2
Centro Estadual de Educacão Tecnológica Paula Souza, Faculdade de Tecnologia, Brazil
3
Sakata Seed Sudamerica Ltda., Brazil
Abstract
With the objective to offer alternatives to control soil diseases, was introduced the graft
technique in sweet pepper at Brazil. In the first trials were made test of rootstock inbred
lines of Capsicum annuum to control Phytophthora capsici in 1999. The inbred lines were
inoculated with three different concentration of Phytophthora capsici/mL and were
obtained some resistant inbred lines that were used to create 45 F1 rootstock hybrids. The
most resistant rootstock hybrids to Phytophthora capsici were selected: AF-2607, AF-2622,
AF2633, AF2638, AF2639 and AF2640. It was also evaluated the rootstock hybrids AF2638
and AF2640 to Meloidogyne incognita race 2 reproduction. As susceptible check was used
the pepper hybrid Elisa-Syngenta. The rootstock hybrids AF2638 and AF2640 had nematode
reproduction index of 0,007 and 0,003 respectively, being considerate as no host. In the
sequence, was evaluated the yield and nutrient extraction to verify the compatibility or no
compatibility of rootstocks hybrids (AF2638 and AF2640) and sweet pepper (hybrids Rubia
R-Sakata and Margarita-Syngenta). Obtained yield was of 132t ha-1 and 153 t ha-1 in graft
and no graft plants of hybrid Rubia R, 144t ha-1 and 132 t ha-1 in graft and no graft plants of
hybrid Margarita. About nutrient extraction there was no significant difference between
graft and no graft plants and the nutrient concentration was in decrease sequence of
K>N>Ca>Mg>P>S. Nowadays in Brazil the grafting in sweet pepper is using for commercial
production and seed production with 2 millions grafted plants by year.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Resistance of Indonesian Solanum melongena and wild relatives to
Ralstonia solanacearum
Hartati1,2, H. Kurniawan1,3, E. Sudarmonowati2, G. van der Weerden4, T. Mariani1
1
Plant Cell Biology Departement, Radboud University Nijmegen, The Netherlands.
Contact: [email protected]
2
Research Center for Biotechnology, LIPI, West Java, Indonesia
3
Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development (ICABIOGRAD),
Bogor Indonesia
4
Experimental Garden and Genebank, Radboud University Nijmegen, The Netherlands
Abstract
Three hundred accessions of Solanum subgenus Leptostemonum from an Indonesian Solanum
collection were evaluated for resistance to three isolates of Ralstonia solanacearum
obtained from several diseased Solanaceae, such as eggplant, red pepper and tomato in
Indonesia. In addition, five accessions of Solanum incanum and one accession of Solanum
anguivi provided by the Experimental Garden and Genebank of the Radboud University
Nijmegen were also included in the screening test. In Indonesia, a total of 205 Solanum
accessions were inoculated by using a leaf-cutting method and the remaining plants were
inoculated by using a stem-cutting method. Most of the Solanum melongena accessions
were susceptible to Ralstonia isolates. Three accessions were resistant against the
bacterium with lowest wilt incidence. Furthermore, based on the screening test carried out
in the greenhouse, resistance to R. solanacearum was also found in some wild relatives. In
addition, beside the test in the greenhouse, 205 accessions also were tested in the field.
Three accessions that were found resistant to bacterial wilt in the greenhouse, also were
resistant under field conditions. Interestingly, Solanum jamaicense, which was found
resistant in the greenhouse, was susceptible under the field condition. The identification of
resistance gene(s) against R. solanacearum in the wild relatives of eggplant will help and
provide the plant breeders with a new source for stable resistance.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Molecular mapping of a CMV resistance gene in peppers
(Capsicum annuum L.)
W.H. Kang1, H.N. Huy1, H.-B. Yang1, S.H. Jo2, D. Choi1, B.C. Kang1
Dept. of Plant Science, Plant Genomics and Breeding Institute, and Research Institute for Agricultureand Life
Sciences, Seoul National University, Seoul 151-921, Korea. Contact: [email protected]
2
Bioinformatics Research Center, KRIBB, Daejeon, Korea.
1
Abstract
Cucumber mosaic virus (CMV) is one of the most destructive viruses in plants. Previous
studies have showed that CMV resistance in pepper is determined by partially dominant or
recessive genes. Capsicum annuum ‘Bukang’ is a commercial cultivar known to contain a
single dominant gene resistant to Cucumber mosaic virus (CMV).. We designated the name
Cmr1 in ‘Bukang’ to this resistant gene. Mapping study revealed the Cmr1 gene is located
at the centromeric region of LG2 near TG31.
Keywords: Capsicum, CMV, SNP, comparative mapping
Introduction
CMV has the broadest host range among plant viruses throughout the temperate regions
of the world. This virus infects more than 800 species in over 70 families of plants
including Solanaceae crops, and it spreads naturally by more than 60 aphid (Palukaitis et
al., 1992).
Within the last decade or so, various new sources of resistance to CMV have been
identified by pepper breeders. The new sources include such species as several accessions
of Capsicum: C. annuum ‘Perennial’ (Caranta et al., 1997; Lapidot et al., 1997; Grube
et al., 2000; Chaim et al., 2001), ‘Vania’ (Caranta et al., 2002), ‘Sapporo- oonaga’ and
‘Nanbu-oonaga’ (Suzuki et al., 2003); C. frutescens ‘BG2814-6’ (Grube et al., 2000); ‘LS
1839-2-4’ (Suzuki et al., 2003); and C. baccatum ‘PI 439381-1-3’ (Suzuki et al., 2003).
Most of these sources display partial resistance controlled by multiple genes.
Resistance in ‘Perennial’ is controlled by one to several genes and inherited recessive or
dominant (Lapidot et al., 1997). Previous researches reported two or four quantitative
trait locus (QTL) in ‘Perennial’ (Caranta et al., 1997; Chaim et al., 2001). Resistance in
‘BG2814-6’ is reported to be controlled by at least two major recessive genes (Grube et
al., 2000). These studies demonstrate that the inheritance in each source is controlled
by quantitatively.
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In contrast, Korean seed companies have bred CMV resistant commercial varieties
containing a single dominant CMV resistance gene. Despite the practical use of the CMV
resistance gene in seed companies, there have been no reports on the resistance gene.
Here, we show genetic analysis and mapping of a new CMV resistance gene (Cmr1) in
pepper.
Material and methods
Plant materials and DNA extraction
The two mapping populations used in this study were a C. annuum ‘Bukang’ F2 population,
and an AC 99 F2 population (Livingstone et al. 1999). The ‘Bukang’ variety, which is a
commercial variety known to contain a resistance gene against CMV, was obtained from
Monsanto Korea (Chochiwon, Korea). Approximately three decades ago, CMV resistance
line was indentified from a Chinese open-pollinated variety ‘Likeumjo’. Since then,
Korean seed companies have used this variety to develop commercial pepper (‘Bukang’)
that are resistant to CMV. To study the inheritance pattern of the resistance gene to CMV,
the F1 ‘Bukang’ plants were self-pollinated to obtain an F2 population. The procedure of
genomic DNA extraction was preformed as described in Hwang et al. (2009).
Virus materials, inoculation and ELISA analysis
The pepper seedlings were inoculated with CMV strains when two cotyledons were fully
expanded. The inoculums of CMV strains were prepared from infected leaves of Nicotiana
benthamiana or Cucumis sativus. One gram of infected leaves was ground in 10 ml of 0.1
M phosphate buffer pH 7.0. The plants were dusted with Carborundum #400 (Hayashi
Pure Chemical Ind., Japan) and inoculated by rubbing the viruses onto the two cotyledons.
We performed ELISA to test systemic infection at 7 dpi, and we checked the symptoms
once more at 14 dpi to avoid contamination. ELISA was used to detect CMV according to
the manufacturer’s protocol (Agdia, USA). Samples were considered positive for the
presence of CMV when the absorbance value (405 nm) of each sample was greater than
that of a healthy control plant.
Testing and development of markers
A total of 134 ‘Bukang’ F2 individuals were used to test the three previously reported
CAPS markers (Kim et al., 2004). PCR was performed in 25 µl reaction volumes containing
2.5 µl of 10X PCR buffer (20 mM Tris-HCl (pH 8.0), 100 mM KCl and 2 mM MgCl2), 2 µl of
10 mM dNTPs, 0.5 µl of 10 µM primers, 18.3 µl dH2O, 0.2 µl of Taq DNA polymerase, and
1 µl of 50 ng/µl DNA template. The PCR profile comprised an initial 4 min incubation at
94oC for denaturation, followed by (94oC for 1 min, 58oC for 1 min, and 72oC for 2 min) X
35 cycles, and a final extension step of 5 min at 72oC. The PCR reaction was performed
in a thermocycler (My Cyclertm, BioRad, USA). PCR products were digested with the
restriction enzymes XbaI and EcoRI.
PCR reaction of maker development was performed in a total volume of 20 µl containing
1X PCR reaction buffer (20 mM Tris-HCl (pH 8.0), 100 mM KCl and 2 mM MgCl2), 0.1 mM
dNTP, 0.2 U Taq DNA polymerase, 10 pmol of each primer, and 20 ng of genomic DNA. PCR
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conditions involved denaturing the DNA for 4 min at 95oC followed by 35 cycles of 30 sec
at 95oC, 30 sec at 55oC, and 40 sec at 72oC.
One tomato BAC clone, which is approximately 53000bp, was used for marker development.
It contains the Tm-1 gene that is located at the syntenic region of the Cmr1 gene. Pepper
EST sequence (cacn8446) was selected through the sequence analysis in pepper EST
database (www.210.218.199.240/SOL/). The primers were designed based on the predicted
intron position using Intron Finder software (www.sgn.cornell.edu). The primers used to
amplify intron sequences in pepper. The polymorphic analysis was conducted in AC99 and
‘Bukang’ F2 populations using High resolution melting (HRM) method. The condition and
procedure of HRM analysis was as described Park et al. (2009)
Results and discussion
Inoculation results of C. annuum ‘Bukang’ to CMV strains
Resistance spectrun of C. annuum ‘Bukang’ were investigated with three different CMV
strains (CMVKorean, CMVFNY and CMVP1). C. annuum ‘Jeju’ was used as a susceptible control.
The results of CMV screening showed that all the inoculated ‘Jeju’ were completely
susceptible to all three CMV strains. ‘Bukang’ was resistant to CMVKorean and CMVFNY but
was susceptible to CMVP1 strain.
To confirm the results, ELISA was performed using inoculated and uninoculated Bukang
leaves. As can be seen in Figure 1, CMVFNY coat protein was detected in inoculated
cotyledons and upper leaves of ‘Jeju’ plants. However, ‘Bukang’ showed CMV accumulation
in only inoculated cotyledons. These results demonstrated that the resistance gene in
‘Bukang’ inhibits CMV systemic movement.
Figure 1. Detection of CMV accumulation by enzyme-linked
immunosorbent assay (ELISA).
Inheritance study of resistance to CMV in C. annuum ‘Bukang’
To investigate inheritance of resistance gene in ‘Bukang,’ we constructed F2 ‘Bukang’
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population containing 134 individuals. CMVFNY was inoculated onto cotyledons of F2
individuals. The segregation of resistance and susceptibility scored in F2 ‘Bukang’
population was 104 to 30. It was fitted to a 3:1 Mendelian segregation model with Chi
squared (X2) and probability value (P) of 0.488 and 0.4848, respectively. These results
were consistent with dominant inheritance pattern and strongly demonstrated that
resistance in C. annuum ‘Bukang’ is controlled by a single dominant resistance gene. We
designated the name Cmr1 to this resistant gene.
Figure 2. The linkage analysis of Cmr1 region in pepper and tomato using comparative analysis.
Markers on tomato ESPEN 2000 chromosome 2 (A) and pepper AC 99 LG2 (B) are
only partially shown here. (C) Linkage group of the Cmr1 region in the Cmr1
segregating population. One SNP marker (cacn8446-2) was located around the
Cmr1 locus in Cmr1 segregating population (Bukang).
Locating the Cmr1 gene in a linkage map
The previous research reported that three CAPS markers were linked to the CMV
resistance gene (Cmr1) in pepper (Kim et al., 2004). However, the map location of Cmr1
has been not reported. To confirm the map location, we tested these markers. Testing
markers result showed that two out of three markers, CAPS-A and CAPS-B were located
at the centromeric region of LG2 near the TG31 marker in AC99 (Figure 2).
Development of Cmr1 linked markers
To develop Cmr1 linked marker, we used comparative analysis between tomato and pepper.
One tomato BAC sequence which is located at the syntenic region of Cmr1 gene was used
for more marker development. A blast search with BAC sequence revealed Tomato mosaic
virus resistance gene (Tm-1) sequence and several pepper EST sequences. Introns of the
EST were predicted using Intron Finder program (www.sgn.cornell.edu) for design intronbased marker. Four introns were predicted for EST sequence Cacn8446. Primers were
designed to amplify intron sequences. The second intron of cacn8446 showed polymorphism
in ‘Bukang’ F2 population and a SNP marker was developed. This marker showed three
recombinant individuals in 134 F2 populations. Several other SNP markers for pepper EST
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sequences were also developed but all markers were located on one side of the Cmr1 gene
(Figure 2). Markers on the opposite side and more closely linked markers are needed in
order to clone Cmr1. However, finding more closely linked markers may be very challenging,
because Cmr1 is located on the short arm of pepper chromosome 2, for which little
genomic information is available as it is a heterochromatic region (Gill et al. 2008).
References
Brasileiro-Vidal, A.C.; Melo-Oliveira, M.B.; Carvalheira, G.M.G.; Guerra, M. 2009. Diffe­
rent chromatic fractions of tomato (Solanum lycopersicum L.) and related species.
Micron 40:851-859.
Caranta, C.; Palloix, A.; Lefebvre, V.; Daubeze, A.M. 1997. QTLs for a component of
partial resistance to cucumber mosaic virus in pepper: restriction of virus installation
in host-cells. Theoretical and Applied Genetics 94:431-438.
Caranta, C.; Pfliege, S.; Lefebvre, V.; Daubeze, A.M.; Thabuis, A.; Palloix, A. 2002. QTLs
involved in the restriction of Cucumber mosaic virus (CMV) long-distance movement
in pepper. Theoretical and Applied Genetics 104:586–591.
Chaim, A.B.; Grube, R.C.; Lapidot, M.; Jahn, M.; Paran, I. 2001. Identification of quan­
titative trait loci associated with resistance to Cucumber mosaic virus in Capsicum
annuum. Theoretical and Applied Genetics 102:1213–1220.
Gill, N.; Hans, C.S.; Jackson, S. 2008. An overview of plant chromosome structure.
Cytogenetic and Genome Research 120:194-201.
Grube, R.C.; Zhang, Y.; Murphy, J.F.; Loaiza-Figueroa, F.; Lackney, V.K.; Provvidenti, R.;
Jahn, M. 2000. New source of resistance to Cucumber mosaic virus in Capsicum
frutescens. Plant Disease 84:885-891.
Hwang, J.; Li, J.; Liu, W.Y.; An, S.J.; Cho, H.; Her N.H.; Yeam, I.; Kim, D.; Kang, B.C. 2009.
Double mutations in eIF4E and eIFiso4E confer recessive resistance to Chilli veinal
mottle virus in pepper. Molecules and Cells 27:329-336.
Kim, S.; Hwang, J.; Kim, G.; Kim, S. 2004. Development of markers linked to CMV resistant
gene. Patent (10-2004-0086321). The Republic of Korea.
Kwon, J.K.; Kim, B.D. 2009. Localization of 5S and 25S rRNA genes on somatic and meiotic
chromosomes in Capsicum species of chili pepper. Molecules and Cells 27: 205-209.
Lapidot, M.; Paran, I.; Ben-Joseph, R.; Ben-Harush, S.; Pilowsky, M.; Cohen, S.; Shifris, C.
1997. Tolerance to Cucumber mosaic virus in pepper: Development of advanced
breeding lines and evaluation of virus level. Plant Disease 81:185-188.
Livingstone, K.D.; Lackney, V.K.; Blauth, J.R.; van Wijk, R.; Jahn, M. 1999. Genomic
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Palukaitis, P.; Roossinck, M.J.; Dietzgen, R.G.; Francki, R.I.B. 1992. Cucumber mosaic
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Park, S.W.; An, S.J.; Yang, H.B.; Kwon, J.K.; Kang, B.C. 2009. Optimization of high
resolution melting analysis and discovery of single nucleotide polymorphism in
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Schiex, T.; Gaspin, C. 1997. CARTHAGENE: constructing and joining maximum likelihood
genetic maps. Fifth international conference on intelligent systems for Mol Biol
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Suzuki, K.; Kuroda, T.; Miura, Y.; Muria, J. 2003. Screening and field traits of virus resistant
source in Capsicum spp. Plant Disease 87:779-783.
Tanksley, S.D.; Ganal, M.W.; Prince, J.P.; Devicente, M.C.; Bonierbale, M.W.; Broun, P.;
Fulton, T.M.; Genobannoni, J.J.; Grandillo, S.; Martin, G.B.; Messeguer, R.; Miller,
J.C.; Miller, L.; Paterson, A.H.; Pineda, O.; Roder, M.S.; Wing, R.A.; Wu, W.; Young,
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COSII genetic map of the pepper genome provides a detailed picture of synteny with
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Gall insects damaging eggplant and bell peppers in South India
N.K. Krishna Kumar1, D.K. Nagaraju1, C.A. Virakthamath2, R. Ashokan1, H.R. Ranganath1,
K.N. Chandrashekara1, K.B. Rebijith1, T.H. Singh1
1
Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore-560 089, India.
Contact: [email protected]
2
University of Agricultural Sciences, GKVK, Bangalore 560 065, India
Abstract
A complex of pests induces galls on egg plant and peppers. Recent reports regarding gall
forming insects on sweet peppers and eggplant as a single species (Asphondylia capparis
Rubsaamen) although earlier they were regarded as two distinct species, the one infesting
peppers A. capsisci Barnes, and the other infesting eggplant A. solani Tavares. In the present
study using molecular methods we were able to positively establish that they are two distinct
species. Larvae are creamy white to yellow in color. Pupa is light to dark brown and 3.25 mm
in length. Pupation was within the ovary or among anthers. Total developmental period from
egg to adult emergence was 11 days. Results of insecticide screening (July-November 2009)
consisting of conventional insecticides, fungicides and botanicals indicated that none out of
eleven insecticide/fungicide/botanicals was effective in limiting gall insect damage both in
eggplant and chilli pepper. Of the 147 eggplant genotypes evaluated (December 2009-March
2010) five genotypes viz., Solanum macrocarpon, Bhagyamati, African scarlet Eggplant, IC249387 and IC-90901 showed no gall midge or gall wasp infestation. Correlation between
flower damage and fruit damage was significant (r= 0.33). Thus, initial screening can be
focused on flower, to determine resistance to gall midge.
Keywords: Accessions, Asphondylia, Capsicum annuum, Ceratoneura, Chilli, Eggplant, Gall
midge, Solanum melongena
Introduction
Gall midge infesting eggplant and sweet pepper was first reported by Krishnaiah et al,
1975 in India. The species infesting peppers was named Asphondylia capsici Barnes, and
those infesting eggplant A. solani Tavares. Later reports regarded midge infesting
eggplant and chilli as one and the same. The species was A. capparis Rubsaamen. So far
no gall midge infestation is reported on tomato and potato. Until 2005-06, damage by
gall midge was largely restricted to sweet pepper and egg plant. However, in the last 3-4
years perceptible host shift has been observed to encompass chilli pepper too. Damage
due to midge in chilli is estimated to be 10-40% in Karnataka, Tamil Nadu, Andhra
Pradesh, Orissa, and Chhatisgarh. No chemical is reported to give satisfactory control of
the pest (Nagaraju per. communication).
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In recent years a group of gall forming insects has been noticed to inflict considerable
damage on peppers (Capsicum annuum L.) and eggplant (Solanum melongena L.) in
south and central India. The gall formers on these plants belong to Diptera and
Hymenoptera (Table 1). Galls induced by these insects are morphologically similar and
can be distinguished only after dissection of infested flowers. The ovary of infested
flowers bulges prominently towards one side with whitish discoloration. The petals
towards the infested part of the ovary are coarse textured and whitish green. Majority
of the infested flowers drop off and retained flowers develop into malformed fruits.
Another hymenopteran pest Ceratoneura indi Girault was reported as a pest on both egg
plant and sweet pepper (Narendran and Krishna Kumar, 1995). The damage is often similar
to gall midge. Sometimes more damage is inflicted by C. indi than the gall midge. Other
important gall inducing species include Geothella asulcta and Eurytoma chaitra, being
first report from India. The eggs are laid in very young flower buds and the life cycle is
completed within the infested flowers. The adults emerge prior to fruit set, leaving a fed
area on the ovary, which later manifests on the fruit as a sunken area. The extent of
flower drop or fruit malformation depends on the extent of damage to the ovary, which
in turn is linked to the species. However, in a few cases different stages of gall insects
were also observed in pea sized fruits and among anthers (Nagaraju et al., 2002).
The infestation due to gall insects on Capsicum flowers ranged from 10 –56% depending
on the variety/hybrid, stage of the crop, location and management practices followed
(Krishna Kumar et al., 1998; Nagaraju et al., 2002), where as, on eggplant it ranged
from 2-44% (Tewari et al., 1987). These infested flowers either drop off or develop into
to malformed fruits. The malformed fruits are unfit for market and they are culled out
at the farm gate itself. In addition, studies indicate that gall insects affect pollen
germination (Shashikumar et al., 2000; Nagaraju et al., 2002). Further, infested fruits
will have less number of seeds with reduced seed germination, 34–53% reduction in fruit
size, 52-88% reduction in seed number and 60-88% reduction seed weight/fruit (Nagaraju
et al. (2002).
In the last years there is an increased infestation of gall midge in many parts of south
and central India especially on hot peppers. Damage exceeds 40% at a few places.
Further, while peppers are infested, often adjacent eggplant is not damaged or viceversa. Thus, the species compositions on these host plants, possible biotypes that have
started damaging chilli peppers were investigated. Since management of gall midges on
a number of host plants has been through host plant resistance, 147 eggplant accessions
were screened. As a first step, a number of chemicals including new insecticide mole­
cules/botanicals/fungicides were evaluated for their efficacy to limit damage due to
gall insects in chilli and eggplant.
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Table 1. Gall forming species on Capsicum annuum L. and
Solanum melongena L.
Capsicum annuum L.
Species
Distribution
Reference
Diptera: Cecidomyiidae
Asphondylia capparis
Rubsaamen
India (Andhra Pradesh,
Karnataka, Madhya Pradesh,
Tamil Nadu)
Ayyanna and Raghaviah, 1990;
Nagaraju et al. 2002; Tomar et al.,
1996; Rangarajan and Mahadevan, 1974
Java
Frenssen et al., 1953
Turkey
Alkan, 1958
Cyprus
Orphanides, 1975
Hymenoptera: Eulophidae
Ceratoneura indi
Girault
India (Karnataka, Madhya
Pradesh, Maharashtra)
Narendran and Krishna Kumar, 1995;
Boucek, 1988; Ukey et al., 1989
Sri Lanka
Australia
Indonesia
New Caledonia
New Guinea
China
Japan
Goethella asulcata
India (Karnataka, Madhya
Girault
Pradesh, Maharashtra)
Hymenoptera: Eurytomidae
Nagaraju et al., 2002; Ukey et al.,
1989
Eurytoma dentata
India (Maharashtra)
Ukey et al., 1989
Eurytoma chaitra
Narendran
India (Karnataka)
Nagaraju et al., 2002
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Solanum spp.
Species
Distribution
Host
Reference
Diptera: Cecidomyiidae
Asphondylia capparis
Solanum
melongena
Nagaraju et al. (2002)
India (Karnataka,
Madhya Pradesh,
Maharashtra)
Solanum
melongena
Boucek, 1988
Narendran and Krishna Kumar,
1995
Senegal
Solanum
aethiopicum L.
Etienne and Delvare (1987)
Karnataka
Hymenoptera: Eulophidae
Ceratoneura indi
Sri Lanka
Ikeda, 2001
Australia
Ikeda, 2001
Indonesia
Ikeda, 2001
New Caledonia
Ikeda, 2001
New Guinea
Ikeda, 2001
China
Ikeda, 2001
Japan
Ikeda, 2001
Materials and methods
Biology and species complex
Bell pepper, hot pepper and eggplant flowers and flower buds showing typical symptoms
of gall formation were collected at regular intervals from field in and around Bangalore.
They were individually placed in glass vials containing water soaked cotton swab to
prevent desiccation of samples, the open end of the vial was covered using muslin cloth
held in place by a rubber band. Samples were frequently observed for insect emergence.
The number of gall midges and hymenopterans emerging from each flower were recorded.
The emerged insects were collected and preserved in 70% ethyl alcohol and labeled for
identification. Some galls were carefully dissected and observations on the presence of
fungus, gall midge and hymenopterans, and their numbers were made. These dissected
galls were again closed in order to facilitate the emergence of adults in order to associate
the immature stages with the adults. This kind of studies was made in the galls with only
one or two species of immature stages and at the later stages of their development. The
representative immature stages of different species of insects were also preserved in
70% ethyl alcohol.
Molecular systamatics of gall midge
(a) Genomic DNA isolation: Gall midges affected flowers and developing fruits were
collected on eggplant and capsicum. The samples were dissected in the laboratory and
the pupae were stored in a glass tube for adult emergence. Modified CTAB extractions
protocols were carried out as described. A single insect was transferred into sterile 1.5
ml eppendorf tube, to which 100µl of lysis buffer was added (100mM Tris, 1.5M NaCl,
10mM EDTA, 2% CTAB, 2% β-marcaptoethanol and 1% PVP) and incubated at 650C on
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water bath for 15 minutes. Samples were ground using micro pestle and incubated for
another 30 minutes and allowed to stand at room temperature. To this 100µl chloroform:
isoamyl alcohol mixture (24:1) was added, vortexed briefly and allowed to stand for 2-3
minutes. Tubes were centrifuged for 2 minutes at 10,000 rpm, supernatant was collected
and precipitated in presence of 1/10th volume of 3M sodium acetate pH 5.2 and 2.5
volume 70% ethanol. Then samples were centrifuged for 10 minutes at 10,000 rpm. The
pellet was air dried and resuspended in 20µl nuclease free water. Five micro liters was
used as template for PCR.
(b) Polymerase chain reaction (PCR): Primers specific to mitochondrial cytochrome
oxidase I (mtCOI), viz. LCO1490 (5’-GGTCAACAAATCATAAAGATATTGG-3’) and HCO2198
(5’-TAAAC­TTCAGGGTGACCAAAAAATCA-3’) resulted in the amplification of an approxi­
mately 709bp (Hebert et al., 2003). PCR reaction was performed in a 25 µl volume
containing 20 Pico moles of each primer, 10mM Tris-HCl (pH 8.3), 50mM KCl, 2.5mM
MgCl2, 0.25mM of each dNTPs and 0.5U of Taq polymerase (Fermentas GmBH, Germany).
and PCR cycling conditions consisted of initial denaturation for 5 minutes at 94°C,
followed by 35 cycles of 1 minute denaturation at 94°C, 1 minute annealing at 48°C and
1 minute extension at 72°C, followed by a final extension of 10 minutes at 72°C. The
amplified products were resolved on 1.5% agarose gel, stained with ethidium bromide
(10 mg/ml) and visualized and photographed with gel documentation system (UVP, UK).
The PCR amplified fragments were gel eluted using Nucleospin® Extract Kit, (MacheryNagel) according to the manufacturer’s protocol. The eluted fragment was ligated into
the cloning vector, InsT/Aclone (Fermentas GmBH, Germany) according to the
manufacturer’s protocol. Five micro liters of the ligated sample was transformed into
200 µl of competent Escherichia coli (DH5α) cells by heat treatment at 42oC for 45
seconds and the whole content was transferred into a tube containing 800 µl of SOC
media (tryptone-2% w/v, yeast extract - 0.5% w/v, NaCl-8.6mM, KCl-2.5mM, MgSO4 2.0mM, Glucose-20mM in 1000 ml water, pH 7.0) and incubated at 150 rpm, 37oC for 1
hour. 200 µl of the culture was spread on Luria Bertani agar (LBA) (Tryptone-10 g, Yeast
extract-5g, NaCl-5g, Agar- 15g in 1000 ml water, pH 7.0) containing ampicillin (100mg/
ml), IPTG (4mg/ml) and X-gal (40mg/ml). The plates were incubated at 37oC for 16
hours. Blue/white selection was carried out, white colonies were with insert. Plasmids
were isolated from the overnight cultures grown in LB broth (Enzymatic casein-10g,
Yeast extract-5g, NaCl-5g in 1000 water, pH 7.0) using modified alkali lysis method
(Birnboim & Dolly, 1979). Plasmids were resolved on 1.0% agarose gel and documented.
Plasmid which had insert was of 2.5 kb as compared to control plasmid (1.8 kb) was
selected for sequencing. Plasmids were isolated using plasmid kit minutes (Qiagen,
Germany) according to manufacturer’s protocol, from five randomly selected clones.
Sequencing was performed using an automated sequencer (ABI Prism 310; Applied
Biosystems, USA) with M13 universal primers from both forward and reverse directions.
Homology search was carried out using BLAST (http://www.ncbi.nlm.nih.gov), and the
differences in mtCOI sequences of both eggplant gall midge and capsicum gall midge
were determined using the sequence alignment editor ‘Bioedit’. The sequence has been
deposited with the NCBI database.
Evaluation of newer molecules in management of gall midge in eggplant and Chilli
A field trial was carried out to evaluate the efficacy of eleven chemicals viz., Endosulfan,
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Imidacloprid, Neem soap, Rynaxipyr, Novaluron , Methomyl, Profenophos, Deltamethrin,
Spinosad, Pencycuron and Chlorthalonil to control chilli/eggplant gall midge.
Bacterial wilt resistant Eggplant hybrid Arka Anand and Chilli var.Bydagi Dabbi were
planted in the field with a spacing of 80 x 50 cm in a RBD during July-November 2009.
Experiment consisted of 11 insecticides/fungicides as stated and a control. All treatments
were replicated thrice. Insecticide sprays were given at 15 days interval starting from
the date of inflorescence set. Fifteen flowers randomly picked at weekly interval from
each replication in each treatment were dissected for gall midge presence. Six such
pickings of flowers were made. Harvested fruits were also screened for midge damage.
Percent gall midge infestation in flowers and fruits on each harvest for each treatment
was recorded. The data were subjected to ANOVA.
Screening Eggplant genotypes for resistance
A total number of 147 genotypes were screened for gall midge resistance during December
2009- March 2010. Twenty five flowers were randomly picked from each genotype at weekly
interval from the day of inflorescence set. Flowers were dissected in the laboratory for
presence of gall midge and percent infestation was calculated. Nine such pickings of
flowers were made. Five harvests of fruits and were sorted for presence of viz., fruit borer,
gall midge damage. Percent gall midge infestation in flowers and fruits on each harvest for
each accession was recorded. The data were subjected to CORELATION analysis.
Results and Discussion
Biology and species complex
The gall midge passed through egg, three larval instars and a pupal stage. The egg was
elongate, cylindrical and whitish hyaline. The egg and all the three instars of larvae
were associated with a fungus. The larvae were creamy white to yellowish white in
color. Pupa is light to dark brown and 3.25 mm in length. Pupation was within the ovary
or among the anthers. The total developmental period from egg to adult emergence was
11 days. Adult survived for a maximum of 2 days under laboratory conditions. Ceratoneura
indi Girault (Hymenoptera: Eulophidae) was another gall forming insect commonly
observed in flowers of Capsicum sp. and Solanum sp. The larvae of C. indi were enclosed
in mustard shaped black bodies within the infested ovary or among anthers. Nagaraju et
al., 2004 recorded 2-14 C. indi emerging from a single infested flower. In addition to this
Goethella asulcata Girault (Hymenoptera: Eulophidae), one more gall forming species
was observed in groups in the infested flowers. As many as 28 adults emerged from a
single infested flower.
There is some confusion on pest status of Eurtyoma sp. which is one more gall forming
hymenopteran. Species of Eurytoma can exploit food resource from flowers of chilli/
eggplant or a parasitoid or even hyperparasitoid of other gall forming species. Thus it is
not surprising that while E. dentata is a pest on capsicum (Ukey et al., 1989), another
species of Eurytoma is reported as parasitoid on gall midge on chilli (Tomar et al., 1997).
In such situations, identification of insect species such as Eurytoma is all the more
important lest we identify it as a parasitoid or a pest or vice-versa that could paralyze
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pest management strategy. Eurytoma chaitra is solitary. Occasionally, both gall midge
and larva of E. chaitra were found in a single infested flower. In such cases, both
developed independently (Nagaraju et al., 2004).
It was also observed that at the early stage of the crop more than 90% of the flowers
were infested only by gall midge and only a few by C. indi. As the crop stage progressed,
gall formation by hymenopterans increased.
Parasitoids
Tomar et al. (1997) have reported three hymenopteran parasitoids viz., Eurytoma sp.
Dinaramus sp. and Bracon sp. on larvae/pupae of chilli gall midge. The overall
parasitism by three parasitoids varied from 23-97%. The Eurytoma sp. was associated
throughout the period of pest activity. While the Dinaramus sp. remained associated
only up to last week of March and Bracon sp. during November and December. Thus
Eurytoma sp. was found to be fittest and the potent natural enemy of this pest in
Madhya Pradesh region.
Earlier, gall midge infesting sweet pepper was named A. capsici Barnes and egg plant A.
solani Tavares. The species infesting both was later identified as A. capparis Rubsaamen.
But using molecular methods we were able to distinguish that in fact they are two
different species (Figure 1 and 2). Gall midge found in capsicum and eggplants were
identified as different species using LCO/HCO primers (Hebert et al, 2003). There was
24.82 % variation (176 base pair) out of 709 base pairs (Figure 2). Further studies are
needed to determine whether gall midge infesting chilli is a biotype of the midge species
infesting sweet peppers.
Evaluation of chemicals in management of gall midge on eggplant and chilli
Results indicated that none of the insecticides/fungicide/botanical screened was
effective in limiting gall midge damage on both eggplant and chilli peppers (Table 3-6).
The results were consistent during sampling carried over a period of two months (Table
3). The findings are further supported by the data on eggplant marketable and infested
yield which again did not differ across treatments indicating the inability of the evaluated
molecules to limit the damage by this pest (Table 6). Similarly, Nagaraju et al. (2002)
reported that insecticides have hardly capable of bringing down gall insect infestation in
bell pepper.
Damage by the gall midge is not in the reality infestation damage but a manifestation
of plant response to midge infestation. Thus, even a small oviposition puncture can
trigger a plant response in flowers and developing fruits. Thus, it is not surprising that
insecticides hardly could limit the damage. In literature host plant resistance has played
a major role in limiting gall midge damage in crops such as rice and sorghum. This again
indicates need for identifying source of resistance in eggplant and peppers including
wild relatives.
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Table 2. Parasitoids reported on gall midge, A. capparis infesting Capsicum annuum
and Solanum melongena.
Capsicum spp.
Species and
Family
Preferred
stage
Distribution
Remarks
Reference
Pteromalidae Dinaramus sp.
Larva
Madhya
pradesh
Exhibited super parasitism as
many as 13 parasites emerged
from a single infested flower
Tomar et al., 1996
Larva
5-62%
Tomar et al., 1997
Mesopolobus sp.
Madhya
pradesh
Tamil Nadu
Rangarajan and
Mahadeven, 1975
Tamil Nadu
Braconidae
Bracon sp.
Eulophidae
Madhya
pradesh
3-12%, active for short time
Rangarajan and
Mahadeven, 1975
Tomar et al., 1997
Rangarajan and
Mahadeven, 1975
Syntomosphyrum sp.
Tamil Nadu
more common, 5-6 pupae/
flower
Eurytomidae
Eurytoma sp.
Larva
Madhya
pradesh
18-67%, appeared along with
Tomar et al., 1997
pest and remained throughout.
Tamil Nadu
Jesudasan and
David, 1988
Solanum melongena
Eurytomidae
Eurytoma sp.
Larva
Karnataka
8-15%, first report
Tewari and
Moorthy, 1986
Molecular systamatics of gall midge
Out of 147 genotypes evaluated, based on 9 observations on flowers and five harvests,
five genotypes Solanum macrocarpon, Bhagyamati, African scarlet Eggplant, IC-249387
and IC-90901 showed no gall midge or gall wasp infestation. Correlation between flower
damage versus fruit damage was significant (r = 0.33). Thus initial screening can be
focused on flower, to determine the resistance to gall midge. A lack of significant corelation would have indicated that the affected flowers don’t set fruits. However
significant co-relation indicates retention of affected flowers that will lead deformed
fruits. Flower shedding is the one of the important problems raised by many pepper
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growing farmers in South Asia and it would be interesting to note what proportion of
flowers that are shed is due to gall midge damage.
One notable feature of the resistant genotypes is the small sized flower especially ovary.
In comparison to those that are susceptible. The weight of 10 flowers (African scarlet
eggplant) was 1.45 g in resistant genotypes compared to significantly higher flower
weight in others. In case of accessions (IC-249387 and IC-90901), spines are observed on
leaves and flower calyx. Ovary is small in size with maximum inferior ovary. The weight
of 10 flowers is 3.92 g and 5.82 g respectively. Average fruit weight in case of IC-249387
is 49.9 g and 26.8 g in case of IC-90901. In case of accession Bhagyamati, spines are not
seen, flowers are with small ovary. The weight of 10 flowers is 2.16 g. Average fruit
weight is 26.3 g.
Table 3. Gall midge recovered from Chilli flowers at different intervals from
different chemical treatments (July-November 2009).
Treatments (Ml/l)
T1: Endosulfan @ 2.5 ml/L
T2: Imidacloprid @ 0.5 ml/L
T3: Neem soap @ 10 g/L
T4: Rynaxipyr @ 0.3 ml/L
T5: Novaluron @ 2 ml/L
T6: Methomyl @ 1.5 g/L
T7: Profenophos @ 2 ml/L
T8: Deltamethrin @ 0.5 ml/L
T9: Spinosad @ 0.3 ml/L
T10: Pencycuron @ 2 ml/L
T11: Control
T12: Chlorthalonil @ 2 g/L
F-test (p = 0.05)
CV (%)
Mean gall midge infestation /15 flowers
02 Nov
09 Nov
17 Nov
30 Nov
07 Oct
15 Oct
1.33
(1.29)
1.67
(1.46)
2.33
(1.57)
2.33
(1.49)
1.33
(1.29)
1.33
(1.27)
1.67
(1.44)
1.00
(1.10)
2.00
(1.47)
2.00
(1.56)
1.00
(1.10)
3.00
(1.87)
4.00
(1.89)
2.00
(1.56)
5.33
(2.03)
1.67
(1.35)
1.67
(1.39)
1.67
(1.35)
1.67
(1.39)
2.33
(1.49)
2.67
(1.56)
2.67
(1.77)
1.67
(1.39)
1.00
(1.17)
0.33
(0.88)
0.67
(1.05)
0.00
(0.71)
0.33
(0.88)
0.67
(1.05)
0.67
(1.05)
0.67
(1.05)
0.67
(1.00)
0.67
(1.05)
0.00
(0.71)
1.67
(1.44)
0.67
(1.00)
0.33
(0.88)
0.67
(1.05)
0.67
(1.00)
0.00
(0.71)
1.00
(1.17)
0.33
(0.88)
0.33
(0.88)
0.67
(1.00)
0.67
(1.05)
0.33
(0.88)
1.33
(1.34)
0.00
(0.71)
0.33
(0.88)
0.33
(0.88)
0.33
(0.88)
1.00
(1.17)
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
1.00
(1.17)
0.33
(0.88)
0.00
(0.71)
1.00
(1.22)
0.67
(1.00)
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
0.67
(1.00)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
NS
NS
NS
NS
NS
NS
42.5
48.6
34.3
32.4
32.9
23.15
* Figures in parenthesis indicate Square root + 0.5 transformed values
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Table 4. Gall midge incidence in chilli pods (%).
Treatments
Yield (Kg/ 12 m2)
Mean Gall midge
infestation (%)
9.33 (17.45)
T1 : Endosulfan @ 2.5 ml/L
6.05 (2.42)
T2 : Imidacloprid @ 0.5 ml/L
4.23 (2.04)
9.34 (17.38)
T3 : Neem soap @ 10 g/L
2.80 (1.58)
11.96 (19.11)
T4 : Rynaxipyr @ 0.3 ml/L
3.32 (1.80)
5.71 (12.49)
T5 : Novaluron @ 2 ml/L
4.35 (2.07)
7.45 (15.72)
T6 : Methomyl @ 1.5 g/L
4.83 (2.18)
9.54 (17.81)
T7 : Profenophos @ 2 ml/L
4.48 (2.10)
10.34 (18.28)
T8 : Deltamethrin @ 0.5 ml/L
4.66 (2.15)
7.97 (16.30)
T9 : Spinosad @ 0.3 ml/L
4.61 (2.13)
10.06 (17.79)
T10 : Pencycuron @ 2 ml/L
4.03 (2.00)
11.83 (19.85)
T11 : Control
4.12 (2.02)
7.77 (15.56)
T12 : Chlorthalonil @ 2 g/L
2.39 (1.52)
16.29 (23.74)
F-test (p = 0.05)
CV (%)
NS
NS
16.13
26.21
Total yield – Square root transformation, GM% in yield – Angular transformation.
Gall midges larvae which are apodous require a minimum developmental space inside
the ovary sufficient for normal development and pupation leading to successful normal
adult emergence. Ovary which are medium to large provide adequate breathing space
to develop while, the resistant genotypes having small flower/ovary appear inadequate
for larval development and pupation.
The preference even among the gall midges to sweet peppers over chilli pepper in the
last 25 to 30 years was hypothesized to large ovary in sweet pepper compared to chilli.
Recent infestation on chilli peppers, we presume is due to development of a biotype
which is small in size. Our observations on gall midge which emerged from chilli seem to
substantiate this. Further studies on this aspect are needed.
Resistance to gall midge may be a combination of many factors in addition to flower
size. Biochemical mechanisms governing resistance need to be investigated. Solanum
macrocarpon is reported resistant to borer and is now being reported resistant to gall
midge. Solanum macrocarpon is edible. However molecular intervention is required to
have viable inter-specific crosses that can contribute to borer and gall midge resistance
with desirable Horticultural attributes.
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Table 5. Gall midge recovered from eggplant flowers at different intervals
in different chemical treatments (July-November 2009).
Mean gall midge infestation/15 flowers
Treatments
3/10
8/10
15/10
22/10
5/11
12/11
T1 : Endosulfan @ 2.5 ml/L
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
0.67
(1.00)
0.00
(0.71)
0.00
(0.71)
0.67
(1.05)
0.33
(0.88)
1.00
(1.10)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
1.00
(1.17)
1.00
(1.17)
1.00
(1.17)
0.33
(0.88)
0.33
(0.88)
0.00
(0.71)
0.33
(0.88)
0.33
(0.88)
0.33
(0.88)
0.33
(0.88)
0.67
(1.05)
0.33
(0.88)
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
0.67
(1.05)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
1.00
(1.17)
0.33
(0.88)
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.33
(0.88)
0.00
(0.71)
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
1.00
(1.17)
1.00
(1.17)
0.00
(0.71)
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.00
(0.71)
0.33
(0.88)
0.00
(0.71)
0.00
(0.71)
0.33
(0.88)
0.67
(1.05)
0.00
(0.71)
0.00
(0.71)
T2 : Imidacloprid @ 0.5 ml/L
T3 : Neem soap @ 10 g/L
T4 : Rynaxipyr @ 0.3 ml/L
T5 : Novaluron @ 2 ml/L
T6 : Methomyl @ 1.5 g/L
T7 : Profenophos @ 2 ml/L
T8 : Deltamethrin @ 0.5 ml/L
T9 : Spinosad @ 0.3 ml/L
T10 : Pencycuron @ 2 ml/L
T11 : Control
T12 : Chlorthalonil @ 2 g/L
F-test (p = 0.05)
CV (%)
NS
NS
NS
NS
NS
NS
46.9
41.6
26.7
33.4
37.6
28.2
* Figures in parenthesis indicate Square root + 0.5 transformed values
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Table 6. Gall midge incidence (%) in eggplant fruits.
Treatments
Gall midge incidence (%)
T1 : Endosulfan @ 2.5 ml/L
4.10
T2 : Imidacloprid @ 0.5 ml/L
4.40
T3 : Neem soap @ 10 g/L
4.32
T4 : Rynaxipyr @ 0.3 ml/L
2.13
T5 : Novaluron @ 2 ml/L
4.04
T6 : Metholy @ 1.5 g/L
2.88
T7 : Profenophos @ 2 ml/L
4.64
T8 : Deltamethrin @ 0.5 ml/L
3.53
T9 : Spinosad @ 0.3 ml/L
3.52
T10 : Pencycuron @ 2 ml/L
3.94
T11 : Control
1.94
T12 : Chlorthalonil @ 2 g/L
3.08
NS
F-test (p = 0.05)
36.4
CV (%)
Table 7. Gall midge damage (%) in different eggplant genotypes
(December 2009-March 2010).
Sl.
No.
164
Accessions
Fruit
Infestation*
(%)
Flower
Infestation*
(%)
Sl.
No.
Accessions
Fruit
Infestation*
(%)
Flower
Infestation*
(%)
1
IC-261803
12
12.4
18
IC-089823
6.2
11.5
2
IC-344557
26.3
15.6
19
IC-89947-A
33.3
12.9
3
IC-215020
7.4
23.3
20
IC-112741
8.6
11.6
4
IC-136268
17.9
19.9
21
IC-34971
20
18
5
IC-089964
18.3
17.6
22
IC-20061 A
41.2
14.7
6
IC-111003
10.6
15.5
23
IC-261772
7.8
8.8
7
IC-111060
9
19.6
24
IC-2099
IC-249368
0
10
18.2
15.4
8
IC-38608
18.1
16.3
25
9
IC-136461
22.8
15.6
26
IC-347961
0
14.2
10
IC-20061-A
14.9
17.9
27
IC-90812
22.2
15.2
11
IC-249323
36.5
16.4
28
IC-910116
17.7
12.8
12
IC-249365
17.9
17.9
29
IC-144144
17.5
10.8
13
IC-249329
12.2
8.9
30
IC-261818
42.6
12.2
14
IC-336423
9.3
8.6
31
IC-354573
29.9
12.6
15
IC-261786
15.5
12.9
32
IC-74209
18.1
15.9
16
IC-90092
14.7
14.2
33
IC-111027
24.6
14.2
17
IC-117347
16
15.5
34
IC-9078
14.1
13.1
Advances in Genetics and Breeding of Capsicum and Eggplant
Sl.
No.
Accessions
Fruit
Infestation*
(%)
Flower
Infestation*
(%)
35
IC-90906
12.9
15.4
36
IC-261782
8.2
19.1
37
IC-261785
0
38
IC-382582
0
39
IC-136375
40
IC-144021
41
Sl.
No.
Accessions
Fruit
Infestation*
(%)
17.6
Flower
Infestation*
(%)
19.3
72
Arka sheel (OP)
10
73
KS 331 (OP)
9.8
13
10
74
S. mani (OP)
29.7
18.3
12.5
16
75
A. Anand
14.6
10.9
0
10
76
PH 5 (OP)
19
13.5
IC-84900
10.7
11.5
77
JBH -1(OP)
7.9
16.9
42
IC-127063
4.3
7
78
DBSR-91(OP)
18.2
18.2
43
IC-99674
15.8
11.2
79
13.6
19.1
44
IC-249344
37.5
10
Pusa kranthi
(OP)
45
IC-90937
33.3
10
80
IIHR -322
9.4
5.4
46
IC-099686
4.3
10
81
PH-2 (OP)
17.9
13.8
82
P. barsathi (OP)
11.1
12.7
47
IC-336393
25
12.5
48
IC-111017
23.4
11.8
49
IC-92719-A
0
10
83
PPC
8.8
15.1
50
IC-090846
20
10
84
S. Prathibha
16.1
13.4
51
IC-349371
0
10
85
IIHR-3
6.7
10
52
IC-99614
50
19.4
86
Arka keshav
12.8
9
53
IC-090767
0
10
87
Arka nidhi
15
12.5
54
IC-216264
30
14.1
88
BB 54
7.4
11.8
55
IC-383102
21.4
12.7
89
Bolanath
28.9
10.7
56
IC-249387
0
0
90
A. neelakanth
11.1
13.7
57
IC-111323
13.6
18.6
91
P. upkar
22.2
13.1
58
IC-90901
0
0
92
Singhnath
29.4
14.6
59
IC-90851
21.2
15.8
93
IIHR-586
8.9
13.8
60
IC-90942
9
15.8
94
Pusa ankur
20.6
18.3
61
IC-24923
33.9
18.1
95
VNR-218
7.9
15.3
62
IC-201231-A
14
19.7
96
2 BMG-1
28.6
15.3
63
IC-90822
35.7
16.5
97
5.6
8
64
Polur local
33.3
13.9
Pusa hybrid 6
(PH-6)
65
PLR-1 (OP)
9.3
13.6
98
Pant rituraj
7.1
17
66
A. Kusumakar
0
4
99
Punjab sadabhar
6.7
13.3
67
KS-224 (OP)
25
13.3
68
S. Shree (OP)
20
14.1
100
DBSR-2
14.9
13.3
69
Azad kranthi
(OP)
17.6
13.1
101
Swarna shyamili
34
17.5
70
ABSR-2 (OP)
12.3
12
102
Bhagyamati
0.8
0
71
JB 15 (OP)
17.1
17
103
IIHR-105
15
11.4
165
Advances in Genetics and Breeding of Capsicum and Eggplant
Fruit
Infestation*
(%)
Flower
Infestation*
(%)
Sl.
No.
Accessions
MS-1
0
11.8
126
IC-354562
105
IC-280952
0
11.8
127
106
PPL
0
10
128
107
Gulabi
11.8
14.1
108
Pusa hybrid - 9
4.3
Sl.
No.
Accessions
104
Fruit
Infestation*
(%)
Flower
Infestation*
(%)
40.5
11.5
IC-90084
0
12.6
IC-90068
41.2
10
129
IC-89986
18.2
10
13
130
IC-89912
9.1
11.5
109
Pusa hybrid - 5
1.7
1.8
131
IC-89905
17.1
19.3
110
Pusa bindu
22.2
10
132
IC-90146
23.8
12.7
111
Pant samrat
9.1
12.4
133
IC-90777
0
13.2
112
Arka shirsh
10
12
134
IC-112341
40
14.4
113
IC-90898
16.7
14.2
135
IC-112322
0
12.1
114
IC-545948
0
16.9
136
IC-111443
16.7
10
115
IIHR -555
10.3
10
137
IC-111439
0
10
116
IIHR-5
7.1
12.4
138
IC-111387
0
10
117
IIHR-3
3.6
11.7
139
IC-90987
0
10
118
IC-545884
22.2
15.5
140
IC-99676
0
10
119
IC-438608
5.3
12
141
IC-99691
0
10
120
IIHR-7
0
13
142
IC-104083
0
10
121
IC-354564
29.5
11.1
143
IC-111010
23.5
13.7
122
African scarlet
eggplant
0.4
0
144
EC-329327
60
11
145
EC-379244
15.6
10.8
123
IC-285125
24.1
10
146
0
IC-285126
28.6
10
Solanum
macrocarpon
0
124
125
IC-310884
20.7
11.8
147
EC-316275
13.6
13.2
* Based on five harvests
** Based on nine pickings
1.Lambda Eco RI and Hind III
digested ladder
2.Non template PCR negative
3.LCO/HCO amplified Gall midge
Eggplant
4.LCO/HCO amplified Gall midge
Capsicum
5.LCO/HCO amplified
Ceratoneura Chilli
Figure 1. PCR amplification Gall midge (eggplant and Capsicum) and Ceratoneura.
166
Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 2. Sequence comparison of Mitochondrial Cytochrome Oxidase, LCO/HCO
(Hebert et. al, 2003).
167
Advances in Genetics and Breeding of Capsicum and Eggplant
Acknowledgements
The authors are grateful to Dr. Marcela Skuhrava, Praha, Czech Republic and Dr. T. C.
Narendran, University of Calicut, Calicut for identification of gall midge and Hymenoptera,
respectively.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Economics of management of eggplant shoot and fruit borer (ESFB),
Leucinodes orbonalis Guenee raised under low cost net house
N.K. Krishna Kumar, D. Sreenivasa Murthy, H.R. Ranganath,
P.N. Krishnamoorthy, S. Saroja
Indian Institute of Horticultural Research, Hessaraghatta Lake Post, Bangalore 560 089, India.
Contact: [email protected]
Abstract
Damage by the due to shoot & fruit borer (Leucinodes orbonalis Guenee) in eggplant
(Solanum melongena L.) often exceeds > 30 - 50 per cent. Indiscriminate application of
cocktail insecticides is a major concern in fruit borer management. Eggplant shoot and fruit
borer (ESFB) has developed a high level of resistance to a number of insecticides including
some of the new molecules. In this scenario, experiments were conducted using low-cost
net house for two seasons at the Indian Institute of Horticultural Research, Hessaraghatta,
Bangalore, India. A number of plants with identical spacing and fertigation were transplanted
outside the net house for comparison. Fruits were harvested at regular intervals and the
number of fruits bored was recorded at each harvest. Besides, the number of fruits damaged
by the gall midge, Asphondylia capparis was also recorded.
The results indicated that it was possible to reduce to < 2 per cent ESFB damage in eggplant
using low cost net house without a single spray of target insecticide. Further, there was no
infestation of gall midge, very low leaf hopper (Amrasca biguttula biguttula Ishida) damage
and no incidence of little leaf inside the net house. On the contrary, nearly 60 per cent of
eggplant fruits were damaged in open cultivation. A sevenfold increase in marketable yield
was observed under protected cultivation. The added costs in the form of nets and other
structures (annualized based on its total use) were more than compensated by very low fruit
borer damage, reduced cost of plant protection, returns obtained from increased and extended
pickings. The indirect benefits accrued from reduced pesticide residue are discussed.
Keywords: Eggplant, protected cultivation, shoot and fruit borer.
Introduction
Eggplant (Solanum melongena L.) is extensively damaged by the shoot & fruit borer,
Leucinodes orbonalis Guenee, (Pyralidae: Lepidoptera) in the Indian subcontinent.
Damage, often exceeds > 30 - 50 per cent (Ahmad, 1977), though the extent of damage
vary from one location and season to the other (Alam et al., 2003). Farmers resort to
indiscriminate use of insecticides. Synthetic pyrethroids are extensively used in
managing ESFB. The number of chemical sprays imposed on the crop often exceeds
30-40 at an interval of 3-4 days. In spite of this, management of ESFB is unsuccessful
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Advances in Genetics and Breeding of Capsicum and Eggplant
and the pest has developed a high level of resistance to a number of insecticides
including many new molecules. The level of natural parasitism is extremely low and
that of parasitism is often < 2% (Srinivasan, 1994). No significant resistance in cultivated
S. melongena is reported (Dhankar, 1988 ) Use of synthetic sex pheromone (Zhu et al.,
1987; Attygalle et al. 1988; Cork et al., 2001) at best can be used to monitor ESFB
infestation, but as an IPM tool, has not been very successful. There is a strong national
debate under the circumstances whether to introduce Bt-eggplant into the market.
The use of Bt eggplant is beset with ecological concerns and policy decisions general
to a number of GM crops. Furthermore, in the Indian subcontinent different types of
eggplant fruits are preferred depending on the region and culinary taste. Some of the
fruits of an average weigh > 300 g and it is paramount that such fruits are borer free.
Furthermore, pesticide residue is a serious concern considering the large quantity of
pesticide used for the management of ESFB. In this scenario low-cost net house
cultivation of eggplant was attempted not only to manage the EFSB but also ensure
better quality and find safety.
Material and methods
Design of the experiment
Experiments were carried out at the Indian Institute of Horticultural Research, Bangalore,
India using low cost net house for two seasons (October 2007 to February 2008 and
October 2008 to March 2009). The large fruited eggplant hybrid lndam 19794 was raised
inside the protected nursery and 326 seedlings were transplanted at a spacing of 75 x 50
cm inside the net house. Same number of plants with similar spacing was transplanted
outside the net house for comparison. Flowers were hand pollinated during the morning
hours both inside (sometimes essential as no fruit set is observed inside the net house
without hand pollination) and outside the net house to ensure pollination and fruit set.
Data characterization
Fruits were harvested at regular interval and the number of fruits bored was recorded
at each harvest. Besides, the number of fruits affected by the gall midge, Asphondylia
capparis was also recorded. The data on extent of damage, total and marketable yield,
infestation of other pests, problems of pollination and economics of net house cultivation
were collected. Cost accounting method of data collection was used for recording the
actual cost details of egg plant cultivation during 2007-08 and 2008-09.
Data analysis
Mean and percentage values obtained were used for comparing infestation and yield
attributes between net house and open cultivation. For economic analysis, cost of
production (break even costs), net return and benefit: cost ratios (BCR) were used.
Computation of cost of production bit tricky as it involves two types of costs viz.,
establishment costs which is a one-time investment and annual costs which are incurred
for every crop. Straight-line depreciation was used to apportion the total value of the
establishment items like stone pillars, net sheets and irrigation equipments, etc.,
depending on their life span. The price of Rs. 10/kg of fruit (= 0.22 US $) was used for
estimating the gross return.
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Results and Discussion
Fruit yield
Raising eggplant in a low cost net house resulted in a higher mean fruit yield of 25.9 t/
ha as compared to open cultivation which recorded 17.0 t/ha (Table 1). The mean yield
of egg plant was higher nearly by 52 per cent mostly due to the better vegetative growth
inside net house. This was possible as net house cultivation provided a better congenial
environment like less variations in temperature and RH for the growth of the eggplant
than open cultivation.
Marketable yield, which is estimated after discarding the ESFB damaged fruits, was also
higher in low-cost net house cultivation as the fruit borer damage was negligible in net
house (1.7 %) as compared to the open house cultivation (46.0 %). The mean marketable
yield for two years under net house was 25.59 t/ha, which is higher nearly by 156 per
cent as compared to the marketable yields obtained in open cultivation (9.99 t/ha).
Table 1. Effect of net house cultivation on eggplant fruit yield (Kg).
Si/No Particulars
1
2
2007
2008
Mean
Total fruit yield
Net house
24,861
26,966
25,914
Open
7,261
26,813
17,037
Net house
24,861
26,321
25,591
Open
3,369
16,603
9,986
Marketable yield
Size and number of fruits
The details on the effect of raising eggplant in net house on size and quality of fruits are
presented in Table 2. Net house cultivation of eggplant resulted in large sized, healthy
fruits (marketable) compared to open cultivation both in 2007-08 and 2008-09. The main
reason for the 38 per cent increase in fruit size appears to be the congenial growth
environment that prevailed in the net house. The mean size of the healthy fruits grown
in the net house cultivation was 272 g as compared to 194 g in open cultivation. As
regards to damaged fruits due to the pest infestation, there was virtually no difference
in the size of the fruits.
The effect of net house cultivation on fruit bearing habits, the total number of fruits set
under net house was marginally higher (97472 fruits/ha compared to 91363/ha under
open cultivation). This suggests that growing eggplant under net house has marginal
influence on the fruit bearing habit. On the contrary the number of marketable plants
under net house was nearly double than that of open house cultivation obviously due to
better ESFB management resulting in less damage which will be discussed in the following
section. The per cent ESFB infestation was <1 per cent as compared to ~55 per cent
under open cultivation.
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Table 2. Effect of net house cultivation on eggplant fruit size. (g/fruit).
Si/No
Particulars
2007
2008
Mean
Net house
272
262
267
Open
216
172
194
Size of fruits
1
Healthy (marketable) fruits
Bored fruits
Net house
0
203
203
208
198
203
Net house
91307
100455
95881
Open
15625
96761
56193
Open
2
Number of fruits
Healthy fruits
Bored fruits
Net house
Open
0
3182
1591
18750
51591
35170
EFSB damage
In south Asia, undoubtedly L. orbonalis, is the most serious pest limiting successful
cultivation of eggplant. In parts of north India the whole fruit is roasted for culinary
purposes and in such a situation it is paramount that the fruit is free of borer. Raising
eggplant inside the net house, a barrier to infestation and spread of ESFB was a major
success as the damage was < 2 per cent compared to a mean damage of 46 per cent
outside net house. The results were similar for both the years though there was a
difference in the magnitude of damage. Similar results were also observed on damage to
fruits on number basis.
Table 3. Effect of net house cultivation on per cent L. orbonalis damage.
Si/No
1
2
Particulars
2007
2008
Mean
Net house
0.00
2.39
1.70
Open
54.00
38.08
46.04
On weight basis
On Number basis
Net house
0.00
3.07
1.54
Open
55.00
34.54
44.77
Breakeven analysis and Income
It is clear from the discussion so far that the low-cost net house not only prevents
infestation and damage by ESFB, but also increases the marketable yield substantially.
We examined economic feasibility of raising eggplant under low-cost net house as it
requires substantial capital. This is critical as in south Asia land holdings are small (<1
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ha), fragmented and most farmers lack resources to erect sophisticated polyhouses. It
is clear from the data generated from the present study that for raising the net house
structures using granite pillars, polythene net, twine thread and wires, etc. Rs 11.90
lakhs/ha as an initial capital investment is required and an additional amount of Rs 1.77
lakhs is also essential for provisioning drip irrigation. The mean annual expenses for
cultivation of eggplant for two years worked out to Rs 56,678/ha for net house cultivation
and Rs 44,178/ha for open cultivation. Under these costs scenarios, the annualized cost
of production, net return and the BCR were estimated and analyzed.
The cost of production of large fruited (500-750 g), eggplant when raised in open
cultivation was Rs 4.78/kg. In comparison it was Rs. 3.69/kg, under low cost net house
i.e. the annualized cost of production which has taken into account the apportioned cost
of the fixed (establishment) inputs and annual costs is lower in the net house production.
In other words, egg plant could be successfully raised at a lower cost than the conventional
open production. The gross return is higher by 156 per cent mainly through realizing
higher yield. Though the annualized costs of net house cultivation of eggplant is nearly
double due to the costs on fixed inputs (Rs 94,376/ha in net house cultivation compared
to Rs 47,731/ha in open cultivation), the net income was observed to be higher by three
times (Rs 161,534/ha in net house cultivation compared to Rs 52,129/ha in open
cultivation). The BCR was also higher in net house cultivation at 2.71 compared to 2.01
in open cultivation. Thus, growing eggplant in low-cost net house for controlling the
most devastating pest ESFB was also observed to be economically profitable.
Table 4. Effect of net house cultivation on income and economic feasibility
of eggplant cultivation (per ha).
Si/No
Particulars
1
Cost on net house structures
(stones pillars, wires, etc)
2
Costs on irrigation structures and drip
system
Net house
cultivation (Rs)
11,90,030
Open field
cultivation (Rs)
-
Change
(%) (Rs)
-
1,76,650
1,76,650
28.29
3
Mean annual cultivation expenses
56,678
44,178
4
Annuity values for items 1 and 2
37,698
3,553
-
Annualized cost of cultivation
(item 3 + item 4)
94,376
47,731
97.72
5
Cost of Production
3.69
4.78
-22.85
6
Gross returns
2,55,910
99,860
156.27
7
Net returns
161,534
52,129
209.87
8
BC Ratio
2.71
2.09
-
* Note: 1 US $ = 45 Indian rupees.
Pesticide residue remains one of the main concerns on vegetables especially in the
tropical, developing world. This is all the true in case of eggplant wherein 30-40 spays
are given especially targeting ESFB though often not with much success. While many
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Advances in Genetics and Breeding of Capsicum and Eggplant
new molecules such as indaxocarb and novaluron were effective on many lepidopteron
such as cotton bollworm, Helicoverpa armigera Hubner, they were not effective on
BSFB. It is a euphemism to attribute the main reason for high insecticide resistance
to the monophagous nature of ESFB. A national debate to introduce Bt eggplant is
raging. Irrespective of the fact whether Bt eggplant is allowed for cultivation or not,
raising eggplant using low cost net house for management of ESFB with no pesticide
residue, reduced infestation, and higher returns to the grower remains a clear
alternative.
Conclusions
Low-cost net house cultivation of egg plant was observed to very significantly reduce
ESFB infestation and damage. Further, there was an increase in the total fruit yield,
mostly through bigger size rather than number. Further, there was a reduction in
leafhopper infes­tation and damage and no incidence of little leaf, a phytoplasma disease
inside the net hou­se. This capital intensive net house cultivation was also economically
superior to the open cultivation reducing not only the cost of production but also yielding
a higher net return.
Acknowledgements
The authors are grateful to the Director, IIHR, Bangalore for providing the necessary
facilities to carry out this research work. We thank Late Ramaiah and Chandrappa for
field help.
References
Ahmad, R. 1977. Studies on the pests of brinjal and their control with special reference
to fruit borer, Leucinodes orbonalis Guenn, (Pyralidae: Lepidoptera). Entomologist
Newsletter 7(4): 2-3.
Alam, S.N.; Rashid, M.A.; Rouf, F.M.A.; Jhala, R.C.; Patel, J.R.; Satpathy, S.; Shivalinga­
swamy, T.M.; Rai, S.; Wahundeniya, I.; Cork, A.; Ammaranan, C.; Talekar, N.S. 2003.
Development of an Integrated Pest Management strategy for eggplant fruit and
shoot borer in South Asia, AVRDC Technical Bulletin No. 28, p 1-66.
Attygalle, A.B.; Schwaraz, J.; Gunawaralena, N.E. 1988. Sex pheromone of brinjal fruit
and shoot borer, Leucinodes orbonalis’ Guenee (Lepidoptera: Pyralidae). Zeitschrift
fur Naturforschung 43:790-792.
Cork, A.; Alam, S.N.; Das, A.; Das, C.S.; Ghosh, G.C.; Farman, D.I.; Hall, D.R.; Maslen,
N.R.; Vedam, K.; Phytian, S.J.; Rouf, F.M.A.; Srinivasan, K. 2001. Female sex
pheromone of brinjal fruit and shoot borer, Leucinodes orbonalis (Lepidoptera:
Pyralidae) blend optimization. Journal of Chemical Ecology 27:1867-1877.
Dhankar, B.S. 1988. Progress in resistance studies in the eggplant (Solanum melongena L.)
against shoot and fruit borer (Leucinodes orbonalis Guen.) infestation. Tropical Pest
Management: 34:343-345.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Srinivasan, K. 1994. Recent trends in insect pest management in vegetable crops, pp.345372, in G S. Dhaliwal and Arora (eds). Trends in Agricultural Insect Pest Management.
Commonwealth publishers, New Delhi.
Zhu, P.; Kong, F.; Yu, S.; Yu, N.; Jin, S.; Hu, X.; Xu, J. 1987. Identification of the sex phe­
romone of eggplant borer, Leucinodes orbonalis Guenee (Lepidoptera: Pyralidae).
Zeitschriftfiir Natuiforschung 42:1347-1348.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Evaluation of resistance of pepper varieties from the Basque
Country to Phytophthora cryptogea
S. Larregla, E. Pérez, B. Juaristi, M. Nuñez
Departamento de Producción y Protección Vegetal, NEIKER-Tecnalia, Centro Derio.
C/ Berreaga 1, 48160 Derio (Bizkaia), Spain. Contact: [email protected]
Abstract
Phytophthora capsici and Phytophthora cryptogea are the main soilborne fungi causing crown
and root rot disease in Basque Country pepper crops. In this study, resistance of diverse
pepper accessions were evaluated against isolates of P.cryptogea. Three isolates of P.
cryptogea from pepper plants from the Basque Country showing different pathogenicity levels
were inoculated on 30 Basque varieties of 6 different varietal types: goat-horned (2), Gernika
(18), thick-grilled (4), thick Loyolan (2), corigero (1) and long yellow pepper (3), and on six
varieties with known resistance to P.capsici, five resistant (`SCM-334´, `SCM-331´, `PI201234´, `PI-201232´, `Smith-5´) and one susceptible (`Yolo Wonder´). Pepper seedlings at
the 8-10 leaf stage were inoculated by watering roots with suspensions containing 124.000,
163.000 or 254.000 zoospores per plant. After inoculation, they were maintained in a growth
chamber (14h light, 20+3°C). Two factors (pathogen isolate and pepper variety) combinations
comprised the treatments of the factorial experiment that were arranged in a completely
randomized design with two replicates per treatment and 7 plants per replicate. Data were
analyzed by ANOVA. Mean separation was done with Waller-Duncan’s Bayesian K-ratio LSD rule
(α=0.05). P.cryptogea isolate, pepper variety and their combinations showed highly significant
differences in the final expression of root necrosis, the severity of symptoms of the aerial
part, their progression over time and the percentage of plants affected in two dates of
assessment (29 and 54 days after inoculation). None of the Basque varieties were significantly
more resistant than the susceptible reference `Yolo Wonder’. With the exception of the
grilling type, `Leuna´, Basque varieties were significantly more susceptible than the five
resistant reference varieties to P.capsici. The latter showed less necrosis of the root system
against P.cryptogea in comparison to Basque varieties. `Leuna´, `Luzea´, `7E´, `49E´ (thickgrilled type), `Cor-01´ (corigero type) and `NC-8´ (goat-horned type) were the most resistant
varieties considering the assessment criteria. The three isolates of P.cryptogea differed in
their average pathogenicity against the 36 pepper accessions inoculated.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Development of test methods and screening for resistance to thrips
in Capsicum species
A. Maharijaya, B. Vosman, G. Steenhuis-Broers, R.G.F. Visser, R.E. Voorrips
Wageningen UR Plant Breeding, P.O. Box 16, 6700 AA Wageningen, The Netherlands.
Contact:[email protected]
Abstract
Thrips are one of the most damaging pest organisms in field and greenhouse pepper
(Capsicum) cultivation. They can cause damage on pepper directly by feeding on leaves,
fruits and flowers, and indirectly by transferring viruses, especially Tomato Spotted Wilt
Virus (TSWV). No commercial pepper varieties are available with an effective level of
resistance to thrips. Our research is aimed at the development of tools for breeding
varieties with a broad resistance to thrips. This encompasses setting up of effective test
methods, the identification of sources of resistance and mapping of QTLs for resistance.
Thirty-two pepper accessions of four species of pepper (Capsicum annuum, C. baccatum, C.
chinense and C. frutescens) originating from different geographic and climatic regions were
tested for resistance using several screening methods. The tests were performed in
Indonesia and the Netherlands with Thrips parvispinus and Frankliniella occidentalis,
respectively. Accessions were tested under choice (screenhouse, greenhouse) and nonchoice (leaf disc, detached leaf and cuttings) conditions. Screening methods were compared
and correlations among these methods were assessed. We observed a large variation for
resistance to thrips in pepper. Our results also indicate that the leaf disc test can be used
as an efficient and predictive screening method for thrips resistance in pepper. An F2
population from a cross between a highly resistant and a susceptible accession was produced
and currently we are studying the inheritance of resistance in this population.
Keywords: Thrips parvispinus, Frankliniella occidentalis.
Introduction
Pepper (Capsicum), one of the most widely grown vegetables in the world faces problems
from thrips both in the tropics and temperate regions. At least 16 thrips species have
been reported to occur on Capsicum (Capinera, 2001; Talekar, 1991). Frankliniella
occidentalis is the most common thrips species in greenhouse cultivation in Europe
(Tommasini and Maini, 1995), while Thrips parvispinus is the main species on Capsicum
in Indonesia, Malaysia, the Philippines, Thailand and Taiwan (Reyes, 1994). Thrips do not
only cause direct damage by feeding and laying eggs on pepper leaves and fruit, but also
cause indirect damage by transmitting plant viruses, especially Tomato Spotted Wilt
Virus (TSWV) (Ulman et al., 1992).
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Advances in Genetics and Breeding of Capsicum and Eggplant
The main approach to control thrips in pepper is the use of pesticides. However, thrips
rapidly develop resistance to pesticides. Also, pesticides are costly and have harmful
effects on growers, consumers and the environment. As an alternative, integrated pest
management (IPM) has started to be implemented. To help IPM become a success,
(partially) resistant varieties are needed. Resistance to thrips not only decreases direct
damage but may also be useful for controlling insect-transmitted plant viruses(Maris et
al., 2004; Jones, 2005).
Breeding programs for obtaining pepper varieties resistant to thrips involve the screening
of potential sources of resistance and selection of promising plants or lines in more
advanced stages. Screening tests with thrips can pose problems, however: thrips are
difficult to contain and so may spread to other experiments. Therefore evaluation
methods are needed that are easy to conduct; accurate; reproducible; require little
space, time, and energy; and pose no risk of contamination.These characteristics are
present in in vitro tests.Several tests have been described in the past, e.g. a leaf disc
assay for thrips resistance in cucumber(Kogel et al., 1997), a detached leaf test for
Helicoverpa armigera resistance in pea (Sharma et al., 2005) and a screen cage test for
aphids resistance in sweet pepper (Pineda et al., 2007). Our objective in this study is to
develop a good method for testing thrips resistance in pepper with the previously
mentioned characteristics.
Materials and methods
Pepper accessions
Pepper accessions used in this study were collected from gene banks based on several
previous studies and from East West Seed Indonesia (EWINDO). Thirty-two pepper
accessions from four species of pepper (Capsicum annuum, C. baccatum, C. chinense
and C. frutescens) were used in this study.
Thrips population
Two thrips species were used in this study: Thrips parvispinus and Frankliniella
occidentalis. F. occidentalis was selected as it is the most prevalent thrips species in
European pepper cultivation, while T. parvispinus was selected as representative of
Asian thrips. T. parvispinus was collected from the field in Purwakarta (Java, Indonesia),
while F. occidentalis was collected from glasshouses in the Netherlands.
Screening Methods
a. Screenhouse and glasshouse test
In the screenhouse test, pepper accessions were grown on raised beds in a screenhouse
of EWINDO at Purwakarta, West Java, Indonesia.Seedlings were raised under insect-free
conditions in a seedling bed and transplanted six weeks after germination.Six plants per
accession were planted in a plot, with two replications in a randomized block design.
Plants were spaced 75 cm between rows and 45 cm between plants in a row.Pepper
plants were grown according to standard screenhouse pepper cultivation techniques
(Rossel and Ferguson, 1979). Thrips infestation occurred naturally.Thrips were identified
as T. parvispinus.After the thrips attack, peppers were rated for damage using a relative
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scale from 0 (no damage) to 3 (severe damage, i.e. strongly curled leaves, silvering and
black spots).
In the glasshouse test, pepper accessions were grown at 25oC under 16/8 hr day/night
cycle under standard glasshouse conditions at Wageningen University and Research
Centre, Wageningen, the Netherlands. Four plants per accession were planted in a plot,
with two replications in a randomized block design.After a spontaneous thrips (F.
occidentalis) infestation, plant were rated using relative scale from 0 (no damage) to 3
(severely curled leaves).
b. Leaf Disc Test
F. occidentalis were reared on susceptible Chrysanthemum cultivar Spoetnik (Fides, De
Lier, the Netherlands) in a greenhouse at 25oC and 70% relative humidity (Koschier et al.,
2000), while T. parvispinus were collected from a pepper field at Purwakarta, Indonesia.
Adult female thrips were starved for 24 hours in a chamber with only water.Leaf discs (4
cm in diameter) were cut from the youngest fully opened leaves using a leaf punch and
placed in petri dishes on water agar (15g/l agar) with the lower (abaxial) side upward.
Ten starved female adult thrips were placed on each leaf disc using a wet brush.Dishes
were closed using air-permeable plastic (in the Netherlands) or silk-like textile (in
Indonesia) and placed in a climate room at 24oC, 16 h light, 70% RH.There were six
replicates for each accession. The extent of ‘silver damage’ and destruction by thrips
feeding and secretion were rated using a relative scale from 0 (no damage) to 3 (severe
damage) two days after inoculation.
c. Detached Leaf Test
The detached leaf tests were performed as the leaf disc test, except that intact leaves
from each accessions were placed with their petioles in wet Oasis® (2cm x 5cm x 4cm)
and were put in a jar. Jars were closed using air-permeable plastic (in the Netherlands)
or silk-like textile (in Indonesia) and placed in a climate room at 24oC, 16 h light, 70%
RH.There were six replicates for each accession. The extent of ‘silver damage’ and
destruction by thrips feeding and secretion were rated together using a relative scale
from 0 (no damage) to 3 (severe damage) two days after inoculations.
d. Cutting Test
Three week old cuttings of pepper plants were grown at 25oC, 16 h light under greenhouse
conditions at Wageningen, the Netherlands.Two cuttings from the same accession were
placed in one pot (20 cm diameter). Pollen grains were added to each pot before
releasing 40 synchronized thrips larvae (L1 stages) per pot. To obtain L1, F. occidentalis
were reared at 25oC day and 20oC night in glass jars containing small cucumber fruits and
a few grains commercial pollen (Bijenhuis, Wageningen, the Netherlands).The use of
pollen grain in this experiment is to stimulate thrips and larvae to feed.L1 stage were
obtained by allowing female thrips to lay eggs in new fruits for one day, after which the
adult thrips were brushed off and fruits were kept at 25oC for three days, when the
larvae emerged (Mollema et al., 1993). After releasing L1 thrips, each pot was enclosed
in a thrips-proof cage to avoid thrips escape.There were four replicates for each
accession.After three weeks the damage was rated using relative scale from 0 (no
damage) to 3 (severely curled leaves).
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We performed screenhouse and glasshouse tests under choice conditions, and leaf disc,
detached leaf and cutting tests in non-choice situations.In a choice situation, thrips are
allowed to move between accessions. In contrast, in a non-choice situation, thrips
cannot move from the accession on which they are placed, and possible preference
effects are excluded.
Results and discussion
We observed large differences in thrips damage among pepper accessions. In all of the
tests, accession means for damage varied from 0.0 (no symptoms) to 3.0 (severe damage)
and Kruskal-Wallis tests for accession effects were always significant. All tests resulted
in relatively high heritability values (0.68 to 0.92), except the cutting test (0.34).
Figure 1. Damage caused by thrips in screening methods. (a) silver damage caused by thrips
feeding and black spots caused by fecal material in the leaf disc test (indicated by arrows) and
(b) leaf curling and deformation in the screen house test (indicated by arrow).
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The damage observed in this study was different in tests using whole plants (screenhouse,
greenhouse and cuttings) or in vitro leaves (leaf discs and detached leaf). The symptoms
in the tests using whole plants were silvering, stunting, curling and deformation, while
those in the leaf (disc) tests consisted of silvering and the incidence of black spots
caused by thrips feeding and secretion (Figure 1). These differences are probably due to
the nature of the material used in the tests. Stunting, curling, and deformation of leaves
only occur when the leaves are still growing, so they could not be observed in the leaf
disc and the detached leaf tests.These damages can be classified into four classes as
shown as Figure 1.
Damage caused by F. occidentalis and T. parvispinus was very similar in all the tests in
our study. There were no differences between the symptoms caused by F. occidentalis
and T. parvispinus in the leaf disc and detached leaf tests. The symptoms in the
screenhouse (T. parvispinus) and glasshouse tests (F. occidentalis) were also identical. In
the literature we found no reports of specific differences in damage caused by different
thrips species on pepper. One report mentions that feeding injury caused by F. occidentalis
is similar to that caused by T. tabaci Lindeman (Capinera, 2001).
Although the symptoms observed in the leaf disc and detached leaf tests were different
from those found in the other tests, the damage scores of almost all tests were
significantly correlated (Table 1). This shows that preference effects, which were
possible in the screenhouse and greenhouse tests but not in the other tests, must be
small compared with antibiosis (non-preference) differences.
Table 1. Spearman correlation coefficients and significance between damage
score in screening methods of thrips resistance in pepper.
F. occidentalis
T. parvispinus
T. parvispinus
Screen house
Leaf disc
Detached leaf
Glasshouse
Leaf disc
F. occidentalis
Leaf disc
Detached
leaf
Glasshouse
Leaf disc
Detached
leaf
Cutting
0.77
***
0.80
***
0.76
***
0.65
**
0.70
***
0.53
*
0.87
***
0.71
***
0.71
***
0.71
***
0.45
*
0.73
***
0.70
***
0.69
***
0.50
*
0.77
***
0.73
**
0.48
*
0.77
***
0.41
Cutting
0.64
**
Top figure: correlation coefficient
Bottom figure: significance. *, **, and *** indicate significance at P<0.05, P<0.01, and P<0.001
respectively
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Advances in Genetics and Breeding of Capsicum and Eggplant
Compared to the screenhouse or glasshouse tests, leaf disc and detached leaf tests are
relatively easy to conduct. A small climate room is sufficient to test many accessions.
Also they require little time: damage can be scored two days after inoculation. An
additional advantage is that the plants from which leaves are tested remain uninfested
by thrips. Finally, environmental factors during these tests are better controlled than in
screenhouses or glasshouses.In this study, the leaf disc and detached leaf tests were
compared to see if the wounding involved in obtaining leaf discs would have any effect
on the response to thrips. We did not observe any difference in the type of symptoms on
leaf discs versus whole leaves, nor in the general amount of damage. The correlation
between leaf disc and detached leaf test was high and significant.An advantage of the
leaf disc test over the detached leaf test is that the sample size is more standardized.
Based on the test results we selected two accessions having contrasting damage scores,
and crossed these to obtain a segregating F2 population. We are currently screening the
F2 population using the leaf disc test as phenotyping method in order to perform QTL
mapping of thrips resistance in pepper.
Our results also show that in vitro tests for evaluating thrips resistance in pepper are
reliable and deliver results similar to whole plant tests. Similar tests might be developed
for other insect pests as well, which will strongly facilitate resistance breeding. The leaf
disc test is the most suitable for assessing the resistance of a large number of pepper
accessions to thrips.
Acknowledgements
The research was financially supported by the Royal Netherlands Academy of Arts and
Sciences in the framework of the Scientific Programme Indonesia-The Netherlands. We
thank P.T. East West Seed Indonesia for providing the necessary facilities in conducting
the Indonesian experiments.
References
Capinera, J.L. 2001. Order Thysanoptera-Thrips. In: Capinera, J.L. (ed). Handbook of Ve­
ge­table Pests. Elsevier Inc. p. 535-550.
Jones, D.R. 2005. Plant viruses transmitted by thrips. European Journal of Plant Pathology
113: 119-157.
Kogel, W.J.; Balkema-Boomstra, A.; Hoek, M.V.d.; Zijlstra, S; Mollema, C. 1997. Resistance
to western flower thrips in greenhouse cucumber: effect of leaf position and plant
age on thrips reproduction. Euphytica 94: 63-67.
Koschier, E.H.; De Kogel, W.J.; Visser, J.H. 2000. Assessing the attractiveness of volatile
plant compounds to western flower thrips Frankliniella occidentalis. Journal of
Chemical Ecology 26: 2643-2655.
Maris, P.; Joosten, N.; Goldbach, R.; Peters, D. 2004. Tomato spotted wilt virus infection
improves host suitability for its vector Frankliniella occidentalis. Phytopathology
113: 706-711.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Mollema, C.; Steenhuis, M.M.; Inggamer, H.; Sona, C. 1993. Evaluating the resistance to
Frankliniella occidentalis in cucumber: methods, genotypic variation and effects
upon thrips biology. Bulletin IOBC/WPRS 16: 77-83.
Pineda, A.; Morales, I.; Marcos-Garcia, M.A.; Fereres, A. 2007. Oviposition avoidance of
parasitized aphid colonies by the syrphid predator Episyrphus balteatus mediated
by different cues. Biological Control 42: 274-280.
Reyes, C.P. 1994. Thysanoptera (Hexapoda) of the Philipine Islands. The Raffles Bulletin
of Zoology 42: 1-507.
Rossel, H.W.; Ferguson, J.M. 1979. A new and economical screenhouse for viruses research
in tropical climates. FAO Plant Protection Bulletin 27: 74-76.
Sharma, H.C.; Pampapathy, G.; Dhillon, M.K.; Ridsdill-Smith, J.T. 2005. Detached leaf
assay to screen for host plant resistance to Helicoverpa armigera. Journal of
Economic Entomology 98: 568-576.
Tommasini, M.; Maini, S. 1995. Frankliniella occidentalis and other thrips harmful to
vegetable and ornamental crops in Europe. In:v.L.J. Loomans A.J.M.; Tommasini
M.G.; Maini S.; Ruidavets J. (eds). Biological Control of Thrips Pests. Wageningen:
Wageningen University Papers. p. 1-42.
Ulman, D.E.; Cho, J.J.; Mau, R.F.L.; Hunter, W.B.; Westcot, D.M.; Suter, D.M. 1992. Thripstomato spotted wilt virus interactions: morphological, behavioural and cellular
components influencing thrips transmission. Advances in Disease Vector Research 9:
196-240.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Breeding for resistance and pathogenicity of chili anthracnose
O. Mongkolporn1,2, P.W.J. Taylor3, P. Temiyakul2,4
1
Department of Horticulture, Kasetsart University, Kamphaeng Saen Campus, Nakhon Pathom 73140,
Thailand. Contact: [email protected]
2
Center for Agricultural Biotechnology, Kasetsart University, Kamphaeng Saen Campus,
Nakhon Pathom 73140, Thailand.
3
BioMarka/Center for Plant Health, Faculty of Land and Food Resources, The University of Melbourne,
Victoria 3010, Australia.
4
Center for Agricultural Biotechnology: (AG-BIO/PERDO-CHE), Thailand.
Abtract
Anthracnose, caused by Colletotrichum spp., is a major disease infecting chili fruit in the
tropics. There are no resistant varieties available in Capsicum annuum, the world most
important Capsicum species; therefore seeking resistance in related Capsicum species is
essential. Immune resistance was initially discovered in wild accessions of C. chinense and
C. baccatum by the World Vegetable Center (Taiwan; formerly known as AVRDC). Genetic
analysis of resistance to anthracnose derived from C. chinense PBC932 and C. baccatum
PBC80 revealed that resistance was differentially expressed at different fruit maturity
stages. Capsicum chinense PBC932 contained two recessive genes, one expressed in mature
green and one in ripe fruit maturity stages with both genes linked ~25 cM. Although two
molecular markers were located flanking the genetic loci at genetic distances of 37 and 24
cM from the genes, closer markers are being developed. Resistance in C. baccatum PBC80,
exhibiting broader resistance to anthracnose than C. chinense PBC932, was also controlled
by two different genes at different fruit maturity stages, however the genes were dominant
and independent. Colletotrichum pathotypes were identified based on differential host
reactions, infection vs. no infection, on a set of differential chili genotypes. Different fruit
maturity stages also played a key role in pathotype identification. Among 33 isolates of
Colletotrichum capsici (Cc), C. gloeosporioides (Cg) and C. acutatum (Ca); three Cc
pathotypes were identified in ripe fruit and two in mature green fruit; five Cg pathotypes
in ripe and six in mature green fruit; three Ca pathotypes in mature green fruit. No Ca
pathotypes were identified in ripe fruit. The identification of genes for resistance and
pathotypes that overcome the resistance highlights the dynamic nature of the host-pathogen
relationship of anthracnose in chili pepper.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
New source of resistance to Thai isolate of Cucumber mosaic virus
and Chilli veinal mottle virus in Capsicum germplasm collection
S. Patarapuwadol1,2, W. Sompratoom1, K. Sitadhani3, S. Wasee3
1
Department of Plant Pathology, Faculty of Agriculture, Kasetsart University, Kamphaeng Saen Campus,
Nakhon Pathom 73140, Thailand. Contact: [email protected]
2
Center for Agricultural Biotechnology, Kasetsart University, Kamphaeng Saen Campus,Nakhon Pathom,
and Center for Agricultural Biotechnology: (AG-BIO/PERDO-CHE), Thailand.
3
Tropical Vegetable Research Center (TVRC) Kasetsart University, Kamphaeng Saen Campus,
Nakhon Pathom 73140, Thailand.
Abstract
Cucumber mosaic virus (CMV) and Chili veinal mottle virus (ChiVMV) are the most common
viruses in Capsicum spp in Thailand. A total of 533 Capsicum accessions maintained by
Tropical Vegetable Research Center (TVRC) and GRIN/SINGER USA were screened for
resistance to Thai isolate of CMV and ChiVMV under greenhouse condition. Percent of
infected plants, ELISA reaction and number of plants infected by ELISA were used for
resistance evaluation. We successfully identified 41 immune or highly resistant accessions
to ChiVMV. CCMV5 and CA 1304 (C. annuum) accessions were found highly resistant to CMV.
In addition, selfed progenies of 4 symptomless and highly resistant accessions to CVMV were
selected for 2 field trials. No infection plant was found in any of the progenies of the four
resistant accessions. Evaluation of Capsicum germplasm collection for resistance to Thai
isolate of CMV and ChiVMV has allowed the identification of new sources of resistance for
breeding new cultivars. However, further investigation is needed to determine the
mechanism and the inheritance of CMV and/or CVMV resistance in these accessions.
Keywords: Capsicum, pepper, CMV, ChiVMV, resistance screening.
Introduction
Cucumber mosaic virus (CMV) and Chili veinal mottle virus (ChiVMV) have been reported
to be the most important viruses of pepper growing throughout Thailand (Chiemsombat
and Kittipakorn, 1997; Chiemsombat et al, 1998). Sources of resistance to different isolates
of CMV and ChiVMV were identified by AVNET member countries including Thailand.
Unfortunately results of these screening tests were not consistent among countries (Duriat
et al 1997). In addition, several virus-resistance genes in Capsicum spp. have been reported
(Caranta and Palloix, 1996; Rubio et al, 2009). Attempts have been made to transfer these
genes to pepper cultivars to control viruses (Lapidot et al, 1997; Suzuki et al, 2003).
However commercial pepper production still sustains losses from infection by both viruses,
this may due to the present of several different strains of CMV and CVMV (García-Arenal
et al, 2000; Tsai et al, 2008). In Thailand, pepper cultivars resistant to local isolates of CMV
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Advances in Genetics and Breeding of Capsicum and Eggplant
and CVMV has not yet been bred. Therefore, it remains necessary to search for a new
source of resistant for breeding resistant cultivars.
Greenhouse testing of accessions is currently used with mechanically transmitted viruses
and ELISA became available to help estimating the level of virus buildup in each plant.
The incorporation of these prescreening methods can increase the efficiency of selection
of resistant genotypes, because a large number of plants can be screened in a short
time.Thus, in this study, 533 Capsicum accessions maintained by Tropical Vegetable
Research Center (TVRC) and GRIN/SINGER, USA were screened for resistance to Thai
isolate of CMV and ChiVMV under greenhouse condition. Furthermore, we assessed the
viral resistance of selected accessions in field trials.
Material and methods
Virus isolation and characterization
Pepper plants showing symptoms such as mosaic, mottle, vein banding and/or leaf
deformation were collected from Kampaengsean district, Nakorn Pathom Province,
Thailand. Indirect ELISA (Clark and Adams, 1977) was used to confirm the presence of
CMV and ChiVMV. Samples positive only for CMV were selected for single lesion isolation
on Phaseolus aureus Roxb. cv. KPS2. Pure CMV isolate, CMV KPS10 was propagated and
maintained in Nicotiana glutinosa. Positive samples only for ChiVMV were also selected
for single lesion isolation on Nicotiana tabacum cv. White Burley. ChiVMV isolate namely
ChiVMV KPS9 was propagated and maintained in Datura stramonium. Infectivity of CMV
KPS10 and ChiVMV KPS9 was confirmed by mechanical inoculation onto C. annuum cv.
CA500 and the presence of virus was reconfirmed by indirect ELISA. They had also been
confirmed to be free from other types of viruses by electron microscopy. Characterization
of each virus isolate was conducted by mechanical inoculation onto differential host set.
Coat protein gene of each virus was cloned, sequenced and submitted to NCBI-GenBank.
Comparison of nucleotide sequences of CP gene showed that CMV KPS10 (GenBank
accession number, EF608461) was similar to the reported CMV isolated from Thailand. In
addition, in silico restriction site analysis of CP gene indicated that CMV KPS10 belonged
to CMV subgroup IB. For ChiVMV-KPS9 (CVMV KPS9, GenBank accession number, EU636198),
nucleotide sequences of CP gene showed 95-97 % identity with those of previously
reported ChiVMV isolates from Thailand.
Plant material and growing conditions
Capsicum germplasm collection comprsing 533 accessions maintained by Tropical
Vegetable Research Center (TVRC) and GRIN/SINGER USA was used for the virus resistant
evaluation.This germplasm contains a wide range of fruit morphological types and
regions of origin. Susceptible pepper accession CA500 and resistant accession CA 446
were used as controls for ChiVMV screening. For CMV screening, only susceptible pepper
accession CA500 was used as a control. Twenty-four pepper seedlings of each accession
were grown in a plastic seed tray with 24 cells (5 X 20 cm) and filled with potting media
comprissing soil, compost and coconut peat at the ration 2:1:1. Plant were maintained
in insect-proof greenhouse facilities of TVRC and Department of Plant Pathology.
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Inoculation
Mechanical inoculation technique was applied to pepper seedlings at 3-5 leaves stage.
Inoculum of CMV KPS10 or ChiVMV KPS9 was prepared by grinding infected leaves in 0.1
M phospate buffer pH7.0 (1 g/ 10 ml ) and 600-mesh Carborundum was added as abrasive
(0.25g/10mL). For each virus, 10 pepper seedlings were inoculated by rubbing the leaves
with inoculum. Inoculation was repeated 1 week following the first inoculation to reduce
the number of plants that escaped infection. Two pepper seedlings for each accession
were not inoculated and used as negative control.
Virus detection
Four weeks after inoculation, samples of the inoculated leaves of each virus plus the
control plants were collected in 6 plants per accession for ELISA test. Detection of virus
in leaf samples was done by indirect ELISA according to (Clark and Adams, 1977) with
anti-CMV or anti-ChiVMV antibody. Absorbance was measured using a microplate reader
at 405 nm. Tests were considered positive when the absorbance value of each sample
was at least two times greater than that of the healthy control plant.
Data analyses
Data were collected on the type of symtoms, percent of infected plants (visually) and
number of plants infected by ELISA. Reaction types of pepper accesssion to CMV or
ChiVMV was based on pecent of infected plants detected by ELISA.
Reaction Types
I
= immune (0% infection)
R
= resistant (1-10% infection)
MR
= moderately resistant (11-30% infection)
MS
= moderately suceptible (30-50% infection)
S
= susceptible (51-100% infection)
Field trials
Based on the results of the greenhouse tests, the ChiVMV KPS9 resistance of four selected
accessions was carried out in the field. These four highly resistant accessions were
CA446, CA1131, CA1195 and CA1258. Two field trials were tested from July to September
2007 and from March to May 2008 at TVRC, Kasetsart University. The experimental design
was a randomized complete blosk design (RCBD) with four replications. One replication
consisted of twelve test plants in the left site and twelve infected CA500 plants in the
right site. For a source of the virus which spread by suitable aphid vectors, ChiVMV KPS9
infected seedlings of the susceptible Capsicum spp cv. CA500 were planted surrounding
the experimental sites. In addition, healthy CA500 plants were planted for the evaluation
of virus infection rate in the experimental fields. Data were collected monthly for 3
months after the test plants were exposed to the infected plants. Symptoms on inoculated
plants and indirect ELISA test for determination of virus concentration were used for
resistance evaluation.
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Results and discussion
Greenhouse screening
During the course of the screening of CMV and ChiVMV resistant sources in Capsicum
spp. in greenhouse condition, several highly resistant (immune) accessions were
successfully identified. A summary of reaction types of Capsicum accessions to
inoculation with CMV KPS10 and ChiVMV KPS9 are shown in Table 1. ChiVMV KPS9 caused
symptoms varying from vein mottling, vein banding necrosis, leaf distortion, green spot
and green flecking in 492 pepper accessions. The results of ChiVMV KPS9 symptom
development agree with ELISA tests. As observed in the greenhouse test, CMV KPS10
caused less and milder symptoms in pepper accessions. In addition, some CMV KPS10
infected plants did not show any symptom or mild chlorosis but high level of viral
antigen was detected by ELISA. Two and forty-one accessions of C. annuum were
exhibited immune response (no symtoms, 0% infection) to CMV KPS10 and ChiVMV-KPS9
respectively (Table 2). One accession, CCMV 5 was highly resistant to both CMV KPS10
and ChiVMV-KPS9. In order to confirm the greenhouse screening results, all these
accessions were re-evaluated. The re-screening results showed that only the result of
accession CA1184 and CA 1611 did not agree with the previous result. This may due to
seed impurity of these two accessions. This greenhouse screening method took only 2
months for screening a large number of accessions at the same time. However, it should
be note that the greenhouse screening is only a quick indication of which accessions of
germplasm collection to test further, and the potential resistant lines can be tested in
controlled temperature greenhouse or in the filed.
Table 1. Summary of reactions of Capsicum accessions to CMV KPS10 and
ChiVMV KPS9 evaluated in greenhouse.
Reaction type
Number of accessions
CMV KPS10
ChiVMV KPS9
I
2
41
R
5
1
MR
49
14
MS
105
35
S
372
442
total number of tested accessions
533
533
Note: Plants were inoculated twice and viruses were detected by ELISA in 6 plants /accession.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Table 2. Fruit characterisation of Capsicum accessions highly resistance
to CMV KPS10 and ChiVMV KPS9.
Fruit characteristics*
Acc.
No.
Source
CA2106
TVRC
1.30
9.01
CCMV5
TVRC
0.98
7.14
wall
width(cm) Length (cm) thickness
(mm)
Weight(g)
shape
surface
1.12
8.32
elongate
smooth
0.46
2.53
elongate
smooth
CMV KPS10 resistance
ChiVMV KPS9 resitance
CA446
TVRC
0.70
2.88
0.39
0.72
elongate
smooth
CA860
TVRC
0.64
3.54
0.37
0.90
elongate
smooth
CA1331
TVRC
0.61
2.26
0.45
0.48
elongate
smooth
CA1195
TVRC
2.71
4.48
2.10
11.33
campanulate
smooth
CA1258
TVRC
0.64
2.49
0.45
0.63
elongate
smooth
CA1338
TVRC
0.65
3.96
0.55
0.94
elongate
smooth
CA1611
TVRC
0.80
4.10
0.70
1.04
elongate
smooth
CCMV2
TVRC
0.46
0.95
6.81
2.35
elongate
wink
CCMV3
TVRC
0.93
6.70
0.47
2.10
elongate
smooth
CCMV5
TVRC
0.98
7.14
0.46
2.53
elongate
smooth
CCMV6
TVRC
0.85
4.48
0.67
1.78
elongate
smooth
CCMV7
TVRC
0.89
5.33
0.63
2.16
elongate
smooth
CCMV8
TVRC
0.85
4.72
0.59
1.57
elongate
smooth
CCMV9
TVRC
0.79
4.64
0.64
2.10
elongate
smooth
CCMV11
TVRC
1.21
4.18
1.04
2.86
elongate
smooth
CCMV12
TVRC
0.71
2.99
0.47
0.82
elongate
smooth
CCMV13
TVRC
0.70
2.93
0.43
0.98
elongate
smooth
CCMV14
TVRC
0.75
2.86
0.42
0.74
elongate
smooth
CCMV15
TVRC
0.72
2.92
0.44
0.76
elongate
smooth
CCMV16
TVRC
0.69
2.91
0.49
0.74
elongate
smooth
CCMV18
TVRC
0.91
4.78
0.72
2.20
elongate
smooth
CCMV19
TVRC
0.76
3.94
0.48
1.28
elongate
smooth
CCMV20
TVRC
0.78
6.07
0.58
2.03
elongate
smooth
CCMV22
TVRC
1.29
6.54
0.72
3.27
elongate
smooth
CCMV23
TVRC
1.10
4.86
0.69
2.69
elongate
smooth
CCMV24
TVRC
1.28
6.60
0.79
3.22
elongate
smooth
CCMV26
TVRC
1.25
6.35
0.72
3.09
elongate
smooth
CCMV31
TVRC
0.69
2.84
0.41
0.72
elongate
smooth
BCMV32
TVRC
0.95
5.07
0.56
2.10
elongate
smooth
BCMV34
TVRC
0.84
5.91
0.51
1.80
elongate
smooth
* Fruit characteristics were evaluated by TVRC in the open field at TVRC, Kasetsart University.
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Field trial
One of the difficulties in field trials is visual scoring for resistance, since the symptoms
may be caused by other viruses or insect in the tested field. Some of the tested plants
showed ChiVMV disease like symptoms; however they were negative in ChiVMV-ELISA tests.
Our results demonstrate that using only visual scoring for resistant selection could be
misleading. Based on indirect ELISA test for determination of virus concentration for
resistance evaluation for 3 months. No infected plant was found in four ChiVMV KPS9 resis­
tant accessions thus confirming that these accessions are resistant to CVMV infection.
Conclusions
Greenhouse testing method using mechanically transmitted viruses and ELISA can increase
the efficiency of selection of resistant genotypes, as a large number of plants can be
screened in a short time. Pepper accessions exhibiting immune reaction to CMV and ChiVMV
in this study can be used not only as resistant sources for breeding but also can be use as
source for the defense mechanism study. In addition, the virus resistance screening results
were deposited together with other trial characteristics at biotec Germplasm Database
website (http://biotec.or.th/germplasm/Pages/find_des.asp). Seed can be provided to
the researchers free of charge by signing a material transfer agreement.
Acknowledgements
This research has been financed by National Center for Genetic Engineering and Bio­
technology (BIOTEC), Thailand.
References
Caranta, C.; Palloix, A. 1996. Both common and specific genetic factors are involved in
polygenic resistance of pepper to several potyviruses. TAG Theoretical and Applied
Genetics, 92, 15-20.
Chiemsombat, P.;Kittipakorn, K. 1997. Confirmation of potentially important pepper viru­
ses. In: AVRDC 1997. Collaborative vegetable research in Southeast Asia. Proceedings
of the AVNET-II Final Workshop, Bangkok, Thailand, 1-6 Sep. 1996. Publication No.
420-431, 451 pp.
Chiemsombat, P.; Sae-Ung, N.; Attathom, S.; Patarapuwadol, S.; Siriwong, P. 1998. Mole­
cular taxonomy of a new potyvirus isolated from chilli pepper in Thailand. Archives
of Virology 143, 1855-63.
Clark, A.X.; Adams, M.J. 1977. Characteristics of the microplate method of enzymelinked immunosorbent assay for the detection of plant viruses. J. Gen. Virol. 34:
475-483.
Duiat, A.S.; Gunaeni,N.; Sulastrini, I. 1997.Further studies on screening pepper varieties
for resistance to CMV strains. In: AVRDC 1997. Collaborative vegetable research in
Southeast Asia. Proceedings of the AVNET-II Final Workshop, Bangkok, Thailand, 1-6
Sep. 1996. Publication No. 119-124, 451 pp.
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Advances in Genetics and Breeding of Capsicum and Eggplant
García-Arenal, F.; Escriu, F.; Aranda, M.A.; Alonso-Prados, J.L.; Malpica, J.M.; Fraile, A.
2000. Molecular epidemiology of Cucumber mosaic virus and its satellite RNA. Virus
Research, 71, 1-8.
Lapidot, M.; Paran, I.; Ben-Joseph, R., Ben Harush, S.; Pilowsky, M.; Cohen, S., Shifriss,
C. 1997. Tolerance to cucumber mosaic virus (CMV) in pepper: development of
advanced breeding lines and evaluation of virus level. Plant Dis 81:185-188.
Rubio, M.; Nicolai, M.; Caranta, C.; Palloix, A. 2009. Allele mining in the pepper gene pool
provided new complementation effects between pvr2-eIF4E and pvr6-eIF(iso)4E
alleles for resistance to pepper veinal mottle virus, pp. 2808-2814.
Suzuki, K.; Kuroda, T.; Miura, Y.; Murai, J. 2003. Screening and Field Trials of Virus Resis­
tant Sources in Capsicum spp, pp. 779-783.
Tsai, W.S.; Huang, Y.C.; Zhang, D.Y.; Reddy, K.; Hidayat, S.H.; Srithongchai, W.; Green,
S.K.; Jan, F.J. 2008. Molecular characterization of the CP gene and 3’UTR of Chilli
veinal mottle virus from South and Southeast Asia, pp. 408-416.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Response of pepper rootstocks for resistance to Meloidogyne incognita
populations in greenhouses of Southeast Spanish
C. Ros1, C. Martínez1, M.M. Guerrero1, C.M. Lacasa1, V. Martínez1, J.L. Cenis1,
A. Cano3, A. Bello2, A. Lacasa1
Biotecnología y Protección de Cultivos. IMIDA. C/ Mayor s/n, 30150 La Alberca, Murcia, Spain.
Contact: [email protected]
2
Centro de Ciencias Medioambientales, CSIC, C/ Serrano, 113, 28006 Madrid, Spain.
3
SSVV. Consejería de Agricultura y Agua. C/ Mayor s/n, 30150 La Alberca, Murcia, Spain.
1
Abstract
Since the elimination of methyl bromide for soil disinfection in greenhouses in the southeast
of Spain, the incidence of nematodes has been growing in pepper crops. Meloidogyne
incognita is the most important species due to its economic impact. The repeated use of
rootstocks resistant to Meloidogyne, as an alternative to methyl bromide, has caused
selection of populations that overcome the resistance in some greenhouses. The response of
rootstocks resistant to Meloidogyne was evaluated by using field trials and laboratory tests
with two populations, one virulent and one avirulent, while trying to identify by molecular
genetics the resistance genes that the rootstocks may carry. The field trials were performed
for two consecutive years in a commercial and an experimental greenhouse, both
contaminated with M. incognita (the commercial one by an avirulent and the experimental
one by a virulent population). In the first growing season the following rootstocks were
assessed: Atlante, C19, DRO-3403, DRO-8801, Snooker and Tresor and in the second: Atlante,
DRO-3403, RT12, Snooker, WS-5051 and WS-5050. In the laboratory, all rootstocks were
inoculated with a virulent population to Atlante and with another one that is non-virulent.
In field trials the nematode incidence (root-knot index and percentage of infested plants)
was evaluated in the rootstocks and in a commercial production in an experimental design
of randomized blocks. In laboratory tests the nematode incidence was evaluated. In the first
year of field trials the virulent population affected 50% of the rootstocks (Atlante, DRO-3403
and Tresor) with an average index of 4.4 and a percentage of infested plants of more than
80% and in the second growing season, more than 80% of the rootstocks were infested with
an index above 3 and percentages of infested plants above 60%. In the greenhouse with the
non-virulent population the incidence in the first year was very low, but in the second year
the rootstocks DRO-3403, WS-5050 and WS-5051 were infested. In the laboratory, only 7
rootstocks were infested with the virulent population and 2 with the non-virulent one,
behaving as susceptible. The response to the virulent population is related to the combination
of resistance genes carried by each rootstock.
Keyswords: soil borne diseases, nematodes, pepper, greenhouse.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Introduction
Meloidogyne incognita is one of the main soil borne pathogens in pepper greenhouses in
the Campo de Cartagena region (Murcia, Spain). (Tello and Lacasa, 1997). The control
was disinfecting the soil with Methyl bromide (MB) (Lacasa and Guirao, 1997). The
withdrawal of the use of this fumigant and the limitations that may arise to dispose of
the chemical, leads to finding non-chemical alternatives. Grafting on nematode resistant
rootstocks has been assayed as a means of mitigating the effect of these (Lacasa et al.,
2002; Ros et al., 2004). The stability of resistance to pathogens seems essential for its
continuous and stable use. The apparent complexity of resistance to M. incognita in
pepper (Hendy et al., 1985; Castagnone-Sereno et al., 2001), could explain the variations
in the response of some rootstocks against nematodes, when using resistant rootstocks
repeatedly in the same soils (Robertson et al., 2006).
The objective of this study was to evaluate the response of rootstocks against virulent
and avirulent populations of M. incognita under greenhouse conditions in the Campo de
Cartagena region (Murcia, Spain) and under controlled conditions.
Materials and methods
Field studies
The rootstocks used were: Atlante, C25, from Semillas Ramiro Arnedo S.A.; DRO 3403 and
DRO 8801 from De Ruiter Semillas, S.A.; Snooker and RT12 from Syngenta Seeds S.A.;
Tresor from Nunhems Semillas, S.A. and WS-5050 and WS-5051 from Western Seeds.
The field trial was conducted for two consecutive years in two greenhouses, an
experimental one and a commercial one. Both greenhouses were infested by Meloidogyne
incognita. In experimental greenhouse (Ch) the pepper crop has been growing for about
7 years without soil disinfection prior to planting and the nematode population is
considered virulent for the rootstock Atlante (Roberston et al, 2006). In the other
greenhouse (K) the pepper crop has been grown for 22 years without soil disinfection and
the initial population was considered avirulent for Atlante. In both greenhouses as an
experimental design randomized blocks were used with three repetitions per rootstock,
each experimental plot being 60m2 in the CH greenhouse and 25m2 in greenhouse K,
housed 1 row at 1.0 x 0.40 m. Both greenhouses had plots treated with methyl bromide
(MB 98:2) at 30 g m-2 under plastic VIF (Virtually impermeable films) of 0.04 mm thickness
with plants without grafting, as a control.
The date of planting was every year in the first week of January. In greenhouse CH
variety Almudén (Syngenta Seeds) was planted in both campaigns and in greenhouse K
Quito variety was planted in the first year and variety Herminio (Syngenta Seeds) in the
second. The crops were finished the first week of August, in greenhouse CH in both
campaigns and in the first week of September in greenhouse K. In both greenhouses the
crops were grown with standard procedures as used in this area.
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To evaluate the behaviour the following items were measured: a) when the crop was
finished, ten grafted plants and ten non grafted plants of each plot were dug from the
soil in a randomized way and the root system was observed. Damage caused by M.
incognita was measured according to the Bridge and Page scale (1980), b) the incidence
of Phytophthora: every week the plants were examined in the elementary plots, noting
those affected by the disease, after isolating the fungus, c) Commercial and total
marketable yield (kg m-2): at each harvest the fruits were classified in each elementary
plot as to their commercial grade of each type of variety and they were weighed.
Percentage of infested plant and the root-knot index were transformed with arc sin √x
and log10 (x+1) prior to analysis of variance (ANOVA) (P>0.05). Percentage of affected
plants for P. capsici was transformed with arc sin √x and examined with ANOVA (P>0.05).
Marketable yield categories and total yield were transformed with log10 (x+1) and
examined with ANOVA. In both significant differences among treatments were compared
with the LSD test (P> 0.05).
Laboratory assays
Test inoculation with J2 of M. incognita
Some rootstocks used in the field trials were inoculated with two populations of M.
incognita, MI-CH and MI-E; both were obtained from experimental greenhouses in which
pepper was grown. The susceptible commercial pepper cultivar Sonar (Clause-Tezier,
S.A.), was included as a control.
The MI-CH population was isolated from infested roots of pepper cv Almuden in 2002/03 in
the experimental greenhouse Ch, and the MI-E population was obtained from pepper cv
Ribera (De Ruiter Seeds) in the campaign of 2001/2002 in the experimental greenhouse E.
The two populations of M. incognita were of race 2 and they were characterized as virulent
(MI-CH) and avirulent (MI-E) when used to inoculate under controlled conditions the two
susceptible varieties Capino (Enza Zaden) and Sonar, and the resistant rootstock Atlante.
Eight plants of each rootstock and the susceptible cultivar Sonar were transplanted one
by one to plastic pots of 7.5L containing horticultural substrate and perlite (50:50 by
volume) autoclaved at 120ºC for 1 hour. Egg and juvenile inocula were extracted from
infected tomato roots using 0,5% sodium hypochlorite (NaClO) (Hussey and Barker, 1973).
Seven days after transplanting the pepper seedlings were inoculated with 1,000 eggs and
juveniles in two holes near the root system. Plants were grown for two weeks in a growth
chamber at 23-34 ºC, with a relative humidity of 45-60% during the dark period and 85100% during the light period and with a photoperiod of 14:10 hours of light: darkness,
and watered three times a week.
Each rootstock and susceptible variety was inoculated with the two populations MI-CH
and MI-E using 3 replicates of 8 plants per replication of each combination. Eight weeks
after inoculation the roots of each plant were washed and the root nodulation index
scored (Bridge and Page, 1980). The results are expressed as the average percentage of
infected plants and as a means of nodulation index. For statistical analysis these data
were transformed by arcsin expression for the percentage of infestation and the
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expression Log10 (x) for the average nodulation index. The analysis of variance (factors,
treatments and blocks) and the comparison of means by LSD was performed at 95%.
Molecular Testing
DNA was extracted of rootstocks from young leaves following the protocol Dneasy Plant
Mini Kit de Qiagen.
Tests were performed via PCR to identify the existence of areas linked to resistance
genes Me1, Me3 and Me7using the SCAR markersB94 and CD and the CAPS marker F4R4
(Djian-Caporalino et al, 2007). Some of the conditions of the PCR programs were modified
(Table 1). Each test was repeated 4 times.
Amplification products were separated by electrophoresis in agarose gels (2-3%) and
stained with ethidium bromide for visualization.
Table 1. PCR conditions.
SCAR B94
SCAR CD
CAPS F4R4
3 min 94ºC
3 min 94ºC
3 min 94ºC
35
cycles
30s 94º
35 30s (53-70ºC)
cycles
45s 72ºC
30s 94ºC
38
30s 53ºC
cycles
45s 72ºC
30s 94ºC
30s 61ºC
90s 72ºC
10min 72ºC
10min 72ºC
10min 72ºC
Results and discussion
Field studies
M. incognita incidence
In the first season, the differences between rootstocks found in greenhouse Ch (virulent
for the rootstock Atlante) were more pronounced than those found in greenhouse K
(avirulent populations). Both greenhouses had rootstocks that provided nematode
control levels similar to or better than MB to plants without grafting (Table 2).
In the second year, differences were found among rootstocks in the two greenhouses
(Table 3), regardless of the original virulence of the populations. Some resistant root­
stocks improve or are equal to the level of nematode control obtained with MB disinfected
soil with plants without grafting. Noteworthy are, the behaviour of resistant rootstock
RT12 in the experimental greenhouse Ch and the stability of the resistant rootstock
Atlante in greenhouse K.
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Table 2. Percentage of plants infected by Meloidogyne incognita and nodulation
index in greenhouses Ch and K in the first year.
Greenhouse Ch
Plant material
Nodulation
index
b
Greenhouse K
% plants
infected
Nodulationb
index
% plantsa
infected
80,0cd
0,1a
6,7ab
a
Atlante
4,8c
C19
0,3a
13,3a
0,0a
0,0a
DRO 3403
3,4c
93,3d
0,2a
6,7ab
DRO 8801
0,3a
13,3a
0,3a
6,7ab
Snooker
1,0ab
53,3bc
0,1a
6,7ab
Tresor
5,0c
93,3d
0,3a
20,0b
MB + non grafted
1,6b
46,7ab
0,0a
0,0a
The same letter in each column indicates no significant difference (P< 0,05) ANOVA
(a= Test LSD y=arcsen √x; b= Test LSD y= log10(x+1)).
Of the three rootstocks (Atlante, DRO 3403 and Snooker) that were repeated in both
greenhouses and in the two campaigns, the behaviour of Atlante was stable against the
two populations. Snooker maintained its behaviour in greenhouse K with avirulent
populations, but not against the virulent greenhouse population Ch, indicating that the
repeated use of the crop in the same soil would facilitate the selection of populations
capable of overcoming its resistance, as with Atlante (Ros et al., 2008). The behaviour
of the rootstocks WS5050 and WS5051 shows that the aggressiveness of the populations
of the two greenhouses is similar, but that there are variations in their virulence.
Table 3. Percentage of plants infected by Meloidogyne incognita and nodulation index in
greenhouses Ch and K in de second year.
Greenhouse Ch
Plant material
Greenhouse K
Nodulationb
index
% plantsa
infected
Nodulationb
index
% plantsa
infected
Atlante
4,2c
83,3bc
0,1a
4,8a
DRO 3403
4,9c
86,7c
2,0b
57,1bc
14,3ab
Snooker
3,7c
80,0bc
0,3a
RT12
0,0a
0,0a
0,0a
0,0a
WS-5050
2,1b
56,7bc
3,1c
80,9c
WS-5051
3,9c
86,7c
3,5c
90,5c
MB + non grafted
1,9b
46,7b
1,5b
47,6bc
Means within a column followed by the same letter are not significantly different (P< 0,05)
according to ANOVA (Test LSD y=arcsen √x; b= Test LSD y= log10(x+1)).
Phytophthora incidence
The incidence of Phytophthora in greenhouse K (Table 4) was reduced in grafted plants,
except for resistant rootstock Tresor, considered as sensitive to isolates of Phytophthora
parasitica that were detected in the greenhouse soil. The rootstocks provided similar
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levels of incidence as in plants without grafting grown in soil disinfected with MB.
Overall, the incidence was low. In addition, most of the plants are affected at the end
of the season, so that the impact on production was reduced.
Table 4. Incidence of Phytophthora rootstocks tested in greenhouse K
in the two test campaigns.
% plants affected by Phythophtora
Plant material
First campaign
Second campaign
Atlante
1,3a
0,0a
C19
0,0a
ns
DRO 8801
0,7a
ns
DRO 3403
3,3a
2,0b
Tresor
16,7b
ns
Snooker
0,0a
0,0a
RT12
ns
0,0a
WS-5050
ns
0,7a
WS-5051
MB + non grafted
ns
0,0a
0,0a
4,0b
ns= Not tested. Means within a column followed by the same letter are not significantly
different (P< 0,05) according to ANOVA(Test LSD y=arcsin √x)
Marketable yield
In the first season, in greenhouse Ch and K, differences were found among rootstocks in
the commercial yields and in the three categories (Tables 5 and 6). All rootstocks
provided similar or superior commercial yields to non-grafted plants planted in soil
disinfected with MB, although in some the percentage of plants killed by Phytophthora
(Table 4) was higher than 10%.
Table 5. Marketable yield (kg m-2) according to marketable categories of rootstock
and plots treated with MB in greenhouse Ch.
Plant material
Extra
First
Second
Third
Marketable
Non Marketable
Atlante
0,0a
2,3 a
2,3 c
1,3 c
5,9 bc
0,9 ab
C19
0,0a
2,4 a
3,0 ab
1,8 b
7,2 ab
0,7 b
DRO 3403
0,0a
2,0 ab
2,3 c
1,5 bc
5,8 bc
1,3 a
DRO 8801
0,0a
1,7 b
2,7 bc
1,4 bc
5,8 bc
1,0 a
Snooker
0,0a
1,7 b
3,5 a
2,4 a
7,6 a
0,6 bc
Tresor
0,0a
2,0 ab
2,6 bc
1,5 bc
6,1 ab
0,5 c
MB + non grafted
0,0a
2,1 ab
2,8 b
1,2 c
6,1 ab
0,4 c
Means within a column followed by the same letter are not significantly different (P< 0,05)
according to ANOVA(Test LSD y= log10(x+1))
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Table 6. Marketable yield (kg m-2) according to marketable categories of rootstock
and plots treated with MB in greenhouse K.
Plant material
Extra
First
Second
Third
Marketable
Non Marketable
0,5ab
Atlante
0,1a
1,6bc
2,4a
0,9b
4,9abc
C19
0,0b
1,8ab
2,1abc
0,7c
4,6bcd
0,3c
DRO 3403
0,1a
1,6bc
1,9bcd
0,9b
4,4cd
0,6a
DRO 8801
0,0b
1,9ab
1,9bcd
1,2a
5,0abc
0,4bc
0,3c
Snooker
0,0b
2,0a
2,3ab
1,3a
5,5a
Tresor
0,1a
1,6bc
1,9bcd
0,5d
4,0de
0,3c
BM + non grafted
0,1a
1,4c
1,7d
0,6cd
3,7e
0,4bc
Means within a column followed by the same letter are not significantly different (P< 0,05)
according to ANOVA (Test LSD y= log10(x+1)).
In the second campaign, there were no differences among rootstocks in the crop
productions at the end of the season, in greenhouse Ch, but there were differences in
some commercial categories (Table 7), these being similar to those of plants grown
without grafting in soil disinfected with MB. In greenhouse K the differences among
rootstocks in total commercial production and commercial categories were very
pronounced (Table 8) and all rootstocks except DRO 3403 produced more than plants
grown without grafting in soil disinfected with MB.
Table 7. Marketable yield (kg.m-2) according to marketable categories of rootstocks
and plots treated with MB in greenhouse Ch.
Plant material
Extra
First
Second
Third
Marketable
Non Marketable
1,7ab
Atlante
0,2a
1,6ab
4,2a
2,0bc
7,9a
DRO 3403
0,1b
1,4b
3,4a
1,7c
6,6a
1,9ab
RT12
0,1b
1,6ab
4,1a
2,6a
8,3a
1,5ab
Snooker
0,0b
1,3b
4,1a
2,7a
8,0a
0,7c
WS-5050
0,0b
1,6ab
4,1a
2,2ab
7,8a
2,1a
WS-5051
0,0b
2,0a
4,1a
2,2ab
8,3a
1,4ab
MB + non grafted
0,2a
1,3b
3,7a
2,7a
7,8a
1,1bc
Means within a column followed by the same letter are not significantly different (P< 0,05)
according to ANOVA (Test LSD y= log10(x+1)).
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Table 8. Marketable yield (kg.m-2) according to marketable categories of rootstocks
and plots treated with MB in greenhouse K.
Plant material
Extra
First
Second
Third
Marketable
Non Marketable
0,9b
Atlante
0,6a
2,4c
2,6d
0,8cd
6,4c
DRO 3403
0,5ab
1,9d
2,8cd
0,7de
5,9cd
1,2a
RT12
0,4c
2,5c
3,6a
1,2a
7,8ab
0,9b
Snooker
0,5ab
3,0ab
3,3ab
1,0ab
7,8a
0,5c
WS-5050
0,5ab
3,5a
2,9bcd
0,9bc
7,8a
0,8b
WS-5051
0,1d
2,7bc
3,1abc
0,8cd
6,7bc
1,2a
MB + non grafted
0,2d
1,8d
2,7d
0,6e
5,3d
1,2a
Means within a column followed by the same letter are not significantly different (P< 0,05)
according to ANOVA (Test LSD y= log10(x+1)).
Laboratory assays
Inoculation with J2 of M. incognita
All rootstocks inoculated with the virulent population (MI-CH), except for DRO 8801 and
RT12, (Table 9) were infested for around 100% of the plants and with a nodulation index
similar to those of the susceptible reference variety (Sonar), however, these rootstocks
were not affected by the avirulent population (MI-E), except WS-5050 and WS-5051 that
were infested at the same level as the control variety.
Table 9. Nodulation index and Percentage of infected plants on Me-gene resistance rootstocks,
and susceptible cv Sonar 8 weeks after the inoculation of 1,000 eggs per plant.
M. incognita, MI-CH
Plant material
M. incognita, MI-E
Nodulation
index
% infected
plants
Nodulation
index
% infected
plants
C19
5,2c
100,0c
0,0a
0,0a
Atlante
6,3c
100,0c
0,0a
0,0a
DRO 3403
3,9b
100,0c
0,6a
38,9a
DRO 8801
0,3a
16,7b
0,0a
0,0a
RT12
0,0a
0,0a
0,0a
0,0a
Snooker
4,8b
83,3c
0,0a
0,0a
Tresor
6,6c
100,0c
0,0a
0,0a
WS-5050
5,2c
100,0c
5,2c
100,0b
WS-5051
6,0c
100,0c
4,4c
100,0b
Sonar
6,0c
100,0c
4,5b
100,0b
Means within a column followed by the same letter are not significantly different (P< 0,05)
according to ANOVA(Test LSD y= log10(x+1)).
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Molecular assays
The results of the identification of genes conferring resistance to M. incognita in
rootstocks are shown in Table 10.
SCAR marker B94 was associated with the presence of Me3 gene in one rootstock. With
SCAR marker CD a polymorphism was found by modifying the conditions of the
programreported by Djian- Caporalino et al. (2007) (Table 1). The agarose gel showed 2
resistant rootstocks that carry Me7 and/or Me1 and 6 susceptible rootstocks, besides the
susceptible variety (Table 10). With the F4R4 CAPS marker and under the same conditions
used by Djian-Caporalinoet al. (2007), the agarose gel showed 5 resistantand 3
susceptiblerootstocks, besides the control variety (Table 10).
Table 10. Presence of bands of sensitivity or resistance of each rootstocks
for each marker and candidate genes.
Plant material
SCAR B94
SCAR CD
CAPS F4R4
Genes
Atlante
S
S
R
Me7
C19
R
S
R
Me3 y Me7
DRO 3403
S
S
S
DRO 8801
S
R
R
Me1 y/o Me7
RT12
S
R
S
Me1
Snooker
S
R
R
Me1 y/o Me7
Tresor
S
S
R
Me 7
WS-5050
S
S
S
None of the genes
WS-5051
S
S
S
None of the genes
Sonar
S
S
S
None of the genes
None of the genes
According to resistance or susceptibility bands of SCAR marker B94, one rootstockdid not
shows the 220 bp band so they carry gene Me3, (C19,), 2 rootstocks and susceptible variety
do not possess any genes, 3 rootstocks carry the gene Me 7 (Atlante, Tresor and C19), 2 other
rootstocks that showed bands of resistance to the two markers, possibly are carriers of genes
Me1 and Me7 (DRO 8801, Snooker,) and one rootstockcarries gene Me1 (RT12) (Table 10).
In field trials in the first campaign C19, DRO 8801 and Snooker showed a nodulation
index less than Atlante (Table 2), but these differences did not remain the same for C19
and Snooker when inoculating with the virulent population under controlled conditions
(Table 9), nor when Snooker was grown for a second consecutive year in greenhouse Ch
(Table 3). This indicates that resistance to M. incognita is conferred by major genes
carried by Atlante, which is confirmed by molecular analysis (Table 10). It was shown
that in some cases there were populations of M. incognita that overcome the resistance
conferred by gene Me3 (Castagnone-Sereno et al., 1992, 1994) and by gene Me7 (DjianCaporalino, 2009). In contrast, DRO 8801 showed a similar response in the field as in
inoculations under controlled conditions, showing resistance to populations that are
virulent on theAtlante rootstock, probably because it is carrying another resistance gene
(Me1), as detected by molecular determinations (Table 10).
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In the trials of the second campaign, RT12 was resistant to the virulent population of
greenhouse Ch (Table 3) and also under controlled conditions (Table 9.), probably due to
it carrying the Me1 gene (Table 10), like DRO 8801.
Tresor and DRO 3403 had good response to avirulent populations of greenhouse K in the
first year (Table 2), but not against the virulent one in greenhouse Ch. When DRO 3403
was grown again in greenhouse K in the second year, the infestation and nodulation index
increased (Table 3) as it was shown to be slightly susceptible to inoculations made under
controlled conditions with the MI-E population (avirulent), probably because it carries
the gene Me7 of which it is known that it is overcome by other populations of Meloidogyne
incognita (Djian- Caporalino, 2009) (Tabla 10). WS-5050 and WS-5051 rootstocks were
susceptible to the virulent and avirulent populations (Table 3), Both rootstocks had a
similar behaviour in inoculations carried out in the laboratory conditions than under field
conditions for each population (virulent and avirulent) which it was confirmed with
molecular tests since none of the genes was detected (Tabla 10).
Infestation by M. incognita did not have much impact on production in both greenhouses
(Tables 4 to 8), since the crop productions occurred late in the year, with a growing
season that begins in winter, when soil temperatures stay below 15 º C until the middle
of April.
This research is being continued with the aim to evaluate in the field the stability of the
resistance conferred by the gene Me1, by repeatedly growing resistant rootstocks that
carry this gene in soil infested by populations of M. incognita that overcome the
resistance conferred by genes Me3 and Me7.
Acknowledgments
This research has been supported by funding of FEDER through the projects RTA20050209 and INIA RTA2009-0058, in collaboration with the Partnership Program of Agricultural
Cooperatives Federation of Murcia and the Ministry of Agriculture and Water. Murcia. Our
thanks to Caroline Dijan-Caporalino formonitoring the molecular analyses, to seed
companies for providing seeds, to the nursery El Mirador for the production of the grafts
and to Jerome Torres Corcuera for technical assistance and to Wim Deleu for reviewing
the written English.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
CM334 rootstock improves the resistance of grafted chili pepper to
root necrosis and plant wilting caused by Phytophthora nicotianae
M. Saadoun, M.B. Allagui
Institut National de la Recherche Agronomique de Tunisie (INRAT), rue Hédi Karray, 2080 Ariana, Tunisia.
Contact: [email protected]
Abstract
Root rot necrosis and plant wilting caused by Phytophthora nicotianae is still a severe
disease of chilli pepper in open field and under plastic house in Tunisia. Chilli pepper
grafting is recalling an increasing interest in the last years. Our work was at first devoted
to adapt the tube grafting technique to hot peppers, so that it enabled us to produce a high
number of well developed grafted plants. With this technique, different successful
combinations of scion/rootstock were made using CM334 and the local chili peppers Beldi
or Baker. The landrace CM 334 is strongly resistant to P. nicotianae, while the varieties Beldi
and Baker are susceptible to the disease. Plant inoculation was performed with zoospore
suspension deposited on plant crown. Root necroses were observed 30 days post-inoculation
using a scale ranging from 0 (healthy plant) to 5 (dead plant). When CM334 is the rootstock
and Beldi or Baker the scion, the root necrosis intensity was very weak (0.1-0.2) so the
grafted plants were healthy. However, when Baker or Beldi are rootstocks and CM334 is the
scion the root necrosis intensity was high (3.1-4.6) leading to a high number of plant
mortality by wilting. Such high root necrosis intensity was similar to that observed on nongrafted plants of Baker and Beldi inoculated by the same pathogen. Since plant foliage is
not attacked by this pathogen, the results show that susceptible chili pepper grafted onto
CM334 is a hopeful method to improve pepper yields by taking all the advantages of the
resistance of CM334 to P. nicotianae root rot.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Aggressiveness and genetic diversity of Phytophthora capsici
isolates infecting pepper
P. Sánchez-Torres1, C. Gisbert2, F. Nuez2
1
Centro de Protección Vegetal y Biotecnología, Instituto Valenciano de Investigaciones Agrarias (IVIA),
Apartado Oficial, 46113-Moncada, Valencia.
2
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana. Universidad Politécnica de Valencia
Camino de Vera 14, 46022 Valencia Spain. Contact: [email protected]
Abstract
Phytophthora capsici is now one of the most serious threats facing pepper (Capsicum
annuum) plant production. Despite breeding efforts, currently, commercial cultivars with
resistance to this pathogen are unavailable. Probably both, the polygenic nature of resistance
and pathogen diversity have limited it. In this work, characterization of different P. capsici
isolates from various geographical origins was performed. Molecular variability and
differences in aggressivenes were observed. Random amplified polymorphic DNA (RAPD)
markers as well as microsatellites analyses were employed to assess genetic variation among
P. capsici isolates. Although no association was observed between RAPD and microsatellites
patterns and aggressivenes, a perfect correlation was found between RAPD profiles or
microsatellite pattern and geographic origin. Within all P. capsici strains evaluated, isolates
Pc 122, Pc129, Pc130 and Pc450 displayed the highest virulence. This information could be
useful for pathogen detection and provides an important tool for pathogen identification. P.
capsici isolates with higher virulence could be useful for germplasm resistance evaluation.
Keywords: Capsicum annuum, Phythopthora capsici, agressiveness, rDNA, Microsatellites.
Introduction
The oomycete Phytophthora capsici (Leon) has become one of the most serious threats
to production of pepper and constitute a limiting factor to profitable production of many
crops worldwide (Thabuis et al., 2003). In Spain, it is potentially the most destructive
disease of this crop (Silvar et al., 2006).The pathogen also causes severe crop losses in
cucurbits, eggplant, and tomato (Islam et al., 2004).
P. capsici can strike pepper plants at any stage of growth and spread quickly. Chemical
fungicides used to manage P. capsici are often ineffective (Silvar et al., 2006) and
biological control has also been unsuccessful (Miller et al., 2002). Nowadays, no single
method is currently available to provide adequate control.
Genotypes that exhibit resistance to Phytophthora crown rot have been used in breeding
programs but to date, no pepper P. capsici resistant cultivars have been commercially
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released. Probably both, the polygenic nature of P. capsici (Pochard et al., 1983: Thabuis
et al., 2003) and pathogen diversity (Silvar et al., 2006) have limited it.
In P. capsici the presence of pathotypes and physiological races have been reported (Oelke
and Bosland, 2003). Also, differences in virulence among the P. capsici isolates from pepper
and pumpkin have been observed (Lee et al., 2001) and the relative virulence of isolates
of P. capsici from cucumber and squash on pepper was also evaluated (Ristaino, 1990).
Although virulence testing provides valuable information regarding to strain characterization,
the recent development of genetic markers based on polymerase chain reaction (PCR)
such as random polymorphic DNA (RAPD) (Williams et al., 1990) or microsatellites (SSR)
(Lees et al., 2006) offers markers to conduct population genetic analyses.
The objective of this study was to investigate phenotypic and genetic diversity of six
different P. capsici isolates from pepper. Characterization was carriend out based on
agressivenes on two different pepper lines using different P. capsici isolates under
controlled environmental conditions. Genetic analysis was performed using rDNA,
random amplified polymorphic DNA (RAPD) and microsatellites methods.
Material and methods
Plant material
Genotypes ‘SCM 334’ (PI636424) and ‘Charleston Hot’ (PI640825) from (UDSA-Plant
Genetic Resources Conservation Unit, U.S.A.) were use for aggressivenes assesment
P. capsici isolates
Six P. capsici isolates from different geographical origin were used in this study and are listed
in Table 1. All isolates were maintained on potato dextrose agar (PDA) for further use.
Table 1. P. capsici isolates used in this study.
Isolate
Origin
MATING TYPE
Pc448
France
A1
Pc450
France
A1
Pc122
Almería (Spain)
A1
Pc123
Almería (Spain)
A1
Pc129
País Vasco (Spain)
A1
Pc130
País Vasco (Spain)
A1
Agressivenes assesment
Suspensions of zoospores from different P. capsici isolates were obtained according to Larkin
et al. (1995). P. capsici isolates were grown in V8 agar at 24ºC for 7 days to obtain zoospores.
V8 agar cultures were then cut into small pieces and incubated with SDW at 24 ºC for 72 h.
Zoospore release was induced by chilling cultures at 5ºC for 1h and then incubating at 24ºC
for 2 h. Zoospore suspensions were filtered through a gauze to remove hyphal and sporangial
debris. Zoospore concentration was counted using a haemocytometer.
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Seeds were sown in multipots filled with commercial peat:perlite (2:1, v:v) mixture.
Plants were maintained on benches in a greenhouse at 22–26°C until inoculation. Relative
humidity in the greenhouse ranged from 60% to 90%.
Inoculation was performed by irrigation of seedling with 5 ml of a solution containing 106
or 107 zoospores ml-1 (z.ml-1) of each of six isolates and seedlings treated with soil drench
(mock inoculated) were used as control. Ten seedlings per treatment were inoculated.
This assay was conducted twice. Plants affected by P. capsici were visually assessed. A
plant was considered dead when it looked irreversibly wilted.
Molecular characterization
Fungal DNA isolation was performed as previouly described by Raeder and Broda (1985), with
some modifications, using fresh mycelia after growing on PDA plates for 7 days at 24ºC.
PCR amplification of ribosomal ITS region was performed with the primers ITS1 and ITS4
(White et al., 1990). PCR reactions were performed in a total volume of 50 μl containing
1 μl (20 to 60 ng) of template DNA; 1 μM each primer; 200 μM each dNTP; 1.25 U of Taq
DNA polymerase (Invitrogen),MD); Cycling parameters were 94°C for 5 min followed by
30 cycles of 94°C for 30 s, 52°C for 45 s, and 72°C for 1 min with final extension of 72°C
for 10 min. Amplification products were analyzed by electrophoresis through 1.0%
agarose in TAE buffer.
PCR products were purified using the Ultra Clean TM PCR Clean-up (MoBio, Lan Inc.,
California) and then sequenced using primers ITS1, ITS4. DNA sequencing was performed
using the fluorescent chain-terminating dideoxynucleotides method (Prober et al., 1987)
and an ABI 377 sequencer (Applied Biosystems, Madrid, Spain). DNA sequences were
compared with those from the EMBL database with the Washington University-Basic
Local Alignment Search Tool (WU-BLAST) algorithm (Altschul and Gish 1996).
RAPD fingerprinting
To determine genetic similarity among P. capsici isolates, RAPD fragments were generated
for all isolates. RAPD was performed using fungal genomic DNA as template. Three
different primers Pari1, Pnor1, Pomt1 (Geisen et al., 2001) were used on PCR reactions
done in a total volume of 50 μl containing 1 μl (20 to 60 ng) of template DNA; 1 μM each
primer; 200 μM each dNTP; 1.25 U of Taq DNA polymerase (Invitrogen, MD); Cycling
parameters were 94°C for 5 min followed by 30 cycles of 94°C for 30 s, 48°C for 45 s,
and 72°C for 1 min and final extension of 72°C for 10 min Amplification products were
analyzed by electrophoresis through 2% agarose in TAE buffer. RAPD reproducibility was
confirmed by repeating the reactions at least three times for each isolate.
Microsatellites
Microsatellites were performed using (AAG)6, (CAG)5 and (GTC)5 primers and diluted
fungal genomic DNA as template following 30 cycles of 94°C for 30 s, 48°C for 45 s, and
72°C for 1 min and final extension of 72°C for 10 min. Amplification products were
analyzed by electrophoresis through 3% agarose in TAE buffer.
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Results and discussion
P. capsici aggressiveness assay
P. capsici is the most destructive pathogens affecting pepper. In Spain it is considered as
a major limiting factor in pepper production (Thabuis et al., 2003; Silvar et al., 2006).
In this work, aggressiveness level of six P. capsici Spanish isolates was compared, Pc122
and Pc123 from the south of Spain, Pc129 and Pc130 from the north of Spain and Pc448
and Pc450 from France. The six different P. capsici isolates were evaluated in two pepper
genotypes SCM 334’ (PI636424) and ‘Charleston Hot’ (PI640825) that differed in their
degree of susceptibility to the pathogen.
First symptoms appeared after 5 to 10 days post-inoculation (dpi) only in the susceptible
genotype Charleston Hot and there was no correlation between the aggressiveness and
zoospores concentration in inoculation Charleston Hot plants resulted wilted at 70 dpi
by only five P. capsici isolates: Pc122, Pc123, Pc129, Pc130, and Pc450. (Figure 1).
SCM334 plants were found to be tolerant to all isolates although symptomps on the stem
decay were observed.
Figure1. Percentage of symptomatic Charleston Hot seedlings at 10 and 70 dpi with 5 ml
of either 106 (white bars) or 107 (dark bars) z.ml-1 of six different P. capsici strains.
Error bars show the standard errors of the mean of two independent experiments.
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All data indicate that Pc122, Pc129, Pc130, and Pc450 isolates are more aggressive than
Pc123 and Pc448 under our experimental conditions. The most virulent isolate from
those assayed was Pc450 since exhibited 100% of wilted plants in 10 dpi although the rest
Pc122, Pc129 and Pc130 reached 100% of wilted plants at 70 dpi (Figure 1). P. capsici
isolates with higher virulence could be useful for germplasm resistance evaluation.
No correlation was found between the P. capsici origin and aggressiveness since strains
of each origin were able to produce 100% of wilted plants.
Molecular characterization of P. capsici isolates
Molecular characterization was performed in order to find any marker that allows
distinguishing genetic diversity of the six studied P. capsici isolates. ITS region comprising
ITS1, 5,8S and ITS2 was amplified by PCR and then analyzed by sequencing. rDNA was
analyzed but no differences were found. Therefore, RAPD and microsatellites were used
for genetic variation studies.
Figure 2. Electrophoretic separation of polymerase chain reaction amplicons of 6 P. capsici
strains obtained using A: the microsatellite primer (GTC)5 and B: RAPD primers Pari1.
M: Correspond to 1Kb Plus ladder of Invitrogen.
Microsatellites (SSR) were carried out using three different primers that were screened
for their ability to produce polymorphic bands within P. capsici isolates. Microsatellites
(SSR) were carried out in three independent amplifications from which only (GTC)5
primer was efficient in checking for genetic differences in all independent amplifications.
This technique enabled to differentiate P. capsici isolates from pepper, which encompass
three characteristic profiles (Fig. 2). The three profiles found corresponded to different
geographical sources. Isolates from the north of Spain Pc129 and Pc130 displayed a
pattern; isolates from the south of Spain showed another profile and those from France,
Pc448 and Pc450, showed another. Nevertheless, genotype differentiation was not
related to aggressivenss level of each P. capsici isolate.
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RAPDs fingerprinting were performed with three different primers, from which only
Pari1 was suitable for further investigation. The remained primers rendered no bands or
poor patterns.
The RAPD markers confirmed the clear assignation of isolate geographical origin (Figure
2). The genotype differentiation was not related to phenotypic characters such as
agressiveness or mating type.
Despite the absence of correlations between RAPD and microsatellites analysis and
virulence, both techniques have provided useful information about genetic variability
and perfect correlation was found between RAPD profiles or microsatellite pattern and
geographic origin. This information could be useful for pathogen detection and provides
an important tool for pathogen identification.
Acknowledgements
This research has been financed by AGROALIMED Foundation (Comunidad Valenciana). P.
Sánchez-Torres is a recipient of INIA contract from Spanish Ministry of Science and Inno­
vation. The authors acknowledge Dr. Merino, Dr. Díaz and Dr. Julio C. Tello for providing
P. capsici isolates and UDSA-Plant Genetic Resources Conservation Unit for providing
pepper genotypes.
References
Altschul, S.F.; Gish, W. 1996. Local alignment statistics. Methods in Enzymology 266:460480.
Geisen, R.; Cantor, M.D.; Hansen, T.K.; Holzapfel, W.H.; Kaobsen, M. 2001. Characterization
of Penicillium roquefortii strains used as cheese starters cultures by RAPD typing.
International Journal of Food and Microbiology 65:183-191.
Islam, S.Z.; Banadoost, M.; Lambert, K.N.; Ndeme, A. 2004. Characterization of Phytophthora
capsici isolates from processing Pumpkin in Illinois. Plant Disease 89:191-197.
Larkin, R.P.; Ristaino, J.B.; Campbell, C.L. 1995. Detection and quantification of
Phythophtora capsici in soil. Phytopathology 85:1057-1063.
Lees, A.K.; Wattier, R.; Shaw, D.S.; Sullivan, L.; Wiiliams, N.A.; Cookie, D.E. 2006.Novel
microsatellite markers for the analysis of Phytophthora infestans populations. Plant
Pathology 55:311-319.
Lee, B.K.; Kim, B.S.; Chang, S.W.; Hwang, B.K. 2001. Aggressiveness to pumpkin cultivars of
isolates of Phytophthora capsici from pumpkin and pepper. Plant Disease 85:497-500.
Miller, S.A.; Miller, M.L.; Ivey, L.; Mera, J. 2002. Responses of pepper cultivars and expe­
rimental breeding lines to Phytophthora blight. Biol. Cultural Test Control Plant Dis.
Rpt. 17: V16. Online publication DOI: 1094/BC17. American Phytopathological Society,
St. Paul, MN.
Oelke, L.M.; Bosland, P.W.; Steiner, R. 2003. Differentiation of race specific resistance to
Phytophthora root rot and foliar blight in Capsicum annuum. Journal of the American
Society of Horticultural Science 128:213–218.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Pochard, E.; Molot, P.M.; Dominguez, G. 1983. Etude de deux nouvelles sources of ré­
sistance à Phytophthora capsici Leon. Chez le piment: confirmation de l’existence
de trois composantes distinctes dans la résistance. Agronomie 3:333-342.
Prober, J.M.; Trainor, G.L., Dam, R.J.; Hobbs, F.W.; Robertson, C.W.;Zagursky, R.J.;
Cocuzza, A.J.; Jensen, M.A.; Baumeister, K. 1987. A system for rapid DNA sequencing
with fluorescent chainterminating dideoxynucleotides. Science 238:336-341.
Raeder, U.; Broda, P. 1985. Rapid preparation of DNA filamentous fungi. Letters in Applied
Microbiology 1:17-20.
Ristaino, J.B. 1990. Intraspecific variation among isolates of Phytophthora capsici from
pepper and cucurbit fields in North Carolina. Phytopathology 80:1253-1259.
Silvar, C.; Merino, F.; Díaz, J. 2006. Diversity of Phytophthora capsici in North-West Spain:
analysis of virulence, metalaxyl response and molecular characterization. Plant
Disease 9:1135-1142.
Thabuis, A.; Palloix, A.; Pflieger, S.; Daubèze, A.M.; Caranta, C.; Lefebvre, V. 2003. Com­
parative mapping of Phythophtora resistance loci in pepper germplasm: evidence
for conserved resistance loci across Solanaceae and for a large genetic diversity.
Theoretical and Applied Genetics 106:1473-1485.
White, T.J.; Bruns, T.; Lee, S.; Taylor, J. 1990. Amplification and direct sequencing of
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Williams, J.G.; Kubelik, A.R.; Livak, K.J.; Rafalski, J.A.; Tingey, S.V. 1990. DNA polymor­
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
New resistant source to viruses, particularly Tomato leaf curl
Joydebpur virus, infecting chilli in India and its utilization
in hybrid development
D. Singh, R.K. Dhall
Department of Vegetable Crops, Punjab Agricultural University, Ludhiana-141004, Punjab, India. Contact:
[email protected], [email protected]
Abstract
Chilli is one of the most important vegetable crop in India and more recently a new disease
“Tomato Leaf Curl Joydebpur Virus” is reported first time by Shih et al., (2007). Earlier
Senanayake et al. (2006) reported begomovirus from Punjab. The work is in continuation
with the work of Briddon et al., (2002), Maruthi et al., (2006) and Shih et al., (2003). The
new resistant source from a land variety “Bengali selection” from U.P. state of India is
reported under field conditions which will be utilized for hybrid seed production. In India
only one genetic male sterile line i.e. MS-12 was developed at Punjab Agricultural University,
Ludhiana and being utilized by public and private sector for hybrid seed production. Since
the parental lines in hybrid seed production programme of chilli are becoming highly
susceptible to tomato leaf curl Jodebpur virus, resulting in mild yellowing, severe leaf
curling, leaf distortion, stunting and blistering symptoms. The fruiting span is decreased by
one month not only in Punjab state but also in India. The chilli breeding strategies will be
discussed in context to transfer of resistance against Tomato leaf curl Joydebpur virus to
male sterile line and male parents for hybrid seed production in chilli.
Keywords: male sterility, resistance, yield, virus score.
Introduction
Hot Pepper (Capsicum annuum L.) commonly known as chilli in India is grown throughout
the world as an important vegetable and condiment crop. In India it is believed to be
through the Portuguese in the 16th century. India is one of the leading countries in the
world with respect to chilli growing area (0.95 million ha) and production (0.82 million
tonnes of dry chilli). During 1998-99, India exported chilli near about 55,750 tonnes with
value of Rs. 2101.3 million (Peter, 1999). In India in public sector institutes only Punjab
Agricultural University has developed male sterile line (MS-12) by transferring sterility
gene from France (ms-509) into the multiple disease resistant cultivar “Punjab Lal”
through backcrossing (Singh and Kaur, 1986). The private sector is using this male sterile
line throughout India, however by using this male sterile (MS-12) line, Punjab Agricultural
University has released two chilli hybrids viz. CH-1 and CH-3.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Main breeding objectives particularly in heterosis breeding in India are yield, fruit
length, fruit weight, fruit quality and resistant to pests and diseases (Hundal and
Khurana, 1993; Hundal and Khurana, 2001; Gopalakrishnan et al., 1987; Thomas and
Peter, 1988). In India, CH-1 hybrid of chilli is one of the most popular particularly in
Northern India because of CMV and leaf curl virus resistant and agro-climatic adaptation.
The hybrid was developed in 1992 at PAU and still under cultivation. Hundreds of hybrids
have been developed but this hybrid is still in great demand only because of its high
degree of resistance to viruses.
Material and methods
Evaluation of elite material
The elite material (44) along with two resistant and one susceptible check were grown
under north Indian agro climatic conditions in rainy season. The Tomato Leaf Curl
Joydebpur Virus is very serious under natural epiphytotic conditions because of high
vector population and favourable environmental conditions. One local indigenous
collection (Lorai) and two introductions (Perennial and VR-16) were kept as a resistant
check and one susceptible check (Punjab Surkh).These checks were grown along with 44
elite genotypes in completely randomized block design. The row to row and plant to
plant distance was kept at 75 cm and 30 cm respectively. There were eight plants on
which the data was recorded in each replication and there were three replications.
Observations recorded under open field conditions
Yield was recorded per plant and expresses as kg m-2. The vector was sufficient in nature
to transmit virus during rainy season. When there was 100% incidence on susceptible
check, scoring for Tomato Leaf Curl Joydebpur Virus was done based on 0-4 scale (0=010%, 1=10-25%, 2=25-50%, 3=50-75%, 4=75-100%). Plant height and fruit length were
measured in centimeter.
Results and discussion
The resistant checks (VR-16 and Perennial) differ significantly from elite material
particularly for reaction to Tomato Leaf Curl Joydebpur Virus incidence and susceptible
check (Punjab surkh). The genotype “Lorai” was found to be tolerant to Tomato Leaf
Curl Joydebpur Virus. On all the elite material, the incidence of Tomato Leaf Curl
Joydebpur Virus ranged from 25-100 per cent.
Horticultural Traits
The selections 1, 13,14, 35 and 36 recorded high yield ranging from 3.6 – 3.8 kg m-2
(Table 1).However, the resistance scores in these selections ranged from 2-3. The fruit
length of Selections 2, 21, 29 and 35 were high ranged from 7.2-7.5 cm. The plant height
was lowest on selection-10 and VR-16 whereas highest in selection-17 (Table 1).
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Table 1. Yield, plant height, fruit length and incidene of Tomato Leaf Curl Joydebpur Virus.
Genotype
Origin
Selection-1
Selection-2
Selection-3
Selection-4
Selection-5
Selection-6
Selection-7
Selection-8
Selection-9
Selection-10
Selection-11
Selection-12
Selection-13
Selection-14
Selection-15
Selection-16
Selection-17
Selection-18
Selection-19
Selection-20
Selection-21
Selection-22
Selection-23
Selection-24
Selection-25
Selection-26
Selection-27
Selection-28
Selection-29
Selection-30
Selection-31
Selection-32
Selection-33
Selection-34
Selection-35
Selection-36
Selection-37
Selection-38
VR-16
Perennial
Lorai
Punjab Surkh
CD (0.05)
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
India
USA
India
India
India
Yield
(Kg m-2)
3.8
2.8
1.9
2.7
2.8
2.7
2.7
1.9
2.8
2.8
4.5
2.7
3.6
3.6
2.8
1.9
1.9
2.8
2.8
2.7
2.7
1.9
2.7
2.7
2.7
2.8
2.7
2.8
1.9
2.8
2.7
2.7
2.7
2.8
3.6
3.6
2.7
2.8
2.0
2.9
3.3
2.2
0.6
Plant height
(cm)
95
83
83
75
88
79
82
72
82
70
87
72
72
73
77
72
122
71
97
94
80
99
104
110
81
96
79
75
75
78
96
98
93
97
97
94
90
86
70
78
95
78
7.5
Fruit length
(cm)
6.4
7.3
4.7
6.7
5.5
4.5
4.4
6.2
5.5
3.6
6.3
2.9
5.2
4.2
4.6
5.4
6.2
6.8
6.1
6.0
4.7
7.5
6.8
5.3
5.3
4.7
2.1
5.0
7.4
8.0
7.4
6.0
6.9
2.0
7.2
6.1
6.9
4.7
2.5
2.7
3.1
6.0
1.4
Virus score
(0-4 scale)
2
3
3
2
2
4
4
4
3
3
2
4
3
3
3
2
3
4
2
2
2
3
3
3
3
4
4
4
3
2
3
3
3
1
3
2
3
4
0
0
1
4
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Tomato leaf curl Joydebpur virus
All the elite material were found to be susceptible (Score 2-4) except Selection-34 (Score
1). The Lorai and indigenous collections were found to be having less score comparable
to the Selection-34. Out of all the material evaluated, VR-16 and Perennial were found
to be resistant to tomato leaf curl Joydebpur virus (Table 1).
Conclusion
More recently in during 2002-2004 in chilli fields of PAU Ludhiana symptoms of mild
yellowing, severe leaf curling, leaf distortion, stunting and blistering symptoms were
observed. The samples were sent to AVRDC, Taiwan and Shih et al., (2006) extracted DNA
from three such symptomatic plants and tested for the presence of begomoviral DNA-A,
DNA-B and associated satellite DNA by polymerize chain reaction (PCR) using previously
described primer pairs (Shih et al., 2003).The selections which were high yielder viz.
selections 1, 13,14, 35, 36 need to be improve for resistance by transferring resistance
genes from VR-16 and Perennial so that productivity is enhanced. Male sterile line(MS12) also need to be improved for Tomato leaf curl Joydebpur virus resitance by using
backcross method with VR-16 so that heterosis breeding is strengthen in India.
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Hundal, J.S.; Khurana, D.S. 2001. A new hybrid of chilli ‘CH-3’- Suitable for processing.
Journal ofResearch Punjab Agricultural University 39:326.
Maruthi, M.N.; Rekha, A.R.; Alam, S.N.; Kader, K.A.; Cork, A.; Colvin, J. 2006. A novel be­
go­­movirus with distinct genomic and phenotypic features infests tomato in
Bangladesh. Plant Pathology 55:290.
Peter, K.V. 1999. Spice res. development. An updated overview. Agro India August:16-18.
Senanayake, D.M.J.B.; Mandal, B.; Lodha, S.; Verma, A. 2006. First report of Chilli leaf
curl virus affecting chilli in India. (First published online: New Disease Reports 13,
http://bspp.org.uk/ndr/july2006/2006-35.asp
Shih, S.L.; Tsai W.S.; Green, S.K.; Khalid, S.; Ahmad, I.; Rezaian, M.A. 2003. Molecular cha­
ract. of tomato and chilli leaf cyrl begomovirus from Pakistan. Plant Disease 87:200.
Shih, S.L.; Tsai, W.S.; Green, S.K.; Singh, D. 2006. First report of Tomato leaf curl Joydepur
virus infecting chilli in India. Plant Pathology 56:343.
Singh, J.; Kaur, S. 1986. Present status of hot pepper breeding of for multiple disease
resistance in Punjab. Proceeding of VI EUCARPIA Meeting on Genetic and Breeding
on Capsicum and Eggplant, Zaragoza (Spain), p 111-114.
Thomas, P.; Peter, K.V. 1988. Heterosis in intervarital crosses of bellpepper (Capsicum
annuum var. grossum) and hot chillies bellpepper (Capsicum annuum var. fasciculatum).
Indian Journal of Agricultural Sciences 58:747-750.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Viruses on Capsicum plants in the Czech Republic - challenge to
resistance breeders
J. Svoboda
Crop Research Institute, Drnovská 507, 16106 Prague 6, Czech Republic.
Contact: [email protected]
Abstract
In the years 2006-2009 a survey of viruses on capsicum plants in the Czech Republic was
carried out. Altogether, two hundred and sixty-nine leaf samples with symptoms of viral
infection were collected both from open fields and greenhouses. These samples were
examined for the presence of Alfalfa mosaic virus (AMV), Broad bean wilt virus-1 (BBWV-1),
Cucumber mosaic virus (CMV), Pepper mild mottle virus (PMMoV), Potato virus Y (PVY),
Tobacco mosaic virus (TMV) and Tomato spotted wilt virus (TSWV) by ELISA. Positive results
were obtained only for AMV, BBWV, CMV and PVY. The most prevalent viruses were CMV and
PVY which were present in 23 % and 36 % of tested samples respectively. In some cases a
complex infection of two viruses was detected. The symptoms on infected plants were
mosaic, yellowing and stunting which led to a decreased yield and lesser fruit quality. All of
the found viruses are easy transmissible by aphids, thus the protection against them in open
fields is difficult. Only resistant cultivars can solve the problem.
Keywords: pepper, viral infection, AMV, BBWV, CMV, PVY, ELISA, resistance, Czech Republic.
Introduction
Peppers (Capsicum annuum) belong to an important sort of vegetables. Many diseases
can decrease their yield and fruit quality. Among them, viral infections have a high
importance, because they cannot be cured. The only way of protection is breeding for
resistance.
Some pepper viruses occur throughout Europe. Marchoux et al. (2000) reported that five
viruses are common on peppers in France: Cucumber mosaic virus (CMV), Pepper mild
mottle virus (PMMoV), Potato Y virus (PVY), Tobacco mosaic virus (TMV) and Tomato
spotted wilt virus (TSWV). Some of them are frequent in Sicily, Italy. Three viruses were
found infecting peppers: Broad bean wilt virus 1 (BBWV-1), CMV and PVY, which resulted
in heavy yield losses (Davino et al., 1989). The highest loss of pepper production, nearly
100 %, was caused by Broad bean wilt virus 1 (BBWV-1) in Slovenia (Mehle et al., 2008).
In tobacco, pepper and tomato plantations, TSWV significantly reduced yields in Hungary
(Jenser et al., 1996). The most devastating are early infections. Avilla et al. (1997)
informed that CMV and PVY drastically decreased fruit weight per plant up to 70 % and
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80 % respectively when they had been inoculated on the bell pepper ‘Yolo Wonder’
plants as early as one week after transplanting to the field.
Peppers are grown on nearly 300 hectares in the Czech Republic with a yearly production
of about 15,000 tonne (Smotlacha, 2010). The aim of the presented work is to show the
most frequent viruses on capsicum plants in the Czech Republic against which the
resistant cultivars would be bred.
Material and methods
Plant material
Both field and greenhouse pepper plants of various cultivars were inspected for the
presence of viral symptoms. Leaves showing yellow mosaic or pitting, discoloration,
yellowing or stunting were collected and potential viruses were identified by ELISA
afterwards. Samples were taken both from the main capsicum producing areas in
southern Moravia and marginal growing areas in Bohemia and northern Moravia.
ELISA
The Double-antibody sandwich ELISA (DAS-ELISA), described by Clark and Adams (1977),
was used for the examination of leaf samples. Samples for ELISA were prepared by
grinding 0.2 g of leaf tissue in phosphate buffered saline, pH 7.4 with 2 %
polyvinylpyrrolidone and 0.2 % of bovine albumin, in ratio 1:20. AMV, BBWV-1, CMV,
PMMoV, PVY, TMV and TSWV specific polyclonal antibodies were used according to the
manufacture’s manual (Loewe Biochemica, Sauerlach, Germany). Positive and negative
controls were included on each ELISA microtiter plate to improve the validity of the
tests. Plates were incubated for one hour at 20 °C after pipetting the substrate solution,
and the absorbance value was read at 405 nm using the MR 5000 Dynatech reader. A
reaction was considered positive when the absorbance value was at least five times
higher than that for the health control; the absorbance value of the positive control
(Loewe) was above 1.6 and the absorbance value of the negative control (leaves taken
from healthy pepper plants) was at most 0.02.
Electron microscope
Leaf samples with symptoms of viral infection were ground in a mortar with a 0.01 M
HEPES buffer, pH 8.2 , in ratio 1:2. The homogenate was filtered through a silon sieve
and negatively stained by phosphotungstenic acid, pH 6.9, in ratio 1:1. Then the mixture
was used for the preparation of an electron microscope mount. Electron microscope
grids were observed by means of the Philips 2085 transmission microscope.
Results and discussion
In the last four years a survey of selected viruses on peppers planted in the Czech
Republic was carried out. Altogether, two hundred and sixty-nine leaf samples were
examined by ELISA. Positive findings were confirmed by observation in electron
microscopy. It was found that the most prevalent viruses were PVY and CMV followed by
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BBWV-1 and AMV. PVY was the most frequent virus on peppers with an average occurrence
of 36 % and AMV was the least common virus with an incidence of 6 %. No other virus was
found. In some samples a complex infection of two viruses was discovered. PVY and CMV
were found both in Moravia and Bohemia whilst BBWV-1 and AMV were detected only in
southern Moravia. CMV was the sole virus detected also in marginal areas in northern
Moravia (Tab. 1).
The occurrence of the found viruses was similar in all of the four monitored years with
a decrease in 2009. The highest presence of 70% and 37% of PVY and CMV in tested
samples respectively was detected in the year 2008 (Tab. 2).
Table 1. Incidence of viruses on capsicum plants in the Czech Republic.
Virus
Positive samples /
tested
Infection
rate (%)
Origin of infected samples
AMV
13 / 218
6
Břeclav, Prostějov, Znojmo
BBWV-1
17 / 190
9
Břeclav, Uherské Hradiště, Zlín, Znojmo
CMV
63 / 269
23
Břeclav, Litoměřice, Česká Lípa, Karviná,
Praha-východ, Prostějov, Uherské Hradiště,
Znojmo
PVY
98 / 269
36
Břeclav, Česká Lípa, Praha-východ, Prostějov,
Znojmo
Table 2. Comparison of the incidence of viruses on capsicum plants in four
subsequent years in the Czech Republic.
Virus
AMV
No. positive samples / tested in years
2006
2007
2008
2009
NT *)
3 / 62
2 / 77
8 / 79
BBWV-1
2 / 51
2 / 62
13 / 77
NT
CMV
10 / 51
18 / 62
29 / 77
6 / 79
PVY
2 / 51
28 / 62
54 / 77
14 / 79
* Not tested
All of the found viruses are easy transmissible by aphids in a non-persistent manner
(Plant Viruses Online, 2010). In practice it means that viruses are transmitted rapidly in
several minutes without any long-time acquisition and inoculation feeding. The great
difference in virus frequency in the last two years (2008 and 2009) could be closely
related to the different development of aphids. The total amount of aphids monitored
by the State Phytosanitary Administration of the Czech Republic was only 74% in 2008
compared to the year 2009. The maximum of the aphid population was recorded in the
middle of June in 2008 in contrast to the second half of September in 2009 (Aphid
Bulletin, 2010). Consequently the virus spreading by aphids in 2009 started later and
then could not be as effective as in 2008.
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Protection of pepper plants grown in open fields focused against aphids by insecticide
spraying may not be functional, because aphids can successfully transmit viruses by a
short quick test feeding before they are killed. The only efficient method of protection
seems to be using resistant pepper cultivars. Mazourek et al. (2009) reported that
they had developed a new tabasco pepper (C. frutescens) ‘Peacework’ with CMV
resistance. Similarly Liang GengSheng, et al. (2005) reported a new chilli pepper
hybrid F1 ‘Tianjiao No. 4’, highly resistant to CMV. Concerning PVY, efficient resistance
to PVY (gene Pvr4) was identified in the wild hot pepper ‘Criollo de Morelos 334’
(Janzac et al., 2009). Another new PVY resistant jalapeno pepper is ‘TAM Dulcito’
(Crosby et al., 2007).
The resistance genes are often connected with chilli peppers. Only some cultivars possess
complex resistance to CMV and PVY concurrently. For example ‘Cecil F1’ displays extreme
resistance to both viruses (Horvath et al., 2000). There however is very rare evidence
about a combined resistance against CMV and PVY in sweet peppers. This is the task for
capsicum breeders for the future.
Acknowledgements
This work was supported by the Project QH 71229 of the Ministry of Agriculture, the
Czech Republic.
References
Aphid Bulletin. 2010. [www dokument]. [cited 19.1.2010]. Available on:http://www.srs.
cz/portal/page/portal/SRS_Internet_CS/so/so_mon_so/so_mon_so_mo_msic_
aphid.
Avilla, C.; Collar, J.L.; Duque, M.; Fereres, A. 1997. Yield of bell pepper (Capsicum
annuum) inoculated with CMV and/or PVY at different time intervals. Zeitschrift fur
Pflanzenkrankheiten und Pflanzenschutz. 104: 1, 1-8.
Clark, M.F.; Adams, A.N. 1977. Characteristic of the microplate method of enzyme-linked
immunosorbent assay for the detection of plant virus. Journal of General Virology,
34: 475-483.
Crosby, K.M.; Jifon, J.L.; Villalon, B.; Leskovar, D.I. 2007. TAM Dulcito, a new, multiple
virus-resistant sweet jalapeno pepper. Horticultural Science. 42: 6, 1488-1489.
Davino, M.; Areddia, R.; Polizzi, G.; Grimaldi, V. 1989. Observations on pitting in pepper
fruit in Sicily. Difesa delle Piante. 12: 1-2, 65-73.
Horvath, J.; Kazinczi, G.; Takacs, A.; Pribek, D.; Bese, G.; Gaborjanyi, R.; Kadlicsko, S.
2000. Virus susceptibility and resistance of Hungarian pepper varieties. International
Journal of Horticultural Science. 6: 4, 68-73.
Janzac, B.; Fabre, M.F.; Palloix, A.; Moury, B. 2009. Phenotype and spectrum of action of
the Pvr4 resistance in pepper against potyviruses, and selection for virulent variants.
Plant Pathology. 58: 3, 443-449.
Jenser, G.; Gaborjanyi, R.; Vasdinnyei, R.; Almasi, A. 1996. Tospovirus infections in Hunga­
ry. Acta Horticulturae. 431: 51-57.
228
Advances in Genetics and Breeding of Capsicum and Eggplant
Liang GengSheng; Yin YabLan; Zhao GuoZhen. 2005. A new pepper F1 hybrid‚Tianjiao No.
4‘. China Vegetables. 3, 27-28.
Marchoux, G.; Ginoux, G.; Morris, C.; Nicot, P. 2000. Pepper: the breakthrough of viruses.
PHM Revue Horticole. 410 Sup, 17-20.
Mazourek, M.; Moriarty, G.; Glos, M.; Fink, M.; Kreitinger, M.; Henderson, E.; Palmer, G.;
Chickering, A.; Rumore, D.L.; Kean, D.; Myers, J.R.; Murphy, J.F.; Kramer, C.; Jahn,
M. 2009. ‘Peacework’: a Cucumber mosaic virus-resistant early red bell pepper for
organic systems. Horticultural Science 44: 5, 1464-1467.
Mehle, N.; Znidaric, M.T.; Tornos, T.; Ravnikar, M. 2008. First report of Broad bean wilt
virus 1 in Slovenia. Plant Pathology. 2008. 57: 2, 395.
Plant Viruses Online, [www dokument]. [cit. 5.1.2010]. Available on: http://www.agls.
uidaho.edu/ebi/vdie//sppindex.htm
Smotlacha, R. 2010. Czech and Moravian Vegetable Union (CMVU), Krapkova 3, 779 00
Olomouc, personal communication.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Interaction of the gds and Bs-2 gene during the defense against the
pepper pathogen Xanthomonas vesicatoria bacterium
E. Szarka1, G. Csillery2,3 and J. Szarka1
Primordium Ltd., H-1222 Budapest, Fenyopinty u. 7, Hungary. Contact:[email protected]
Budakert Ltd., 1114-H Budapest, Bartok B. u. 41, Hungary
3
Esasem SpA, Via G. Marconi 56, 37052 Casaleone (VR), Italy
1
2
Abstract
In order to improve disease resistance of our pepper lines, we incorporated the general
defense system in our breeding programme and we combined the gds with the Bs-2 gene.
The recessive gds gene is responsible for the general defense system of plants against
microbes. The reaction regulated by it is accompanied by cell enlargement, cell division
and tissue compaction instead of cell necrosis. The Bs-2 gene ensures specific defense to
pepper against Xanthomonas vesicatoria bacterium which manifests itself in purplish
colouration of infected tissues. We have examined the interaction of the gds gene and the
Bs-2 gene which are inherited independently. Leaves of pepper lines being homozygotes
regarding both the recessive gds gene and the dominant Bs-2 gene reacted to the infection,
performed by suspension of the X. vesicatoria bacterium, with the phenotype characteristic
of the gds gene while only a slight purple colouration of tissues along the leaf veins referred
to the operation of the Bs-2 gene. This unexpected type of symptom can be explained by
the low stimulus threshold and high reaction speed of the general defense reaction (gds
gene). Purple colouration of the leaf veins, referring to the operation of the Bs-2 gene here,
happened due to the fact that during inoculation leaf veins are injured. Investigating
reactions of injured cells of such pepper lines that are homozygotes with respect to the gds
and the Bs-2 gene as well, we revealed new connections concerning the roles of the two
genes in disease resistance. The general defense system, encoded by the gds gene, operates
only in healthy cells thus the general defense reaction is preventive. In healthy cells the
Bs-2 gene is completely inactive beside the gds gene. But injured cells are not able to give
the general defense reaction. The specific defense reaction, determined by the Bs-2 gene,
is the reaction of cells attacked and diseased by pathogens. On the basis of the above the
general defense system is able to fulfill the role of the plant immune system, while specific
defense reactions serve for correcting deficiencies of the general defense system in the
integral whole of plant disease resistance. With knowledge of relations of the general and
specific defense reactions, strengthening of the general defense system of plants is
indispensable in the course of breeding mostly based on specific resistance genes.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Relationship between pepper flower abortion and enzymes activity
under low night temperature
N. Tarchoun1, S. Ben Mansour1, S. Rezgui2, A. Mougou2
1
Centre Régional des Recherches en Horticulture et Agriculture Biologique BP47- 4042 Sousse, Tunisia.
Contact: [email protected]; [email protected]
2
Institut National Agronomique de Tunisie (INAT) 43, av. Charles Nicolle 1082, Cité Mahrajène, Tunis, Tunisia
Abstract
Effects of night temperature on flower bud abortion were investigated for two local hot
pepper varieties (‘Beldi’ and ‘Baklouti’) grown under a low night temperature(25°C/10°C
day/night) or optimum night temperature (25°C/20°C) regime. The activity of sucrose
synthase and soluble and insoluble acid invertase were strongly dependent on temperature
regime; sucrose synthase and soluble acid invertase activities were reduced 50%, while the
insoluble acid invertase activity were reduced by more than 90% in response to the low
night temperature regime. Floral bud abortion induced by low night temperature was
negatively and significantly correlated with soluble acid invertase activity for ‘Beldi’ (r=0.82**), while for ‘Baklouti’, both sucrose synthase and insoluble acid invertase activities
were correlated with floral bud abortion (r=-0.78**).
Keywords: Abortion, bud, flower, hot pepper, low night temperature, sucrose synthase, acid
invertase.
Introduction
Hot peppers grown in unheated greenhouses for early season harvest are frequently
exposed to low night temperature that often prevails during winter in Tunisia. These
conditions have a considerable negative effect on pepper flower development and limit
the crop yield. Flowers and fruit retention are highly sensitive to environmental and
metabolic factors in many species (Van Doorn and Stead, 1997).
Several studies indicate that reproductive organ abortion depends on differentiation
stages of these organs and the stress type. Under shade conditions, Wien et al. (1989a)
noted that open flowers were the most susceptible organs to abortion, while Aloni et al.
(1991), applying heat stress on sweet pepper, concluded that immature flower buds
were more susceptible to abortion. Applying shade and heat stress at different stages of
flower differentiation, Marcelis et al. (2004) noted that flowers/fruits of sweet pepper
were susceptible to abortion a few days before anthesis.
Previous studies demonstrated that sucrose synthase and acid invertase regulate phloem
unloading (Geiger and Servaites, 1991) and are reliable measures of sink strength (Black,
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1993; Jenner and Hawker, 1993), but that their activities are highly subject to environmental
stress (Roitsch, 1999; Sturn and Tang, 1999).Aloni et al. (1996) showed that both soluble
acid invertase and sucrose synthase are active in pepper flowers. However, while acid
invertase is almost evenly distributed between the various flower parts, sucrose synthase
is abundant, mainly in the ovary and petals, where starch accumulates.
The present experiment was conducted to determine the effect of low night temperature
on sucrose synthase and acid invertase activities and their relation to floral bud abortion
in hot pepper.
Material and methods
Plant material and growth conditions
Seeds of two hot pepper varieties (‘Beldi’ and ‘Baklouti’ from INRAT, Tunisia) were sown
inalveolated trays containing fertilized peat (NPK, 12-14-24) and germinated in a growth
chamber at 25°C ± 2°C. Plants were transferred to growth chambers with a low night
temperature regime (25°C/10°C day/night) or optimum temperature regime (25°C/20°C).
The photoperiod was 16 h with light intensity of 250 ± 5 µmol.m-2 s-1 (PAR). The relative
humidity was maintained at approximately 70 ± 5%. Ten plants per variety were placed,
at random, in each chamber, watered when needed and fertigated with Nutri chem
(N:P:K 22:5: 11) at 1g/l.
Enzyme activity essays
Sucrose synthase and acid invertase activities were determined for floral structures at
three immature floral bud developmental stages designated as stage A, B and C and
compared to the ovary in flowers at anthesis.
—Stage A corresponding to the bud stage,
—Stage B corresponding to the floral bud with 3-4 mm diameter and 4-5 mm height
(green petals welded to sepals, 4-5 days before anthesis),
—Stage C corresponding to floral buds with diameter ≥ 4 mm, height ≥ 5 mm (white
petals lightly welded to sepals, 2-3 days before anthesis) (Fig. 1).
bud
1
2
3
Figure 1. Floral growth stage based on the dimensional and morphological criteria:
bud (stage A) [1] flower bud (stage B) [2] and flower bud (stage C) [3].
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Sucrose synthase activity, in cleavage sense, was determined according to the method
applied by Schaffer et al. (1987) while soluble and insoluble acid invertase activities
were determined by an extraction procedure comparable to that described by Aloni et
al. (1991b).
Statistical analysis
The experiment was carried out as a split-split-plot model where temperature constitutes
the main factor, the varieties are considered as the second factor (sub-plot) and the
floral structures represent the smallest experimental unit (sub-sub-plot). Analysis of
variance was performed using SAS (1985); means are separated by LSD. The relationship
between enzymatic activity and floral structure abortion was estimated by Pearson
correlation coefficient using proc corr of SAS (1985).
Results
Effect of low night temperature on sucrose synthase and acid invertase activities
The activity of the sucrose synthase and soluble and insoluble acid invertase (expressed
on a fresh weight basis) were strongly dependent on temperature regime (Table 1). Fifty
to 90% of the acid invertase activity was found in the soluble fraction at optimal and at
low night temperature regimes. The lowest activity was noted for the insoluble acid
invertase under the low night temperature regime of 25/10°C.
Table 1. The average effect of low night temperature on sucrose synthase and acid
invertase activities expressed as µmol.(gfwt)-1.min-1 ).
Temperature regime
Sucrose Synthase
Soluble acid
invertase
Insoluble acid
invertase
25/20°C
6.5a*
22.0 a
11.8 a
25/10°C
3.6 b
11.1 b
0.8 b
1.7
2.5
0.9
LSD
* means followed by different letters are significantly different at P≤ 0.05
Effect of varieties on enzymatic activity
Enzymatic activity varied depending on variety. Levels of enzymatic activity for ‘Beldi’
were greater than for ‘Baklouti’ (Table 2). Sucrose synthase activity was greatly
suppressed in ‘Baklouti’ (3.4 µmol/gfwt/min) compared to ‘Beldi’ (6.6 µmol/gfwt/min).
Insoluble and soluble acid invertase followed a similar pattern, but was less pronounced
for the soluble fraction.
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Table 2. The average enzymatic activity expressed on µmol.(gfwt)-1.min-1 evaluated on
pepper flower structure of two localhot pepper varieties ‘Beldi’ and ‘Baklouti’.
Varieties
Sucrose Synthase
soluble Acid0
invertase
insoluble Acid
invertase
‘Beldi’
6.6 a*
18.9 a
8.4 a
‘Baklouti’
3.4 b
14.2 b
4.3 b
0.9
3.3
2.1
LSD
* means followed by different letters are significantly different at P≤ 0.05
Enzymatic activity in different floral structures
Table 3 shows that enzymatic activity varies depending on the floral structures. Enzyme
activity was greater in ovaries from flowers at anthesis in comparison to immature stage
A and stage B flower buds and less pronounced in flower buds at stage C. The activity of
the soluble acid invertase appeared to be more important than other enzymes for sucrose
cleavage in all floral structures and was characterized by increasing activity at successive
stages of flower development. The insoluble acid invertase activity exhibited a different
behavior; a decrease in activity occurred during development from the bud stage to
flower bud stage and increased acitivty occurred in ovaries from flowers at anthesis.
In spite of the similar activity for sucrose synthase in buds (stage A) and flower buds
(stage B), soluble and insoluble acid invertase activity was greater at corresponding
flower bud vs. bud stages. Sucrose synthase and soluble acid invertase activities were
greater in stage C flower buds in comparison to the bud and fower bud-stage B structures.
Abortion of these floral structures seems to be controlled differentially by one or the
other type of enzymes.
Table 3. The enzymatic activity expressed on µmol.(gfwt)-1.min-1 on four different pepper flower
structures, buds (stage A), flower buds (stage B and C) and flower ovaries at anthesis.
Structures
Sucrose synthase
Soluble Acid
invertase
insoluble Acid
invertase
4.0 b
Buds (stage A)
2.9 c*
10.7 c
Flower buds (stage B)
2.0 c
15.9 b
2.3 c
Flower buds (stage C)
4.6 b
19.4 a
4.8 b
Ovaries
10.5 a
20.2 a
14.2 a
1.0
2.7
1.1
LSD
* means followed by different letters are significantly different at P≤ 0.05
Low night temperature reduced sucrose synthase activity in ‘Baklouti’ by 53% and by 38%
on ‘Beldi’ (Table 4).
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Table 4. The average activity of sucrose synthase and acid invertase expressed as µmol.(gfwt)-1.
min-1 on ‘Beldi’ and ‘Baklouti’ varieties grown under optimal night temperature
(25/20°C) or low night temperature (25/10°C) regimes.
Enzymes
‘Beldi’
25/20°C
‘Baklouti’
25/10°C
25/20°C
25/10°C
Sucrose synthase
8.2 ± 2.1*
5.1±0.2
4.7 ± 1.0
2.2±0.3
Soluble Acid invertase
26.1±7.1
11.8 ± 4.9
17.9±5.2
10.4±3.2
Insoluble Acid invertase
15.7± 6.0
1.0±0.2
7.9 ± 1.5
0.7±0.08
* means ± SE (n= 12 replications)
Under low night temperature of 10°C, reduction of soluble and insoluble acid invertase
activities were more pronounced than for sucrose synthase activity. The insoluble
fraction of acid invertase was more affected for both ‘Beldi’ and ‘Baklouti’ varieties
with 1 to 0.7µmol/gfwt/.min, respectively.
Relationships between floral structures abortion and enzymatic activity
Correlation coefficients between floral structure abortion and enzymatic activities for
‘Beldi’ and ‘Baklouti’ grown under the optimal night temperature (25/20°C) or low night
temperature (25/10°C) regime revealed that, under low night temperature, the abortion
of ‘Baklouti’ floral structures was associated negatively with sucrose synthase and
insoluble acid invertase (r= -0.78**), while for ‘Beldi’, this coefficient was only significant
for soluble acid invertase (r= -0.82**). However, under the optimal temperature regime
(25/20°C), floral structures abortion of ‘Beldi’ and ‘Baklouti’ was associated with the
insoluble or soluble acid invertase, respectively (Table 8).Moreover, the abortion of
different floral structures seems to be dependant on the enzyme type (Table 5).
Table 5. Pearson correlation coefficients between floral structures abortion in ‘Beldi’ and
‘Baklouti’ grown under optimal night temperature (25/20°C) or low night temperature
(25/10°C) regimes and enzymatic activity expressed as µmol.(gfwt)-1.min-1
Temperature
regimes
‘Beldi’
Sucrose
synthase
‘Baklouti’
soluble
insoluble acid
acid invertase
invertase
Sucrose
synthase
soluble acid
invertase
insoluble acid
invertase
25/20°C
-0.13 ns
-0.44 ns
-0.70*
-0.13 ns
-0.72*
-0.49 ns
25/10°C
-0.12
-0.82
-0.17
-0.78
-0.35
-0.78**
ns
**
ns
**
ns
*, ** significant differences at p<0.05 and p<0.01 respectively; ns differences not significant at p>0.05
Bud abortion was associated mainly with acid invertase activity for ‘Beldi’ and ‘Baklouti’,
while sucrose synthase activity was associated with abortion of flower bud (stage B)
abortion. Although abortion of stage C flower buds depended on the varieties; soluble
and insoluble acid invertase was associated with bud abortion for ‘Baklouti’.Only the
insoluble fraction of acid invertase was associated with flower bud abortion for ‘Beldi’.
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Discussion
Sucrose synthase and acid invertase enzymatic activity was strongly reduced by the low
night temperature regime (Table 1). Indeed, the activities of sucrose synthase and the
soluble and insoluble acid invertase were significantly higher under the optimal
temperature regime (25/20°C) and were greater in ‘Beldi’ than in ‘Baklouti’ (Table 2).
This result suggests that, in addition to temperature, other factors such as the genetic
aspect influence metabolic activity (Shiffriss et al., 1994).
Geiger et al. (1996) showed that distribution of assimilates is controlled by at least two
enzymes: sucrose synthase and acid invertase and this distribution is controlled by the
strength of sink organs. It seems, however, that this distribution is governed by the
intensity of the organ strength. Buds (stage A) and flower buds at stage B presented the
weakest enzymatic activity in comparison to ovaries in anthesis stage flowers, while
flower buds at stage C had intermediate activity (Table 3). The differential abortion of
these structures could be attributed to the activity of these two enzymes that may serve
as an indicator of organ sink strength (Sun et al., 1992).
On the other hand, Bertin (1995) suggested that the abortion of tomato inflorescences
before anthesis is a result of competition for assimilate between the young vegetative
organs and the last inflorescences. In this investigation, our results suggest that the
floral structure abortion could be attributed to poor translocation capacity of assimilates.
Furthermore, a direct effect of the temperature regime can be suggested. Flowers, at
anthesis stage, have been considered as a strong sinks (Black 1993; Marcelis 1996). In the
present study (Table3) the most intense enzymatic activity has been found in the ovaries;
this could explain their low abortion under low night temperature.Working under high
temperature, Aloni et al. (1997) found more intense activity of sucrose synthase at postanthesis stage. Bud abortion seems to be associated with acid invertase activity,
especially its soluble fraction and to a lesser extent with the insoluble fraction for both
‘Beldi’ and ‘Baklouti’. Sucrose synthase seems to be associated with stage B flower bud
abortion for both varieties. Compared to the flowers at anthesis stage, studies on floral
structure abortion at the first stages of differentiation (buds and flower buds) in relation
to the metabolic activity are scarce.
Our analysis of the association between low night temperature floral bud abortion and the
enzymatic activity revealed a possible genotype influence on bud abortion; thus, the soluble
acid invertase seems to control abortion for ‘Beldi’, whereas for ‘Baklouti’, the combination
of sucrose synthase and insoluble acid invertase controls this phenomenon (Table 4). The
amplitude of variation for flower bud abortion is likely influenced by the simultaneous
effects of endogenous metabolic factorsand exogenous environmental factors.
References
Aloni, B.; Pashkar T.; Karni, L. 1991. Partitionning of [14]-C sucrose and acid invertase
activity in reproductive organs of pepper plants in relation to their abortion under
heat stress. Ann. Bot.67:371-377.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Aloni, B., Karni, L.; Zaidman Z.; Schaffer, A.A. 1996. Changes of carbohydrates in pepper
(Capsicum annuum L.) flowers in relation to their abortion under different shading
regimes. Ann. Bot. 78:163-168.
Aloni, B.; Karni, L.; Zaidman Z.; Schaffer, A.A. 1997. The relationship between sucrose su­
pply, sucrose cleaving enzymes and flower abortion in pepper. Ann.Bot. 79:601-605.
Bertin, N. 1995. Competition for assimilates and fruit position affect fruit set in
indeterminate greenhouse tomato. Ann. Bot. 75:55-65.
Black, C. C. 1993. Sink strength : it is real or measurable? Plant Cell Environ. 16:10371038.
Geiger, D. R.; Koch K.E.; Shieh, W.J. 1996. Effect of environmental factors on whole plant
assimilate partioning and associated gene expression. J. Exp. Bot. 47:1229-1238.
Geiger, D. R.; Servaites, J.C. 1991. Carbon allocation and response to stress. p. 103-125.
In: Response of plants to multiple stress. Mooney H.A. et al. (Eds) Academic press,
San Diego.
Jenner, C. F.; Hawker, J.S. 1993. Sink strength: soluble starch synthase as a measure of a
sink strength in wheat endosperm. Plant Cell Environ. 16:1023-1024.
Marcelis, L.F.M. 1996. Sink strength as a determinant of gray matter partitioning in the
whole plant. J. Exp. Bot. 47: 1281-1291.
Marcelis, L.F.M.; Heuvelink, E.; Baan Hofman-Eijer, L.R.; Den Bakker, J.; Xue, L.B.2004.
Flo­wer and fruit abortion in sweet pepper in relation to source and sink strength. J.
Exp. Bot.55: 2261-22268.
Roitsch, T. 1999. Source-sink regulation by sugar and stress. Current Opinion in Plant Biol.
2:198-206.
Statistical Analysis System ( 1985).SAS User’s guide Statistics. Ed. Cary, NC, USA.
Schaffer, A.A.; Aloni, B.; Fogelman, E. 1987. Sucrose metabolism and accumulation in de­
ve­loping fruit of sweet and non-sweet genotypes of Cucumis. Phytochemistry 26:
1883-1887.
Shiffriss, C.; Pilowsky M.; Aloni, B. 1994. Variation in flower abortion of pepper under stress
shading conditions. Euphytica 78: 133-136.
Sturn, A.; Tang, G.O.1999. The sucrose-cleaving enzymes of plants are crucial for
development, growth and carbon partitioning. October 4: 401-407.
Sun, J.; Loboda, T.; Sung, S.S.; Black, C.C.Jr. 1992. Sucrose synthase in wild tomato Ly­
copersicon chmielewskii, and tomato fruit strength. Plant Physiol. 98: 1163-1169.
Van Door, W.G.; Stead, A.D.1997. Abortion of flowers and floral parts. J. Exp. Bot.48: 821837.
Wien, H.C.; Turner, A.D.;Yang, S.F. 1989b. Hormonal basis for low light intensity induced
flower bud abortion of peppers. J. Amer. Soc. Hort. Sci. 114:981-985.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Biochemical and molecular analyses of Rfo-sa1 resistant eggplant
interaction with Fusarium oxysporum f. sp. melongenae and/or
Verticillium dahliae
L. Toppino1, G.L. Rotino1, G. Francese2, A. D’Alessandro2, G.P. Vale’3, N. Acciarri4,
V. Barbierato1, P. Rinaldi1, G. Caponetto1, G. Mennella2
CRA-ORL, Unità di Ricerca per l’Orticoltura, Montanaso Lombardo (LO), Italy.
CRA-ORT, Centro di Ricerca per l’Orticoltura, Pontecagnano (SA), Italy.
Contact: [email protected]
3
CRA-GPG, Centro di Ricerca per la Genomica e Postgenomica, Fiorenzuola d’Arda (PC), Italy.
4
CRA-ORA, Unità di Ricerca per l’Orticoltura, Monsampolo del Tronto (AP), Italy.
1
2
Abstract
The Rfo-sa1 gene conferring resistance to Fusarium oxysporum f.sp. melongenae was intro­
gressed from the allied species S. aethiopicum into cultivated eggplant through protoplasts
electrofusion. Dihaploids obtained from anther culture of the tetraploid somatic hybrids were
successfully backcrossed with recurrent eggplants to obtain advanced introgression lines (IL).
In order to characterize genes and proteins involved in the early interaction of Rfo-sa1
resistant eggplant with F. oxysporum and/or Verticillium dahliae, we analysed the root
extracts from susceptible and IL collected after different inoculation time points with
Fusarium, Verticillium and both fungi together. Eight and 24 hours post inoculation were
chosen to perform detailed molecular and biochemical analyses. Anionic exchange-high
performance liquid chromatography (AE-HPLC) analyses highlighted differences between
protein accumulation from susceptible and resistant genotypes. Studies are currently being
performed on protein extraction and mass fingerprint analysis using a liquid chromatography
coupled with mass spectrometry tandem (LC/MS/MS). The first proteins differentially
detected in the extracts from the Fusarium inoculated plants were identified by the
alignments with protein sequences or cDNA/EST present in the databases. Three PCR-select
cDNA libraries obtained from inoculated roots were enriched with pathogen induced genes
through subtraction. The most promising 800 infection-regulated cDNAs were subjected to
Blast analyses at different ESTs databases and assigned to functional categories. A reduced
overlapping was observed for Fusarium and Verticillium responsive genes while a more similar
transcriptional response was observed when Fusarium and Fusarium/Verticillum infected
samples were compared. For selected genes of particular interest, including cell wall related
and regulatory genes, a more detailed analysis of transcriptional regulation is being performed
using qRT-PCR and some of them will be further functionally characterized.
Keywords: advanced introgression lines, radical extracts, plant-pathogen interaction,
resistance proteins, resistance genes, Solanum melongena.
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Introduction
The two fungal wilts caused by Verticillium dahliae (Vd) (Bhat et al., 1999) and Fusarium
oxysporum f.sp melongenae (Fom) (Urrutia Herrada et al., 2004, Cappelli et al. 1995) are
among the most serious diseases of eggplant (Kennet et al., 1970; Stravato et al., 1993;
Urrutia Herrada et al., 2004). The resistance levels found in the cultivated eggplant are
often insufficient for effective utilization in breeding programs (Rotino et al. 2005), while
allied species of S. melongena are a source of valuable traits of resistance to diseases. The
resistance to Fom was introgressed from the allied specie S. aethiopicum by somatic
hybridization followed by anther culture of the tetraploid somatic hybrid to obtain dihaploid
plants (Rizza et al., 2002) which were successfully backcrossed with different typology of
recurrent eggplant. Advanced introgression lines (IL) were obtained through 6-8 backcross
cycles and selection, followed by selfing and/or anther culture to obtain pure lines.
Molecular characterization of the ILs enabled to demonstrate that the introgressed
resistance trait is controlled by a single dominant gene (named Rfo-sa1, Resistance to
Fusarium oxysporum f. sp. melongenae from Solanum aethiopicum 1) and to develop
molecular markers associated to the resistance locus (Toppino et al., 2008). Characterization
of Rfo-sa1 gene could lead to a better understanding of the resistance mechanism. Here we
present the preliminary results aimed to characterize the resistance triggered by Rfo-sa1
by studying genes and proteins involved in Rfo-sa1-mediated resistance. Another aspect
that we investigated was the improved tolerance of ILs to Vd after simultaneous inoculation
with Vd+Fom compared with inoculation with Vd alone. Therefore, in order to characterize
genes and proteins involved in these plant-pathogen interactions at early inoculation time
points, we analysed the root extracts of resistant and susceptible plants inoculated with
Fom, Vd or in a mixed inoculation and compared the protein composition and the expressed
genes at different timing (8 and 24 h) after artificial inoculation.
Materials and methods
Plant material and growing conditions; Fusarium, Verticillium and mixed infections
Seed-derived plantlets of the susceptible parent S. melongena 1F5(9), of the resistant
parent S. aethiopicum and of the resistant IL All 96-6 x 1F5(9) have been grown under
greenhouse conditions.
Artificial inoculation was performed according to the root-dip method described in Cappelli
et al. (1995), using plantlets at the 3-4th true leaf stage. Samples of inoculated and mockinoculated (dipping in water) roots were taken at 8 (T0+8h) and 24 hours (T1) after artificial
inoculation by a conidia suspension of Fom (1.5x106/ml), or Vd (1.0x106/ml) or both the
pathogens. Samples were subsequently frozen in liquid N2 and stored at -80°C. Some
inoculated plants were kept under greenhouse condition, and disease outcomes were
evaluated after 4-6 weeks as percent of survival and symptoms severity.
T0+8h and T1 stages where chosen because preliminary molecular analysis of tobacco
chitinase IV gene expression and spectrophotometer analyses of the total protein
contents suggested that T0+8h and T1 stages were the more suitable (among T0+4h to
72h) to study early interaction with Fom.
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Biochemical characterization
Eight samples at T0+8h and T1 stages, collected from four controls (mock-inoculated)
and four inoculated samples, were employed. Each sample was ground in liquid nitrogen
to a fine powder, resuspended in extraction buffer and total proteins were quantified as
reported in Mennella et al. (2005). At this point the protocol of analysis followed two
different strategies.
Strategy (1). 100 μl of each supernatant was filtered through a 0.22 μm membrane and
partially purified by anionic exchange-high performance liquid chromatography (AEHPLC); for each sample, fifteen fractions (each gathered for one minute) were collected
in the range 3-18 min, concentrated and analysed by sodium dodecyl sulphatepolyacrylamide gel electrophoresis (SDS-PAGE) as reported in Mennella et al. (2005,
2008). Silver staining was used to visualize proteins according to the methodology of
Heukeshoven and Dernick (1985).
Strategy (2). The remaining aliquots of supernatants were concentrated about 4-fold
through 3K Microsep (Pall Life Sciences, molecular weight cut off 3 kDa) until to 3.5 mg/
ml final proteic concentration. Because of the presence of phenol contaminants, the
samples were methanol/chloroform precipitated before SDS-PAGE analysis. Denaturing
horizontal 12% polyacrylamide homogeneous gel electrophoresis was performed loading
50 µg of total proteins for each sample. In correspondence of the different molecular
weights, compared to reference markers, the electrophoretic fragments (25 fragments/
lane) were excised from the gel, subjected to in-gel tryptic digestion and the resulting
peptide mixtures were analysed by liquid chromatography coupled with mass spectrometry
tandem (LC/MS/MS); the spectra were evaluated through MASCOT software.
Molecular characterization
Samples of T0+8h either mock-inoculated or inoculated roots of the resistant IL All 96-6
x 1F5(9) were employed. mRNA was isolated through a phenol-chloroform extraction,
enriched for poly(A)+ RNA by chromatography on oligo(dT)-cellulose (Sigma). The poly(A)
RNA was then used for cDNA synthesis, followed by digestion with RSA I. Two-step
subtraction followed by PCR amplification was performed using the Clontech PCR-select
cDNA subtraction Kit (BD Bioscience): mRNA from mock-inoculated roots (Driver) was
subtracted from mRNA of inoculated roots (Tester) (Diatchenko et al., 1996), to enrich
the resulting sample in differentially expressed sequences. The product of the subtraction
was amplified using two-step PCR as recommended by the manufacturer. The amplified
products were cloned into the pGEM T-easy vector (Promega) to obtain three cDNA
libraries (one for each inoculation).
Data were validated by reverse Northern analysis, using mRNAs of inoculated and mockinoculated samples as labelled probes. The clones were selected through comparison of
the different intensity (also confirmed in the inverted hybridisation) of the correspondent
spots in the two filter series. The selected clones were grown overnight in LB containing
100 mg L-1 ampicillin. Plasmid DNA was extracted using the Pure Yield TM Plasmid
Miniprep System (Promega) and sequenced. FASTA sequences were trimmed and cleaned
with the Vector NTI software. (www. Invitrogen.com). Cleaned sequences were subjected
to Blast analyses, using the BlastN homology search tool, employing the NCBI (www.ncbi.
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Advances in Genetics and Breeding of Capsicum and Eggplant
nlm.nih.gov/), SGN (www.sgn.cornell.edu/) and MiBASE (www.kazusa.or.jp/jsol/micro­
tom) databases. The clones identifying sequences with known function in the databases
were then subjected to UNIPROT (www.uniprot.org), BRENDA (www.brenda-enzymes.
info/) and KEGG (www.genome.jp/kegg/pathway.html) databases for their allocation in
metabolic groups of interest.
Results and discussion
Biochemical characterization
Preliminary spectrophotometric and chromatographic studies indicated that, between 8
and 24 hours after the inoculation, the total protein amounts decreased only in the
inoculated susceptible genotype 1F5(9). This evidence suggested that such a stage may be
the most interesting to detect differentially expressed proteins (Mennella et al., 2008).
Strategy (1). The chromatographic and electrophoretic analyses showed marked diffe­ren­
ces between the susceptible and the resistant genotypes in all the three different
inoculations considered. In particular, at different retention times, novel or differently
detected proteins were highlighted when the extracts from the Fusarium inoculated
plants were compared to those from mock-inoculated ones. For example, the presence in
the inoculated susceptible genotype of 3 proteins (25, 30 and 60 kDa approximately) in
fraction XIII of T0+8 (Fig. 1, gel XIII, lane 2) was highlighted, as well as differences were
found in fractions IV (about 40 and 48 kDa), VII (about 43 kDa), XI (about 26 kDa), XII
(about 44 kDa) of T0+8 in the inoculated resistant genotype (Fig. 1, gels IV, VII, XI and XII,
lane 4). Similar differences were also noted at 24 hours after the inoculation (T1 stage,
data not shown). Further studies are needed to find out if these proteins belong to the
fungus or to the plant.
Almost all AE-HPLC fractions, collected during the chromatographic separation of Fom
and/or Fom+Vd inoculated root extracts, contained additional protein bands putatively
involved in the resistance mechanism to Fom (data not shown).
Unfortunately, such proteins could not be analysed by mass spectrometry because of the
incompatibility of the aldehydes, contained in the silver staining solution used to
visualize proteins, with LC/MS/MS. Due to the high sensibility of silver staining, even few
nanograms of protein amounts were detected on the gels; however, it was not possible
to highlight such proteins when using the LC/MS/MS-compatible less sensitive (about
100-fold) coomassie stain.
Strategy (2). The first identified proteins were excised from a gel band corresponding to
a MW of 75.0 kDa, and were obtained from the resistant genotype inoculated at T1. Mass
spectrometry data were used to perform a homology search through MASCOT software
searching alignments in NCBI against “All entries”. The search enabled the identification
of two proteins: Methionine synthase (Acc. number: gi/8439545) and Lipoxygenase (Acc.
number: gi/1407703) from Solanum tuberosum.
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Figure 1. AE-HPLC elution profiles and SDS-PAGE of proteic crude root extracts from [All 96-6 x
1F5(9)] resistant and [1F5(9)] susceptible genotypes inoculated and mock-inoculated at T0+8h.
The five gels reported correspond to 5 (IV, VII, XI, XII and XIII) out of 18 fractions collected and
concentrated after AE-HPLC analyses; the lanes of each gel correspond to the four AE-HPLC
elution profiles; the arrows indicate the differential proteic bands among the four samples.
1= susceptible mock-inoculated; 2= susceptible inoculated; 3= resistant mock-inoculated;
4= resistant inoculated; M= low molecular weight marker.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Molecular characterization
Three subtracted cDNA libraries were obtained from T0+8h Fom, Vd and Fom+Vd
inoculated roots, each composed by 1000 clones containing putative differentially
accumulated transcripts. Northern analysis verification of differential expression enabled
validation of 800 differentially regulated cDNAs from the three libraries that were
subsequently sequenced. After elimination of redundancy, 119, 98 and 150 unique
sequences were obtained from Fom, Vd and Fom+Vd libraries, respectively. Putative
gene functions were assigned on the basis of their significant alignment to the databases.
cDNAs were grouped in fourteen functional categories: primary metabolism and
photosynthesis, DNA replication/ regulation and expression, translation, protein
synthesis/ degradation and modification, cell wall/ division and cytoskeleton, secondary
metabolism, development, signal transduction, transport and translocation/membrane
associated, stress induced, disease resistance, fungal, unknown function, no matches
(Table 1).
Table 1. Distribution of the up-regulated and down-regulated sequences belonging to the three
libraries, grouped in each functional group. Number of clones are indicated in brackets.
Fom (119)
Functional category
Vd (98)
Fom + Vd (150)
up
down
up
down
up
down
regulated regulated regulated regulated regulated regulated
(94)
(25)
(96)
(2)
(128)
(22)
Unknown function
20%
12%
22%
14%
22%
No match
6%
4%
26%
21%
5%
Primary metabolism and photosynthesis
7%
8%
13%
11%
9%
Secondary metabolism
4%
4%
1%
2%
0%
Protein Synthesis, Degradation and
Modification
9%
16%
14%
8%
9%
DNA Replication, Regulation
and Expression
4%
0%
8%
0%
5%
Translation
9%
12%
3%
Cell Wall, Division and Cytoskeleton
11%
4%
2%
Signal Transduction
2%
4%
Transport and translocation/ Membrane
associated
8%
Development
Stress induced
50%
2%
9%
6%
5%
1%
9%
13%
4%
4%
13%
9%
1%
4%
0%
0%
5%
0%
4%
2%
5%
0%
Defence response
18%
24%
4%
9%
9%
Fungal
1%
0%
0%
0%
0%
50%
Particular interest was dedicated to the identification of genes associated with the
different inoculations utilized. In the library from Vd inoculated roots, only two downregulated genes (belonging to basal metabolism and cell wall) were found while all the
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Advances in Genetics and Breeding of Capsicum and Eggplant
other clones were up-regulated (98%). Most of the sequences with known function were
associated to primary and secondary metabolism, while few sequences of the defence
response group were identified (4%); 2% of the known sequences were stress induced.
Conversely, in the library from Fom inoculated roots, genes involved in defence responses
were the most frequently represented category of up-regulated genes (18%). As regards
the up-regulated genes involved in defence response, cell wall modification and composition
categories, differed markedly between libraries from Fom (18% and 11%) and Vd (4% and
2%) suggesting that a specific resistance reaction is triggered in the Fom resistant line
when the Rfo-sa1 gene is activated by Fom attack. Cell wall modifications represent a well
characterized defence response (Hammond-Kosack and Jones, 1996) and in our experimental
system could also represent a Rfo-sa1 gene-specific response to Fom. Some of the ESTs
were expected as originating from fungi, because of the inoculation system, but only one
gene was found to align with Fusarium sequences and was obtained from the Fom library.
In the library Fom+Vd, a significant number of up-regulated genes was classified as related
to defence (9%), cell wall (6%), transport (13%), signal transduction (9%) and stress induced
(5%). Therefore, genes derived from roots of Fom and Fom+Vd inoculations have a more
similar expression profiles with each other than when compared to the Vd library. Moreover,
the plants infected with Fom+Vd showed lower symptoms with respect to plants inoculated
with Vd alone. Both phenotypical and molecular characterization lead to the conclusion
that a defence strategy mediated by the Rfo-sa1 locus in the IL seems to be able to
improve the responses against a different fungal wilt infection (i.e. Vd), towards which
the plant wouldn’t be otherwise able to organize a response.
When the sequences of the three libraries were compared, we observed that very few
sequences (15) are in common between at least two of them. The higher similarity (9
common sequences) was observed between Fom and Fom+Vd libraries, (common genes
are for example xyloglucan endonuclease inhibitors, PR proteins, osmotin precursors
and TMV induced proteins). Three common genes were identified between Vd and mixed
inoculation libraries and only two between Fom and Vd libraries (2-nitropropane
dioxigenase releated, caffeoil CoA methyl transferase). Finally, only one sequence was
shared by the three libraries (a TMV-induced protein). A more detailed gene transcription
analysis is currently underway using qRT-PCR to better investigate the biological
processes implicated in these plant-pathogen interactions.
Acknowledgements
This work was partially supported by the MiPAAF in the framework of the projects “Pro­
teoStress” and “Agronanotech”.
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BREEDING FOR RESISTANCE
TO BIOTIC AND
ABIOTIC STRESSES
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Characterization of volatile and non-volatile compounds of fresh
pepper (Capsicum annuum)
P.M. Eggink1, J.P.W. Haanstra1, Y. Tikunov2, A.G. Bovy2, R.G.F. Visser3
Rijk Zwaan Breeding B.V., P.O. Box 40, 2678 ZG De Lier, The Netherlands. Contact: [email protected]
Plant Research International, 6700 AA Wageningen, The Netherlands
3
Laboratory of Plant Breeding, Wageningen University, P.O. Box 386, 6700AJ Wageningen, The Netherlands
1
2
Abstract
In this study volatile and non-volatile compounds and several agronomical important
parameters were measured in mature fruits of elite sweet pepper breeding lines and hybrids
and several genebank accessions from different Capsicum species. The sweet pepper
breeding lines and hybrids were chosen to roughly represent the expected variation in
flavor of Capsicum annuum in the Rijk Zwaan germplasm. The genebank accessions were
either chosen because they were expected to have unique combinations of aromas and
flavors, according to experience and/or literature, or were parents of mapping populations.
The biochemical profiling allowed visualization of between- and within-species metabolic
variation and stability during the year. In general, total soluble solids content (Brix) was
genotype-dependent and fluctuated only slightly throughout the growing season, with
uncultivated genotypes showing the largest changes. The species C. chinense, C. baccatum
var. pendulum and C. annuum could be clearly separated by principle component analysis
based on profiles of 391 volatile compounds. Especially for breeding purposes it seems to
be interesting to study this variation in more detail, trying to unravel the complex genetics
of the different pepper flavor aspects.
Keywords: biochemical profiling, flavor, SPME-GC-MS, multivariate analysis, PCA.
Introduction
Flavor is an important quality parameter for fruits and vegetables. External qualities
such as color, texture and shape are relatively easy to evaluate by both producers and
consumers. However, evaluation of flavor attributes is more complex. In tomato flavor
research measuring physical, biochemical and sensory properties, the latter were
considered the most difficult to quantify (Fulton et al. 2002). Flavor of fruits and
vegetables, as perceived during consumption has been defined as the overall sensation
provided by the interaction of taste, odor, mouth feel, sight and sound. The composition
of non-volatile compounds influences mainly the sensory perceived taste, while the
aroma is affected by volatile compounds (Luning, 1994b).
Although literature addressing flavor of some fruit crops, like tomato, strawberry, peach
or melon, is abundant, specific research for the fruit crop pepper (Capsicum annuum) is
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limited. Pepper fruits are commonly used in the diet because of their typical color,
pungency, taste and/or distinct aroma (Govindarajan, 1985). Peppers are eaten fresh or
processed, as unripe (green or white) or ripe (e.g. red, yellow and orange) fruits. In the
breeding of pepper, the factors production and quality (e.g. shelf life, firmness and
disease resistances) are of main interest. However, since consumers have become more
critical, attention in pepper, like in tomato, is shifting towards flavor as an important
quality parameter (Verheul, 2008).
Research on pepper flavor has mainly focused on characterization of volatile and nonvolatile component variation in cultivated and/or wild species (e.g. Buttery et al. 1969,
Jarret et al. 2007, Kollmannsberger et al. 2007). However, correlations between flavor
components and sensory evaluations by taste or odor panels are generally missing. We
aim to combine biochemical and agronomical analyses with sensory evaluations in order
to elucidate the genetic and biochemical basis underlying pepper fruit flavor and,
eventually, define strategies to predict and control flavor of fresh pepper. In this paper,
initial results of agronomic evaluations, Brix measurements and volatile profiling will be
discussed.
Material and methods
Plant material
In this study, elite pepper breeding lines and hybrids provided by Rijk Zwaan, and several
genebank accessions from multiple Capsicum species were used (Table 1). The pepper
breeding lines and hybrids were chosen to roughly represent the variation in flavor of C.
annuum in the germplasm of Rijk Zwaan. The genebank accessions were either chosen
because they were expected to have unique combinations of aromas and flavors,
according to experience and/or literature, or to be parents of available mapping
populations. In 2008, the genotypes were grown in soil in a greenhouse at Rijk Zwaan (De
Lier, The Netherlands), according to standard Dutch pepper management conditions
with 2.5 plants/m2. Potential shading effects, because of the diverse nature of the
genotypes, were avoided by ordering the plants by (expected) plant height in the
greenhouse in 3 separate blocks (i.e. tall, intermediate and short plants). All genotypes
were grown in 3 plots of 5 plants, which were randomized within the separate blocks.
From the beginning of May till the end of September 2008, all completely (95-100%)
colored fruits were harvested, counted and weighed on a (bi)weekly base. In that period,
9 harvests, evenly spread over the season, were used for biochemical measurements, of
which 3 harvests (29 May, 31 July and 4 September) were also used for sensory evaluation.
After harvesting, fruits were stored in a climate room at 20°C with 80% relative humidity
for 4-5 days to optimize ripening. For each individual repetition of the genotypes, a
selection of 5-8 fruits was pooled to make a representative fruit sample. Fruits were cut
(top and bottom parts were discarded) in 1-2 cm pieces, mixed and seeds were removed.
For fruits subjected to sensory analysis, half of the fruit pieces of each sample were
immediately frozen in liquid nitrogen, ground in an electric mill and stored at -80°C
while the other half was used for flavor evaluation. Fruits of harvests that were only
used for biochemical measurements were prepared similarly, but were freshly processed
prior to freezing in liquid nitrogen and stored at -80°C.
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Metabolic profiling
The profiling of volatile metabolites was performed using headspace SPME-GC-MS, as
described in Tikunov et al. 2005. Frozen fruit powder (1 g fresh weight) was weighed in a
5-ml screw-cap vial, closed and incubated at 30°C for 10 minutes. An EDTA-NaOH water
solution was prepared by adjusting of 100 mM EDTA to pH of 7.5 with NaOH. Then, 1 ml
of the EDTA-NaOH solution was added to the sample to a final EDTA concentration of 50
mM. Solid CaCl2 was then immediately added to give a final concentration of 5 M. The
closed vials were then sonicated for 5 minutes. A 1 ml aliquot of the pulp was transferred
into a 10-ml crimp cap vial (Waters), capped and used for SPME-GC-MS analysis.
Volatiles were automatically extracted from headspace and injected into the GC-MS via
a Combi PAL autosampler (CTC Analytics AG). Headspace volatiles were extracted by
exposing a 65 µm PDMS-DVB SPME fiber (Supelco) to the vial headspace for 20 minutes
under continuous agitation and heating at 50°C. The fiber was inserted into a GC 8000
(Fisons Instruments) injection port and volatiles were desorbed for 1 min at 250°C.
Chromatography was
performed on an HP-5 ( 50 m x 0.32 mm x 1.05 µm) column with helium as carrier gas
(37 kPa). The GC interface and MS source temperatures were 260°C and 250°C,
respectively. The GC temperature program began at 45°C (2 min), was then raised to
250°C at a rate of 5°C/min and finally held at 250°C for 5 min. The total run time
including oven cooling was 60 min. Mass spectra in the 35-400 m/z range were recorded
by an MD800 electron impact MS (Fisons Instruments) at a scanning speed of 2.8 scans/
sec and an ionization energy of 70 eV. The chromatography and spectral data were
evaluated using “XcaliburTM” software (http://www.thermo.com).
For pH analysis, crude extracts of blended samples were measured directly. Clear
supernatants of shortly centrifuged samples were used for refractive index measurement
of total soluble solids content (TSS; °Brix) and for an enzymatic determination of glucose,
fructose and sucrose (Velterop and Vos 2001). Anion exchange chromatography on the
same supernatants was used for citric, malic and ascorbic acid determination based on
standard protocols (Dionex Corporation, Sunnyvale, CA; http://www.dionex.com/ Appli­
cation Note 143 “Determination of Organic Acids in Fruit Juices”). Dry matter content was
calculated by drying weighed samples at 60-80°C for up to 48h in a standard oven.
GC-MS data processing
The GC–MS profiles derived using the SPME-GC–MS method were processed by the
MetAlignTM software package (http://www.metalign.nl) for baseline correction, noise
estimation and ion-wise mass spectral alignment. The Multivariate Mass Spectral
Reconstruction (MMSR) approach (Tikunov et al., 2005) was used to reduce data to
volatile compound mass spectra. Each compound was represented by a single selective
ion fragment in the following multivariate data analysis. The compounds (number of
fragment ions in a mass spectrum ≥5) were then subjected to a tentative identification
using the NIST mass spectral library (http://www.nist.gov). Identities were assigned to
compounds with a forward match factor (fmf) ≥700. The rest of the compounds were
considered of unknown identity. Identities of 21 volatiles were confirmed by authentic
chemical standards.
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Volatile data analysis
The (non-)volatile data has been analyzed using GeneMaths XT version 2.0 (http://www.
applied-maths.com). The data sets have been log2 transformed and normalized to the
mean. Principle component analysis (PCA) implemented in GeneMaths was used for
unsupervised cluster analysis of the metabolites. Pearson’s correlation coefficient was
used as a measure for metabolite-metabolite correlation and hierarchical clustering.
Results and discussion
Agronomical evaluations
In correspondence to the genetic diversity in our collection of 35 Capsicum genotypes
representing 4 different species, we found a wide range of agronomical characteristics
(Table 1). Fruits were ranging 0.5-22 cm in length and 0.5-8.5 cm in width, within the
fruit types blocky, dulce italiano, dolma, kapya, lamuyo, conical, elongated, round and
Habenero. The majority of the genotypes were red, as this is the predominant color in
cultivated and wild material; yellow and orange genotypes were less represented. The
accession Chinense-WA segregated for yellow and red fruits. Therefore biochemical
measurements and sensory evaluations of this accession were performed on samples of
the separate fruit colors. Due to the fact that we were also interested in studying some
non-cultivated accessions, several pungent genotypes were included in the analyses.
Total yield was reported throughout the complete analysis period (May-September) and
large differences were observed (0.1-15.3 kg/m2). Since C. frutescens BG2814-6 and C.
annuum Turrialba yield a large amount of very small fruits, the total yield was estimated
based on the approximate amount of harvested fruits and the average fruit weight.
Biochemical analyses
The non-volatile compounds including total soluble solids, pH, sugars (fructose, glucose
and sucrose) and acids (malic, citric and ascorbic acid) were measured on 9 harvests in
the period May-September, evenly spread over the season, of which 3 harvests (29 May,
31 July and 4 September) were also used for sensory evaluation and volatile profiling. All
35 genotypes of the latter 3 harvests were included in the (non-)volatile measurement,
whereas from the other 6 harvests only a subset (marked * in Table 1) of 12 genotypes,
which were most contrasting in flavor and (non-)volatile profile, were included in nonvolatile analyses.
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Table 1. Description of Capsicum genotypes evaluated for fruit quality attributes.
Genotype
Species
Fruit type
Mazurka
Size1 (cm) Color
Pungency
°Brix2
Yield3 (kg/m2)
C. annuum (elite)
Blocky
8x8
Red
Sweet
7.6
12.1
Hybrid 1*/**
C. annuum (elite)
Blocky
8x8
Red
Sweet
8.0
12.8
Line A
C. annuum (elite)
Blocky
8x8
Red
Sweet
7.6
11.7
Line B
C. annuum (elite)
Blocky
8.5 x 8
Red
Sweet
7.8
9.6
Line C *
C. annuum (elite)
Blocky
8.5 x 8
Red
Sweet
8.4
12.9
Line D *
C. annuum (elite)
Blocky
8x8
Red
Sweet
7.8
9.1
Line F *
C. annuum (elite)
Blocky
9x8
Yellow
Sweet
5.6
11.8
Line G **
C. annuum (elite)
Blocky
8x8
Yellow
Sweet
6.4
15.3
Line H
C. annuum (elite)
Blocky
8x8
Yellow
Sweet
8.0
12.9
Line I
C. annuum (elite)
Blocky
8 x 8.5
Yellow
Sweet
7.2
14.6
Line J **
C. annuum (elite)
Blocky
8 x 8.5
Orange
Sweet
7.4
12.4
Line K
C. annuum (elite)
Mini block
5x5
Orange
Sweet
8.3
7.2
Hybrid 2 *
C. annuum (elite)
Dulce italiano
20 x 4
Red
Sweet
9.4
10.9
Hybrid 3
C. annuum (elite)
Dulce italiano
22 x 4.5
Red
Sweet
9.5
13.0
Line L */**
C. annuum (elite)
Dulce italiano
22 x 4
Red
Sweet
7.7
11.5
Line M *
C. annuum (elite)
Dulce italiano
18 x 4.5
Red
Sweet
9.4
9.8
Line O
C. annuum (elite)
Dulce italiano
22 x 4
Red
Sweet
7.6
11.6
Line P
C. annuum (elite)
Dulce italiano
22 x 4
Red
Pungent
7.8
13.5
Line E
C. annuum (elite)
Dolma
7 x 6.5
Red
Sweet
8.7
8.7
Line N
C. annuum (elite)
Kapya
12 x 4
Red
Sweet
8.3
8.8
Piquillo **
C. annuum
Conical
9x4
Red
Sweet
10.5
6.6
Buran
C. annuum
Lamuyo
10 x 7
Red
Sweet
9.1
11.0
PBC1405 */**
C. annuum5
Elongated
18 x 2
Red
Sweet
9.8
8.8
PI543188
C. annuum6
Conical
10 x 4
Red
Pungent
7.8
5.9
Habanero
5x5
Red
Pungent
6.3
6.4
Habanero
5x5
Red/
yellow7
Pungent
6.0
8.3
0.5-1
Red
Pungent
25.7
0.18
4
Antillais Caribbean C. chinense
*/**
Chinense-WA */**
C. chinense
BG 2814-6**
C. frutescens
Round
Numex RNaky
C. annuum
Dulce Italiano
20 x 4
Red
Pungent
9.2
9.9
PEN-45 */**
C. baccatum var.
pendulum
C. baccatum var.
pendulum
Conical
6-7 x 2
Red
Pungent
11.2
8.9
Conical
6-7 x 2
Red
Pungent
11.8
11.1
1-1.5
Red
Pungent
14.8
0.58
10.1
PEN-79 *
Turrialba **
C. annuum
Round
Vania
C. annuum
Lamuyo
14 x 8
Red
Sweet
9.0
CM334
C. annuum
Conical
6-7 x 4
Red
Pungent
9.0
2.4
Maor
C. annuum
Blocky
8x8
Red
Sweet
7.9
12.0
Perennial **
C. annuum
Elongated
3-4 x 1
Red
Pungent
13.0
1.5
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Size is indicated by length x width, 2Average total soluble solids of the fruit samples (9/genotype)
that were used for sensory evaluation, 3 Average yield in the harvesting period May through
September, 4 Control variety (e.g. Luning et al 1994a and 1994b), 5 Accession formerly classified as
C. baccatum (AVRDC), 6 Accession formerly classified as C. chinense (USDA), 7 Accession is segregating
for yellow and red fruits, 8 Yield is estimated based on the approximate amount of harvested fruits
and the average fruit weight *Subset containing genotypes most contrasting in (non-)volatiles and
flavour, **Genotypes included in bulk reference sample.
1
Figure 1 shows an overview of the total soluble solids content (TSS) of the 12 genotypes
in the subset, which gives an impression of the non-volatile compound concentration
behavior during the year and the variability between repetitions of the same genotype
in the experiment. In general TSS fluctuated only slightly throughout the growing season
with relatively small standard errors of the means, indicating uniformity of the
experimental setup. Uncultivated genotypes, like C.baccatum var. pendulum PEN45 and
PEN79 showed the largest fluctuations, mainly at the start of the experiment.
Figure 1. Total soluble solids content of the 12 selected genotypes in the subset
during the year. Mean values and standard errors from three
measurements (error bars) are shown.
In addition,to the stability of TSS compounds, their effect on yield is also an important
breeding parameter. In the total set of 35 genotypes, the correlation between TSS and
yield is -0.64 (41.4% explained variance), whereas in elite material this correlation is
-0.38 (14.3% explained variance). The negative relationship between TSS and yield has
been observed before. Utilizing 20 years of processing tomato field data, Grandillo and
co-workers (1999) reported a negative correlation between °Brix and yield ranging
between -0.23 and -0.57 depending on period and environment.
Using SPME-GC-MS 391 volatile compounds were detected, of which 189 compounds
were of unknown origin [fmf<700]). This number of pepper volatiles is in the same order
of magnitude as the number of compounds (322) found in a diverse set of tomato
genotypes (Tikunov et al 2005). In Figure 2, the hierarchical clustering from 16 genotypes
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(harvest 29 May) based on intensity patterns of all measured volatile compounds is
shown. Genotype repetitions and bulk samples, consisting of a balanced mixture of 12
representative genotypes (marked ** in Table 1), were used as reference in all SPME-GCMS measurements, and generally clustered together confirming the quality of the data.
Principal component analysis (PCA) proved to be a powerful method to visualize diffe­
rences between the genotypes, discriminating between- and within-species variation.
The species C. chinense, C. baccatum var. pendulum and C. annuum clustered separately
along the primary axis (58.3% explained variance). Separation along the vertical axis
(8.9% explained variance) is mainly based on within-species variation.
A
B
Figure 2. Multivariate analyses of 35 Capsicum genotypes in 3 repetitions (harvest 29 May).
A, Hierarchical tree of the genotypes based on intensity patterns of 391 volatile compounds
(16 genotypes shown). B, PCA plot showing the major types of differences between all
genotypes: between-species variation, discriminating C. chinense, C. baccatum and
C. annuum along the horizontal axis (58.3% explained variance) and within-species
variation along the vertical axis (8.9% explained variance). Genotypes in both figures are
shade-colored according to the legend in B. Bulk (see footnote **, Table 1) is indicated in white.
Conclusion and continuation
The biochemical profiling allowed visualization of between- and within-species (non-)
volatile variation and stability during the year. The PCA plot (Fig. 2b) shows individual
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grouping of C. chinense, C. baccatum var. pendulum and C. annuum, indicating potentially
interesting volatile variation present in the former two groups. In addition, the variation
within the C.annuum (elite) group itself gives sufficient reason to justify more detailed
study. In both cases, mapping populations resulting from crossing extreme and contrasting
genotypes would possibly allow the unraveling of the different aspects of pepper flavor
genetics. Because of the complex nature of flavor, thorough biochemical, sensory and
agronomical evaluation in combination with QTL mapping will be needed.
Finally, in addition to biochemical profiling, the genotypes have been subjected to
sensory evaluation by a trained descriptive expert panel (data not shown). In a subsequent
publication, we will describe the relation between specific biochemical compounds and
sensory attributes.
Acknowledgements
The authors kindly acknowledge Harry Jonker and Yvonne Birnbaum at Plant Research
International for performing the SPME-GC-MS analyses. In addition we thank Sjaak van
Heusden for technical support and useful discussions. Finally we are grateful to Laure
Flament, Suzanne de Wit, Femke Willeboordse, Gerald Freymark, Sander Bos, Tineke
Benning and Paula de Grauw for performing a massive job on sample preparation and
non-volatile measurements, and all other people at Rijk Zwaan who took care of perfect
greenhouse management.
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I. History, botany, cultivation and primary processing. CRC Critical Reviews in Food
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Grandillo, S.; Zamir, D.; Tanksley, S.D. 1999. Genetic improvement of processing
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Jarret, R.L.; Baldwin, E.; Perkins, B.; Bushway, R.; Guthrie, K. 2007. Diversity of fruit
quality characteristics in Capsicum frutescens. HortScience 42:16-19.
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analysis of volatile compounds involved in the flavor of Capsicum annuum fruits.
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Roozen, J.P. 1994b. Combined instrumental and sensory evaluation of flavor of
fresh bell peppers (Capsicum annuum) harvested at three maturation stages.
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A.G. 2005. A novel approach for nontargeted data analysis for metabolomics.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
The assessment of variability in fruits of local pepper
(Capsicum annuum L.) from individual plants
K. Lahbib, M. El Gazzah
Laboratoire de Génétique des Populations et Ressources Biologiques, Department de Biologie,
Faculté des Sciences de Tunis, Campus Universitaire Tunisie, 2092 Tunis El Manar, Tunis, Tunisie (Tunisia).
Contact: [email protected]
Abstract
Fruit of pepper (Capsicum annuum L.) is considered one of the most appreciated vegetable
and spice grown and consumed by Tunisian people. In Tunisia, cropping system is based on
both commercial and local varieties but local germplasm is used frequently by farmers to
seeds production. In fact, seeds harvested from potential fruits at different parts of the
plant were used for sowing at the next season regardless fruit position in the plant. In this
work, we have performed a morphological and biochemical characterization of individual
fruits harvested at the same time from apical, basal and middle part from single plants. The
assessment of genetic variability through the study of fruit morphological characters and the
capsaicin content of individual fruits of local 3 pungent cultivars of pepper (Capsicum
annuum L.) from a single plant exhibits a wide range of values. Analysis of fruits from a
second and a third plant for several harvest times were undertaken to confirm this
observation. The objective of this study was to lead farmer choice in seeds selection criteria.
This study presents an advantage for agronomist to achieve plants with better fruit traits.
Keywords: local germplasm, fruit position, characterization, wide range, farmer choice.
Introduction
Fruit of pepper is widely known for its culinary use as flavouring and colorant agent.
Although being an introduced crop by Spanish travels, it has adapted very well to hard
environmental conditions including soil salinity (Van der Beek and Ltifi, 1991) and fungus
attack (Allagui, 1993). His cultivation is of increasing relevance for Tunisian agriculture
Annually 18,500 ha are harvested yielding approximately to 255,000 tons of fruit production.
Fruit production comes essentially from local accessions of pepper cultivated at season
having a high fruit load. Better fruits were chosen from whole plant and correspondent
seeds were used for the next season But the choice was varied and hard if it done from
apical, basal or middle zone in relation to resources allocation. In the scientific research,
the concept of source and sink strengths is well recognized and described by the mechanisms
of carbohydrate partitioning into the different and competing organs at a whole plant
(González-Real et al., 2008). This concept is pertinent approach in plants especially those
presenting successive fruit production cycles and harvests, and also alternate periods of
low and heavy fruit load as Capsicum plant (Bertin and Gary, 1993; Marcelis and BaanHofman
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Eijer, 1997; Heuvelink and Körner, 2001; González-Real et al., 2008). Unfortunately, this
concept is limited by environmental factors as light in Capsicum plants (Estrada et al.,
2002). In this work, we try to examine this concept by the assessment of variability from
individual fruits collected from apical, basal or middle zone in single plants.
Materials and methods
Plant material
Plant material was formed by 3 accessions of pungent pepper (Capsicum annuum L.)
“Baklouti”, “Beldi” and “Knaiss”. The first two accessions were commonly cultivated in
all the parts of Tunisia. Accession “Knaiss” is originated from “Sousse” located in middle
coast of Tunisia. Accessions of pepper were grown in open field from February to
September and individual fruits were numbered and their dates of fruit set up were
recorded. For each harvested time, 10 fruits having same age (15, 25 and 35 days after
fruit setup) were collected from the top, middle and down part of the plant. Three
single plants as repetition were used for each accession
Morphological study
Eight morphological characters were recorded on every fruit (Table 1). To exhibit va­
riation among individual fruits collected, univarite (Mean, F test) and multivariate sta­
tistical analysis (Canonical analysis) were carried out.
Table 1. Morphological characters and symbols.
Characters studied
Fruit weight (g)
symbol
FW
Fruit length (cm)
FL
Fruit diameter (cm)
FD
Fruit thickness (mm)
FTh
Fruit width (cm)
FWd
Fruit number of seeds
Weight of 100 seeds (g)
Placenta weight (g)
Ns
W100s
WPl
Biochemical characterization
Three plants from each accession were used and divided into apical, middle and basal
parts. Individual fruits having the same age were collected from each part. Based on
results developed by Iwai et al. 1979 and Suzuki et al. 1980, we chose placenta tissue to
determine capsaicin content. 2 grams of tissues were used for quantification of capsaicin
content by spectrophotometric measurement as protocol proposed by (Sadasivam and
Manikkam, 1992). Absorbance was measured for at 720nm. Capsaicin content (Cap%)
calculated from the standard curve was expressed as ug/100g of dry matter.
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Results and discussion
The means of characters and test F were calculated respectively in Tables 2 and 3. Data
shown in these tables exhibit a wide range of variation within fruits collected from
different parts of plant in each accession studied.
Table 2. Means of characters for individual fruits collected from different parts
(apical, middle, basal) of single plant.
“Baklouti”
“Beldi”
Apical
middle
basal
FW
16,35
18,31
FL
7,460
8,640
FD
3,235
2,410
“Knaiss”
Apical
middle
basal
Apical
middle
basal
17,16
29,76
41,588
42,748
28,564
25,456
18,155
8,305
15,330
14,920
15,650
11,720
10,300
8,350
2,655
3,080
3,080
3,075
3,140
2,810
2,565
FTh
2,500
2,262
2,450
2,525
2,762
3,354
2,820
2,300
2,625
FWd
9,210
7,750
8,680
9,110
9,580
8,959
9,920
9,020
8,672
Ns
W100s
162
140
160
168
199
174
204
198
180
1,634
1,253
1,701
1,945
1,986
1,708
1,740
1,874
1,688
WPl
3,563
2,707
3,007
5,053
5,329
4,980
4,808
5,158
3,475
Cap%
0,514
0,501
0,437
0,425
0,426
0,371
0,568
0,449
0,511
Table 3. F test applied for fruit characters colleted from different parts
(apical, middle, basal) of single plant of three different accessions.
F test
“Baklouti”
“Beldi”
“Knaiss”
FW
0,191
4,620
2,235
FL
0,370
0,153
8,875
FD
7,54
0,587
1,767
FTh
0,439
5,900
2,921
FWd
3,82
0,683
1,042
Ns
0,64
1,177
0,399
W100s
1,31
0,338
0,116
WPl
1,52
0,090
2,062
Cap%
0,62
0,582
1,347
Canonical analysis were used also to scrutinize the magnitude of variation in a single plant
for each accession “Baklouti” (table 4), “Beldi” (table 5) and “Knaiss” (table 6).
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Advances in Genetics and Breeding of Capsicum and Eggplant
Table 4. Correlation between characters measured and the first two axis
of the canonical Analysis calculated for “Baklouti” accession.
Eigenvalue
Proportion of Variation (%)
Cumulative Variance (%)
Variables Correlations
Axis1
Axis2
0,022
65,663
65,663
0,005
15,088
80,751
FW
0,325
FW
-0,152
FL
0,438
FL
0,158
FD
0,121
FD
0,198
FTh
0,127
FTh
0,055
FWd
0,102
FWd
0,168
Ns
-0,068
Ns
-0,003
W100s
-0,07
W100s
-0,075
WPl
-0,076
WPl
-0,074
FW
0,202
FW
0,074
Table 5. Correlation between characters measured and the first two axis of the
canonical Analysis calculated for “Beldi” accession.
Eigenvalue
Proportion of Variation (%)
Cumulative Variance (%)
Variables Correlations
264
Axis1
Axis2
0,018
71,229
71,229
0,004
15,514
86,743
FW
0,268
FW
-0,077
FL
0,205
FL
0,188
FD
0,051
FD
0,102
FTh
0,154
FTh
0,144
FWd
0,044
FWd
0,073
-0,008
Ns
-0,077
Ns
W100s
-0,115
W100s
0,149
WPl
-0,039
WPl
-0,064
Cap%
0,013
Cap%
0,205
Advances in Genetics and Breeding of Capsicum and Eggplant
Table 6. Correlation between characters measured and the first two axis of the
canonical Analysis calculated for “Knaiss” accession.
Eigenvalue
Proportion of Variation (%)
Cumulative Variance (%)
Variables Correlations
Axis1
Axis2
0,021
68,607
68,607
0,005
17,418
86,025
FW
0,354
FW
FL
0,173
FL
-0,112
0,212
FD
0,198
FD
0,116
0,156
FTh
0,171
FTh
FWd
0,24
FWd
0,192
Ns
-0,074
Ns
-0,007
W100s
0,052
W100s
-0,128
WPl
0,154
WPl
-0,115
Cap%
0,094
Cap%
0,241
Within our study, position of individual fruits at whole plant displays significant difference for agronomic characters studied and a wide range of variability among each accession studied. This observation is confirmed by a second and third replicates at several
harvested times. Variation of some characters don’t allow an increasing or decreasing
gradiant, this may be due to interaction of environnmental effect on fruit position and
fruit development depending of resources allocation.
In other works, fruit’s position in the whole plant plays an important role in the accumulation of capsaicinoids (Estrada et al., 2002), and the top of plant has a higher content in capsaicinoids than the basal part. Zewdie and Bosland (2000) measured the
pungency of fruits from the different nodes of chile plants and reported that the most
pungent fruits came from the lower or earliest nodes. As well as, in other aspects of the
fruits, like seed quality and their germination percentage, fruit position showed a significant effect on seed quality (Osman and George, 1984). Seeds obtained from fruits
at the lower level on the plant gives the highest mean seed weight, germination percentage and the shortest time to germination and seedling emergence. The fact that
dominant characters of fruits is coming from the lower parts of the plant was in relation
to source-sink competition. Zewdie and Bosland (2000) speculated that the higher pungency in Capsicum was probably due to the fewer number of fruits on the lower part of
the plant, and that the early fruits received most of the nutriments responsible for
capsaicin development. The later fruits had to share the nutriments, so they produce
less capsaicin. This gradient was not constant, Estrada and al. (2002) attribute the
higher content of capsainoids on the apical part to the fact that these fruits receive a
greater quantity of light than those located in the middle and lower part. light exposure as an environmental condition was an important factor in capsaicinoids formation
and accumulation.
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Advances in Genetics and Breeding of Capsicum and Eggplant
References
Allagui, M.B. 1993. Evaluation of pepper genotypes for Leveillula taurica Lev.(Arn) resistance in Tunisia. Capsicum and Eggplant Newsletter 12:81-82.
Bertin, N.; Gary, C. 1993. Evaluation d’un modèle dynamique de croissance et de développement de la tomate (Lycopersicum esculentum Mill.), TOMGRO, pour différents niveaux d‘offre et de demande en assimilats. Agronomie 13:395-405.
Estrada, B.; Bernal, A.; Diaz, J.; Pomar, F.; Merino, F. 2002. Capsaicinoids in vegetative
or­gans of capsicum annuum L. in relation to fruiting. Agricultural and Food Chemistry 50:1188-1191.
González-Real, M.M.; Baille, A.; Liu, H.Q. 2008. Influence of fruit load on dry matter and
N-distribution in sweet pepper plants. Scientia Horticulturae. 117:307-315.
Heuvelink, E.; Körner O. 2001. Parthenocarpic fruit growth reduces yield fluctuation and
Blossom-end Rot in sweet pepper. Annals of Botany 88:69-74.
Marcelis, L.F.M.; BaanHofman-Eijer, L.R. 1997. Effects of seed number on competition
and dominance among fruits in Capsicum annuum L. Annals of Botany 79:687-693.
Osman, A.; George, R.A.T. 1984. The effet of mineral nutrition and fruit position on
seed yield and quality in sweet pepper (Capsicum annuum L.) Acta Horticulturae
143:133-141.
Sadasivam, S.; Manikkam, A. 1992. Capsaicin. In Biochemical methods for agricultural
sciences (pp. 193-194). New Delhi: Wiley Eastern Limited.
Van der Beek, J.G.; Ltifi, A. 1991. Evidence for salt tolerance in pepper varieties (Capsicum annuum. L.) in Tunisia. Euphytica. 57:51-56.
Zewdie, Y.; Bosland, P.W. 2000. Pungency of chile (Capsicum annuum L.) fruit is affected
by node position. HortScience 35:1174.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Effect of storage on stability of capsaicin and colour content in chilli
(Capsicum annuum L.)
J. Pandey1, J. Singh2, R. Kumar2, K. Srivastava1, S. Kumar2, M. Singh2, B. Singh2
1
Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University,
Varanasi, 221005. Contact: [email protected]
2
Indian Institute of Vegetable Research, PO Box 5002, PO BHU, Varanasi-221005
Abstract
The objective of this study was to assess the stability of quality traits in stored chilli powder.
The red ripe fruits of eight chilli genotypes (Capsicum annuum L) were evaluated for quality
parameters viz capsaicin, extractable colour and colour value in freshly grinded powder as
well as in powder stored at ambient temperature for six months. Significant differences
(p<0.05) were recorded for the quality parameters amongst the genotypes. During six month
storage at ambient temperature degradation of capsaicin was recorded in the range of 11.11
– 19.51 %, whereas extractable colour and colour value degraded from 52.52 -78.02, 52.59
– 78.38 % respectively. Large difference was recorded between the analyzed parameters for
fresh and stored powder for colour traits in comparison with capsaicin content. Capsaicin
content in fresh powder ranged from 0.22 - 0.63 %, whereas, in stored powder varied from
0.19 - 0.52 %. Extractable colour content in fresh powder ranged from 205 ASTA to 369.62
ASTA, whereas, extractable colour in stored powder varied only from 59.04 -175.48 ASTA.
Colour value in fresh powder varied from 81840 c.u. to 148252.5 c.u., whereas, in stored
powder it ranged from 23430. to 70290c.u. Average values of above parameters expressed
inverse relationship with storage period. From this experimentation it may be concluded
that the capsaicin is a stable trait than the powder colour in chilli.
Keywords: Chilli, capsaicin, extractable colour, colour value and stability
Introduction
The genus Capsicum consists of approximately 25 wild and 5 domesticated species.
Cultivated Capsicum is originated from central and south America (Pickersgill, 1991). Chilli
(Capsicum annuum L.) is become used as vegetables, spice, colourant and has some
therapeutic applications. Chilli is known for its pungent principle. Pungency in chilli is due
to capsaicin and its analogous (Thresh, 1876), which are known as capsaicinoids.
Capsacinoids are exclusively being found with in the genus Capsicum. More than 15
different capsaicinoids are known to be found in pepper fruits, which are synthesized and
accumulated in the epidermal cells of placenta of the fruits. There are so many uses of
capsaicinoids The pharmaceutical industry uses capsaicin as a counter-irritant balm for
external application (Carmichael, 1991) to stop pains of arthritis (rheumatoid arthritis,
osteoarthritis), artily diseases (peripheral neuropathies) and to relive cramps (Cordell and
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Advances in Genetics and Breeding of Capsicum and Eggplant
Araujo, 1993; Bosland, 1996). The red fruit colour originates from the carotenoid pigments.
More than 30 different pigments have been identified in the fruits (Bosland and Votava,
2000). The red colour in chilli is due to pigments capsanthin and capsorubin collectively
known as oleoresin, which is exclusively produced in pepper fruits. Colour extracts from
non-pungent fruits of chilli is used as a natural colouring agent in food products mainly in
food processing industries, beverage industries to improve colour and flavors of its
products. In Japan and South Korea, red colour (oleoresin) is mixed with chicken feed in
order to impart attractive red colour to chicken skin and yolk (Kumar et al., 2006). The
extractable colour is the total pigment content measured by a spectrophotometer process,
designated ASTA units (ASTA, 1985). In general, higher the ASTA colour value, the greater
the effects on the brightness or richness of the final product. Colour value is the principal
criterion for assessing the quality of paprika. Colour retention in stored powder is a major
problem in most of the oleoresin extracting factories and enterprises. Therefore this
experiment was planned to observe the effect of storage on the colour and capsaicin
quality of the chilli powder.
Material and methods
Seeds of all the germplasm material were sown in nursery beds. Thirty days old seedlings
were transplanted on raised bed at the distance of 60 x 45 cm. Recommended agronomic
and plant protection practices were exercised in order to raise healthy crop. Red ripe
fruits were collected from 3-5 plants and bulked before the analysis. The fruit samples
were oven dried and grinded for the biochemical estimations, after quantifying capsaicin
and oleoresin in freshly grinded powder the same was stored for six months at ambient
temperature for the study of the degradation of the quality components.
Capsaicin estimation by spectrophotometer
Capsaicin content in chilli powder was estimated by the method of Thimmaiah (1999).
Harvested red ripe fruits were dried in an oven at 60±20 C until it was completely
dehydrated. Samples were ground to fine powder and passed through a 2 mm sieve. For
the extraction of capsaicin, 500 mg of powder was taken in a centrifuge tube and
dissolved in 10 ml of dry acetone by continuous shaking on a mechanical shaker at room
temperature for 3-5 hours. Thereafter, samples were centrifuged for 10 minutes at
10,000 rpm, and after centrifugation, 1 ml of supernatant was pipetted out in a test
tube. The supernatant was evaporated to dryness on a hot water bath. The residue was
dissolved in 5 ml (0.4%) NaOH and 3 ml (3.0%) phosphormolybdic acid by vigorous shaking.
The solution was gently shaked using vortex and incubated for one-hour and solution was
filtered into centrifuge tubes and centrifuged for 10 min at 5000 rpm. The absorbance
of the sample was recorded at 650 nm using UV-visible double beam (Shimadzu UV-1601)
spectrophotometer. The blank solution contained 5 ml 0.4% NaOH and 3 ml (3.0%)
phosphomolybdic acid. The capsaicin percentage was calculated by following formula:
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Capsaicin (%) =
µg Capsaicin
1000 x 1000 x
100
1
x
100
2
Advances in Genetics and Breeding of Capsicum and Eggplant
Extractable colour and colour value estimation
The procedure described by AOAC (1995) was used to determine the extractable color
and color value. Acetone (5 ml) was used to dissolve colour of 20 mg of grinded powder
by continuous shaking. This process was repeated by adding 5 ml of acetone in the
sample followed by continuous shaking. The absorbance was recorded at 455 nm and 460
nm using a UV-visible double beam (Shimadzu uv-1601) spectrophotometer. The
absorbance was adjusted in the range of 0.25-0.50. Blank reference was set using
acetone. Then the extractable colour and colour value were calculated by the following
formulae.
Extractable colour =
I =
f
Absorbance at 460 nm x 16.4
Sample weight (g)
x If
Declared absorbance of Glass Reference
Absorbance obtained at 465 nm on glass reference standard
If = Instrument correction factor
Colour value =
Absorbance at 462 nm x 6600
Sample weight (g)
Data analyses
All the above analyses were performed in triplicate. The range and mean were calculated
to assess the variability. Data were subjected to one-way analysis of variance (ANOVA)
using standard statistical methods. Means were tested with p≤ 0.05 and p≤ 0.01
confidence level.
Results and discussion
The analysis of variance revealed significant differences (p≤ 0.05 and p≤ 0.01) between
chilli genotypes for the quality components of the fruits. Data presented in Table 1 and 2.
Capsaicin content in fresh and stored powder
Capsaicin content in fresh powder ranged from 0.22 - 0.63 %, whereas, in stored powder
varied from 0.19 - 0.52 %. In fresh powder, maximum capsaicin content was recorded in
LCA-235 (0.63%), followed by 92-1203 (0.55%), whereas, minimum capsaicin was observed
in Bullet-B3 (0.22%), followed by Bullet-B1 (0.24%), in stored powder maximum capsaicin
content was recorded in LCA-235 (0.52 %.), whereas, minimum capsaicin was observed
in Bullet-B3 (0.19%).
Extractable colour content in fresh and stored powder
Extractable colour content in fresh powder ranged from 205 ASTA to 369.62 ASTA in the
tested genotypes and the maximum extractable colour was recorded in EC-391094
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Advances in Genetics and Breeding of Capsicum and Eggplant
(369.62 ASTA), followed by LCA-235 (332.10 ASTA), whereas, the minimum extractable
colour was recorded in IC- 119310B (205 ASTA), followed by 92-1203 (216.48 ASTA).
Extractable colour in stored powder varied from 59.04 to 175.48 ASTA. EC-391094 (175.48
ASTA) had maximum extractable colour, followed by Bullet-B1 (150.06 ASTA). The
minimum extractable colour in stored powder was found in BS-38 (59.04 ASTA), followed
by IC- 119310B (72.98 ASTA) .
Colour value content in fresh and stored powder
Colour value in fresh powder varied from 81840.0 c.u. to 148252.5 c.u., and the maximum
colour value was recorded in EC-391094 (148252.5 c.u), followed by LCA- 235 (134310
c.u), whereas, minimum colour value was recorded in IC-119310B (81840.0 c.u) followed
by 92-1203 (90750 c.u.). Colour value in stored powder ranged from 23430 to 70290c.u.
The maximum colour value was recorded in EC-391094 (70290.0 c.u.) followed by
Bullet-B1 (59730 c.u.), whereas, the minimum colour value was recorded in BS-38 (23430
c.u.), followed by IC- 119310B (28710 c.u.).
From the result it has been observed that in the fresh and stored samples, Capsaicin was
degraded from 11.11 – 19.51 %. Maximum capsaicin percent degradation was recorded in
DC-24, whereas, minimum was observed in BS-38. The result clearly indicates that there
was significant deterioration in the extractable colour and colour value in all the genotypes
(Pandey et al, 2007). The percent deterioration of extractable colour and colour value
ranged from 52.52 to 78.02% and 52.59 to 78.38 % respectively. LCA-235 had maximum
colour deterioration whereas in EC-391094 minimum color deterioration has been
observed. The degradation of colour depends on many factors such as genotype (Lease
and Lease, 1956), moisture content (Malchev et al., 1982), ripening stage at harvest
(Kanner et al., 1979) and healthy status of the fruits before grinding. Red colour in chilli
is due to presence of two major carotenoids i.e., capsanthin and capsorubin collectively
known as oleoresin. Capsnthin contributes up to 60% of the total carotenoids (Bosland and
Votava, 2000). These pigments have been rapidly undergoing oxidative degradation
process such as lipoxygenase catalyzed linolic oxidation (Biacs et al., 1992).
Conclusions
From the table 2 it is evident that the percent degradation in capsaicin content between
the fresh and stored powder is lesser cooperatively colour, whereas extractable colour
and colour content drastically decreased in all the genotypes after storing the powder
for six months at ambient temperature. Therefore from above experimentation, it has
been concluded that the capsaicin is more stable trait then the colour in chilli.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Table 1. Analysis of variance for quality traits in fresh and stored powder of chilli
Mean Sum of Squares
Source of
Variance
Fresh Powder
Stored Powder
D.F.
Capsaicin
(%)
Extractable
colour
(ASTA)
Colour
value
(c.u.)
2
124.53
104278200.00
Treatment
7
11766.69**
Error
14
203.22
Replication
Capsaicin
(%)
Extractable
colour
(ASTA)
Colour
value
(c.u.)
0.0002
48.80
21654320
0.00002
1960608010.37**
0.067**
4988.78**
810863566.07**
0.04386**
20909813.34
0.0004
26.88
2260866.09
0.0003
** Significant at 1 % selection intensity level
Table 2. Quality estimates in fresh and stored powder
Fresh powder
Genotype
Capsaicin
(%)
Six month stored powder
Percent deterioration
in quality trait
Extractable
colour
(ASTA)
Colour
value
(c.u.)
Capsaicin
(%)
Extractable
colour
(ASTA)
Colour
value
(c.u.)
Capsaicin
Extractable
colour
Colour
value
LCA-235
0.63**
332.1**
134310**
0.52**
72.98**
29040**
17.46
78.02
78.38
92-1203
0.55**
216.48**
90750**
0.46**
100.86
39600
16.36
53.41
56.36
IC-119310B
0.31**
205**
81840**
0.25**
72.98**
28710**
19.35
64.40
64.92
DC-24
0.41**
227.14**
91080**
0.33*
102.50
40920
19.51
54.87
55.07
Bullet-B1
0.24**
328**
134310**
0.21**
150.06**
59730**
12.50
54.25
55.53
Bullet-B3
0.22**
264.04
103620.00
0.19**
82**
32010**
13.63
68.94
69.11
BS-38
0.27**
232.88**
90750**
0.24**
59.04**
23430**
11.11
74.65
74.18
EC-391094
0.32*
369.62** 148252.5**
0.26**
175.48**
70290**
18.75
52.52
52.59
Mean
0.36
271.90
109364.06
0.30
101.98
40466.25
16.08
62.63
63.26
Range
(Maximum)
0.63
369.62
148252.5
0.52
175.48
70290
19.51
78.02
78.38
11.11
52.52
52.59
(Minimum)
0.22
205
81840
0.19
59.04
23430
CD at 5%
0.035
24.96
8007.77
0.030
9.07
2633.14
CD at 1%
0.049
36.64
11114.41
0.042
12.60
3654.67
*, **, Significant at 5% and 1% levels, respectively
References
AOAC. 1995. Official Methods of Analysis. Association of Official Analytical Chemists
43.1.02. (971.26).
Biacs, P.A.; Czinkotai, B.; Hoschke, A. 1992. Factors affecting stability of coloured
substances in paprika powders. J. Agric. Food Chem 40:363-367.
271
Advances in Genetics and Breeding of Capsicum and Eggplant
Bosland, P.W.; Votava, E.J. 2000. Peppers: Vegetable and Spice Capsicums. CABI
Publishing, Wallingford, UK.
Bosland, P.W. 1996. Capsicums: innovative uses of an ancient crop. In: Janick J (ed.),
Progress in New Crops. ASHS Press, Arlington, VA, pp. 479-487.
Carmichael, J.K. 1991. Treatment of herpes zoster and postherpetic neuralgia. Amer.
Family Physician 44:203-210.
Cordell, G.A.; Araujo, O.E. 1993. Capsaicin: identification, nomenclature, and pharma­
cotherapy. Ann. Pharmacother 27:330-336.
Kanner, J.; Mendel, H.; Budowskai, P. 1979. Carotene oxidizing factors in red pepper
fruits. J. Food Sci. 43: 709-712.
Kumar, S.; Kumar, R.; Singh, J. 2006. Cayenne/American pepper (Capsicum species). In:
Peter KV (ed), Handbook of Herbs and Spices, Vol. 3. Woodhead Publishing,
Cambridge, UK, pp. 299-312.
Lease, J.G.; Lease, E.J. 1956. Effect of fat soluble antioxidants on the stability of the
red colour or peppers. Food Technol 10:403-405.
Malchev, E.; Ioncheva, N.; Tanchev, S.; Kalpakchieva, H. 1982. Quantitative changes in
carotenoids during storage of dried pepper. Nahrung 26:415-420.
Pandey, J.; Singh , J.; Verma, A.; Singh, A.K.; Rai, M.; Kumar, S. (2007). Storage effect
on colour traits in chilli (Capsicum annuum L) powder. Processed Food Industry. 10
(11):20-24.
Pickersgill, B. 1991. Cytogenetics and evolution of Capsicum L. in chromosome engineering
in plants: genetics, breeding, evolution. Edited by T. Tsuchiya and P. K. Gupta. Part
B. pp. 139-160.
Thimmaiah, S.K. 1999. Standard Methods of Biochemical Analysis. Kalyani Publishers,
Ludhiyna, pp. 301-302.
Thresh, J.C. 1876. Capsaicin the active principal of Capsicum fruits. Pharmaceutical
Journal 7:21.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
QTLs for capsaicinoids content in Capsicum
I. Paran, T. Akler, Y. Borovsky
Institute of Plant Sciences, Agricultural Research Organization, The Volcani Center, Israel.
Contact: [email protected]
Abstract
While the presence or absent of pungency in pepper is inherited as a monogenic trait
controlled by the dominant Pun1 gene, variation in capsaicinoids content among pungent
cultivars is inherited as a quantitative trait. We previously identified a major quantitative
trait locus (QTL) in chromosome 7, termed cap, that controls capsaicinoids content in an
inter-specific F2 cross of the pungent Capsicum frutescens line BG 2816 and the nonpungent C. annuum line Maor. In follow up experiments, we verified the effect of cap7.1
(formerly cap) in additional generations and backgrounds. These included an independent
F2 population of the same cross as described above and an F3 population from the cross of
the pungent C. annuum Perennial and the non-pungent Maor. In addition to cap7.1, we
detected a second QTL in chromosome 7 (cap7.2) in the C. frutescens X C. annuum cross.
In addition to cap7.1 in the Perennial X Maor cross, we detected a second more minor QTL
in chromosome 8 (cap8.1). For all QTLs, the allele associated with increased capsaicinoids
content was originated from the pungent parent. The effect of cap7.1 on capsaicinoids
content was found to be mediated by increasing the transcription level of Pun1. Because
none of the known genes in the capsaicinoids biosynthetic pathway are linked to the mapped
QTLs, we assume that these QTLs are regulators of the pathway and do not encode structural
biosynthetic enzymes.
Keywords: pepper, pungency, molecular markers, quantitative trait locus
Introduction
Pungency results from the accumulation of the capsaicinoid alkaloids in the placenta of
the fruit, and is unique to the Capsicum genus. The pathway for capsaicinoid biosynthesis
is composed of enzymes from the phenylpropanoid and benzenoid metabolisms,
branched-chain fatty acid and branched-chain amino acid biosynthesis (Mazourek et al.
2009). The presence or absence of pungency is controlled by the dominant Pun1 gene
that encodes a putative acyltrasferase which has been postulated to be Capsaicin
Synthase, the last enzyme in the capsaicinoid biosynthesis pathway. Until recently, all
non-pungent accessions of C. annuum examined were found as carrying the recessive
allele at Pun1 which contains a deletion spanning the promoter and the first exon of the
gene (Stewart et al. 2005). Additional non-pungent alleles at Pun1 were detected in C.
frutescens and C. chinense (Stellari et al. 2009).
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Advances in Genetics and Breeding of Capsicum and Eggplant
An additional acyltrasferase was found as associated with pungency because a single
nucleotide polymorphism (SNP) was detected as distinguishing pungent from non-pungent
cultivars, however its role in the capsaicinoid biosynthesis pathway is not known (Lang et
al. 2006; Garces-Claver et al. 2007). Recently, non-pungency as a result of mutations in
other genes than Pun1 was demonstrated (Lang et al. 2009; Stellari et al. 2009). Analysis
of CH-19 Sweet which is a non-pungent C. annuum mutant derived from the pungent CH19 cultivar, indicated that loss of pungency results from mutation in the pAMT gene, a
putative aminotransferase in the capsaicinoid biosynthesis pathway. Additionally, a nonpungent accession was detected in C. chacoense that is controlled by a non-allelic, yet
unknown gene to Pun1, termed Pun2.
Large quantitative variation for capsaicinoid content exits in Capsicum (http://aces.
nmsu.edu/chilepepperinstitute). Quantitative trait locus (QTL) mapping for capsaicinoid
content allowed identification of a major QTL, termed cap, in chromosome 7 (Blum et
al. 2003). Furthermore, six QTLs in chromosomes 3, 4, and 7 were identified by Ben
Chaim et al. (2006). Because non of the genes coding for enzymes in the capsaicinoid
biosynthesis pathway co-localized with these QTLs, it was postulated that they correspond
to genes that regulate the pathway.
The goals of the present study were to (1) verify the effect of the QTL cap in additional
crosses and genetic backgrounds and (2) test the relationship between cap and Pun1.
Materials and Methods
Plant material
The QTL mapping population used in this study was described by Blum et al. (2003) and
was constructed from an F2 population derived from a cross between C. annuum cv.
Maor, a non-pungent bell inbred variety and C. frutescens BG 2816, a pungent wild
pepper accession. This population was used for mapping the QTL cap and reanalyzed in
the present study by adding more markers, mostly SSRs provided by Syngenta Seeds, Inc.
Data for capsaicinoid content were the same as in Blum et al. (2003).
A second population used to map capsaicinoid QTLs is an F3 population from a cross of
Maor and Perennial described by Ben Chaim et al. (2001). The F2 plants were genotyped
with Pun1 and only plants carrying the dominant allele at this locus were included in the
experiment. For measuring capsaicinoid content, F3 families (20 plants per family
arranged in 2 blocks) were grown in the open field in the summer of 2005 and 2006.
Capsaicinoid content measurement
Ten fruits from each pungent plant were harvested at the color break stage, pedicels
were removed, fruits were bulked and dried in an oven at 500C for 5-7 days. Dried fruits
were ground in a coffee grinder and processed for capsaicinoid quantification by HPLC
according to the protocol described by Blum et al. (2003). The values are presented as
ppm for the sum of capsaicin and dihydrocapsaicin (total major capsaicinoids).
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QTL mapping
For QTL mapping, interval and single point QTL analyses were performed with QGENE v.
3.04 software (Nelson 1997) using LOD 3.0 and P ≤ 0.001 as minimum significance levels
for QTL detection. The percentages of phenotypic variation explained by the QTL was
obtained from QGENE.
Expression of Pun1 and Acl1
To determine the expression of Pun1and Acl1, cDNA was synthesized from RNA extracted
from pericarp tissue of plants from the F2 population of Maor x BG 2816 differing at
contrasting alleles at the cap QTL. RNA was extracted using the GenElute Mammalian Total
RNA Kit (Sigma). Semi-quantitative RT-PCR analysis was performed at the linear stage of the
reaction (20 cycles); PCR products were run on Agarose gel, blotted to membrane and
hybridized with the corresponding probe. Quantification of the hybridization signal was
done with the Image Gauge software after exposure in a Phosphor Imager Fuji FLA 5000.
Forward and reverse primers for Pun1 were 5’-TAGTTCCATCTCCTAGATTTG-3’ and 5’-CATG­
TTA­GTTGCTTCTATGG-3’; for Acl1 5’- CCTTCGCTATCTCTTCCTTCA-3’ and 5’-CAATCAA­GTCA­
GCAGCATCT-3’. As a reference gene for determining relative expression level we amplified
Ubiquitin (SGN-U198046) with forward and reverse primers 5’- CTCGCCGACTACAACATCCA-3’
and 5’- TGAGCCCACACTTACCACAG-3’, respectively.
Results and Discussion
QTLs for capsaicinoid content in chromosome 7
Based on the mapping results of Blum et al. (2003), it was inferred that in addition to
cap, a second QTL may exist in the centromeric region of chromosome 7, however,
because of lack of markers in this region we could not establish this significant linkage.
Therefore, based on the map of Ben Chaim et al. (2006), we added SSR markers in the
putative chromosome region. By reanalyzing the QTL data, we were able to identify a
second QTL in chromosome 7. Accordingly, we renamed cap as cap7.1 and the second
QTL as cap7.2 (Figure 1, Table 1).
Figure 1. Interval mapping of QTLs for capsaicinoid content in chromosome 7 in the F2 cross of
Maor X BG 2816. Solid and dashed lines represent Summer and Winter data, respectively.
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Table 1. QTLs for capsaicinoid content (ppm) in the F2 cross of Maor X BG 2816.
Trait
QTL
Marker
AA3
Aa
aa
P value
R2
LOD
cap7.1
NP2510
93.4
383.6
481.3
<0.0001
0.36
14.37
Total capsaicinoids 2
cap7.1
NP2510
56.1
279.3
382.2
<0.0001
0.27
9.24
Total capsaicinoids 1
cap7.2
PG242
142.6
340
495.6
<0.0001
0.24
8.88
Total capsaicinoids 2
cap7.2
PG242
95.4
236.7
416.5
<0.0001
0.21
7.08
Total capsaicinoids
1
summer season; 2 winter season; 3 AA = mean homozygous class for the Maor allele,
Aa = heterozygotes; aa = mean homozygous class for the BG 2816 allele.
1
In order to verify the existence of the two QTLs, we planted an independent F2 population
of 197 individuals from the same cross, measured capsaicinoids content and genotyped
the population with the linked markers at the QTLs. Single marker analysis at cap7.1 and
cap7.2 indicated that both QTLs were significant in the new F2 population (Table 2).
Table 2. Single marker QTL analysis for total capsaicinoid content (ppm)
in a new F2 cross of Maor X BG 2816.
Marker1
QTL
UBC20
cap7.1
CT84
PG242
AA2
Aa
aa
P value
R2
676.44
2,375.92
2,939.74
<0.0001
0.25
cap7.1
836.63
2,434.71
2,845.28
<0.0001
0.20
cap7.2
1,341.12
2,318.07
2,916.42
<0.0001
0.14
Markers for cap7.1 were from Blum et al. (2003); AA = mean homozygous class for the Maor allele,
Aa = heterozygotes; aa = mean homozygous class for the BG 2816 allele.
1
3
Figure 2. Interval mapping of QTLs for capsaicinoid content in chromosomes 7 and 8 in the cross
of Maor X Perennial. The QTL in chromosome 7 was detected in both 2005 (dashed line)
and 2006 (solid line). The QTL in chromosome 8 was detected in 2006.
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In order to test the effect of the QTLs in chromosome 7 in additional genetic backgrounds,
we measured capsaicinoid content in an F3 population derived from a cross of Maor X
Perennial. The progenitor F2 population was genotyped with molecular markers scattered
throughout the genome (Ben Chaim et al. 2001) and the markers were tested for
association with capsaicinoid content measured in the F3 generation during two seasons.
Interval mapping analysis indicated a significant association in 2005 and 2006 with CT84
resides at the cap7.1 region but no significant association in the cap7.2 region (Figure 2,
Table 3). An additional QTL, cap8.1, was detected in chromosome 8 in 2006.
Table 3. Capsaicinoid content (ppm) QTLs in the F3 cross of Maor X Perennial.
Trait
QTL
Marker
AA3
Aa
aa
P value
R2
LOD
Total
capsaicinoids1
E49/M60cap7.1
152-P2
205.1
465.4
619.6
<0.0004
0.14
3.44
Total
capsaicinoids2
cap7.1
E49/M60152-P2
148.2
709.7
921.4
<0.0007
0.16
3.22
Total
capsaicinoids2
cap8.1
E41/M49290-P2
349.9
638.6
1032
<0.0002
0.19
3.7
2005; 2 2006; 3 AA = mean homozygous class for the Maor allele,
Aa = heterozygotes; aa = mean homozygous class for the Perennial allele.
1
To test whether cap7.1 affects capsaicinoid content by regulating the expression of
Pun1, we extracted RNA from fruit placenta of selected F2 plants from the cross of Maor
X BG 2816. The RNA was used as a template for semi-quantitative RT-PCR analysis of
Pun1 in different genotypic combinations of Pun1 and cap7.1 (Figure 3). The results
show that the expression of Pun1 is almost 2-fold higher in the presence of the BG 2816
allele at cap7.1 (Pun1+cap7.1) compared to the presence of the Maor allele at the latter
locus (Pun1). We also determined the expression of Acl1 from the capsaicinoid biosynthesis
pathway as a function of the presence of cap7.1, however, no significant differences
were observed among the genotypic combinations of Acl1 and cap7.1 (data not shown).
Figure 3. Semi-quantitative RT-PCR analysis for Pun1. In the bottom of each column,
the allelic combination at Pun1 and cap7.1 is indicated. cap7.1 = plants are homozygous
for the BG 2816 allele at cap7.1 and homozygous for the Maor allele at Pun1; Pun1 = plants are
homozygous for the BG 2816 allele at Pun1 and homozygous for the Maor allele at cap7.1;
Pun1+cap7.1 = plants are homozygous for the BG 2816 allele at both Pun1 and cap7.1.
Error bars represent standard errors.
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In conclusion, our mapping data indicate that cap7.1 is a major QTL controlling
capsaicinoid content in Capsicum as it was detected in multiple populations and genetic
backgrounds with the strongest effect on the trait. Additional more minor QTLs exist in
Capsicum that are population-specific. For all QTLs, the allele with increased effect on
the trait was originated from the pungent parent. The recent mapping of genes from the
capsaicinoid biosynthesis pathway and lack of co-localization with the QTLs, indicate
that these QTLs likely represent genes that regulate the pathway. The expression analysis
of Pun1 indicates that the effect of cap7.1 on increase of capsaicinoid content is at least
partially mediated by increasing the expression of Pun1.
References
Ben-Chaim, A.; Paran, I.; Grube, R.; Jahn, M.; Van Wijk, R.; Peleman, J. 2001. QTL map­
ping of fruit related traits in pepper (Capsicum annuum). Theoretical and Applied
Genetics 102: 1016-1028.
Ben-Chaim, A.; Borovsky, Y.; Falise, M.; Mazourek, M.; Kang, B. C.; Paran, I.; Jahn, M.
2006. QTL analysis for capsaicinoid content in Capsicum. Theoretical and Applied
Genetics 113:1481-1490.
Blum, E.; Mazourek, M.; O’Connell, M.; Curry, J.; Thorup, T.; Liu, K.; Jahn, M.; Paran, I.
2003. Molecular mapping of capsaicinoid biosynthesis genes and quantitative trait
loci analysis for capsaicinoid content in Capsicum. Theoretical and Applied Genetics
108: 79–86.
Graces-Claver, A.; Fellman, S.M.; Gil-Ortega, R.; Jahn, M.; Arnedo-Andres, M.S. 2007.
Identification, validation and survey of a single nucleotide polymorphism (SNP)
associated with pungency in Capsicum spp. Theoretical and Applied Genetics 115:
907-916.
Lang, Y.; Yanagawa, S.; Sasanuma, T.; Sasakuma, T. 2006. A gene encoding a putative
acyl-transferase involved in pungency of Capsicum. Breed Science 56: 55–62.
Lang, Y.; Kisaka, H.; Sugiyama, R.; Nomura, K.; Morita, A.; Watanabe, T.; Tanaka, Y.;
Yazawa, S.; Miwa, T. 2009. Functional loss of pAMT results in biosynthesis of cap­si­
noids, capsaicinoid analogs, in Capsicum annuum cv. CH-19 Sweet. The Plant
Journal 59: 953-961.
Mazourek, M.; Pujar, A.; Borovsky, Y.; Paran, I.; Mueller, L.; Jahn, M.M. 2009. A dynamic
interface for capsaicinoid systems biology. Plant physiology 150: 1806-1821.
Stellari, G.M.; Mazourek, M.; Jahn, M.M. 2009. Contrasting modes for loss of pungency
between cultivated and wild species of Capsicum. Heredity In Press
Stewart, C.; Kang, B.C.; Liu, K.; Mazourek, M.; Moore, S.L.; Yoo, E.Y.; Kim, B.D.; Paran,
I.; Jahn, M.M. 2005. The Pun1 gene for pungency in pepper encodes a putative
acyl-transferase. The Plant Journal 42: 675–688.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Occurrence and genotypic differences of flavour-active
volatile 3-isobutyl-2-methoxypyrazine among accessions
of Jalapeno pepper
A. Rodríguez-Burruezo1, A. Fita1, O. Holguin2, M. O´Connell2, P.W. Bosland2
1
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universidad Politécnica de Valencia,
Camino de Vera 14, 46022 Valencia, Spain. Contact: [email protected]
2
Plant and Environmental Science Department. College of Agricultural, Consumer and Enviromental Sciences.
New Mexico State University. Las Cruces (NM), USA.
Abstract
Due to its low content in sugars and organic acids, pungency and aroma are considered the
most relevant flavour active factors in chile peppers. Historically (since the beginning of
20th century), most studies have been focused on pungency and its active compounds:
capsaicinoids. By contrast, aroma has been studied at a lower extent, and the first reports
date from the end of 60s. Rencetly, the interest on this trait has increased and, consequently,
the number of scientific reports on this topic has increased. Up to date, many compunds
(>300) have been identified in the volatile fraction of fresh peppers, although the volatile
profile depends on ripening stage and varietal type. Despite such diversity, only a few
contribute to the aroma. In this respect, 3-isobutyl-2-methoxypyrazine, or bell pepper
pyrazine, due to its very low sensory threshold (2-3 ppt) is considered one of the most
relevant volatile compound for the aroma of peppers, particularly when green and specially
in “jalapeño” and “serrano” types. Studies on volatiles in peppers have been based on
comparing different varietal types (on most ocassions very few cultivars), while there is a
lack of comparative studies to assess differences between genotypes within the same
varietal type. In this experiment we have compared the levels of bell pepper pyrazine in
unripe fruits from 10 accessions of Jalapeno type, many of them ancient landraces.
Extraction was performed by head space-solid phase micro extraction (HS-SPME) of 1 g
samples, sliced in 2 mm pieces, placed inmediately in 20 mL headspace vials and sealed
with a septum and an aluminium cap. The volatile fraction was analysed by a gas
cromatograph directly coupled to a mass spectrometer (GC-MS). Our results confirmed the
relevance of this pyrazine in the volatile fraction of green jalapenos. The peak corresponding
to this compound was found in the chromatograms of all the accessions studied, altough
quantitative differences were detected among accessions. Thus, levels of relatively modern
cultivars like Early Jalapeno or Mucho Nacho were among the lowest (195-229x103 peak
area units, p.a.u.), while the group of landraces showed a wide range of higher values,
comprised between 198 and 461x103 p.a.u. with accessions J656 and J657 showing the
highest values. Probably, the phylogenetic proximity of these landraces to their ancestor
the Serrano, whose levels in this pyrazine are among the highest within C. annuum, may
explain such contents. Our results suggest that landraces might be utilised as sources of
variation to improve flavor in modern cultivars of the same varietal type.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
A versatile PCR marker for pungency trait in Capsicum spp.
M.J. Rodríguez-Maza, A. Garcés-Claver, M.S. Arnedo-Andrés
Centro de Investigación y Tecnología Agroalimentaria de Aragón, Avda. Montañana 930, 50059-Zaragoza, Spain.
Contact: [email protected]
Abstract
Pungency in pepper (Capsicum spp.) is a relevant trait for pepper researchers and breeders.
The perception of pungency in pepper is due to the presence of a group of compounds named
capsaicinoids and found only within the Capsicum genus. Up to now, how pungency is
controlled, at genetic and molecular level, is not completely elucidated. Non-pungent
peppers result from domestication and its control in pepper fruits is a challenge. A genetic
analysis of the capsaicinoid biosynthesis pathway was performed and DNA sequence analysis
revealed a 15 bp deletion in non-pungent genotypes. PCR primers were designed to amplify
the region where this deletion was identified and they generated specific DNA fragments of
479 bp from non-pungent and 494 bp from pungent genotypes. This polymorphism was tested
in a wide group of genotypes, belonging to several Capsicum species, including pungent and
non-pungent genotypes of C. annuum L., and pungent genotypes of C. chinense Jacq., C.
baccatum L., C. frutescens L. C. pubescens Ruiz & Pavón, C. galapagoense Hunz., C. eximium
Hunz., C. tovarii Eshbaugh, Smith & Nickrent, C. cardenasii Heiser & Smith, and C. chacoense
Hunz. The obtained results demonstrate the suitability of this marker to detect pungent and
non-pungent genotypes in domesticated and wild Capsicum species and therefore its use in
marker assisted selection of the pungency trait. Compared to previous identified markers
associated with this complex character, the one described in this study is more universal
comprising a larger range of Capsicum genotypes.
Keywords: Capsicum spp, marker, pungency.
Introduction
Capsicum spp. is one of the main Solanaceae family members. Pepper’s sensation of
pungency is due to capsaicinoids, compounds synthesized as secondary metabolism
products and only found in placental tissues of Capsicum fruits. Pungency is one of the
most important traits, in terms of quality, and it requires a deep knowledge about its
genetic control. Capsaicinoid biosynthesis pathway, the accumulation and profiles of
these compounds remain still unclear.
Pun1 is the only locus known to date that has a qualitative effect on pungency and it is
required for the presence of pungency (Blum et al., 2002). This locus encodes for an
acyltransferase enzyme named as AT3 (Stewart et al., 2005) with an unknown function.
Several DNA markers linked to pungency have been developed, most of them based on
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the Pun1 locus: the RFLPs, CD35 (Tanksley et al., 1988) and two more (Blum et al.,
2002); two CAPS markers (Blum et al., 2002; Minamiyama et al., 2005) and five SCAR
markers (Lee et al., 2005), also an AFLP and one PAP-SSR marker (Sugita et al., 2005).
Moreover, a major QTL (cap) was identified (Blum et al., 2003) and a later study described
six QTLs controlling capsaicinoid content (Ben-Chaim et al., 2006). More recently a SNP
marker was described in another sequence possibly related to pungency (Garcés-Claver
et al., 2007).
Thus, the aim of this work was to develop a robust and reliable marker for pungency in
Capsicum spp.
Material and methods
Plant materials and phenotyping of Capsicum spp
Six pepper genotypes from different Capsicum species were used for candidate gene
sequencing and analysis. These included one non-pungent, C. annuum Yolo Wonder (YW)
and five pungent, C. annuum ‘SCM-334’ (SCM-334), C. chinense ‘Habanero’ (Hb), C.
chinense ‘C-158’, C. frutescens ‘C-126’, and C. baccatum ‘C-235’. To confirm the utility
of the marker described in this study, it was tested in a wide range of pepper genotypes;
C. annuum, C. chinense, C. baccatum, C. frutescens, C. pubescens, C. galapagoense, C.
eximium, C. tovarii, C.cardenasii, and C. chacoense.
Plants were grown under greenhouse conditions at Zaragoza (Spain), with temperatures
ranging between 15 ºC and 25 ºC, until matured red fruits were collected. To evaluate
pungency, mature red fruits of each genotype were tasted, by at least two trained
persons.
DNA extraction and genome-walking
Total DNA was extracted from leaf tissue of each plant according to Doyle and Doyle
(1987), with minor modifications from Arnedo-Andrés et al. (2002). From a previous
partial DNA sequence, possibly related to pungency (Garcés-Claver et al., 2007), a
complete DNA sequence was firstly obtained from YW. To obtain this sequence, genome
walking was performed using gene-specific primers and universal primers included in the
Universal Genome-Walking Kit following manufacturer’s instructions (Clontech, Palo
Alto, CA).
The PCR products were gel purified using the Montage DNA Gel Extraction Kit (Millipore,
Bedford, MA), and cloned into pGEM-y using the pGEM-t Easy Kit (Promega, Madison, WI).
Sequencing was carried out by the Secugen S. L. (CIB, CSIC, Madrid). A contig was created
using overlapping PCR clones with BioEdit ver. 5.0.6 (Hall 1999).
Obtaining of full-length sequences from Capsicum spp genotypes
Several pairs of primers (Table 1) were generated using the sequence of YW to obtain
full-length sequences for candidate gene in the selected pepper genotypes.
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PCRs were carried out in a 20 µl volume containing 40 ng of genomic DNA, 0,5 pmol.µl-1
of each primer,1x Taq DNA polimerase PCR Buffer, 3 mM MgCl2, 400 µM of dNTPs and 0,5
U of Taq DNA Polymerase (Invitrogen Carlsbad, CA). PCR conditions were 2 min at 94 ºC;
30 s at 94 ºC, 1 min at the annealing temperature (Table 2) and 2 min at 72 ºC for 35
cycles; and 2 min at 72 ºC.
PCR products were separated in a 1,2% agarose gel in 1x TAE buffer and visualized under
UV light. Amplified fragments were treated with ExoSAP-IT (USB, Cleveland, OH)
according to manufacturer protocol, and sequencing was performed by Secugen.
Sequences were aligned using BioEdit ver. 5.0.6.
Table 1. PCR primers set used to amplify the complete sequence.
AT: annealing temperature.
Primer
Sequence (5’→ 3’)
InF
InR
CAAGAACATCTATATGTCGTTTTCTGA
TAAATAATAGTGAAAAGTCCCGCAAC
AT (ºC)
65
F5
R5
TGTGTCATAAAGTGTTGGATAGGG
TCCTTGAGATCTCCTCTTTGTTG
61
F2
R3
ATGGCTTTTGCATTACCATC
AGGCAACGCATGAATCCTAA
55
F7
R4
GGTTTGATTTGACACTGGGTTT
ACCTCAACTTCCTTCCTCAAATTAC
60
F8
R6
ATGCAGCAGGCAGAGGTC
TTGACCGTAAACTTCCGTTG
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Analysis and validation of allele-specific marker
To obtain specific amplification of the marker detected, two primers were designed
flanking the deletion, MAP1F (5’-CCATTAGTCGTTCATTTTTGTTTG-3’) and MAP1R
(5’-TCTGCCCTTGTTGGATTTTC-3’). PCRs were performed using the same conditions as
stated above with an annealing temperature of 55ºC. PCR products were separated on a
3% MetaPhor Agarose (Lonza, Rockland, ME) gel in 1x TAE buffer.
Results and discussion
Phenotyping of pungency trait
The 70 pepper genotypes used in this study were phenotypically tested for the pungent
trait by tasting. There were 16 non pungent and 54 pungent genotypes (Table 2). In all
cases, enough pepper fruits were harvested to obtain consistent data for this trait.
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Table 2. Capsicum spp. genotypes, their phenotypes and results obtained with the
allele-specific marker MAP1. Ph: phenotype; P: pungent; NP: non-pungent;
MAP1 ‘-‘: DNA fragment of 479 bp; MAP1 ‘+’: DNA fragment of 494 bp.
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Genotype
Ph
Ph
MAP1
Capsicum annuum ‘Jupiter’
NP
MAP1 Genotype
-
C. baccatum var. pendulum C-323
P
+
C. annuum ‘Yolo Wonder’
NP
-
C. baccatum var. pendulum C-232
P
+
C. annuum ‘Calatauco’
NP
-
C. baccatum var. pendulum C-233
P
+
C. annuum ‘Cherry Sweet’
NP
-
C. baccatum var. pendulum C-235
P
+
C. annuum ‘Antibois’
NP
-
C. baccatum var. pendulum C-57
P
+
C. annuum ‘Canada Cheese’
NP
-
C. baccatum var. pendulum C-70
P
+
C. annuum ‘Podorok Moldovii’
NP
-
C. baccatum var. pendulum C-117
P
+
+
C. annuum ‘Ikeda-1’
NP
-
C. baccatum var. pendulum C-130
P
C. annuum ‘Cristal’
NP
-
C. baccatum var. pendulum C-134
P
+
C. annuum ‘Doux D’Alger’
NP
-
C. baccatum var. pendulum C-135
P
+
+
C. annuum ‘UF15’
NP
-
C. baccatum var. pendulum C-137
P
C. annuum ‘Morrón de fresno’
NP
-
C. baccatum var. pendulum C-138
P
+
C. annuum ‘Yolo Y’
NP
-
C. baccatum var. pendulum C-131
P
+
+
C. annuum ‘Florida VR2’
NP
-
C. baccatum var. pendulum C-209
P
C. annuum ‘Doux des Landes’
NP
-
C. baccatum var. pendulum C-234
P
+
C. annuum ‘Truhar’
NP
-
C. baccatum var. pendulum C-236
P
+
C. annuum ‘Sweet 3575’
P
+
C. baccatum var. pendulum C-237
P
+
C. annuum ‘Bukeh’
P
+
C. baccatum var. pendulum C-238
P
+
C. annuum ‘Lungo Dolce Sottile’
P
+
C. baccatum var. praetermissum C-172
P
+
C. annuum ‘Agridulce’
P
+
C. baccatum var. praetermissum C-180
P
+
C. annuum ‘SCM-334’
P
+
C. baccatum var. praetermissum C-181
P
+
C. chinense ‘Orange Habanero’
P
+
C. baccatum var. praetermissum C-182
P
+
C. chinense ‘30036’
P
+
C. pubescens C-139
P
+
C. chinense ‘30080’
P
+
C. pubescens C-140
P
+
C. frutescens C-126
P
+
C. pubescens C-60
P
+
C. frutescens C-158
P
+
C. pubescens C-228
P
+
C. frutescens C-161
P
+
C. pubescens C-342
P
+
C. frutescens C-103
P
+
C. eximium C-177
P
+
C. frutescens C-162
P
+
C. tovarii C-261
P
+
C. frutescens C-163
P
+
C. chacoense C-152
P
+
C. frutescens C-164
P
+
C. chacoense C-153
P
+
C. frutescens C-166
P
+
C. chacoense C-154
P
+
C. frutescens C-189
P
+
C. chacoense C-175
P
+
C. galapagoense C-167
P
+
C. chacoense C-176
P
+
C. galapagoense C-179
P
+
C. cardenasii C-306
P
+
Advances in Genetics and Breeding of Capsicum and Eggplant
Sequences analysis
The genomic sequence from YW was obtained using a genome walking approach. In
total, a DNA sequence containing 3658 bp was obtained.
In order to amplify the targeted sequence in the other five pepper genotypes of interest,
the five pairs of primers, designed sequentially from the obtained sequence of YW, were
used to amplify several PCR products of interest. The overlapped fragments from each
genotype were sequenced and assembled to determine the full genomic sequences in
the selected genotypes.
Alignment of these five sequences detected several single nucleotide polymorphisms
(SNPs) and several insertion/deletions (data not shown). Within this second type of DNA
changes, a 15 bp deletion was identified in the non pungent genotype YW whereas it was
absent in the other five pungent pepper genotypes.
Allele specific marker
The specific primers (MAP1F and MAP1R) based on this deletion were developed and the
PCR and electrophoresis conditions were optimized using the six pepper genotypes
where sequencing were performed. A specific and expected DNA fragment of 479 bp was
amplified in all non-pungent genotypes, while the 494 bp fragment was detected in all
the pungent genotypes (Figure 1).
Several heterozygous materials for this trait were also tested and correctly discriminated
(data not shown). Finally, to assess the utility of this marker, the detected polymorphism
was tested in 70 cultivated varieties, including pungent and non-pungent genotypes.
In all cases, the obtained PCR fragment corresponded with the data phenotypically ob­
tai­ned for each genotype, as it is shown in Table 2, and consequently this PCR marker is
useful to assess pungency in a wide range of Capsicum species.
Figure 1. Allelic specific marker used to discriminate between pungent and non-pungent
genotypes. Non-pungent genotypes showed a 479 bp fragment and pungent genotypes
showed a 494 bp fragment. M: 50 bp ladder; 1: YW; 2: SCM-334; 3: C-234; 4: C-235; 5:
C-236; 6: C-237; 7: C-238; 8: C. tovarii C-261; 9: Doux D’Alger; 10: C-306; 11: C-323;
12: Agridulce; 13: UF15; 14: C-342; 15: Morrón de fresno.
Marker assisted selection allows pungency genotyping even before fruit setting, sho­
wing great advantages over phenotypic selection for the presence or absence of
pungency by tasting or by chromatography based methods, that are not suitable for
high-throughput analyses.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Pungency markers based on markers linked to Pun1 locus showed several disadvantages.
CD35 (Tanksley et al., 1988) is at 10 cM away from the locus; Blum et al. (2002) CAPS
marker, is closer, but even is not universally observed between pungent and non-pungent
C. annuum varieties. Also, Minamiyama et al. (2005) marker is restricted to the F2
population where it was designed and the SCARs markers reported by Lee et al. (2005),
based on the deleted region in AT3, were no tested in a large range of different Capsicum
species. Finally, SSR from Sugita et al. (2005) was examined in genotypes from three
different Capsicum species (annuum, chinense, and chacoense) and not always
discriminates between pungency and non pungency.
On the other hand, the cap QTL for capsaicinoid content, described by Blum et al., (2003),
could be useful as a marker for increasing capsaicin content and the QTLs (Ben-Chaim et
al., 2006) controlling capsaicinoid content are consistently and likely alleles with relatively
stable effects that may be useful in breeding programs related to pungency.
In spite of the greater universality of the SNP developed by Garcés-Claver et al, (2007),
not all the Capsicum genotypes were correctly assessed (C. chacoense C-153, C- 154,
C-175, and C-176 and C. pubescens C-139, C-140, and C-342) whereas all these entries
have been correctly genotyped with the marker described here. The MAP1 marker works
in genotypes from the five cultivated species C. annuum, C. baccatum, C. chinense, C.
frutescens and C. pubescens as well as in wild species C. galapagoense, C. eximium, C.
tovarii, C. cardenasii, and C. chacoense.
Nowadays, the marker here described, is the most universal marker for pungency
comprising a wide range within the Capsicum genus, including some species where other
pungency markers do not work. In addition, this robust, co-dominant, and one-step PCR
marker could be applied in large-scale breeding programs to marker assisted selection
for pungency trait at early stages of development and with a little amount of plant
material required.
Acknowledgements
This study was supported by the Spanish Ministry of Science (project INIA (RTA200800095-00-00) and by the Aragon Government (Group A16).
References
Arnedo-Andrés, M.S.; Gil-Ortega, R.; Luis-Arteaga, M.; Hormaza, I. 2002. Development
of RAPD and SCAR markers linked to the Pvr4 locus for resistance to PVY in pepper
(Capsicum annuum L.). Theoretical and Applied Genetics 105:1067-1074.
Ben-Chaim, A.; Borovsky, Y.; Falise, M.; Mazourek, M.; Kang, B.C.; Paran, I.; Jahn, M.
2006. QTL analysis for capsaicinoid content in Capsicum. Theoretical and Applied
Genetics 113 8:1481-1490.
Blum, E.; Liu, K.; Mazourek, M.; Yoo, E.Y.; Jahn, M.M.; Paran, I. 2002. Molecular mapping
of the C locus for presence of pungency in Capsicum. Genome 45:702-705.
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Blum, E.; Mazourek, M.; O’Connell, M.A.; Curry, J.; Thorup, T.; Liu, K.; Jahn, M.M.; Pa­
ran, I. 2003. Molecular mapping of capsaicinoid biosynthesis genes and quantitative
trait loci analysis for capsaicinoid content in Capsicum. Theoretical and Applied
Genetics 108:79-86.
Doyle, J.J.; Doyle, J.L. 1987. A rapid DNA isolation procedure for small quantities of
fresh leaf tissue. Phytochemistry Bulletin 19:11-15.
Garcés-Claver, A.; Moore Fellman, S.; Gil Ortega, R.; Jahn, M.M.; Arnedo Andrés, M.S.
2007. Identification, validation and genotyping of a single nucleotide polymorphism
SNP associated with pungency in Capsicum spp. Theoretical and Applied Genetics
115, 7: 907-916.
Lee, C.J.; Yoo, E.Y.; Shin. J.H.; Lee, J.; Hwang, H.S.; Kim, B.D. 2005. Non-pungent
Capsicum contains a deletion in the Capsaicinoid synthetase gene, which allows
early detection of pungency with SCAR markers. Molecular Cells 19:262-267.
Minamiyama, Y.; Kinoshita, S.; Inaba, K.; Inoue, M. 2005. Development of a cleaved
amplified sequence (CAPS) marker linked to pungency in pepper. Plant Breeding
124:288-291.
Stewart, C.; Kang, B.C.; Liu, K.; Mazourek, M.; Moore, S.L.; Yoo, E.Y.; Kim, B.D.; Paran,
I.; Jahn, M.M. 2005.The Pun1 gene for pungency in pepper encodes a putative acyltransferase. Plant Journal 42:675-688.
Sugita, T.; Kinoshita, T.; Kawano, T.; Yuji, K.; Yamaguchi, K.; Nagata, R.; Shimizu, A.;
Chen, L.; Kawasaki, S.; Todoroki, A. 2005. Rapid construction of a linkage map
using high-efficiency genome scanning/AFLP and RAPD, based on an intraspecific,
doubled-haploid population of Capsicum annuum. Breed. Science. 55: 287-295.
Tanksley, S.D.; Bernatzky, R.; Lapitan, N.L.; Prince, J.P. 1988. Conservation of gene
repertoire but not gene order in pepper and tomato. Proccedings of the National
Academy of Science. 85:6419-6423.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Traditional eggplant varieties and their hybrids:
Vitamin C characterization
R. San José1, M.C. Sánchez1, M. Cámara1, J. Prohens2, F. Nuez2
1
Dpto. Nutrición y Bromatología II. Bromatología. Facultad de Farmacia. Universidad Complutense de Madrid.
Pza. Ramón y Cajal s/n, 28040 Madrid, Spain
2
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universidad Politécnica de Valencia,
Camino de Vera 14, 46022 Valencia, Spain. Contact: [email protected]
Abstract
Eggplant (Solanum melongena L.) fruits have great nutritive potential due to their high
fiber content as well as high phenolics concentration that results in a high antioxidant
capacity. Most of the commercial production of eggplant in Western Europe is based on the
‘Black’ and ‘Striped’ types of eggplant. Three eggplants from these types (one black, one
striped and one Almagro eggplant, a typical Spanish type) were selected for this study. The
aim of this work was to evaluate the differences in vitamin C composition of three traditional
(H-11, CS-16 and IVIA-371) eggplant varieties and their hybrids, cultivated both in open air
and greenhouses. Samples were analyzed for: pH, titratable acidity, dry matter and vitamin
C (both ascorbic acid, AA and dehydroascorbic acid, DHA fractions). As it has been observed
in previous studies, the DHA form was the major one in all samples, possibly due to the
activity of ascorbate-oxidase at pH levels of 5-6, as was found in the samples. The results
of physicochemical parameters on the six varieties analyzed in both growing conditions
were similar, with no significant differences in vitamin C content of parental varieties
depending on their growing conditions, and significant differences in case of hybrids, but
not as clear as in previous studies. Vitamin C content in hybrids for both growing conditions
was in between the parental values. The Almagro eggplant type, H-11, showed the highest
vitamin C content in both open field and greenhouse conditions (21.60 and 21.70 mg/100 g,
respectively) as well as AA content (6.81 mg/100 g under open field conditions and 6.10
under greenhouse conditions). Although most of the Vitamin C is lost during the cooking
processes, Vitamin C has been shown to prevent fruit flesh browning and, therefore,
increases in their concentration are desirable.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Exploring the variation of health-related compounds in pepper
Wahyuni1,2, A.R. Ballester1, E. Sudarmonowati2, R.J. Bino3, A.G. Bovy1
1
Plant Research International, Droevendaalsesteeg 1, Wageningen 6708PB, The Netherlands.
Contact: [email protected]
2
RC for Biotechnology, Indonesian Institute of Sciences, Jl. Raya Bogor KM. 46, Cibinong,
Bogor 16910, Indonesia.
3
Wageningen University, Laboratory of Plant Physiology, Arboretumlaan 4, 6703 BD Wageningen,
The Netherlands
Abstract
Pepper (Capsicum spp.) is a major constituent of the human diet, consumed as vegetable
or spice. In addition to its attractive color, aroma and taste, pepper is a rich source of
health-related metabolites, such as carotenoids, capsaicinoids, vitamin A, ascorbic acid
(vitamin C), tocopherols (vitamin E), and flavonoids. These are expected to enhance the
human immune system and prevent degenerative diseases. The level and composition of
these compounds varies greatly due to genotypic differences, fruit maturity, environmental
conditions and processing methods. However, these results were mainly based on studies
conducted with limited numbers of pepper genotypes or varying growth conditions, making
comparisons very difficult. To gain insight in the metabolic diversity of a broad range of
Capsicum germplasm, we explored the variation in health-related compounds among 32
diverse pepper accessions. These represented four crossable Capsicum species, C. annuum,
C. chinense, C. frutescens and C. baccatum and included commercial cultivars, landraces
and wild accessions. The accessions were obtained from the Centre for Genetic Resources
(CGN) and were selected for their uniqueness in fruit morphologies, pungency, and country
of origin. They were grown under controlled conditions in a greenhouse in Wageningen (The
Netherlands). Ripe fruits were harvested and analyzed for the above-mentioned healthrelated metabolites, using high-performance liquid chromatography coupled with spectral
absorbance and fluorescence detector. The results showed a large variation in levels and
composition of the metabolites analyzed. Most accessions were rich in vitamin C, which was
up to 1-2 times higher than the recommended daily intake level. One of the accessions
contained outstanding levels of vitamin E and A and another accession had a remarkable
quercetin level, up to 4 times higher than the average flavonoid level found in the germplasm
collection. Moreover, both accessions were low pungent due to their very low capsaicinoid
levels. These outstanding accessions are potential candidates for breeding programs aimed
at developing new pepper cultivars with improved consumer quality characteristics.
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SESSION IV.
BREEDING FOR YIELD
1. SPICY PROJECT
SYMPOSIUM
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Exploratory QTL analyses of some pepper physiological traits
in two environments
N.A. Alimi1,2, M.C.A.M. Bink2, A. Dieleman3,4, A.M. Sage-Palloix1, R.E. Voorrips4,
V. Lefebvre1, A. Palloix1 , F.A. van Eeuwijk2
1
INRA- Avignon, GAFL UR 1052, BP 94, 84143 Montfavet Cedex France.
Contact: [email protected]; nurudeenadeniyi, [email protected] 2Wageningen UR
Biometris, P.O. Box 100, 6700AC, Wageningen, The Netherlands
3
Wageningen UR Greenhouse Horticulture, P.O. Box 644, 6700 AP, Wageningen, The Netherlands
4
Wageningen UR, Plant Research International, P.O. Box 16, 6700 AA, Wageningen, The Netherlands
Abstract
The use of molecular breeding techniques has increased insight into the genetics behind
phenotypic differences and led to selection of genotypes having favourable traits. Continuous
monitoring of environmental conditions has also become an accessible option. Rather than
single trait evaluation, we would prefer smarter approaches capable of evaluating multiple,
often correlated and time dependent traits simultaneously as a function of genes (QTLs) and
environmental inputs, where we would like to include intermediate genomic information as
well. In this paper, an exploratory QTL analysis over two environments was undertaken using
available genetic and phenotypic data from segregating recombinant inbred lines (RIL) of
pepper (Capsicum annuum). We focused on vegetative traits, e.g. stem length, speed of stem
development, number of internodes etc. We seek to improve the estimation of allelic values
of these traits under the two environments and determine possible QTL x E interaction.
Almost identical QTLs are detected for each trait under the two environments but with
varying LOD scores. No clear evidence was found for presence of QTL by environment
interactions, despite differences in phenotypes and in magnitude of QTLs expression. Within
the EU project SPICY (Voorrips et al., 2010 this issue), a larger number of environments will
be studied and more advanced statistical analysis tools will be considered. The correlation
between the traits will also be modelled. The identification of markers for the important QTL
(Nicolaï et al., 2010 this issue) will improve the speed and accuracy of genomic prediction of
these complex phenotypes.
Keywords: QTLs, SPICY project, pepper, molecular markers.
Introduction
The use of molecular breeding techniques has contributed considerably to the unraveling
of crop traits that have impacted the quality and yield of plant products. It has increased
insight into the genetics behind the genotypic differences and allows breeders to achieve
earlier and more accurate selection of genotypes having favorable traits. Yield in
agronomic and horticultural crops is a composite trait with many underlying traits and
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genetic factors that may mask or accentuate each other and also interact with
environmental factors. Dealing with such a complex trait requires more advanced
approaches capable of evaluating multiple traits simultaneously rather than single trait
evaluation. This will enable breeders to investigate issues related to pleiotropy and
genetic linkage that underlie commonly observed genetic correlations between traits.
For such complex traits exhibiting considerable genotype by environment interaction,
these QTLs have to be analyzed by considering their combination under different
environment using the so called QTL x E analysis. The specific goal of this work is
therefore to study the presence and magnitude of interaction between QTLs and
environment.
Materials and methods
Data Sources and Description
Data from the first SPICY experiment at Wageningen University and Research Center
(WUR), the Netherlands and the already published data from INRA, France (Barchi et al,
2009) are used. The genotypes are from the fifth generation of Recombinant Inbred
Lines (RILs) of an intraspecific cross between large – fruited inbred cultivar ‘Yolo Wonder’
(YW) and the hot pepper cultivar ‘Criollo de Morelos 334’ (CM 334). There are a total of
297 RILs from the INRA experiment from which a subset of 149 lines was selected in the
WUR experiment, using the MapPop software (Brown and Vision 2000), for selective
phenotyping. The 149 most informative individuals were selected using the full linkage
map as the input file, and the maximum bin length (eMBL) as the selection criterion. The
genetic linkage map was constructed from genotypic data on a set of 587 markers (507
AFLPs, 40 SSRs, 19 RFLPs, 17 SSAPs and four STSs). A total of 489 markers were assembled
into 49 linkage groups (LGs). Twenty-three of these LGs, composed of 69% of the markers
and covering 1553 cM, were assigned to one of the 12 haploid pepper chromosomes,
leaving 26 small LGs (304 cM) unassigned (Barchi et al., 2007).
The WUR data was obtained in a glasshouse experiment (glasshouse trial) in the
Netherlands between December and May (winter/spring season). The plants were
planted by randomizing genotypes in a designed but unbalanced way across four
compartments in replicates of 4, 8 or 16 plants per genotypes. The replicates occurred
within and between compartments. The data from INRA were measured in open field
cultivation (open field trial) between July and August (summer season) in the south of
France, in a randomized complete block design with 3 blocks of 3 individual plants
(repeats) per genotype and block.
This paper concentrates on the following five traits that were in common in the two
experiments:
1.The primary axis length (Axl) defined as the length (in cm) of the primary axis from
the cotyledons to the first branch;
2.The number of leaves on the primary axis (Nle);
3.The mean internode length (Inl) given by the ratio Axl:Nle in cm;
4.The axis growth speed (Axs) given by the ratio Axl:(Flw-15 days), in cm.day-1, in which
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Flw is the number of days from sowing to first flower anthesis from which the 15 days
corresponding to the time of hypocotyl and cotyledons emergence after sowing were
deducted to obtain the growth time of the axis; and
5.The mean internode growth time (Int) given by the ratio (Flw-15 days):Nle, in day.
internode-1.
The focus of this paper is the analysis of these common traits to discern if the same QTLs
underlie identical traits in the two environments and possible interaction between QTL
and environment.
Data Evaluation
Each trait was graphically explored for possible variation across blocks and presence of
extreme observations (outliers). Further, multivariate analysis of variance (MANOVA)
models were fitted to the traits simultaneously across blocks and genotypes. This model
allows (a) calculation of trait heritability; (b) quantification of the effect of genotype
and/or blocks on the traits and significance testing of these effects and (c) obtaining
least square means per genotype after accounting for block and interaction effects.
The magnitude and pattern of correlation between traits in each experiment and across
experiments are explored where correlation is expected between the original and
derived traits.
Quantitative Trait Locus (QTL) Analysis
QTL detection based on interval mapping (Lander & Botstein, 1989) using the obtained
least square means for all traits and the genetic map developed by Barchi et al. (2007),
was done with MapQTL software (Van Ooijen, 2004). The significance thresholds for
putative QTLs are derived via permutation (10000 runs) of marker genotype and trait
phenotype data.
QTL x Environment (E) Interaction Analysis
Putative QTL by environment interactions were studied for the five common traits by
considering for each genotype the difference (e.g. Axl_diff) and mean (e.g. Axl_ave) for
each trait over the two environments. Identification of QTL for the trait mean would
indicate that the QTL is expressed similarly in both environments, i.e., absence of
interaction. Identification of QTL for the trait difference would indicate that the QTL is
expressed differently, i.e., presence of interaction. These pairs of derived traits are
analyzed using interval mapping, similarly to the original traits. If a QTL is detected
either for mean or difference, its effect size and the percentage of the effect size to the
parental differences in the two trials are calculated and presented.
Result and discussion
Trait Evaluation
The variation between the three blocks in the open field trial (fig. 1) is negligible for all
the traits as the difference in trait means across blocks is small. The variation across
blocks in the glasshouse trial is slightly larger but not significant (fig. 2). Within each
block however, there is prominent variation due to the presence of different genotypes,
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i.e., large genotypic variability. This genotypic variability is more clearly seen in the
glasshouse trial. There are also indications for very few possible outlying or rather
extreme observations. The influence of these outliers was not confirmed yet and they
were left in the data. Mean values are comparable between trials, except for Internode
length with values lower than 2 cm in open field trial and close to 3.5 cm in glasshouse
trial and axis growth speed with a mean value of around 5 cm/day in open field trial and
about 10 cm/day in glasshouse trial. The range of observations for traits in glasshouse
trial is generally higher as compared to the same traits in open field trial. Some of the
traits show very little skewness especially in the glasshouse trial.
Within the open field trial, the correlation among primary axis length (Axl), number of
leaves (Nle) and axis growth speed (Axs) is high and positive (table 1). Internode growth
time (Int) is negatively correlated with all other traits except internode length (Inl),
with which it is weakly but positively correlated. Internode length (Inl) shows high
correlation with axis length (Axl) and axis growth speed (Axs). This same trend is seen in
the glasshouse trial but with generally lower magnitude. The orientation of measurements
for a particular trait in the two trials (e.g. Axl1 and Axl2) coincides as revealed by their
correlation coefficients. However, low correlations were observed between the trials for
Internode length (Inl) and Axis growth speed (Axs).
Figure 1. Box plots showing possible trait variation across blocks in the open field trial.
The mean trait values for the two parents and estimated trait heritability from the
MANOVA model are also listed in table 1. Genotype is consistently significant for all the
traits, while block effect is seen in some of the traits especially in glasshouse trial,
confirming what was observed from the graphical exploration. There is no interaction
between genotype and blocks. The sufficiency of this model to handle the unbalanced
settings in the glasshouse trial is not guaranteed and the randomness created by
genotype and blocks in the two trials deserve to be further explored. Also, the correlation
within each trial is not explicitly modeled. The essence of using this model is to obtain
least square means of the traits per genotype while accounting for possible block and
interaction between genotype and block effects. Heritability is generally higher for
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traits in the open field trial except for axis length. However, our calculated heritability
for the open field trial is lower than those reported in Barchi et al. (2009). This may be
due to a combination of difference in sample size (here we studied a subset of 149 out
of the original 297 RILs), the underlying model assumption and the correction for block
effects. The parental lines display contrasting phenotypes with parent Yolo Wonder
showing shorter axis length, fewer leaves, slower axis development but faster leaf
development. This is consistent with what has been reported in the literature for these
pepper cultivars. The glasshouse trial shows consistently higher rates of vegetative trait
development, as is also revealed from the box plots (figures 1 & 2).
Figure 2. Box plots showing possible trait variation across blocks in the glasshouse trial.
QTL Interval Mapping Analysis
The QTL test statistic (LOD score) profiles for significant linkage groups are presented in
figure 3. In general, the patterns of the profiles for most linkage groups are consistent
among the two trials; however, the magnitude of LOD scores can be different. The latter
implies that a QTL may be significant in one trial but insignificant in the other trial. For
example, such QTL are found for axis length (Axl) on chromosome 1, number of leaves
(Nle) on chromosome 3 and internode growth time (Int) on chromosome 3. These might
indicate that some QTLs are better expressed in certain environment though may be
detected in various environments. Furthermore, some QTL are detected only in one trial.
For example on chromosome 6, QTLs were found for internode length (Inl) and axis speed
(Axs) in the open field trial but not in the glasshouse trial. There is also a possibility of
QTLs for axis length (Axl) and axis speed (Axs) on chromosome 12 in the open field trial.
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Table 1. Correlation coefficients, parent means and heritability for common
traits in the two experiments
OPEN FIELD
Traits
a
Axl1
Nle1
Inl1
GLASSHOUSE
Int1
Axs1
Axl2
Nle2
Inl2
Int2
Axs2
GLASSHOUS
OPEN FIELD
Correlation Matrix
Axl1
Nle1
0.61
Inl1
0.62
-0.23
Int1
-0.48
-0.88
0.28
Axs1
0.94
0.50
0.66
Axl2
0.64
0.48
0.29
-0.36
0.55
Nle2
0.43
0.81
-0.27
-0.69
0.32
0.54
Inl2
0.10
-0.33
0.44
0.21
0.21
0.33
-0.47
Int2
-0.33
-0.76
0.35
0.74
-0.28
-0.45
-0.93
0.36
Axs2
0.35
0.20
0.22
-0.30
0.43
0.66
0.17
0.77
-0.52
-0.31
Parental Means and Trait Heritability
Yolo
Wonder
18.01
12.12
1.49
3.86
3.93
21.75
11.56
2.53
4.11
6.17
Criollo de
Morelos
334
22.92
12.50
1.85
3.09
6.01
38.75
15.75
3.25
3.06
10.64
Parental
Differences
-4.92
-0.38
-0.36
0.77
-2.08
-17
-4.19
-0.72
1.05
-4.46
Heritability
0.78
0.80
0.51
0.62
0.86
0.97
0.19
0.42
0.16
0.94
a
Axl1, Nle1, Inl1, Int1 and Axs1 stand for primary axis length, number of leaves on the primary axis,
mean internode length, mean internode growth time and axis growth speed respectively in the open
field trial; while Axl2, Nle2, Inl2, Int2 and Axs2 represent primary axis length, number of leaves on the
primary axis, mean internode length, mean internode growth time and axis growth speed respectively
in the glasshouse trial.
QTL x Environment interaction
Several QTL were detected for trait means between the two environments but no
significant QTL was detected for trait differences (table 2). The effect sizes of the
detected QTL are mostly in the direction of the parental differences in both trials though
with varying magnitudes (fig. 4). On chromosome 3, there are QTL for means across the
two trials for all five vegetative traits. The effect sizes of QTL detected on chromosome
3 and LG 22 for internode length mean vary significantly between the two trials with the
effect size greater in the glasshouse trial. There are however some QTL for trait means
whose effect sizes are in opposite direction of parental differences in both trials. Such
QTL for average could be seen for axis length (Axl) and axis speed (Axs) detected on
chromosome 3, internode growth time (Int) and number of leaves (Nle) on chromosome
12 and axis speed (Axs) on LG 24.
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Figure 3. QTL profiles of significant chromosomes (P1, P2 etc.) or unassigned
linkage groups (LG29, LG45) in both trials. Abbreviated names of traits are
explained in section Materials and Methods.
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Table 2. Result of the QTL x E Analyses.
Trait
Axl_diff
Axl_ave
Nle_diff
Nle_ave
Inl_diff
Inl_ave
Int_diff
Int_ave
Axs_diff
Axs_ave
Locus
INRA
WUR
95% GW
Threshold
P3
1.413
-0.105
-1.518
3
P1
-1.324
0.645
1.968
P1
1.306
0.910
1.702
2.9
P3
0.324
-0.407
-0.731
3
P12
0.306
0.050
-0.256
LOD
Group
EPMS_472
174.1
2.41$
e36/m52_190y
22.7
2.25$
e41/m48_159y
18.1
2.72$
p11/m49_196y
153
2.41
e41/m54_412c
44
2.09$
$
QTL Effect Size
QTLxE
Position
p11/m49_196y
153
4.06
P3
-0.569
-0.407
-0.731
c33/m54_221y
130.5
3.38
P3
-0.529
-0.415
-0.642
EPMS_472
174.1
3.38
P3
-0.539
-0.392
-0.687
e34/m53_181c
0
2.05
LG22
0.134
-0.018
-0.152
e31/m58_516y
11.7
1.89$
P3
-0.137
0.020
0.156
$
e44/m51_467c
5.8
3.06
LG28
0.117
0.073
0.161
e44/m51_258c
91.1
2.78
P2
-0.109
-0.061
-0.157
e38/m61_158y
111.5
2.25$
P4a
0.081
0.062
-0.019
e41/m54_412c
44
1.89
P12
-0.073
-0.016
0.056
p11/m49_196y
153
3.21
P3
0.119
0.090
0.149
EPMS_472
174.1
2.84
P3
0.116
0.094
0.139
EPMS_472
174.1
2.79$
P3
0.432
0.025
-0.407
p11/m49_197y
18.7
2.15$
LG24
0.374
0.095
-0.279
p11/m49_343c
22.2
2.18$
P2
0.265
0.162
0.368
$
3.1
3
2.9
3
2.9
No significant QTLs found for these traits but the QTLs with the highest LOD scores are reported.
Abbreviated names of traits are explained in section Materials and Methods.
$
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Figure 4. Charts showing positions on the chromosome or LG of QTLs with highest LOD scores
for the traits considered in the QTL x E Analysis. Traits abbreviations are as discussed in
methods section. INRA and WUR represent open field and glasshouse trials respectively.
Concluding Remarks
The vegetative development of pepper plant is more pronounced in the glasshouse trial
than in the open field trial. The glasshouse trial showed higher length of internodes and
faster rate of stem length development with more conspicuous genotypic variability
indicating stronger parental differences or segregation. This is further confirmed from the
parental means for each trait in both trials. Though parental differences exist for all traits
in both trials, the magnitudes of these differences are much larger in the glasshouse trial.
This resulted from a rather stable growth of ‘Yolo Wonder’ in both environments but an
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environment dependent response of ‘CM334’ which displayed a higher increase of vegetative
growth in the winter glasshouse trial. Higher trait heritability seen in the open field trial
could be linked to the higher block effect accounted for in the glasshouse trial.
About 17 putative QTL were detected for all traits in the two trials, 3 for axis length; 3
for number of leaves; 4 for internode length; 3 for internode growth time and 4 for axis
speed. The test statistics scores for the significance of these QTL are generally low.
Similar levels of low LOD scores were reported by Barchi et al. (2009) while analyzing
two subpopulations (141 and 93 RILs) of the whole 297 genotypes in the INRA open field
trial. They noted that LOD scores associated to detected QTL are usually much lower in
the reduced sub populations than in the full RIL population, and only the QTL with the
highest LOD scores remained significant. This is an indication that some QTL may not be
detected in our analysis due to the size of the current dataset, giving room for possible
false-negative QTL. It is known that the power to detect QTL increases as the population
size is maximized (Charcosset and Gallais 1996) and the precision depends on the
adopted sampling methods which can be random or based on selective genotyping/
phenotyping. However, most often population size cannot be increased easily due to the
large costs of phenotyping experiments.
Most of the 17 QTL are found in both trials but with different level of expression. Breeders
know that most of the vegetative traits such as axis length and number of leaves, though
genetically determined in constant environment, are strongly affected by environments.
The detected QTL for axis length on chromosome 1, number of leaves on chromosome 3,
internode growth time on chromosome 3 and axis speed also on chromosome 3 are
better revealed in the glasshouse trial, while those detected for axis length on
chromosome 2, internode length on chromosome 1 and 2 and axis speed on chromosome
2 are better expressed in the open field trial. A few of the QTL such as the one for axis
growth speed on chromosome 6 and 12 were only expressed in one trial.
It was observed that co-localization occurs for many of these QTL i.e. most of the
detected QTL affect more than a single trait. Axis length, internode length and axis
growth speed are all affected by the same QTL on chromosome 2. On chromosome 3,
number of leaves, internode growth time and axis growth speed are influenced by the
same QTL; axis growth speed and internode length on chromosome 6, and axis length
and axis growth speed on chromosome 12. This co-localization of trait QTL is in agreement
with the established correlations between these traits. This may be an indication for
linkage and/or pleiotropic effects of genes on the morphology (internode length, number
of leaves) or growth speed of vegetative organs. Such linkage or pleiotropic effects can
be more accurately studied by explicit modeling of the correlation mechanism and
causal relationship among the traits. We will explore Bayesian QTL mapping approaches
(such as Yandell et al. 2007 and Bink et al. 2008) that allow flexible models and also
inclusion of prior knowledge on model parameters.
The result from our simple QTL by environment analysis does not reveal any significant
QTL masked by environmental interaction since no QTL was detected for trait difference
between the two environments. This result cannot be generalized yet as the number of
environments considered is small and the sufficiency of the analysis is not guaranteed.
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Within the EU-SPICY project, phenotypic data on the same RIL population of 149 genotypes
are being collected under 4 environments covering different seasons (winter and summer)
and different geographical locations (Temperate and Mediterranean). A range of plant
and fruit traits are being recorded and evaluated in these trials. Our model should
incorporate analysis of these complex traits across a range of environmental conditions,
considering the interaction between genotype and environment while accounting for the
different developmental stages (time) for a given trait. We anticipate that the integration
of QTL models and eco-physiological models (Van Eeuwijk et al., 2010) to predict these
complex traits in terms of their underlying QTLs will contribute to the genetic improvement
of important crops across a range of environments.
Acknowledgements
The research leading to these results has received funding from the European Community’s
Seventh Framework Programme (FP7/2007-2013) under grant agreement nº 211347.
References
Barchi, L.; Bonnet, J.; Boudet, C.; Signoret, P.; Nagy, I.; lanteri, S.; Palloix, A.; Lefebvre,
V. 2007. A high-resolution intraspecific linkage map of pepper (Capsicum annuum
L.) and selection of reduced RIL subsets for fast mapping. Genome 50:51-60.
Barchi et al. 2009. QTL analysis of plant development and fruit traits in pepper and
performance of selective phenotyping. Theor. Appl. Genet. 118:1157-1171.
Bink, M.C.A.M.; Boer, M.P.; ter Braak, C.J.F.; Jansen, J.; Voorrips, R.E.; van de Weg, W.E.
2008. Bayesian analysis of complex traits in pedigreed plant populations. Euphytica
161:85-96. DOI: 10.1007/s10681-007-9516-1.
Brown, D.; Vision, T. 2000. MapPop 1.0: Software for selective mapping and bin mapping.
http://www.bio.unc.edu/faculty/vision/lab/mappop/
Charcosset, A.; Gallais, A. 1996. Estimation of the contribution of quantitative trait loci
(QTL) to the variance of a quantitative trait by means of genetic markers. Theor
Appl Genet 93:1193-1201.
Lander, E.S.; Botstein, D. 1989. Mapping mendelian factors underlying quantitative traits
using RFLP linkage maps. Genetics 121:185-199.
Nicolaï, M.; Sage-Palloix, A.M.; Nemouchi, G.; Savio, B.; Lefebvre, V.; Vuylsteke, M.;
Palloix, A. 2010. Providing genomic tools to increase the efficiency of molecular
breeding for complex traits in pepper: this issue.
van Eeuwijk, F.A.; Bink, M.C.A.M.; Chenu, K.; Chapman, S.C. 2010. Detection and use of QTL
for complex traits in multiple environments. Current Opinion in Plant Biology (online).
Van Ooijen, 2004. MapQTL® 5, Software for the mapping of quantitative trait loci in
experimental populations. Kyazma B.V., Wageningen, Netherlands.
Voorrips, R.E.; Palloix, A.; Dieleman, A.; Bink, M.; Heuvelink, E.; van der Heijden, G.;
Vuylsteke, M.; Glasbey, C.; Barócsi, A.; Magán, J.; van Eeuwijk, F. 2010. Crop
Growth models for the –omics era: the EU-SPICY project. (this issue).
Yandell, B.S.; Mehta, T.; Banerjee, S.; Shriner, D.; Venkataraman, R.; Moon, J.Y.; Neely,
W.W.; Wu, H.; von Smith, R.; Yi, N. 2007. R/qtlbim: QTL with Bayesian Interval
Mapping in experimental crosses. Bioinformatics 23:641-643.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Providing genomic tools to increase the efficiency of molecular
breeding for complex traits in pepper
M. Nicolaï1, A.M. Sage-Palloix1, G. Nemouchi1, B. Savio1, A. Vercauteren2,3,
M. Vuylsteke2,3, V. Lefebvre1, A. Palloix1
INRA, UR 1052 GAFL, 84140 Montfavet-Avignon, France. Contact: [email protected]
Department of Plant Systems Biology,VIB, Technologiepark 927, B-9052 Gent, Belgium
3
Department of Plant Biotechnology and Genetics, Gent University, Technologiepark 927, B-9052 Gent, Belgium
1
2
Abstract
The aim of the SPICY European project (“Smart tools for Prediction and Improvement of Crop
Yield”, KBBE-2008-211347) is to develop a suite of tools for molecular breeding of crop plants
for sustainable and competitive agriculture. The model crop is Pepper (Capsicum annuum). A
crop growth model will be constructed to predict the phenotypic response of a genotype
under a range of environmental conditions. Molecular markers of the Quantitative Trait Loci
(QTLs) for yield-related traits and for model parameters are needed for phenotype prediction.
To improve the estimation of allelic values at QTLs, functional markers (sequence
polymorphism controlling the phenotypic variation) are expected instead of QTL flanking
markers. The genomic part of this project explores functions underlying QTLs by
quantitative genomics using both a priori (genes reported in literature as playing an
important role in growth responses) and global gene expression polymorphism that is
genes that are differentially expressed in the RIL population, (eQTL). SNPs in the genes
of interest will be obtained from high-throughput sequencing and mapped in pepper
genome by SNPlex using the 297 RIL population. SNP positions in the genetic map will be
confronted with positions of eQTLs and trait QTLs. Colocalization of a structural gene
(SNP), a trait QTL and an eQTL will argue in favour of causal relationships between the
identified gene and the trait. Because functional validation cannot be achieved for many
genes in pepper, validation will be attempted through genetic association in the pepper
germplasm collection. Successful candidate genes will provide us with potential allelic
values for phenotype prediction.
Keywords: pepper, QTLs, fruit traits, plant growth, functional genomics, SNP, phenotype pre­
dic­tion, crop growth modelling.
Introduction
The EU SPICY project ‘Smart tools for Prediction and Improvement of Crop Yield’ (KBBE2008-211347) aims at the development of genotype-to-phenotype models that fully
integrate genetic, genomic, physiological and environmental information to achieve
accurate phenotypic predictions across a wide variety of genetic and environmental
configurations (van Voorrips et al., this issue). Molecular markers at Quantitative Trait
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Loci (QTL) for yield-related traits and for model parameters are needed for phenotype
prediction. To improve the estimation of allelic values, complex and correlated traits
will be reduced to expect causal components through multivariate and mixed model
analyses and QTLs will be mapped for these components (Alimi et al., this issue).
Functional polymorphisms underlying QTLs will be searched for improving the accuracy
of phenotype prediction from genetic information.
The genomic part of this project explores functions underlying QTLs by quantitative
genomics through two approaches:
— a priori candidate genes: genes reported in literature as playing an important role
in growth responses,
— gene expression QTLs or eQTLs: identification of differentially expressed genes
and mapping QTLs for the expression of these transcripts (Vuylsteke et al., 2006)
in the recombinant inbred line (RIL-YC) population from Barchi et al. 2007.
The genes of interest will be mapped in pepper genome by SNPlex technology after
localization of SNPs. SNP positions will be confronted with positions of eQTLs, trait QTLs
and model parameter QTLs. A colocalization between a structural gene (SNP), an eQTL
and a trait QTL will argue in favour of a causal relationship between the identified gene
and the trait. Validation of the causal relationship will be attempted through genetic
association in the pepper germplasm collection. Successful candidate genes will provide
potential allelic values for phenotype prediction.
Here, we report the advance of the genomic part: I) the list of a priori candidate genes
involved in growth mechanisms, II) the choice of plant tissue for eQTL analysis, and the
validation of a pepper array, III) the technology which will be used to localize SNPs in
genes of interest, and IV) the advance of the selection of core-collections from the
pepper germplasm.
Materials and methods
RIL-YC progeny
A pepper recombinant inbred line (RIL) population obtained from the cross between a
blocky bell pepper cultivar “Yolo wonder” and a hot small fruited landrace “Criollo de
Morelos 334” was genotyped to generate a linkage map (Barchi et al., 2007). Several
plant and fruit traits were analyzed and the corresponding QTLs were localized on the
genetic map (Barchi et al., 2009). A core set of 94 RILs was selected based on genetic
map information using MapPop software and was grown under controlled conditions for
tissue sampling and gene expression analysis. At day 51 after sowing, three samples of
three internodes per genotype were collected. For fruit samples, we harvested three
fruits from three plants per genotype at 8 days after fertilization.
Pepper collection
The whole pepper collection includes 1322 accessions from 11 Capsicum species (5
domesticated and 6 wild). All the domesticated accessions are landraces from more than
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80 different countries. It was previously characterized for geographic origins, horticultural
and disease resistance traits by Sage-Palloix et al. (2007).
mRNA isolation, cDNA synthesis and cDNA-AFLP analysis
Total RNA was prepared from the sample pools using TRIzol reagent (Invitrogen, Carlsbad,
CA, USA). First- and second-strand cDNA synthesis and the cDNA-AFLP template
preparation were carried out according to Vuylsteke et al. (2007) starting from 5 µg total
RNA. The restriction enzymes used were EcoRI and MseI. For the pre-amplifications, a
non-selective MseI primer was combined with a EcoRI primer containing a T end. PCR
conditions were as described (Vos et al., 1995). The amplifications were separated on
acrylamide electrophoresis gel (LI-COR, Lincoln, NE, USA).
DNA Extraction
All the accessions have been sown (9 seeds/accession) in plate of 96 wells and DNA was
extracted from pools of 6 different plants per accession (in average) as described by
Fulton and Tanksley (1995). The DNA was resuspended in 100µl of TE solution and
quantified with Nanodrop system.
Micro Array construction
A collection of 284,500 raw pepper ESTs were found in three databases : NCBI (USA),
Dana-Farber Cancer Institute-The gene Index project (USA), and PepperEST database
from Korea Research Institute of Bioscience & Biotechnology (KRIBB). The raw ESTs
produced 65,049 UniGenes (Consensus and singleton). The Roche NimbleGen 385K format
custom was chosen to design the array. The C. annuum array includes 170,240 probes
and it represents 42,778 unique IDs.
Results and discussion
Establishing an a priori candidate gene collection for plant and fruit growth through
homology detection
The cell cycle proteins (CC) are involved in cellular growth processes such as cell division,
cell proliferation and cell expansion, and constitute a priori valuable candidates for
QTLs involved in plant and fruit development. 61 CC genes are described in Arabidopsis
thaliana (Vandepoele et al., 2002).
Few additional genes were unequivocally expected to be involved in plant or fruit growth
processes and are also good candidates. A list of additional genes was established (Table
1). They are implicated in growth mechanisms of the whole plant or fruit in other species,
as for example, the genes Ovate and SUN in tomato, and WOX and TOR in plants.
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Table 1. Selection of candidate genes known to be involved in growth mechanisms
of the whole plant or the fruit in other plant species.
OVATE
Gene controlling the elongated fruit
SUN (GAox Gibberellin-oxidase)
Increased stature and organ size
FW2.2
Regulation of fruit size
CAF1(CCR4-associated factor 1)
Control of transcription (cell size)
FAS (fasciated-YABBY-like transcription factor)
Effect on locule number
WOX (Wuschel like homeobox)
Effect on leaf development
ANT (AINTEGUMENTA)
Increased or decreased organ size
ARGOS
Increased organ size
Blind (MYB transcription factor)
Shoot branching/inflorescence development
GRF5 (Growth regulating factor)
Effect on organ size
GaLDH (L-Galactono-lactone dehydrogenase)
Decreased of leaf number and fruit
Kdo-8-P (3-deoxy-D-manno-2-octulosonic acid-8-phosphate)
Associated to cell division
TOR (target of rapamycin)
Effect on cell growth (cell cycle-CycD)
Idenfitying the differentially expressed genes by eQTL analysis
Differentially expressed genes underlying QTLs for plant growth and fruit traits will be
identified.
a) Choice of tissue used for expression analysis.
Experiments were carried out in order to optimize the choice of tissue and growth
stages. We analyzed different tissue of Criollo de Morelos 334 and Yolo Wonder by cDNA
AFLP : internodes (young or old), apex (at two stages : emission of the first leave or later
emission of the 7th-8th leaves), flower (early flower buds to open flowers), and fruit.
Apex and flower RNA extracts were eventually rejected due to the presence in the apex
of leaf tissue resulting in a mixture of RNAs from apex and leaves, and the composition
of flower by several tissue (petals, sepals, pollen, ovary). Both the young and the old
internode samples yielded consistent cDNA-AFLP profiles. Finally, we decided to continue
with young internodes which tissue were easier to homogenize.
The cDNA-AFLP analysis of the fruit did not allow deciding on the sampling stage. The
most appropriate sampling time was inferred from fruit growth dynamics of the parental
lines Criollo de Morelos 334 and Yolo Wonder under controlled conditions. In figure 1,
the top graphs show the increase of fruit length and diameter over time, the bottom
graphs show the ratio of length over diameter. As expected for the blocky cultivar Yolo
Wonder, growths in width and length are equal, resulting in a rather constant ratio close
to 1. Contrastingly, for the long fruit cultivar Criollo de Morelos 334, the growth in
length is much higher than in width from the 3rd to the 20th day after fertilization. This
resulted in a steep increase of the length/diameter ratio during this period.
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Figure 1. Fruit length and diameter (top) and ratio length/diameter (bottom)
over time of Yolo Wonder and Criollo de Morelos 334.
In order to detect early gene expression related to the differential growth in length and
diameter, fruits would be sampled optimally at 3 days. The fruit, however, is too small
(~ 0.3 mm). Trade-off between growth dynamics and technical limitations lead us to
collect fruits approximately 8 days after fertilization (+/-0.5 day).
In conclusion, the two chosen tissues were the young internodes and the fruits 8 days
after fertilization.
b) Strategy.
The initial strategy was eQTL analysis using cDNA-AFLP as described in Vuysteke et al.
(2006). The current availability of pepper ESTs, however, encouraged the use of
microarray technology. Microarrays are advantageous over cDNA-AFLP in terms of
coverage of the transcriptome, time cost and the gene identity of the differential.
A C. annuum array was produced and the quality and performance of this ultra-high
density array was tested in a pilot experiment. This pilot experiment, involving three
biological replicates, examined the differential expression between the internodes of
the two parental lines.
Preliminary analysis showed a sufficiently large signal, a good reproducibility of the
hybridizations and a large fraction of expressed genes (more than 40 %). About 600 genes,
involved in various cellular functions, showed a two- or more fold differential expression
(False discovery rate : FDR< 5 %) between the two parental line internode samples.
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In a follow-up experiment, the differential gene expression between ~80 RILs (chosen in
the core of 94 RILs) at the internode level will be assessed in order to map eQTLs in the
RIL-YC population.
Figure 2. Volcano plot contrasting the significance (-log10(FDR) on the ordinate)
and the magnitude of the expression difference (log2 on the abscissa) for the
Yolo wonder and the Criollo de Morelos 334 comparison.
SNP detection between parental alleles at candidate genes, prerequisite tool for
further mapping
For mapping candidate genes, SNPs were targeted for the genes identified in the 2
previous approaches. Considering the cell cycle genes, very few of the 61 A. thaliana
orthologs were found in pepper with few polymorphisms between parental lines. This
resulted in the localization of one or two SNPs for only three cell cycle genes
Consequently, we move to high-throughput sequencing (Illumina technology) in a geno­
me-wide approach for the SNPs identification. In order to perform this sequencing on
the majority of mRNAs, we started to pool RNA extracts from different tissues : fruit,
leaf, apex, internode, root, and stressed leaf and apex. After construction of normalized
cDNA libraries from the 2 parental lines, high-throughput sequencing will be performed
using the Illumina sequencer that is expected to deliver the sequences from million
expressed genes and provide thousands of SNPs. The list of genes tagged with these
SNPs, will be confronted with the list of candidate genes, permitting further mapping of
these genes in the progeny.
Selection of core-collections from the pepper germplasm
Core-collections of pepper will be defined in order to validate the candidate genes. The
whole collection (1322 accessions) has already been phenotyped for primary plant and
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fruit traits. Genotyping the whole collection is presently performed using 29 nuclear SSR
markers from Nagy et al. (2004) and Lee et al. (2004) covering the 12 chromosomes, and
10 chloroplastic SSR markers from Povan et al. (1999). Subsets of unrelated accessions
that maximize genetic and phenotypic diversity will be established.
Conclusions
A suite of tools for molecular breeding of crop plants for sustainable and competitive
agriculture will be provided by the project. Genomic resources useful for the pepper
genetics community will be made available. The microarray technology is widely used in
gene expression studies. The possibility of creating a pepper specific array will not only
highlight the aims of this project but can be of a benefit to the whole Solanaceae scien­
tific community.
The results of the high-throughput sequencing will deliver the sequences of most of pepper
expressed genes, with SNP data. The genetic characterization of the Capsicum INRA co­
llection will be usable for the selection of core collections with different objectives.
References
Barchi, L.; Bonnet, J.; Boudet, C.; Signoret, P.; Nagy, I.; Lanteri, S.; Palloix, A.; Lefebvre,
V. 2007. A high-resolution, intraspecific linkage map of pepper (Capsicum annuum
L.) and selection of reduced recombinant inbred line subsets for fast mapping.
Genome. 50:51-60.
Barchi, L.; Lefebvre, V. Sage-Palloix, A. M.; Lanteri, S.; Palloix, A. 2009. QTL analysis of
plant development and fruit traits in pepper and performance of selective
phenotyping. Theor. Appl. Genet. 118:1157-1171.
Fulton, T.M.; Chunwongse, J.; Tanksley, S.D. 1995. Microprep Protocol for Extraction of
DNA from Tomato and other Herbaceous Plants. Plant Molecular Biology Reporter
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Lee, J.M.; Nahm, S.H.; Kim, Y.M.; Kim, B.D. 2004. Characterization and molecular ge­
netic mapping of microsatellite loci in pepper. Theor Appl Genet. 108:619-627.
Nagy, I.; Stágel, A.; Sasvári, Z.; Röder, M.; Ganal, M. 2007.Development, characterization,
and transferability to other Solanaceae of microsatellite markers in pepper
(Capsicum annuum L.) Genome 50:668-688.
Provan, J.; Powell, W.; Dewar, H.; Bryan, G.; Machray, G.C.; Waugh, R. 1999. An externe
cytoplasmic bottleneck in the modern European cultivated potato (Solanum
tuberosum) is not reflected in decreased levels of nuclear diversity. Proc. R. Soc.
Lond. B 266 :633-639.
Sage-Palloix, A.M.; Jourdan, F.; Phaly, T.; Nemouchi, G.; Lefebvre, V.; Palloix, A. 2007.
Struc­turing genetic diversity in pepper genetic resources: distribution of horticultural
and resistance traits in the INRA pepper germplasm. In: Niemirowicz-Szczytt K ed.,
Progress in research on Capsicum & Eggplant. Warsaw, Poland: Warsaw University of
Life Sciences Press, 33-42.
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Voorrips, R.E.; Palloix, A.; Dieleman, A.; Bink, M.; Heuvelink, E.; van Eeuwijk, F. 2010.
Crop Growth models for the –omics era: the EY-SPICY project (this issue)
Vos, P.; Hogers, R.; Bleeker, M.; Reijans, M.; van de Lee, T.; Hornes, M.; Frijters, A.; Pot,
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Vandepoele, K.; Raes, J.; De Veylder, L.; Rouzé, P.; Rombauts, S.; Inzé, D. 2002. Genomewide analysis of core cell cycle genes in Arabidopsis. Plant Cell. 14(4):903-916.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Crop growth models for the -omics era: the EU-SPICY project
R.E. Voorrips1, A. Palloix2, A. Dieleman1,3, M. Bink4, E. Heuvelink5, G. van der Heijden1,
M. Vuylsteke6,7, C. Glasbey8, A. Barócsi9. J. Magán10, F. van Eeuwijk
1
Plant Research International, P.O. Box 16, 6700 AA Wageningen, The Netherlands.
Contact: [email protected]
2
INRA, UR 1052 GAFL, 84140 Montfavet-Avignon, France.
3
Wageningen UR, Greenhouse Horticulture, P.O. Box 644, 6700 AP, Wageningen, The Netherlands
4
Wageningen UR, Biometris, P.O. Box 100, 6700AC, Wageningen, The Netherlands
5
Department Plant Sciences, Wageningen University, PO Box 630, 6700 AP Wageningen, The Netherlands
6
Department of Plant Systems Biology,VIB, Technologiepark 927, B-9052 Gent, Belgium
7
Department of Plant Biotechnology and Genetics, Gent University, Technologiepark 927, B-9052 Gent, Belgium
8
Biomathematics and Statistics Scotland, The King’s Buildings, James Clerk Maxwell Building, EH9 3JZ Edinburgh,
Scotland, United Kingdom
9
Budapest University of Technology and Economics, Műegyetem rkp. 3-9, H-1111 Budapest, Hungary
10
Estación Experimental de la Fundación Cajamar, Autovía del Mediterráneo km. 419, 04710 El Ejido, Spain
Abstract
The prediction of phenotypic responses from genetic and environmental information is an
area of active research in genetics, physiology and statistics. Rapidly increasing amounts of
phenotypic information become available as a consequence of high throughput phenotyping
techniques, while more and cheaper genotypic data follow from the development of new
genotyping platforms. A wide array of -omics data can be generated linking genotype and
phenotype. Continuous monitoring of environmental conditions has become an accessible
option. This wealth of data requires a drastic rethinking of the traditional quantitative
genetic approach to modeling phenotypic variation in terms of genetic and environmental
differences. Where in the past a single phenotypic trait was partitioned in a genetic and
environmental component by analysis of variance techniques, nowadays we desire to model
multiple, interrelated and often time dependent, phenotypic traits as a function of genes
(QTLs) and environmental inputs, while we would like to include transcription information
as well. The EU project ‘Smart tools for Prediction and Improvement of Crop Yield’ (KBBE2008-211347), or SPICY, aims at the development of genotype-to-phenotype models that
fully integrate genetic, genomic, physiological and environmental information to achieve
accurate phenotypic predictions across a wide variety of genetic and environmental
configurations. Pepper (Capsicum annuum) is chosen as the model crop, because of the
availability of genetically characterized populations and of generic models for continuous
crop growth and greenhouse production. In the presentation the objectives and structure
of SPICY as well as its philosophy will be discussed.
Introduction
Plant breeding has considerably contributed to the increased quality and yield of crops
over the last decades. This was initially achieved by a systematic comparison of crosses
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in an experimental set-up. In the last decade the use of molecular markers has been
added as a tool in breeding and this has increased insight in the genetics behind the
genotypic differences. By selecting genotypes on the basis of molecular markers, we aim
to select the ones having the favorable phenotype. This method of breeding is commonly
known as marker assisted breeding and has proven to be especially successful when used
for simple traits involving a very limited number of genes, e.g. disease resistance.
For complex traits like development and yield, current molecular breeding still has some
severe limitations. By complex traits we mean traits that are the outcome of many
underlying genetic factors that mask or accentuate each other and that interact with
environmental factors. Prediction of the phenotype for complex traits is difficult due to
the many interactions that need to be taken into account and the large variation
observed. These traits are however most crucial to face the challenges of the future. In
order to select and breed the best genotypes for a large range of diverse conditions,
ideally the breeder should test all his crosses under all these conditions. Especially with
complex physiological traits like energy content, food quality or yield, which exhibit
large variation, this would require many expensive and large trials. The considerable
costs involved hamper this approach.
How can molecular breeding help to assist breeders for these complex traits?
The ‘traditional’ approach to link genetic markers to a trait which is the result of
multiple interacting genes, is by quantitative trait loci (QTL) analysis. This analysis is
generally conducted for phenotypes observed in a single environment, but this is often
not sufficient for complex traits that exhibit considerable genotype x environment
interaction. Recently, advances have been made by considering the combination of the
QTL under different environments, a so called QTL x E analysis, and new methods are
still being developed in this area (Alimi et al, this issue). The occurrence of QTLxE
interactions can be discovered by performing experiments at several locations under
different conditions. However, in itself this doesn’t lead to predictive models. In order
to achieve that, it is necessary to know what the important environmental factors are,
and how changes in these factors affect the traits studied. This can be approached
purely statistically (Van Eeuwijk et al., 2010), e.g. by the inclusion of environmental
data as cofactors. However, a different and biologically more meaningful approach is the
use of crop growth models.
Crop growth models have proven to be an excellent tool to predict crop yield of a specific
variety under different environmental conditions. A crop growth model disentangles the
complex trait yield under different conditions in a number of model parameters specific
for the crop, based on known physiological principles like photosynthesis, and for the
environment, like light and temperature (Figure 1). In this project we want to integrate
the two approaches of QTL and crop growth modelling.
Basically we propose to use explanatory models to disentangle the sink and source
components of growth. The hypothesis is that model parameters are more directly linked
to genetic information than direct plant measurements (e.g. length, fruit size, leaf area)
as the latter are the final result of complex interactions between sink and source. Hence
QTL regions for these model parameters are expected to be more specific and stable over
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environments than QTL for those directly measured traits (Van Eeuwijk et al., 2010). The
potential of this “gene-to-phenotype” modeling approach was illustrated in a simulation
study by Chenu et al. (2009). The results of this approach will be compared with those of
a QTL study for the measured traits (Barchi et al., 2009) in the same population.
Figure 1. A simple growth model with three parameters describes the development of yield
over time. The responses are shown of a “default” genotype and of three other genotypes,
each differing from the default in only one parameter: earliness, growth rate or
maximum yield. It is expected that QTLs for such parameters are more
stable across environments than QTLs for yield itself.
If QTLs can be found for the crop growth model parameters, this will help us to predict
the performance of a genotype under a range of environmental conditions, reducing the
need for large scale phenotyping. Recent research has shown the potential of this
approach (Letort et al, 2006). This approach requires extension of existing crop growth
models to better handle the genotype specific parameters and new QTL-analysis tools to
link genetic markers / QTL with these model parameters. An illustration of the concept
is shown in Figure 2.
Figure 2. The concept of QTL identification for model parameters
instead of for phenotypic traits.
QTLs for crop growth model parameters are of use in marker assisted breeding, but they
still pose some drawbacks: QTLs identified in one population may not be useful in
another, due to differences in parental alleles in markers and/or genes, possible loss of
linkage and their interaction with the genetic background. Besides QTLs do not increase
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insight in the true genetic and metabolic processes involved. It would be more interesting
to find the gene(s) underlying the QTL for crop growth model parameters. This would
help to identify their mode of action, and also allow multiple alleles to be found in other
genetic material. Therefore we will apply and develop tools to localize the responsible
genes within the QTL (Nicolaï et al, this issue).
Large scale phenotyping is needed to provide the data for these analyses, and will also
remain necessary in breeding. Therefore we will also develop automated and fast highthroughput tools for large scale phenotyping, thereby reducing the amount of manual
labour necessary in phenotyping experiments.
Solanaceous species are among the major EU-grown crops (EPSO, 2004). Pepper was
selected as a model crop as suitable genetic material (a genotyped set of Recombinant
Inbred Lines) was available, as well as a genetic map and a suitable, although not genotype
specific, crop growth model. Furthermore the crop is grown indoors, allowing better crop
management, hence limiting the environmental variation. The tools developed in this
study have the potential to be applied to other crops as well.
Scientific approach
Plant material and phenotyping experiments
For this project a Capsicum annuum intraspecific Recombinant Inbred Line (RIL) population
of the cross “Yolo Wonder” x “Criollo de Morelos 334” (Barchi et al, 2007) is used, which
was already genotyped. The parents of this population differ markedly in leaf size and
shape, stem length, fruit size and shape and other traits (Barchi et al., 2009), allowing to
study the segregation of many traits involved in crop growth models.
The main phenotyping s done in four large experiments in 2009, two in Wageningen, the
Netherlands and two in Almeria, Spain. In each experiment the RIL population, including
controls and replicates, is grown. Phenotyping is done both manually for plant and leaf
morphology and fruit number and size, and by using the phenotyping tools described in
the next paragraph. Apart from these experiments a pilot experiment was performed in
2008, and a validation experiment will be performed in 2011.
Large-scale phenotyping tools
We have developed two phenotyping tools: an imaging tool for capturing and analyzing
images of the plants growing in a greenhouse, and a tool for measuring chlorophyll
fluorescence as a parameter for photosynthetic potential.
The imaging tool consists of a trolley with 4 color cameras, 4 infrared cameras and 4
range finder cameras, mounted on a vertical frame to capture the entire plant height.
The plants are labeled with a bar code that is also included in the image. We are
developing software that estimates the leaf area, the amount of stem tissue and the
number and size of fruits from the captured images.
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The chlorophyll fluorescence tool consists of a mobile setup with several (currently two)
sensor heads, each containing a chamber to hold a leaf equipped with multi-wavelength
illumination and detection, temperature sensor and humidity sensor, allowing several
plants to be monitored simultaneously.
Genotype specific crop growth and yield models
Three models are compared within this project. The simplest model (SPICY 1; 7 parameters)
simulates growth of vegetative and generative biomass based on light use efficiency.
Partitioning to the fruits (harvest index) is assumed to be constant. The second model
(SPICY 2; 20 parameters) resembles the simplest model, but includes a boxcar train method
to simulate fruit development. The most complex model is INTKAM (> 50 parameters;
Marcelis et al., 2006), which contains many submodels for e.g. light interception,
photosynthesis, respiration, dry matter partitioning and fruit growth.
It is an important research question in this project, to determine which model will best
serve our goals. A simple model with only a few parameters that can all be determined for
all genotypes, or a complex model with many parameters. Such a complex model is more
flexible and ‘physiologically sound’. However, it contains many parameters which cannot
be determined for each genotype and hence have to be assumed equal for all genotypes.
Furthermore, some of the parameters will hardly influence the model output. Based on
probabilistic sensitivity analysis (Oakley and O’Hagan, 2004), the most relevant parameters
in such a complex model will be determined and will be measured on all genotypes.
New QTL analysis tools
A major component in the SPICY project is the development of QTL mapping methodology
for the identification of crop growth parameters. As mentioned before, we will model
the phenotypic traits over time (longitudinally), and more specifically the changes
(increase/decrease and acceleration/deceleration) that these traits show. Furthermore,
this analysis should not be done for each growth trait separately, but for all traits
simultaneously (Alimi et al, this issue).
The mapping of QTL for longitudinal traits may be done by a two step approach comprising
the fitting of a suitable growth curve (e.g., logistic, exponential, Gompertz) and
subsequently treating the curve parameter estimates as trait records (e.g., Malosetti et
al., 2006). However, here we aim to integrate these two steps into one flexible method
that, for example, takes into account the uncertainty in parameter estimates.
A statistical framework that allows explicit specification of prior knowledge (or prior
uncertainty) about model parameters is the Bayesian paradigm. In a Bayesian approach
the prior knowledge on model parameters is integrated with the information contained
by the experimental data. After this integration, conclusions are based on the posterior
knowledge that also quantifies the degree of certainty on the model parameters after
the analyses. Bayesian approaches for QTL mapping have been successfully applied to
analyze complex traits (e.g., Bink et al., 2002; Bink et al., 2008; Yi & Shriner, 2008; Bink
& Van Eeuwijk, 2009; Liu & Wu 2009). The Bayesian approach will likely build upon the
R packages R/qtl and R/qtlbim (Yandell et al., 2007) as the R language is flexible and
publicly available.
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Candidate gene identification
QTL regions are generally large, containing many hundreds of genes. In order to pinpoint
genes in the QTL regions that are likely to be causally related to the QTL effect we will
follow two approaches (Nicolaï et al, this issue). The first is to focus on known genes for
similar traits that have already been validated in other crops. We will generate SNP
markers in the corresponding Capsicum homologues and check whether these are mapped
to the QTL regions in the RIL population.
Another approach to identify the genes involved in the growth of pepper is by studying
the differential gene expression between contrasting QTL-genotypes (Clark et al. 2006;
Clop et al. 2006; Frary et al. 2000). We will assay variation in gene expression of
thousands of loci in the pepper genome. By combining QTL mapping with expression
profiling, called eQTL mapping, one can identify and locate on a linkage map positional
candidate genes for a phenotype of interest whose expression segregates in the progeny.
Those genes that are located in a growth model QTL region and whose eQTL also coincides
with that QTL (so-called cis-acting eQTLs) will be interesting genes for further study.
Conclusion
The European SPICY project is a major approach to develop tools for the genetic analysis
of, and breeding for complex traits like growth and yield. It is multi-disciplinary, involving
contributions from electronics and engineering, crop husbandry, plant physiology and
molecular and quantitative genetics. Most major pepper breeding companies are repre­
sented on the Industrial Advisory Board. All results of this project will be in the public
do­main, made available through scientific publication, presentations and through the pro­
ject website: www.spicyweb.eu. This project is therefore likely to have a significant im­
pact on European pepper breeding.
Acknowledgement
The research leading to these results has received funding from the European Community’s
Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 211347.
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Barchi, L.; Lefebvre, V.; Lanteri, S.; Nagy, I.; Grandbastien, M.A.; Palloix, A. 2007. A high
resolution intra-specific linkage map of pepper (Capsicum annuum L.) and the
selection of reduced RILs subsets for fast mapping. Genome 50:51-60.
Barchi, L.; Lefebvre, V.; Sage-Palloix, A.M.; Lanteri, S.; Palloix, A. 2009. QTL analysis of
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Bink, M.C.A.M.; Uimari, P.; Sillanpaa, J.; Janss, L.L.G.; Jansen, R.C. 2002. Multiple QTL
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Bink, M.C.A.M.; Boer, M.P.; Ter Braak, C.J.F.; Jansen, J.; Voorrips, R.E.; Van de Weg, W.E.
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pert, K.B.; Tanksley, S.D. 2000. fw2.2: a quantitative trait locus key to the evolution
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SESSION IV.
BREEDING FOR YIELD
1. SPICY PROJECT
SYMPOSIUM
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Exploratory QTL analyses of some pepper physiological traits
in two environments
N.A. Alimi1,2, M.C.A.M. Bink2, A. Dieleman3,4, A.M. Sage-Palloix1, R.E. Voorrips4,
V. Lefebvre1, A. Palloix1 , F.A. van Eeuwijk2
1
INRA- Avignon, GAFL UR 1052, BP 94, 84143 Montfavet Cedex France.
Contact: [email protected]; nurudeenadeniyi, [email protected] 2Wageningen UR
Biometris, P.O. Box 100, 6700AC, Wageningen, The Netherlands
3
Wageningen UR Greenhouse Horticulture, P.O. Box 644, 6700 AP, Wageningen, The Netherlands
4
Wageningen UR, Plant Research International, P.O. Box 16, 6700 AA, Wageningen, The Netherlands
Abstract
The use of molecular breeding techniques has increased insight into the genetics behind
phenotypic differences and led to selection of genotypes having favourable traits. Continuous
monitoring of environmental conditions has also become an accessible option. Rather than
single trait evaluation, we would prefer smarter approaches capable of evaluating multiple,
often correlated and time dependent traits simultaneously as a function of genes (QTLs) and
environmental inputs, where we would like to include intermediate genomic information as
well. In this paper, an exploratory QTL analysis over two environments was undertaken using
available genetic and phenotypic data from segregating recombinant inbred lines (RIL) of
pepper (Capsicum annuum). We focused on vegetative traits, e.g. stem length, speed of stem
development, number of internodes etc. We seek to improve the estimation of allelic values
of these traits under the two environments and determine possible QTL x E interaction.
Almost identical QTLs are detected for each trait under the two environments but with
varying LOD scores. No clear evidence was found for presence of QTL by environment
interactions, despite differences in phenotypes and in magnitude of QTLs expression. Within
the EU project SPICY (Voorrips et al., 2010 this issue), a larger number of environments will
be studied and more advanced statistical analysis tools will be considered. The correlation
between the traits will also be modelled. The identification of markers for the important QTL
(Nicolaï et al., 2010 this issue) will improve the speed and accuracy of genomic prediction of
these complex phenotypes.
Keywords: QTLs, SPICY project, pepper, molecular markers.
Introduction
The use of molecular breeding techniques has contributed considerably to the unraveling
of crop traits that have impacted the quality and yield of plant products. It has increased
insight into the genetics behind the genotypic differences and allows breeders to achieve
earlier and more accurate selection of genotypes having favorable traits. Yield in
agronomic and horticultural crops is a composite trait with many underlying traits and
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genetic factors that may mask or accentuate each other and also interact with
environmental factors. Dealing with such a complex trait requires more advanced
approaches capable of evaluating multiple traits simultaneously rather than single trait
evaluation. This will enable breeders to investigate issues related to pleiotropy and
genetic linkage that underlie commonly observed genetic correlations between traits.
For such complex traits exhibiting considerable genotype by environment interaction,
these QTLs have to be analyzed by considering their combination under different
environment using the so called QTL x E analysis. The specific goal of this work is
therefore to study the presence and magnitude of interaction between QTLs and
environment.
Materials and methods
Data Sources and Description
Data from the first SPICY experiment at Wageningen University and Research Center
(WUR), the Netherlands and the already published data from INRA, France (Barchi et al,
2009) are used. The genotypes are from the fifth generation of Recombinant Inbred
Lines (RILs) of an intraspecific cross between large – fruited inbred cultivar ‘Yolo Wonder’
(YW) and the hot pepper cultivar ‘Criollo de Morelos 334’ (CM 334). There are a total of
297 RILs from the INRA experiment from which a subset of 149 lines was selected in the
WUR experiment, using the MapPop software (Brown and Vision 2000), for selective
phenotyping. The 149 most informative individuals were selected using the full linkage
map as the input file, and the maximum bin length (eMBL) as the selection criterion. The
genetic linkage map was constructed from genotypic data on a set of 587 markers (507
AFLPs, 40 SSRs, 19 RFLPs, 17 SSAPs and four STSs). A total of 489 markers were assembled
into 49 linkage groups (LGs). Twenty-three of these LGs, composed of 69% of the markers
and covering 1553 cM, were assigned to one of the 12 haploid pepper chromosomes,
leaving 26 small LGs (304 cM) unassigned (Barchi et al., 2007).
The WUR data was obtained in a glasshouse experiment (glasshouse trial) in the
Netherlands between December and May (winter/spring season). The plants were
planted by randomizing genotypes in a designed but unbalanced way across four
compartments in replicates of 4, 8 or 16 plants per genotypes. The replicates occurred
within and between compartments. The data from INRA were measured in open field
cultivation (open field trial) between July and August (summer season) in the south of
France, in a randomized complete block design with 3 blocks of 3 individual plants
(repeats) per genotype and block.
This paper concentrates on the following five traits that were in common in the two
experiments:
1.The primary axis length (Axl) defined as the length (in cm) of the primary axis from
the cotyledons to the first branch;
2.The number of leaves on the primary axis (Nle);
3.The mean internode length (Inl) given by the ratio Axl:Nle in cm;
4.The axis growth speed (Axs) given by the ratio Axl:(Flw-15 days), in cm.day-1, in which
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Flw is the number of days from sowing to first flower anthesis from which the 15 days
corresponding to the time of hypocotyl and cotyledons emergence after sowing were
deducted to obtain the growth time of the axis; and
5.The mean internode growth time (Int) given by the ratio (Flw-15 days):Nle, in day.
internode-1.
The focus of this paper is the analysis of these common traits to discern if the same QTLs
underlie identical traits in the two environments and possible interaction between QTL
and environment.
Data Evaluation
Each trait was graphically explored for possible variation across blocks and presence of
extreme observations (outliers). Further, multivariate analysis of variance (MANOVA)
models were fitted to the traits simultaneously across blocks and genotypes. This model
allows (a) calculation of trait heritability; (b) quantification of the effect of genotype
and/or blocks on the traits and significance testing of these effects and (c) obtaining
least square means per genotype after accounting for block and interaction effects.
The magnitude and pattern of correlation between traits in each experiment and across
experiments are explored where correlation is expected between the original and
derived traits.
Quantitative Trait Locus (QTL) Analysis
QTL detection based on interval mapping (Lander & Botstein, 1989) using the obtained
least square means for all traits and the genetic map developed by Barchi et al. (2007),
was done with MapQTL software (Van Ooijen, 2004). The significance thresholds for
putative QTLs are derived via permutation (10000 runs) of marker genotype and trait
phenotype data.
QTL x Environment (E) Interaction Analysis
Putative QTL by environment interactions were studied for the five common traits by
considering for each genotype the difference (e.g. Axl_diff) and mean (e.g. Axl_ave) for
each trait over the two environments. Identification of QTL for the trait mean would
indicate that the QTL is expressed similarly in both environments, i.e., absence of
interaction. Identification of QTL for the trait difference would indicate that the QTL is
expressed differently, i.e., presence of interaction. These pairs of derived traits are
analyzed using interval mapping, similarly to the original traits. If a QTL is detected
either for mean or difference, its effect size and the percentage of the effect size to the
parental differences in the two trials are calculated and presented.
Result and discussion
Trait Evaluation
The variation between the three blocks in the open field trial (fig. 1) is negligible for all
the traits as the difference in trait means across blocks is small. The variation across
blocks in the glasshouse trial is slightly larger but not significant (fig. 2). Within each
block however, there is prominent variation due to the presence of different genotypes,
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i.e., large genotypic variability. This genotypic variability is more clearly seen in the
glasshouse trial. There are also indications for very few possible outlying or rather
extreme observations. The influence of these outliers was not confirmed yet and they
were left in the data. Mean values are comparable between trials, except for Internode
length with values lower than 2 cm in open field trial and close to 3.5 cm in glasshouse
trial and axis growth speed with a mean value of around 5 cm/day in open field trial and
about 10 cm/day in glasshouse trial. The range of observations for traits in glasshouse
trial is generally higher as compared to the same traits in open field trial. Some of the
traits show very little skewness especially in the glasshouse trial.
Within the open field trial, the correlation among primary axis length (Axl), number of
leaves (Nle) and axis growth speed (Axs) is high and positive (table 1). Internode growth
time (Int) is negatively correlated with all other traits except internode length (Inl),
with which it is weakly but positively correlated. Internode length (Inl) shows high
correlation with axis length (Axl) and axis growth speed (Axs). This same trend is seen in
the glasshouse trial but with generally lower magnitude. The orientation of measurements
for a particular trait in the two trials (e.g. Axl1 and Axl2) coincides as revealed by their
correlation coefficients. However, low correlations were observed between the trials for
Internode length (Inl) and Axis growth speed (Axs).
Figure 1. Box plots showing possible trait variation across blocks in the open field trial.
The mean trait values for the two parents and estimated trait heritability from the
MANOVA model are also listed in table 1. Genotype is consistently significant for all the
traits, while block effect is seen in some of the traits especially in glasshouse trial,
confirming what was observed from the graphical exploration. There is no interaction
between genotype and blocks. The sufficiency of this model to handle the unbalanced
settings in the glasshouse trial is not guaranteed and the randomness created by
genotype and blocks in the two trials deserve to be further explored. Also, the correlation
within each trial is not explicitly modeled. The essence of using this model is to obtain
least square means of the traits per genotype while accounting for possible block and
interaction between genotype and block effects. Heritability is generally higher for
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traits in the open field trial except for axis length. However, our calculated heritability
for the open field trial is lower than those reported in Barchi et al. (2009). This may be
due to a combination of difference in sample size (here we studied a subset of 149 out
of the original 297 RILs), the underlying model assumption and the correction for block
effects. The parental lines display contrasting phenotypes with parent Yolo Wonder
showing shorter axis length, fewer leaves, slower axis development but faster leaf
development. This is consistent with what has been reported in the literature for these
pepper cultivars. The glasshouse trial shows consistently higher rates of vegetative trait
development, as is also revealed from the box plots (figures 1 & 2).
Figure 2. Box plots showing possible trait variation across blocks in the glasshouse trial.
QTL Interval Mapping Analysis
The QTL test statistic (LOD score) profiles for significant linkage groups are presented in
figure 3. In general, the patterns of the profiles for most linkage groups are consistent
among the two trials; however, the magnitude of LOD scores can be different. The latter
implies that a QTL may be significant in one trial but insignificant in the other trial. For
example, such QTL are found for axis length (Axl) on chromosome 1, number of leaves
(Nle) on chromosome 3 and internode growth time (Int) on chromosome 3. These might
indicate that some QTLs are better expressed in certain environment though may be
detected in various environments. Furthermore, some QTL are detected only in one trial.
For example on chromosome 6, QTLs were found for internode length (Inl) and axis speed
(Axs) in the open field trial but not in the glasshouse trial. There is also a possibility of
QTLs for axis length (Axl) and axis speed (Axs) on chromosome 12 in the open field trial.
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Table 1. Correlation coefficients, parent means and heritability for common
traits in the two experiments
OPEN FIELD
Traits
a
Axl1
Nle1
Inl1
GLASSHOUSE
Int1
Axs1
Axl2
Nle2
Inl2
Int2
Axs2
GLASSHOUS
OPEN FIELD
Correlation Matrix
Axl1
Nle1
0.61
Inl1
0.62
-0.23
Int1
-0.48
-0.88
0.28
Axs1
0.94
0.50
0.66
Axl2
0.64
0.48
0.29
-0.36
0.55
Nle2
0.43
0.81
-0.27
-0.69
0.32
0.54
Inl2
0.10
-0.33
0.44
0.21
0.21
0.33
-0.47
Int2
-0.33
-0.76
0.35
0.74
-0.28
-0.45
-0.93
0.36
Axs2
0.35
0.20
0.22
-0.30
0.43
0.66
0.17
0.77
-0.52
-0.31
Parental Means and Trait Heritability
Yolo
Wonder
18.01
12.12
1.49
3.86
3.93
21.75
11.56
2.53
4.11
6.17
Criollo de
Morelos
334
22.92
12.50
1.85
3.09
6.01
38.75
15.75
3.25
3.06
10.64
Parental
Differences
-4.92
-0.38
-0.36
0.77
-2.08
-17
-4.19
-0.72
1.05
-4.46
Heritability
0.78
0.80
0.51
0.62
0.86
0.97
0.19
0.42
0.16
0.94
a
Axl1, Nle1, Inl1, Int1 and Axs1 stand for primary axis length, number of leaves on the primary axis,
mean internode length, mean internode growth time and axis growth speed respectively in the open
field trial; while Axl2, Nle2, Inl2, Int2 and Axs2 represent primary axis length, number of leaves on the
primary axis, mean internode length, mean internode growth time and axis growth speed respectively
in the glasshouse trial.
QTL x Environment interaction
Several QTL were detected for trait means between the two environments but no
significant QTL was detected for trait differences (table 2). The effect sizes of the
detected QTL are mostly in the direction of the parental differences in both trials though
with varying magnitudes (fig. 4). On chromosome 3, there are QTL for means across the
two trials for all five vegetative traits. The effect sizes of QTL detected on chromosome
3 and LG 22 for internode length mean vary significantly between the two trials with the
effect size greater in the glasshouse trial. There are however some QTL for trait means
whose effect sizes are in opposite direction of parental differences in both trials. Such
QTL for average could be seen for axis length (Axl) and axis speed (Axs) detected on
chromosome 3, internode growth time (Int) and number of leaves (Nle) on chromosome
12 and axis speed (Axs) on LG 24.
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Figure 3. QTL profiles of significant chromosomes (P1, P2 etc.) or unassigned
linkage groups (LG29, LG45) in both trials. Abbreviated names of traits are
explained in section Materials and Methods.
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Table 2. Result of the QTL x E Analyses.
Trait
Axl_diff
Axl_ave
Nle_diff
Nle_ave
Inl_diff
Inl_ave
Int_diff
Int_ave
Axs_diff
Axs_ave
Locus
INRA
WUR
95% GW
Threshold
P3
1.413
-0.105
-1.518
3
P1
-1.324
0.645
1.968
P1
1.306
0.910
1.702
2.9
P3
0.324
-0.407
-0.731
3
P12
0.306
0.050
-0.256
LOD
Group
EPMS_472
174.1
2.41$
e36/m52_190y
22.7
2.25$
e41/m48_159y
18.1
2.72$
p11/m49_196y
153
2.41
e41/m54_412c
44
2.09$
$
QTL Effect Size
QTLxE
Position
p11/m49_196y
153
4.06
P3
-0.569
-0.407
-0.731
c33/m54_221y
130.5
3.38
P3
-0.529
-0.415
-0.642
EPMS_472
174.1
3.38
P3
-0.539
-0.392
-0.687
e34/m53_181c
0
2.05
LG22
0.134
-0.018
-0.152
e31/m58_516y
11.7
1.89$
P3
-0.137
0.020
0.156
$
e44/m51_467c
5.8
3.06
LG28
0.117
0.073
0.161
e44/m51_258c
91.1
2.78
P2
-0.109
-0.061
-0.157
e38/m61_158y
111.5
2.25$
P4a
0.081
0.062
-0.019
e41/m54_412c
44
1.89
P12
-0.073
-0.016
0.056
p11/m49_196y
153
3.21
P3
0.119
0.090
0.149
EPMS_472
174.1
2.84
P3
0.116
0.094
0.139
EPMS_472
174.1
2.79$
P3
0.432
0.025
-0.407
p11/m49_197y
18.7
2.15$
LG24
0.374
0.095
-0.279
p11/m49_343c
22.2
2.18$
P2
0.265
0.162
0.368
$
3.1
3
2.9
3
2.9
No significant QTLs found for these traits but the QTLs with the highest LOD scores are reported.
Abbreviated names of traits are explained in section Materials and Methods.
$
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Figure 4. Charts showing positions on the chromosome or LG of QTLs with highest LOD scores
for the traits considered in the QTL x E Analysis. Traits abbreviations are as discussed in
methods section. INRA and WUR represent open field and glasshouse trials respectively.
Concluding Remarks
The vegetative development of pepper plant is more pronounced in the glasshouse trial
than in the open field trial. The glasshouse trial showed higher length of internodes and
faster rate of stem length development with more conspicuous genotypic variability
indicating stronger parental differences or segregation. This is further confirmed from the
parental means for each trait in both trials. Though parental differences exist for all traits
in both trials, the magnitudes of these differences are much larger in the glasshouse trial.
This resulted from a rather stable growth of ‘Yolo Wonder’ in both environments but an
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environment dependent response of ‘CM334’ which displayed a higher increase of vegetative
growth in the winter glasshouse trial. Higher trait heritability seen in the open field trial
could be linked to the higher block effect accounted for in the glasshouse trial.
About 17 putative QTL were detected for all traits in the two trials, 3 for axis length; 3
for number of leaves; 4 for internode length; 3 for internode growth time and 4 for axis
speed. The test statistics scores for the significance of these QTL are generally low.
Similar levels of low LOD scores were reported by Barchi et al. (2009) while analyzing
two subpopulations (141 and 93 RILs) of the whole 297 genotypes in the INRA open field
trial. They noted that LOD scores associated to detected QTL are usually much lower in
the reduced sub populations than in the full RIL population, and only the QTL with the
highest LOD scores remained significant. This is an indication that some QTL may not be
detected in our analysis due to the size of the current dataset, giving room for possible
false-negative QTL. It is known that the power to detect QTL increases as the population
size is maximized (Charcosset and Gallais 1996) and the precision depends on the
adopted sampling methods which can be random or based on selective genotyping/
phenotyping. However, most often population size cannot be increased easily due to the
large costs of phenotyping experiments.
Most of the 17 QTL are found in both trials but with different level of expression. Breeders
know that most of the vegetative traits such as axis length and number of leaves, though
genetically determined in constant environment, are strongly affected by environments.
The detected QTL for axis length on chromosome 1, number of leaves on chromosome 3,
internode growth time on chromosome 3 and axis speed also on chromosome 3 are
better revealed in the glasshouse trial, while those detected for axis length on
chromosome 2, internode length on chromosome 1 and 2 and axis speed on chromosome
2 are better expressed in the open field trial. A few of the QTL such as the one for axis
growth speed on chromosome 6 and 12 were only expressed in one trial.
It was observed that co-localization occurs for many of these QTL i.e. most of the
detected QTL affect more than a single trait. Axis length, internode length and axis
growth speed are all affected by the same QTL on chromosome 2. On chromosome 3,
number of leaves, internode growth time and axis growth speed are influenced by the
same QTL; axis growth speed and internode length on chromosome 6, and axis length
and axis growth speed on chromosome 12. This co-localization of trait QTL is in agreement
with the established correlations between these traits. This may be an indication for
linkage and/or pleiotropic effects of genes on the morphology (internode length, number
of leaves) or growth speed of vegetative organs. Such linkage or pleiotropic effects can
be more accurately studied by explicit modeling of the correlation mechanism and
causal relationship among the traits. We will explore Bayesian QTL mapping approaches
(such as Yandell et al. 2007 and Bink et al. 2008) that allow flexible models and also
inclusion of prior knowledge on model parameters.
The result from our simple QTL by environment analysis does not reveal any significant
QTL masked by environmental interaction since no QTL was detected for trait difference
between the two environments. This result cannot be generalized yet as the number of
environments considered is small and the sufficiency of the analysis is not guaranteed.
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Within the EU-SPICY project, phenotypic data on the same RIL population of 149 genotypes
are being collected under 4 environments covering different seasons (winter and summer)
and different geographical locations (Temperate and Mediterranean). A range of plant
and fruit traits are being recorded and evaluated in these trials. Our model should
incorporate analysis of these complex traits across a range of environmental conditions,
considering the interaction between genotype and environment while accounting for the
different developmental stages (time) for a given trait. We anticipate that the integration
of QTL models and eco-physiological models (Van Eeuwijk et al., 2010) to predict these
complex traits in terms of their underlying QTLs will contribute to the genetic improvement
of important crops across a range of environments.
Acknowledgements
The research leading to these results has received funding from the European Community’s
Seventh Framework Programme (FP7/2007-2013) under grant agreement nº 211347.
References
Barchi, L.; Bonnet, J.; Boudet, C.; Signoret, P.; Nagy, I.; lanteri, S.; Palloix, A.; Lefebvre,
V. 2007. A high-resolution intraspecific linkage map of pepper (Capsicum annuum
L.) and selection of reduced RIL subsets for fast mapping. Genome 50:51-60.
Barchi et al. 2009. QTL analysis of plant development and fruit traits in pepper and
performance of selective phenotyping. Theor. Appl. Genet. 118:1157-1171.
Bink, M.C.A.M.; Boer, M.P.; ter Braak, C.J.F.; Jansen, J.; Voorrips, R.E.; van de Weg, W.E.
2008. Bayesian analysis of complex traits in pedigreed plant populations. Euphytica
161:85-96. DOI: 10.1007/s10681-007-9516-1.
Brown, D.; Vision, T. 2000. MapPop 1.0: Software for selective mapping and bin mapping.
http://www.bio.unc.edu/faculty/vision/lab/mappop/
Charcosset, A.; Gallais, A. 1996. Estimation of the contribution of quantitative trait loci
(QTL) to the variance of a quantitative trait by means of genetic markers. Theor
Appl Genet 93:1193-1201.
Lander, E.S.; Botstein, D. 1989. Mapping mendelian factors underlying quantitative traits
using RFLP linkage maps. Genetics 121:185-199.
Nicolaï, M.; Sage-Palloix, A.M.; Nemouchi, G.; Savio, B.; Lefebvre, V.; Vuylsteke, M.;
Palloix, A. 2010. Providing genomic tools to increase the efficiency of molecular
breeding for complex traits in pepper: this issue.
van Eeuwijk, F.A.; Bink, M.C.A.M.; Chenu, K.; Chapman, S.C. 2010. Detection and use of QTL
for complex traits in multiple environments. Current Opinion in Plant Biology (online).
Van Ooijen, 2004. MapQTL® 5, Software for the mapping of quantitative trait loci in
experimental populations. Kyazma B.V., Wageningen, Netherlands.
Voorrips, R.E.; Palloix, A.; Dieleman, A.; Bink, M.; Heuvelink, E.; van der Heijden, G.;
Vuylsteke, M.; Glasbey, C.; Barócsi, A.; Magán, J.; van Eeuwijk, F. 2010. Crop
Growth models for the –omics era: the EU-SPICY project. (this issue).
Yandell, B.S.; Mehta, T.; Banerjee, S.; Shriner, D.; Venkataraman, R.; Moon, J.Y.; Neely,
W.W.; Wu, H.; von Smith, R.; Yi, N. 2007. R/qtlbim: QTL with Bayesian Interval
Mapping in experimental crosses. Bioinformatics 23:641-643.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Providing genomic tools to increase the efficiency of molecular
breeding for complex traits in pepper
M. Nicolaï1, A.M. Sage-Palloix1, G. Nemouchi1, B. Savio1, A. Vercauteren2,3,
M. Vuylsteke2,3, V. Lefebvre1, A. Palloix1
INRA, UR 1052 GAFL, 84140 Montfavet-Avignon, France. Contact: [email protected]
Department of Plant Systems Biology,VIB, Technologiepark 927, B-9052 Gent, Belgium
3
Department of Plant Biotechnology and Genetics, Gent University, Technologiepark 927, B-9052 Gent, Belgium
1
2
Abstract
The aim of the SPICY European project (“Smart tools for Prediction and Improvement of Crop
Yield”, KBBE-2008-211347) is to develop a suite of tools for molecular breeding of crop plants
for sustainable and competitive agriculture. The model crop is Pepper (Capsicum annuum). A
crop growth model will be constructed to predict the phenotypic response of a genotype
under a range of environmental conditions. Molecular markers of the Quantitative Trait Loci
(QTLs) for yield-related traits and for model parameters are needed for phenotype prediction.
To improve the estimation of allelic values at QTLs, functional markers (sequence
polymorphism controlling the phenotypic variation) are expected instead of QTL flanking
markers. The genomic part of this project explores functions underlying QTLs by
quantitative genomics using both a priori (genes reported in literature as playing an
important role in growth responses) and global gene expression polymorphism that is
genes that are differentially expressed in the RIL population, (eQTL). SNPs in the genes
of interest will be obtained from high-throughput sequencing and mapped in pepper
genome by SNPlex using the 297 RIL population. SNP positions in the genetic map will be
confronted with positions of eQTLs and trait QTLs. Colocalization of a structural gene
(SNP), a trait QTL and an eQTL will argue in favour of causal relationships between the
identified gene and the trait. Because functional validation cannot be achieved for many
genes in pepper, validation will be attempted through genetic association in the pepper
germplasm collection. Successful candidate genes will provide us with potential allelic
values for phenotype prediction.
Keywords: pepper, QTLs, fruit traits, plant growth, functional genomics, SNP, phenotype pre­
dic­tion, crop growth modelling.
Introduction
The EU SPICY project ‘Smart tools for Prediction and Improvement of Crop Yield’ (KBBE2008-211347) aims at the development of genotype-to-phenotype models that fully
integrate genetic, genomic, physiological and environmental information to achieve
accurate phenotypic predictions across a wide variety of genetic and environmental
configurations (van Voorrips et al., this issue). Molecular markers at Quantitative Trait
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Loci (QTL) for yield-related traits and for model parameters are needed for phenotype
prediction. To improve the estimation of allelic values, complex and correlated traits
will be reduced to expect causal components through multivariate and mixed model
analyses and QTLs will be mapped for these components (Alimi et al., this issue).
Functional polymorphisms underlying QTLs will be searched for improving the accuracy
of phenotype prediction from genetic information.
The genomic part of this project explores functions underlying QTLs by quantitative
genomics through two approaches:
— a priori candidate genes: genes reported in literature as playing an important role
in growth responses,
— gene expression QTLs or eQTLs: identification of differentially expressed genes
and mapping QTLs for the expression of these transcripts (Vuylsteke et al., 2006)
in the recombinant inbred line (RIL-YC) population from Barchi et al. 2007.
The genes of interest will be mapped in pepper genome by SNPlex technology after
localization of SNPs. SNP positions will be confronted with positions of eQTLs, trait QTLs
and model parameter QTLs. A colocalization between a structural gene (SNP), an eQTL
and a trait QTL will argue in favour of a causal relationship between the identified gene
and the trait. Validation of the causal relationship will be attempted through genetic
association in the pepper germplasm collection. Successful candidate genes will provide
potential allelic values for phenotype prediction.
Here, we report the advance of the genomic part: I) the list of a priori candidate genes
involved in growth mechanisms, II) the choice of plant tissue for eQTL analysis, and the
validation of a pepper array, III) the technology which will be used to localize SNPs in
genes of interest, and IV) the advance of the selection of core-collections from the
pepper germplasm.
Materials and methods
RIL-YC progeny
A pepper recombinant inbred line (RIL) population obtained from the cross between a
blocky bell pepper cultivar “Yolo wonder” and a hot small fruited landrace “Criollo de
Morelos 334” was genotyped to generate a linkage map (Barchi et al., 2007). Several
plant and fruit traits were analyzed and the corresponding QTLs were localized on the
genetic map (Barchi et al., 2009). A core set of 94 RILs was selected based on genetic
map information using MapPop software and was grown under controlled conditions for
tissue sampling and gene expression analysis. At day 51 after sowing, three samples of
three internodes per genotype were collected. For fruit samples, we harvested three
fruits from three plants per genotype at 8 days after fertilization.
Pepper collection
The whole pepper collection includes 1322 accessions from 11 Capsicum species (5
domesticated and 6 wild). All the domesticated accessions are landraces from more than
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80 different countries. It was previously characterized for geographic origins, horticultural
and disease resistance traits by Sage-Palloix et al. (2007).
mRNA isolation, cDNA synthesis and cDNA-AFLP analysis
Total RNA was prepared from the sample pools using TRIzol reagent (Invitrogen, Carlsbad,
CA, USA). First- and second-strand cDNA synthesis and the cDNA-AFLP template
preparation were carried out according to Vuylsteke et al. (2007) starting from 5 µg total
RNA. The restriction enzymes used were EcoRI and MseI. For the pre-amplifications, a
non-selective MseI primer was combined with a EcoRI primer containing a T end. PCR
conditions were as described (Vos et al., 1995). The amplifications were separated on
acrylamide electrophoresis gel (LI-COR, Lincoln, NE, USA).
DNA Extraction
All the accessions have been sown (9 seeds/accession) in plate of 96 wells and DNA was
extracted from pools of 6 different plants per accession (in average) as described by
Fulton and Tanksley (1995). The DNA was resuspended in 100µl of TE solution and
quantified with Nanodrop system.
Micro Array construction
A collection of 284,500 raw pepper ESTs were found in three databases : NCBI (USA),
Dana-Farber Cancer Institute-The gene Index project (USA), and PepperEST database
from Korea Research Institute of Bioscience & Biotechnology (KRIBB). The raw ESTs
produced 65,049 UniGenes (Consensus and singleton). The Roche NimbleGen 385K format
custom was chosen to design the array. The C. annuum array includes 170,240 probes
and it represents 42,778 unique IDs.
Results and discussion
Establishing an a priori candidate gene collection for plant and fruit growth through
homology detection
The cell cycle proteins (CC) are involved in cellular growth processes such as cell division,
cell proliferation and cell expansion, and constitute a priori valuable candidates for
QTLs involved in plant and fruit development. 61 CC genes are described in Arabidopsis
thaliana (Vandepoele et al., 2002).
Few additional genes were unequivocally expected to be involved in plant or fruit growth
processes and are also good candidates. A list of additional genes was established (Table
1). They are implicated in growth mechanisms of the whole plant or fruit in other species,
as for example, the genes Ovate and SUN in tomato, and WOX and TOR in plants.
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Table 1. Selection of candidate genes known to be involved in growth mechanisms
of the whole plant or the fruit in other plant species.
OVATE
Gene controlling the elongated fruit
SUN (GAox Gibberellin-oxidase)
Increased stature and organ size
FW2.2
Regulation of fruit size
CAF1(CCR4-associated factor 1)
Control of transcription (cell size)
FAS (fasciated-YABBY-like transcription factor)
Effect on locule number
WOX (Wuschel like homeobox)
Effect on leaf development
ANT (AINTEGUMENTA)
Increased or decreased organ size
ARGOS
Increased organ size
Blind (MYB transcription factor)
Shoot branching/inflorescence development
GRF5 (Growth regulating factor)
Effect on organ size
GaLDH (L-Galactono-lactone dehydrogenase)
Decreased of leaf number and fruit
Kdo-8-P (3-deoxy-D-manno-2-octulosonic acid-8-phosphate)
Associated to cell division
TOR (target of rapamycin)
Effect on cell growth (cell cycle-CycD)
Idenfitying the differentially expressed genes by eQTL analysis
Differentially expressed genes underlying QTLs for plant growth and fruit traits will be
identified.
a) Choice of tissue used for expression analysis.
Experiments were carried out in order to optimize the choice of tissue and growth
stages. We analyzed different tissue of Criollo de Morelos 334 and Yolo Wonder by cDNA
AFLP : internodes (young or old), apex (at two stages : emission of the first leave or later
emission of the 7th-8th leaves), flower (early flower buds to open flowers), and fruit.
Apex and flower RNA extracts were eventually rejected due to the presence in the apex
of leaf tissue resulting in a mixture of RNAs from apex and leaves, and the composition
of flower by several tissue (petals, sepals, pollen, ovary). Both the young and the old
internode samples yielded consistent cDNA-AFLP profiles. Finally, we decided to continue
with young internodes which tissue were easier to homogenize.
The cDNA-AFLP analysis of the fruit did not allow deciding on the sampling stage. The
most appropriate sampling time was inferred from fruit growth dynamics of the parental
lines Criollo de Morelos 334 and Yolo Wonder under controlled conditions. In figure 1,
the top graphs show the increase of fruit length and diameter over time, the bottom
graphs show the ratio of length over diameter. As expected for the blocky cultivar Yolo
Wonder, growths in width and length are equal, resulting in a rather constant ratio close
to 1. Contrastingly, for the long fruit cultivar Criollo de Morelos 334, the growth in
length is much higher than in width from the 3rd to the 20th day after fertilization. This
resulted in a steep increase of the length/diameter ratio during this period.
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Figure 1. Fruit length and diameter (top) and ratio length/diameter (bottom)
over time of Yolo Wonder and Criollo de Morelos 334.
In order to detect early gene expression related to the differential growth in length and
diameter, fruits would be sampled optimally at 3 days. The fruit, however, is too small
(~ 0.3 mm). Trade-off between growth dynamics and technical limitations lead us to
collect fruits approximately 8 days after fertilization (+/-0.5 day).
In conclusion, the two chosen tissues were the young internodes and the fruits 8 days
after fertilization.
b) Strategy.
The initial strategy was eQTL analysis using cDNA-AFLP as described in Vuysteke et al.
(2006). The current availability of pepper ESTs, however, encouraged the use of
microarray technology. Microarrays are advantageous over cDNA-AFLP in terms of
coverage of the transcriptome, time cost and the gene identity of the differential.
A C. annuum array was produced and the quality and performance of this ultra-high
density array was tested in a pilot experiment. This pilot experiment, involving three
biological replicates, examined the differential expression between the internodes of
the two parental lines.
Preliminary analysis showed a sufficiently large signal, a good reproducibility of the
hybridizations and a large fraction of expressed genes (more than 40 %). About 600 genes,
involved in various cellular functions, showed a two- or more fold differential expression
(False discovery rate : FDR< 5 %) between the two parental line internode samples.
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In a follow-up experiment, the differential gene expression between ~80 RILs (chosen in
the core of 94 RILs) at the internode level will be assessed in order to map eQTLs in the
RIL-YC population.
Figure 2. Volcano plot contrasting the significance (-log10(FDR) on the ordinate)
and the magnitude of the expression difference (log2 on the abscissa) for the
Yolo wonder and the Criollo de Morelos 334 comparison.
SNP detection between parental alleles at candidate genes, prerequisite tool for
further mapping
For mapping candidate genes, SNPs were targeted for the genes identified in the 2
previous approaches. Considering the cell cycle genes, very few of the 61 A. thaliana
orthologs were found in pepper with few polymorphisms between parental lines. This
resulted in the localization of one or two SNPs for only three cell cycle genes
Consequently, we move to high-throughput sequencing (Illumina technology) in a geno­
me-wide approach for the SNPs identification. In order to perform this sequencing on
the majority of mRNAs, we started to pool RNA extracts from different tissues : fruit,
leaf, apex, internode, root, and stressed leaf and apex. After construction of normalized
cDNA libraries from the 2 parental lines, high-throughput sequencing will be performed
using the Illumina sequencer that is expected to deliver the sequences from million
expressed genes and provide thousands of SNPs. The list of genes tagged with these
SNPs, will be confronted with the list of candidate genes, permitting further mapping of
these genes in the progeny.
Selection of core-collections from the pepper germplasm
Core-collections of pepper will be defined in order to validate the candidate genes. The
whole collection (1322 accessions) has already been phenotyped for primary plant and
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fruit traits. Genotyping the whole collection is presently performed using 29 nuclear SSR
markers from Nagy et al. (2004) and Lee et al. (2004) covering the 12 chromosomes, and
10 chloroplastic SSR markers from Povan et al. (1999). Subsets of unrelated accessions
that maximize genetic and phenotypic diversity will be established.
Conclusions
A suite of tools for molecular breeding of crop plants for sustainable and competitive
agriculture will be provided by the project. Genomic resources useful for the pepper
genetics community will be made available. The microarray technology is widely used in
gene expression studies. The possibility of creating a pepper specific array will not only
highlight the aims of this project but can be of a benefit to the whole Solanaceae scien­
tific community.
The results of the high-throughput sequencing will deliver the sequences of most of pepper
expressed genes, with SNP data. The genetic characterization of the Capsicum INRA co­
llection will be usable for the selection of core collections with different objectives.
References
Barchi, L.; Bonnet, J.; Boudet, C.; Signoret, P.; Nagy, I.; Lanteri, S.; Palloix, A.; Lefebvre,
V. 2007. A high-resolution, intraspecific linkage map of pepper (Capsicum annuum
L.) and selection of reduced recombinant inbred line subsets for fast mapping.
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Barchi, L.; Lefebvre, V. Sage-Palloix, A. M.; Lanteri, S.; Palloix, A. 2009. QTL analysis of
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netic mapping of microsatellite loci in pepper. Theor Appl Genet. 108:619-627.
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Sage-Palloix, A.M.; Jourdan, F.; Phaly, T.; Nemouchi, G.; Lefebvre, V.; Palloix, A. 2007.
Struc­turing genetic diversity in pepper genetic resources: distribution of horticultural
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Voorrips, R.E.; Palloix, A.; Dieleman, A.; Bink, M.; Heuvelink, E.; van Eeuwijk, F. 2010.
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Vos, P.; Hogers, R.; Bleeker, M.; Reijans, M.; van de Lee, T.; Hornes, M.; Frijters, A.; Pot,
J.; Peleman, J.; Kuiper, M.; et al. 1995. AFLP: a new technique for DNA fingerprinting.
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Vandepoele, K.; Raes, J.; De Veylder, L.; Rouzé, P.; Rombauts, S.; Inzé, D. 2002. Genomewide analysis of core cell cycle genes in Arabidopsis. Plant Cell. 14(4):903-916.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Crop growth models for the -omics era: the EU-SPICY project
R.E. Voorrips1, A. Palloix2, A. Dieleman1,3, M. Bink4, E. Heuvelink5, G. van der Heijden1,
M. Vuylsteke6,7, C. Glasbey8, A. Barócsi9. J. Magán10, F. van Eeuwijk
1
Plant Research International, P.O. Box 16, 6700 AA Wageningen, The Netherlands.
Contact: [email protected]
2
INRA, UR 1052 GAFL, 84140 Montfavet-Avignon, France.
3
Wageningen UR, Greenhouse Horticulture, P.O. Box 644, 6700 AP, Wageningen, The Netherlands
4
Wageningen UR, Biometris, P.O. Box 100, 6700AC, Wageningen, The Netherlands
5
Department Plant Sciences, Wageningen University, PO Box 630, 6700 AP Wageningen, The Netherlands
6
Department of Plant Systems Biology,VIB, Technologiepark 927, B-9052 Gent, Belgium
7
Department of Plant Biotechnology and Genetics, Gent University, Technologiepark 927, B-9052 Gent, Belgium
8
Biomathematics and Statistics Scotland, The King’s Buildings, James Clerk Maxwell Building, EH9 3JZ Edinburgh,
Scotland, United Kingdom
9
Budapest University of Technology and Economics, Műegyetem rkp. 3-9, H-1111 Budapest, Hungary
10
Estación Experimental de la Fundación Cajamar, Autovía del Mediterráneo km. 419, 04710 El Ejido, Spain
Abstract
The prediction of phenotypic responses from genetic and environmental information is an
area of active research in genetics, physiology and statistics. Rapidly increasing amounts of
phenotypic information become available as a consequence of high throughput phenotyping
techniques, while more and cheaper genotypic data follow from the development of new
genotyping platforms. A wide array of -omics data can be generated linking genotype and
phenotype. Continuous monitoring of environmental conditions has become an accessible
option. This wealth of data requires a drastic rethinking of the traditional quantitative
genetic approach to modeling phenotypic variation in terms of genetic and environmental
differences. Where in the past a single phenotypic trait was partitioned in a genetic and
environmental component by analysis of variance techniques, nowadays we desire to model
multiple, interrelated and often time dependent, phenotypic traits as a function of genes
(QTLs) and environmental inputs, while we would like to include transcription information
as well. The EU project ‘Smart tools for Prediction and Improvement of Crop Yield’ (KBBE2008-211347), or SPICY, aims at the development of genotype-to-phenotype models that
fully integrate genetic, genomic, physiological and environmental information to achieve
accurate phenotypic predictions across a wide variety of genetic and environmental
configurations. Pepper (Capsicum annuum) is chosen as the model crop, because of the
availability of genetically characterized populations and of generic models for continuous
crop growth and greenhouse production. In the presentation the objectives and structure
of SPICY as well as its philosophy will be discussed.
Introduction
Plant breeding has considerably contributed to the increased quality and yield of crops
over the last decades. This was initially achieved by a systematic comparison of crosses
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in an experimental set-up. In the last decade the use of molecular markers has been
added as a tool in breeding and this has increased insight in the genetics behind the
genotypic differences. By selecting genotypes on the basis of molecular markers, we aim
to select the ones having the favorable phenotype. This method of breeding is commonly
known as marker assisted breeding and has proven to be especially successful when used
for simple traits involving a very limited number of genes, e.g. disease resistance.
For complex traits like development and yield, current molecular breeding still has some
severe limitations. By complex traits we mean traits that are the outcome of many
underlying genetic factors that mask or accentuate each other and that interact with
environmental factors. Prediction of the phenotype for complex traits is difficult due to
the many interactions that need to be taken into account and the large variation
observed. These traits are however most crucial to face the challenges of the future. In
order to select and breed the best genotypes for a large range of diverse conditions,
ideally the breeder should test all his crosses under all these conditions. Especially with
complex physiological traits like energy content, food quality or yield, which exhibit
large variation, this would require many expensive and large trials. The considerable
costs involved hamper this approach.
How can molecular breeding help to assist breeders for these complex traits?
The ‘traditional’ approach to link genetic markers to a trait which is the result of
multiple interacting genes, is by quantitative trait loci (QTL) analysis. This analysis is
generally conducted for phenotypes observed in a single environment, but this is often
not sufficient for complex traits that exhibit considerable genotype x environment
interaction. Recently, advances have been made by considering the combination of the
QTL under different environments, a so called QTL x E analysis, and new methods are
still being developed in this area (Alimi et al, this issue). The occurrence of QTLxE
interactions can be discovered by performing experiments at several locations under
different conditions. However, in itself this doesn’t lead to predictive models. In order
to achieve that, it is necessary to know what the important environmental factors are,
and how changes in these factors affect the traits studied. This can be approached
purely statistically (Van Eeuwijk et al., 2010), e.g. by the inclusion of environmental
data as cofactors. However, a different and biologically more meaningful approach is the
use of crop growth models.
Crop growth models have proven to be an excellent tool to predict crop yield of a specific
variety under different environmental conditions. A crop growth model disentangles the
complex trait yield under different conditions in a number of model parameters specific
for the crop, based on known physiological principles like photosynthesis, and for the
environment, like light and temperature (Figure 1). In this project we want to integrate
the two approaches of QTL and crop growth modelling.
Basically we propose to use explanatory models to disentangle the sink and source
components of growth. The hypothesis is that model parameters are more directly linked
to genetic information than direct plant measurements (e.g. length, fruit size, leaf area)
as the latter are the final result of complex interactions between sink and source. Hence
QTL regions for these model parameters are expected to be more specific and stable over
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environments than QTL for those directly measured traits (Van Eeuwijk et al., 2010). The
potential of this “gene-to-phenotype” modeling approach was illustrated in a simulation
study by Chenu et al. (2009). The results of this approach will be compared with those of
a QTL study for the measured traits (Barchi et al., 2009) in the same population.
Figure 1. A simple growth model with three parameters describes the development of yield
over time. The responses are shown of a “default” genotype and of three other genotypes,
each differing from the default in only one parameter: earliness, growth rate or
maximum yield. It is expected that QTLs for such parameters are more
stable across environments than QTLs for yield itself.
If QTLs can be found for the crop growth model parameters, this will help us to predict
the performance of a genotype under a range of environmental conditions, reducing the
need for large scale phenotyping. Recent research has shown the potential of this
approach (Letort et al, 2006). This approach requires extension of existing crop growth
models to better handle the genotype specific parameters and new QTL-analysis tools to
link genetic markers / QTL with these model parameters. An illustration of the concept
is shown in Figure 2.
Figure 2. The concept of QTL identification for model parameters
instead of for phenotypic traits.
QTLs for crop growth model parameters are of use in marker assisted breeding, but they
still pose some drawbacks: QTLs identified in one population may not be useful in
another, due to differences in parental alleles in markers and/or genes, possible loss of
linkage and their interaction with the genetic background. Besides QTLs do not increase
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insight in the true genetic and metabolic processes involved. It would be more interesting
to find the gene(s) underlying the QTL for crop growth model parameters. This would
help to identify their mode of action, and also allow multiple alleles to be found in other
genetic material. Therefore we will apply and develop tools to localize the responsible
genes within the QTL (Nicolaï et al, this issue).
Large scale phenotyping is needed to provide the data for these analyses, and will also
remain necessary in breeding. Therefore we will also develop automated and fast highthroughput tools for large scale phenotyping, thereby reducing the amount of manual
labour necessary in phenotyping experiments.
Solanaceous species are among the major EU-grown crops (EPSO, 2004). Pepper was
selected as a model crop as suitable genetic material (a genotyped set of Recombinant
Inbred Lines) was available, as well as a genetic map and a suitable, although not genotype
specific, crop growth model. Furthermore the crop is grown indoors, allowing better crop
management, hence limiting the environmental variation. The tools developed in this
study have the potential to be applied to other crops as well.
Scientific approach
Plant material and phenotyping experiments
For this project a Capsicum annuum intraspecific Recombinant Inbred Line (RIL) population
of the cross “Yolo Wonder” x “Criollo de Morelos 334” (Barchi et al, 2007) is used, which
was already genotyped. The parents of this population differ markedly in leaf size and
shape, stem length, fruit size and shape and other traits (Barchi et al., 2009), allowing to
study the segregation of many traits involved in crop growth models.
The main phenotyping s done in four large experiments in 2009, two in Wageningen, the
Netherlands and two in Almeria, Spain. In each experiment the RIL population, including
controls and replicates, is grown. Phenotyping is done both manually for plant and leaf
morphology and fruit number and size, and by using the phenotyping tools described in
the next paragraph. Apart from these experiments a pilot experiment was performed in
2008, and a validation experiment will be performed in 2011.
Large-scale phenotyping tools
We have developed two phenotyping tools: an imaging tool for capturing and analyzing
images of the plants growing in a greenhouse, and a tool for measuring chlorophyll
fluorescence as a parameter for photosynthetic potential.
The imaging tool consists of a trolley with 4 color cameras, 4 infrared cameras and 4
range finder cameras, mounted on a vertical frame to capture the entire plant height.
The plants are labeled with a bar code that is also included in the image. We are
developing software that estimates the leaf area, the amount of stem tissue and the
number and size of fruits from the captured images.
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The chlorophyll fluorescence tool consists of a mobile setup with several (currently two)
sensor heads, each containing a chamber to hold a leaf equipped with multi-wavelength
illumination and detection, temperature sensor and humidity sensor, allowing several
plants to be monitored simultaneously.
Genotype specific crop growth and yield models
Three models are compared within this project. The simplest model (SPICY 1; 7 parameters)
simulates growth of vegetative and generative biomass based on light use efficiency.
Partitioning to the fruits (harvest index) is assumed to be constant. The second model
(SPICY 2; 20 parameters) resembles the simplest model, but includes a boxcar train method
to simulate fruit development. The most complex model is INTKAM (> 50 parameters;
Marcelis et al., 2006), which contains many submodels for e.g. light interception,
photosynthesis, respiration, dry matter partitioning and fruit growth.
It is an important research question in this project, to determine which model will best
serve our goals. A simple model with only a few parameters that can all be determined for
all genotypes, or a complex model with many parameters. Such a complex model is more
flexible and ‘physiologically sound’. However, it contains many parameters which cannot
be determined for each genotype and hence have to be assumed equal for all genotypes.
Furthermore, some of the parameters will hardly influence the model output. Based on
probabilistic sensitivity analysis (Oakley and O’Hagan, 2004), the most relevant parameters
in such a complex model will be determined and will be measured on all genotypes.
New QTL analysis tools
A major component in the SPICY project is the development of QTL mapping methodology
for the identification of crop growth parameters. As mentioned before, we will model
the phenotypic traits over time (longitudinally), and more specifically the changes
(increase/decrease and acceleration/deceleration) that these traits show. Furthermore,
this analysis should not be done for each growth trait separately, but for all traits
simultaneously (Alimi et al, this issue).
The mapping of QTL for longitudinal traits may be done by a two step approach comprising
the fitting of a suitable growth curve (e.g., logistic, exponential, Gompertz) and
subsequently treating the curve parameter estimates as trait records (e.g., Malosetti et
al., 2006). However, here we aim to integrate these two steps into one flexible method
that, for example, takes into account the uncertainty in parameter estimates.
A statistical framework that allows explicit specification of prior knowledge (or prior
uncertainty) about model parameters is the Bayesian paradigm. In a Bayesian approach
the prior knowledge on model parameters is integrated with the information contained
by the experimental data. After this integration, conclusions are based on the posterior
knowledge that also quantifies the degree of certainty on the model parameters after
the analyses. Bayesian approaches for QTL mapping have been successfully applied to
analyze complex traits (e.g., Bink et al., 2002; Bink et al., 2008; Yi & Shriner, 2008; Bink
& Van Eeuwijk, 2009; Liu & Wu 2009). The Bayesian approach will likely build upon the
R packages R/qtl and R/qtlbim (Yandell et al., 2007) as the R language is flexible and
publicly available.
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Candidate gene identification
QTL regions are generally large, containing many hundreds of genes. In order to pinpoint
genes in the QTL regions that are likely to be causally related to the QTL effect we will
follow two approaches (Nicolaï et al, this issue). The first is to focus on known genes for
similar traits that have already been validated in other crops. We will generate SNP
markers in the corresponding Capsicum homologues and check whether these are mapped
to the QTL regions in the RIL population.
Another approach to identify the genes involved in the growth of pepper is by studying
the differential gene expression between contrasting QTL-genotypes (Clark et al. 2006;
Clop et al. 2006; Frary et al. 2000). We will assay variation in gene expression of
thousands of loci in the pepper genome. By combining QTL mapping with expression
profiling, called eQTL mapping, one can identify and locate on a linkage map positional
candidate genes for a phenotype of interest whose expression segregates in the progeny.
Those genes that are located in a growth model QTL region and whose eQTL also coincides
with that QTL (so-called cis-acting eQTLs) will be interesting genes for further study.
Conclusion
The European SPICY project is a major approach to develop tools for the genetic analysis
of, and breeding for complex traits like growth and yield. It is multi-disciplinary, involving
contributions from electronics and engineering, crop husbandry, plant physiology and
molecular and quantitative genetics. Most major pepper breeding companies are repre­
sented on the Industrial Advisory Board. All results of this project will be in the public
do­main, made available through scientific publication, presentations and through the pro­
ject website: www.spicyweb.eu. This project is therefore likely to have a significant im­
pact on European pepper breeding.
Acknowledgement
The research leading to these results has received funding from the European Community’s
Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 211347.
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Barchi, L.; Lefebvre, V.; Lanteri, S.; Nagy, I.; Grandbastien, M.A.; Palloix, A. 2007. A high
resolution intra-specific linkage map of pepper (Capsicum annuum L.) and the
selection of reduced RILs subsets for fast mapping. Genome 50:51-60.
Barchi, L.; Lefebvre, V.; Sage-Palloix, A.M.; Lanteri, S.; Palloix, A. 2009. QTL analysis of
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phenotyping. Theoretical and Applied Genetics 118:1157-1171.
Bink, M.C.A.M.; Uimari, P.; Sillanpaa, J.; Janss, L.L.G.; Jansen, R.C. 2002. Multiple QTL
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Bink, M.C.A.M.; Boer, M.P.; Ter Braak, C.J.F.; Jansen, J.; Voorrips, R.E.; Van de Weg, W.E.
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Bink, M.C.A.M.; Van Eeuwijk, F.A. 2009. A Bayesian QTL linkage analysis of the common
dataset from the 12th QTLMAS workshop. BMC Proceedings 3:S4.
Chenu, K.; Chapman, S.C.; Tardieu, F.; McLean, G.; Welcker, C.; Hammer, G.L. 2009. Simu­la­
ting the yield impacts of organ-level quantitative trait loci associated with drought
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Clark, R.M.; Wagler, T.N.; Quijada, P.; Doebley J. 2006. A distant upstream enhancer at the
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Clop, A.; Marcq, F.; Takeda, H.; Pirottin, D.; Tordoir, X.; Bibe, B.; Bouix, J.; Caiment, F.;
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pert, K.B.; Tanksley, S.D. 2000. fw2.2: a quantitative trait locus key to the evolution
of tomato fruit size. Science 289:85-88.
Letort, V.; Mahe, P.; Cournède P.-H.; Courtois, B.; De Reffye, P. 2006. Quantitative genetics
and plant growth simulation: a theoretical study of linking quantitative trait Loci
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Marcelis, L.F.M.; Elings, A.; Bakker, M.J.; Brajeul, E.; Dieleman, J.A.; De Visser, P.H.B.;
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BREEDING FOR YIELD
2. GENERAL
CONTRIBUTIONS
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Heterosis in relation to multivariate genetic divergence in eggplant
(Solanum melongena)
P. Hazra, P.K. Sahu, U. Roy, R. Dutta, T. Roy, A. Chattopadhyay
Department of Vegetable crops, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur-741252, West Bengal, India.
Contact: [email protected]
Abstract
The investigations were carried out during 2001 – 07 to examine the magnitude of heterosis
in relation to genetic divergence among 9 parents in a 9 × 9 half-diallel cross of eggplant or
brinjal (Solanum melongena L.). The 9 parents were grouped in 6 different clusters in the
lot of 70 entries (10 elite varieties, 16 stable breeding lines and 44 indigenous cultivars of
India and Bangladesh) based on multivariate analysis using Mahalanobis’ D2-statistic
employing 18 growth, yield components, fruit yield and fruit quality traits from three years
evaluation. Diversity of these 9 parental lines was again determined separately based on 4
important characters including fruit yield. The relationship between intra and inter-cluster
divergence, total divergence of the parents and both relative heterosis and heterobeltiosis
of 36 crosses for 4 important characters viz,. plant height, fruits/plant, fruit weight, and
fruit yield/plant, was determined using correlations and linear regression. Relationship
between genetic distance of the parents and heterosis for fruit yield/plant could be
demonstrated although the relationship was not strong enough to confidently predict the
level of heterosis based on a given value of the parental divergence. It indicated that there
might be optimum level of genetic divergence between parents to obtain heterosis in the
F1 generation. So, reliance should also be placed on the genetic distance apart from the
combining ability while selecting the parents for hybridization in order to realize high
frequency of heterotic hybrids in eggplant.
Keywords: Solanum melongena, eggplant, genetic diversity, D2-statistic, relative heterosis,
heterobeltiosis, diallel crosses.
Introduction
Eggplant, the self-pollinated and most popular and widely cultivated vegetable crop in
China, Japan, Turkey, Egypt, Italy, Indonesia, Spain, Philippines, apart from India (Singh
and Kalda, 2001) is a prominent candidate for commercial exploitation of heterosis even
by manual production of hybrid seeds because considerable number hybrid seeds are
gettable per cross-pollination. However, in pursuit of taking the program of hybrid
eggplant to logical ends, choice of suitable parents through careful and critical evaluation
of the genetics in hand is of paramount importance. This is because per se performance
of parents is not always a true indicator of its potential in hybrid combinations. There are
several criteria by which a breeder can choose suitable parents for successful hybridization,
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of which the two important are: combining ability of the parents and genetic diversity
between the parents. The great interest in genetic diversity arises from the possibility of
demonstrating that phenotypic mean values express, in a larger or smaller degree, the
genotypic value of an individual. Thus, while evaluating the divergence among populations,
based on average phenotypic values, the divergence among genotypic values associated
with gene frequency in different sample units (populations, varieties, clones, etc.) is also
evaluated. Among the several techniques used to express divergence between samples
genetic base, the Mahalanobis’ generalized distance (D2) stands out as one of the most
robust (Rao, 1952). The cluster analysis based on D2 data is used for grouping samples in
such a way that a high level of homogeneity within each group and high heterogeneity
between groups is obtained (Johnson and Wichern, 1982).
In spite of several genetic explanations for the phenomenon heterosis, it was conceived
long before particularly in corn that its manifestation depends on genetic divergence of two
parents (Hayes and Johnson, 1939; Hallauer and Miranda Filho, 1981). According to Falconer
and Mackay (1996), the magnitude of the heterosis manifested in a cross between two
samples depends on the square of the gene frequency difference multiplied by the dominant
deviation of the character under analysis. Several studies on wide array of crops viz,.
mungbean, triticale, rape , tomato, blackgram and sesame established close correspondence
between the magnitude of genetic divergence and heterosis. However, heterosis does not
always occur when divergent lines are crossed as found in alfalfa and sesame. Several
research findings indicated that the magnitude of heterosis for yield and its components
was found to be higher with restricted range of parental diversity than with extreme ones
in different crops like, groundnut, maize, triticale and cowpea. With this background, the
present investigation was designed to elucidate the kind of relationship that exists between
parental diversity and heterosis over both mid-parent and better parent in eggplant.
Materials and methods
Plant material and growing conditions
Materials for the commencement of the investigation comprised of 70 entries of eggplant
entries consisting of 10 elite varieties of India, 16 stable breeding lines developed at
different Agricultural Universities and Research institutes of India and 44 indigenous
cultivars collected from the farmers of eastern and North-eastern part of India and
Bangladesh conserved at the Department of Vegetable crops, Bidhan Chandra Krishi
Viswavidyalaya, West Bengal, India. These entries were evaluated in three consecutive
years (2000-2001 to 2002-2003) following randomized block design with 3 replications at
Central Research Station, Bidhan Chandra Krishi Viswavidyalaya lying at 23oN latitude,
89oE longitude and at 9.75 m elevation above mean sea level during autumn-winter
season (September to March) under the average day and night temperature ranging
between 24.8 to 33.4 oC and 10.2 to 25.1oC for 18 growth, yield components, fruit yield
and fruit quality traits.
Characterization
The growth, yield components, fruit yield and fruit quality traits included plant height
(cm), primary branches/plant, terminal shoots/plant, thickness of terminal shoot (cm),
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leaves/plant, mean leaf area (cm2), leaf area/plant (m2), calyx length, calyx diameter
(cm), fruit length (cm), fruit girth (cm), fruits/plant, fruit weight (g), fruit yield/
plant(kg), moisture (%), crude protein (g/100gfresh), total phenol (mg/100g fresh) and
total sugar (%) contents of fruits of marketable maturity.Each entry was grown in 2 rows
of 6.0 m long with a spacing of 70 cm × 70 cm following all recommended agronomic
practices for raising a healthy crop and observations on 18 characters were recorded on
5 randomly selected plants of each entry in a replication. Different biochemical
compositions of fresh fruits of marketable maturity (15-25 days after anthesis depending
on the genotype) were estimated from the sampled fruits of all the entries following
standard methods: 1) total sugars by anthrone method (Dubois et al. 1951), 2) crude
protein through estimation of nitrogen by micro-kjeldahl method (Sadasivam and
Manickam, 1996) and 3) total phenols by folin-ciocalteau reagent method (Bray and
Thrope, 1954) and expressed on fresh weight basis.
Data analyses for genetic divergence
Genetic divergence among the entries was estimated by the Mahalanobis’ generalized
distance ((Mahalanobis, 1936) as per Rao (1952) which is defined as: D2 = d’W-1d, where d’
is transpose of the vector of difference among means of accesses for all p characters, W is
the p x p matrix of residual variances and covariances and d is the vector of differences
among means of accesses for all p characters. The Tocher method (Rao 1952) was used to
define similarity groups. Estimation of inter and intra-cluster distance averages was
performed according to Singh and Chaudary (1979). Based on the divergence, as measured
by Mahalanobis’ D2 statistic employing pooled data over 3 years for the 18 characters the
70 entries could be grouped into 6 distinct clusters using Tocher’s method as described by
Rao (1952). Diversity of selected 9 parental lines was again determined separately based on
4 important characters, viz, plant height, fruits/plant, fruit weight and fruit yield/plant.
Development of hybrids
The 9 parents selected from the lot of 70 from the 6 clusters (Muktakeshi: cluster 1;
Nadia Local and Uttara: cluster 2; Pusa Purple Cluster, Pusa Anupam and HE-12: cluster
3; Nawabganj Local: cluster 4, Shyamala: cluster 5 and Singnath 666: cluster 6) were
crossed in 9 x 9 diallel mating design excluding the reciprocals.
Data analyses for manifestation of heterosis
The 36 hybrids along with their 9 parents were evaluated during autumn-winter season,
2006-07 following randomized block design with 3 replications at Central Research
Station, Bidhan Chandra Krishi Viswavidyalaya for 4 quantitative traits viz, plant height
(cm), fruits/plant, fruit weight (g) and fruit yield (kg). Each hybrid and parental line was
grown in 2 rows of 6.0 m long with a spacing of 70 × 70 cm. All the recommended
agronomic practices were followed for raising a healthy crop. The observations were
recorded on 5 randomly selected plants of each genotype. Ten fruits of marketable
maturity (well developed but soft, tender and lustrous) from the 5 selected plants per
replication were used to take fruit weight. The mean values computed over three
replications were used for the estimation of relative heterosis over mid-parent (H1) and
heterobeltiosis over better parent (H2). In order to assess the existence of relationship,
if any, between the estimates of both relative heterosis (H1) and heterobeltiosis (H2) of
the crosses and genetic divergence of their respective parents as measured by intra and
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Advances in Genetics and Breeding of Capsicum and Eggplant
inter-cluster D2 values based on 18 characters (D2 1) and total D2 values of two parents
based on 4 characters (D2 2), correlation and regression analysis between heterosis and
parental divergence for the selected characters were estimated.
Results and discussion
Divergence in parental lines
The analysis of variance revealed significant differences among the 70 entries in respect
of all the 18 characters. Based on the divergence between the entries, as measured by
the D2 statistic, the 70 entries were grouped into 6 distinct clusters (Table 1). It revealed
lack of correspondence between geographical origin and genetic divergence of the
entries. Grouping of the eggplant entries only in 6 clusters despite considering 18 wide
arrays of characters indicated that either common character constellation was manifested
simultaneously in the genotypes or mutual balancing was operative in the genotypes. In
fact, no character contributed overwhelmingly towards divergence of the genotypes, the
highest and lowest being 7.03 and 1.39 % by fruit weight and total sugar content of fresh
fruit, respectively. This suggests that, as occurred with the tomato, eggplant suffered
several bottlenecks during domestication (Lester and Hasan, 1991), which has resulted in
a low diversity of the crop (Karihaloo et al., 1995). However, the estimated genetic
divergence among the entries is related only to the variability existing in the characteristics
used for their estimation, not allowing extrapolations to other non-analyzed characters.
Although cluster wise mean values for 18 characters showed appreciable variability (Table
2) divergence of the selected 9 parents, as measured by D2 statistic, were also determined
separately employing fruit yield and 3 other important yield components. Hence, both
intra and inter-cluster D2 values based on 18 characters (D21) and total divergence based
on 4 characters (D22) were utilized to express parental divergence.
Table 1. Clustering pattern of 70 entries of eggplant based on pooled data for 18 characters.
328
Cluster
Brinjal entries under the clustera
1
‘Bhagyamati’(Hyderabad), ‘CH 309’ (Ranchi), ‘Astrang Local’ (Orissa, LC), ‘Kanta Makra’
(West Bengal, LC), ‘Mukta’ (Orissa, LC), ‘BR 112’ (Hisar), ‘Malapur Local’ (Karnataka,
LC), ‘BB 40’( Orissa), ‘Nilgiri Local’ (Orissa, LC), ‘CH 166’ (Ranchi), ‘Coochbehar Local’
(West Bengal, LC), ‘China’ (Bangladesh, LC), ‘CO-2’ (Tamil Nadu), ‘Jafar’s Black’
(Bangladesh, LC), ‘Jessore Local’ (Bangladseh, LC), ‘Makra’ (West Bengal, LC), ‘Hisar
Pragati’ (Haryana), ‘CH 243’ (Ranchi), ‘SM 59’ (Hyderabad), ‘CH 671’ (Ranchi), ‘CH 165’
(Ranchi), ‘CH 668’ (Ranchi), ‘Orissa Muktakeshi’ (Orissa, LC), ‘Muktakeshi ‘(West Bengal,
LC), ‘Makra Long’ (West Bengal, LC), ‘Pusa Purple Long’ (New Delhi), ‘Duli’ (West Bengal,
LC), ‘Orissa Local’ (Orissa, LC), ‘Hisar Shyamal’ (Haryana), ‘Makra Round’ (West Bengal,
LC), ‘Orissa Green’ (Orissa, LC), ‘BB 14 ‘(Orissa), ‘Chakdah Local’ (West Bengal, LC), ‘CH
156’ (Ranchi), ‘Guli’ (West Bengal, LC), ‘HLB 25’ (Haryana), ‘Bholanath’ (Tripura, LC),
‘Bhangar’ (West Bengal, LC)
Advances in Genetics and Breeding of Capsicum and Eggplant
2
‘Haringhata Local’ (West Bengal, LC), ‘Orissa Local’ (Orissa, LC), ‘Puri Local ‘(Orissa,
LC), ‘CH 225’ (Ranchi), ‘CH 207’ (Ranchi), ‘Hisar Jamuni’ (Haryana), ‘KS 352’
(Kalyanpur), ‘NDBS-26-1’ (Faizabad), ‘NDBS-28-2’ (Faizabad), P’LR 1 ‘(Tamil Nadu),
‘KS 331’ (Kalyanpur), ‘Utkal Madhu’ (Orissa), ‘Green Rocket’ (Orissa), ‘DLB 11’ (New
Delhi), ‘Tufanganj Local’ (West Bengal, LC), ‘Nadia Local’ (West Bengal, LC), ‘Sel 4’
(Varanasi), ‘Falakata Local’ (West Bengal, LC), ‘Islampuri’ (West Bengal, LC), ‘Uttara’
(Bangladesh), ‘Melwanki Local’ (Karnataka, LC)
3
‘Pusa Purple Cluster’ (New Delhi), ‘CH 204’ (Ranchi), ‘Pusa Anupam’ (New Delhi),
‘Orissa Green ‘(Orissa, LC), ‘HE 12’ (Punjab)
4
‘Nawabganj Local’ (West Bengal, LC), ‘Singhnath Local’ (Tripura, LC)
5
‘Shyamala’ (Hyderabad)
6
‘Singnath 666’(Bangladesh)
Place of collection/development of the genotype in parenthesis; LC denotes local cultivar;
Other entries are either improved varieties or breeding lines; Entries in bold letter are
selected parents for the diallel cross.
a
Table 2. Cluster-wise mean values for 18 characters.
Calyx
length
(cm)
Calyx
diameter
(cm)
3.27
2.93
3.30
2.96
2.55
2.75
107.29
3.07
2.10
2.06
Cluster
Plant
height
(cm)
Primary Terminal Thickness
Leaves/ Mean leaf Leaf area/
branches/ shoots/ of terminal
plant area (cm2) plant (m2)
plant
plant shoot (mm)
1
72.25
13.65
36.25
3.85
248.06
128.31
2
73.02
13.71
42.68
3.66
261.10
124.73
3
65.67
13.62
40.81
3.27
285.09
4
58.36
8.00
11.97
4.25
68.71
226.28
4.99
3.24
3.47
5
67.67
16.90
86.20
2.50
330.33
58.43
1.95
1.43
1.45
6
98.47
14.00
27.83
3.23
201.83
152.20
3.01
4.05
1.76
Fruit
length
(cm)
Fruit girth
(cm)
Fruit
weight
(g)
Fruits/
plant
Moisture
(%)
Crude
Total sugar
protein
(%)
(g/100 g)
Phenol
(mg/
100g)
Fruit yield/
plant (kg)
1
9.98
6.02
128.95
19.84
92.51
0.09
2.33
2
10.82
5.14
100.61
35.41
91.32
1.49
2.66
0.13
2.93
3
10.52
4.04
51.50
77.81
89.06
1.23
1.69
0.21
3.75
4
14.03
7.91
302.95
3.73
92.48
1.77
3.86
0.08
1.11
5
11.80
2.20
27.27
55.33
89.27
1.29
1.84
0.19
1.54
6
20.43
2.27
53.13
40.50
90.08
1.41
2.49
0.14
2.77
1.68
3.65
Heterosis
Selection of 9 parental lines from all the 6 different clusters was considered relevant in
theoretical consideration that not only pure dominance and its interactions but additive
X additive epistasis also can cause heterosis and it is likely that very low parental
divergence fail to result heterosis. In the 36 cross combinations, the range of relative
heterosis (heterosis over mid-parent), H1 and heterobeltiosis (heterosis over better
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Advances in Genetics and Breeding of Capsicum and Eggplant
parent), H2 (H1: 0.47 to 52.45%, H2: - 12.12 to 35.58% for plant height; H1: -72.71 to
38.06%, H2: - 85.65 to 11.52% for fruits/plant; H1: -36.76 to 40.42%, H2: - 65.73 to 41.03%
for fruit weight and H1: -24.87 to 107.35%, H2: - 37.48 to 83.08% for fruit yield/plant) was
very wide revealing considerable variation in manifestation of heterosis in the hybrids for
these characters (Table 3). Dominance of small fruited ness and internal balancing
between fruit number and fruit weight might have caused marked negative heterosis in
about one third of the hybrids for both fruit number/plant and fruit weight. Although,
significant positive heterosis in fruit yield/plant over both mid-parent and better parent
was manifested in most of the hybrids but it was not always associated with heterosis in
fruits/plant and fruit weight. Six hybrids could be identified as most promising (‘Uttara’
x ‘Pusa Anupam’, ‘Uttara’ x ‘Nawabganj Local’, ‘Pusa Purple Cluster’ x ‘Pusa Anupam’,
‘Pusa Purple Cluster’ x ‘Nawabganj Local’, ‘Pusa Anupam’ x ‘Nawabganj Local’ and
‘Muktakeshi’ x ‘Nawabganj Local’) which manifested commercially exploitable range of
40 to 80 percent heterosis over better parent (Table 3).
Divergence and heterosis
The genetic divergence of the parents (D21, D22) and heterosis (both relative heterosis
and heterobeltiosis) did not exhibit any definite relationship for fruit yield/plant. For
example, of the 6 promising hybrids manifesting high range of heterobeltiosis for fruit
yield/plant, one each had low (‘Pusa Purple Cluster’ x ‘Pusa Anupam’: D21= 19.93, D22 =
63.07) and medium (‘Uttara’ x ‘Pusa Anupam’: D21= 43.25, D22 = 118.41) parental
divergence; one had high (‘Muktakeshi’ x ‘Nawabganj Local’: D21= 33.44, D22 = 2569.15)
and the other three had very high (‘Uttara’ x ‘Nawabganj Local’: D21= 61.66, D22 =
4630.57, ‘Pusa Purple Cluster’ x ‘Nawabganj Local’: D21= 95.44, D22 = 5083.65 and ‘Pusa
Anupam’ x ‘Nawabganj Local’: D21= 95.44, D22 = 5922.26 ) parental divergence. There
are few examples where hybrids having low parental divergence (Uttara x Pusa Purple
Cluster: D21= 43.25, D22 = 16.71; HE12 x Nadia Local: D21= 43.25, D22 = 22.21) manifested
considerable heterobeltiosis for fruit yield/plant and on the contrary hybrids having very
high parental divergence (‘Nawabganj Local’ x ‘Shyamala’: D21= 104.70, D22 = 5719.75
and ‘Nawabganj Local’ x ‘Singnath 666’: D21= 70.74, D22 = 5025.89) registered significant
negative heterosis over both mid and better parent (Table 3). Considering the
manifestation of medium range of positive relative heterosis (26.79 to 43.69%) and
heterobeltiosis (12.17 to 37.82%) in 7 hybrids having low to medium parental divergence,
some level of correspondence between parental divergence and heterosis for fruit yield/
plant could be indicated.
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Table 3. Parental divergences of 36 cross combinations (D2 1 and D2 2) and
percentage relative heterosis (H1) and heterobeltiosis (H2).
Hybrida
D2 1
D2 2
P1 x P2
P1 x P3
P1 x P4
P1 x P5
P1 x P6
P1 x P7
P1 x P8
P1 x P9
P2 x P3
P2 x P4
P2 x P5
P2 x P6
P2 x P7
P2 x P8
P2 x P9
P3 x P4
P3 x P5
P3 x P6
P3 x P7
P3 x P8
P3 x P9
P4 x P5
P4 x P6
P4 x P7
P4 x P8
P4 x P9
P5 x P6
P5 x P7
P5 x P8
P5 x P9
P6 x P7
P6 x P8
P6 x P9
P7 x P8
P7 x P9
P8 x P9
SE±
43.25
43.25
43.25
22.16
42.86
61.66
50.73
39.41
19.93
19.93
43.25
77.74
95.44
32.43
59.07
19.93
43.25
77.74
95.44
32.43
50.07
43.25
77.74
95.44
32.43
50.07
42.86
61.66
50.73
39.41
33.44
83.33
56.93
104.70
70.74
55.82
16.71
118.41
180.98
96.94
353.65
4630.57
130.15
50.32
63.07
122.57
53.22
499.18
5083.65
73.33
61.46
55.54
49.72
827.12
5922.26
93.31
131.09
22.21
980.33
6063.06
253.22
283.19
756.39
5524.57
176.64
204.31
2569.15
697.68
424.51
5719.75
5025.89
81.13
Plant height
Fruits/plant
Fruit weight
Fruit yield/plant
H1
H2
H1
H2
H1
H2
H1
H2
37.22**
35.2**
9.83**
43.94**
21.65**
52.45**
7.72*
9.81**
48.83**
22.39**
25.79**
14.56**
39.05**
4.35
5.67
10.72**
34.76**
7.59*
17.88**
8.82**
6.79*
35.09**
6.89*
25.58**
9.91**
2.51
0.47
16.49**
13.91**
18.94**
15.86**
8.21*
3.59
18.31**
9.53**
9.89**
3.25
29.31**
32.42**
4.26
27.8**
15.87**
35.58**
1.05
-1.42
37.55**
21.47**
18.04**
3.14
30.72**
3.84
-9.98**
3.05
17.5**
4.57
2.95
0.12
-2.31
25.87**
-3.11
17.22**
8.55*
-12.12**
-14.5**
16.27**
7.38*
-3.84
-1.25
-2.99
-2.68
11.73**
-11.31**
-6.77*
3.54
13.56**
38.06**
28.13**
1.76
29.62**
9.06**
3.53
22.83**
0.27
20.93**
-12.81**
6.31
-4.05
-4.97
6.63*
-0.91
5.88
-8.51**
-18.21**
-11.16**
-12.59**
10.77**
-7.26*
-24.22**
-23.65**
38.65**
-24.02**
-35.78**
-14.64**
30.33**
175.7**
-8.73**
1.26
-72.71**
-58.24**
22.69**
3.18
6.06
11.52**
-1.75
-18.55**
-15.92**
-42.44**
-0.01
8.80*
-14.3**
-2.37
-26.23**
-33.13**
-49.71**
-8.21*
-10.98**
-7.52*
4.6
-45.88**
-57.7**
-26.23**
-35.54**
4.57
-46.27**
-60.98**
-39.96**
-2.14
-55.22**
-66.82**
-29.79**
-4.63
63.63**
-41.72**
-29.86**
-85.65**
-77.62**
5.44
3.74
16.22**
28.58**
23.18**
22.58**
-14.68**
-26.19**
2.1
-2.36
40.42**
25.49**
8.11
-13.08**
-30.5**
6.12
3.36
32.68**
31.43**
-11.11*
-37.33**
23.72**
6.75
6.07
-9.21*
-30.61**
28.32**
45.1**
-11.13*
-36.05**
16.19*
16.21**
-36.76**
-4.84
-7.42
-19.4**
-18.7**
14.64**
4.55
3.81
-2.72
1.86
9.99
-36.18**
-56.36**
-30.8**
-17.36**
16.02**
14.92*
7.56
-39.59**
-60.27**
-22.95**
-2.79
18.4**
7.81
-44.25**
-65.73**
4.71
-7.09
-3.32
-39.89**
-61.17**
-0.96
41.03**
-38.05**
-63.39**
-15.91**
8.77
-56.75**
-44.03**
-37.8**
-57.09**
-54.21**
-13.27*
5.97
43.69**
92.07**
36.76**
41.62**
24.31**
107.35**
8.19**
13.86**
50.47**
47.98**
0.52**
17.89**
92.87**
2.74**
0.11
33.47**
38.37**
24.27**
90.55**
-3.1**
-4.59**
26.79**
24.86***
78.52**
-17.28**
49.98**
8.87**
30.91**
-8.64**
43.12**
90.13**
28.85**
-4.86**
-5.56**
-24.87**
6.89**
0.19
37.82**
83.08**
19.74**
31.61**
7.02**
49.86**
-22.68**
0.18
49.51**
25.02**
-10.12**
5.29**
43.24**
-24.61**
-8.53**
12.17**
23.03**
11.62**
42.11**
-28.6**
-12.31**
18.86**
-3.72**
19.13**
-45.3**
17.78**
-11.82**
-9.51**
-37.48**
18.24**
53.74**
2.74**
-7.23**
-7.27**
-40.4**
-16.35**
0.22
P1= ‘Uttara’; P2 = ‘Pusa Purple Cluster’; P3= ‘Pusa Anupam’; P4= ‘HE 12’; P5 = ‘Nadia Local’;
P6= ‘Muktakeshi’; P7 = ‘Nawabganj Local’; P8 = ‘Shyamala’; P9= ‘Singnath 666’.
a
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Advances in Genetics and Breeding of Capsicum and Eggplant
Table 4. Regression and correlation (r) between parental divergence and heterosis
(Relative heterosis and Heterobeltiosis) for four characters. Standard error
of the regression equations in parenthesis.
Parental
divergence
Relative heterosis
Heterobeltiosis
Plant height
D1
Regression equation=21.706 0.0631D2 (5.9887, 0.1032),
r = -0.104
D 22
Regression equation = 16.742 + 0.0012 D2 Regression equation =7.201 + 0.0009D2
(2.7431, 0.0011),
(2.507, 0.808), r = 0.137
r = 0.183
D21
Regression equation = 38.497 0.6569 D2
(15.1194, 0.2606),
r = - 0.396*
Regression equation =21.5748 - 0.8373
D2(9.9242, 0.1711),
r = - 0.642**
D22
Regression equation = 10.658 0.0055 D2
(7.2732, 0.0029),
r = - 0.303
Regression equation = -11.5462 - 0.0088
D2 (4.7211, 0.0019),
r = - 0.617**
D21
Regression equation = 38.477 0.6753 D2
(7.3842, 0.1272),
r = - 0.673**
Regression equation = 28.5487- 0.9183
D2(8.6154, 0.1485),
r = - 0.727**
D22
Regression equation = 13.362 -0.0083 D2
(3.0216, 0.0012),
r = - 0.757**
Regression equation = -6.6824 - 0.0105D2
(3.7863, 0.0015),
r = - 0.759**
2
Regression equation =12.8741­0.0829 D2
(6.2004, 0.1068),
r = - 0.132
Fruits/plant
Fruit weight
Fruit yield/plant
2
D1
Regression equation = 21.108+0.1703D2
(14.7185, 0.253),
r = 0.114
Regression equation = 10.6067 - 0.0499
D2 (12.591, 0.2171),
r = - 0.039
D22
Regression equation = 22.261+0.006D2
(6.377, 0.0025 D2),
r = 0.371*
Regression equation = 5.514034 +
0.00184 D2 (5.7876, 0.0023),
r = 0.133
* P = 0.05, ** P = 0.01
Correlations between relative heterosis and heterobeltiosis and parental divergence
based on both D21 and D22 for four characters registered some what consistent
associationships (Table 4). Although the association between parental divergence and
heterosis for fruit yield/plant was positive in three comparisons, in one case only (D22 vs
relative heterosis), the correlation coefficient (r = 0.371*) was significant (Table 4).
Although the estimates of heterosis for fruit yield/plant regressed towards the genetic
distance of the parents, it was only significant for relative heterosis regressing towards
D22 (Table 4) which was not enough for confident prediction of heterosis. Dominant
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Advances in Genetics and Breeding of Capsicum and Eggplant
manifestation of small fruited ness in the F1 hybrids, internal balancing between fruit
number and weight and internal cancellation of the components of heterosis coupled
with the presence of linkage, epistasis, etc. might have brought about relatively weak
association between parental diversity and heterosis. Divergence of parents with respect
to some characters not included in the present study might be responsible for manifestation
of higher heterosis in certain crosses involving parents having lower parental divergence
or parents grouped in the same cluster.
Conclusions
This study demonstrated positive relationship between genetic distance of the parents
and both relative heterosis and heterobeltiosis for fruit yield/plant which would be of
interest to check the efficiency of selection of parents based on genetic divergence as
envisaged here and in other studies with different crops as well. However, the relationship
was not strong enough for regression of heterosis on genetic distance to confidently predict
the level of heterosis based on a given value of genetic distance between the parents
which also indicated that there was an optimum level of genetic divergence between
parents to obtain heterosis in the F1 generation. It is suggested that reliance should also
be placed on the genetic distance apart from combining ability while selecting the parents
for hybridization in order to realize high frequency of heterotic hybrids in eggplant.
Acknowledgements
This research has been out under National Agricultural Technology Project “Development
of Hybrids in Vegetable crops” financed by Indian Council of Agricultural Research, Govt.
of India.
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variation in the eggplant, Solanum melongena L. (Solanaceae). Theoretical and
Applied Genetics 90:767-770.
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Lester, R.N.; Hasan, S.M.Z. 1991. Origin and domestication of the brinjal eggplant, Sola­num
melongena, from S. incanum, in Africa and Asia. In: Hawkes, J.G.; Lester, R.N.; Nee,
M.; Estrada, N. (eds). Solanaceae III: taxonomy, chemistry, evolution. The Linnean
So­ciety of London, London, UK, p. 369-387.
Mahalanobis, P.C. 1936. On the generalized distance in statistics. Proceedings of the
National Academy of Science India 2:49-55.
Rao, C.R. 1952. Advanced Statistical Methods in Biometrical Research. John Wiley & Sons,
New York.
Sadasivam, S.; Manickam, A. 1996. Biochemical Methods. New Age International (P) Ltd.,
New Delhi, India.
Singh, R.K.; Chaudary, B.D. 1979. Biometrical methods in quantitative genetic analysis.
Kalyani Publishers, New Delhi.
Singh, N.; Kalda, T.S. 2001. Brinjal, In: Thamburaj, S. and Singh, N (eds.) Textbook of Vege­
tables, Tuber Crops and Spices. ICAR, New Delhi, India, p. 29-48.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Per se performance for fruit yield of green chilli varieties
R.M. Hosamani1, B.C. Patil2, P.S. Ajjapplavar2
1
Department of Horticulture, University of Agricultural Sciences, Dharwad-580 005, Karnataka, India.
Contact: [email protected]
2
AICVIP, Zonal Horticultural Research and Extension Centre (UHSB), Dharwad -580005, India.
Abstract
Chilli (Capsicum annuum L.) is an important vegetable and spice crop in India. In Karnataka
there are many local varieties being grown for various valuable traits. They have variable
performance over seasons and locations as well as different response to various biotic and
abiotic stresses, which makes their production unpredictable. New varieties are being
developed in different institutions. Their suitability and performances in other locations
needs to be assessed. With this objective in mind ten varieties/lines developed in different
institutions across India were tested for their performance for green fruit yield under All
India Coordinated Vegetable Improvement Project at the Main Agricultural Research Station,
University of Agricultural Sciences, Dharwad. Ten chilli varieties including checks (PC-2062,
ACS-06-01, ACS-06-02, CCH-05-01, AKC-406, BCC-1, VR-378, LCA-206, JCA-283, Byadagi
Kaddi) were grown using a randomized block design with three replications with a spacing of
60 cm between rows and 45 cm between plants within a row in a plot size of 4.5 m x 3.0 m
during kharif (monsoon crop) 2008-09. Observations on days to 50% flowering, plant height,
branches per plant, number of fruits and yield per plant, fruit length, fruit width/diameter,
fruit weight, green fruit yield per hectare based on plot yield was recorded and statistically
analyzed. These ten varieties differed significantly for all the traits except plant height.
‘VR-338’ recorded highest green fruit yield of 23.79 t/ha followed by ‘PC-2062’ (19.15 t/ha),
‘BCC-I’ (17.65 t/ha), and ‘ACS-06-01’ (12.84 t/ha). The range for days to 50% flowering was
35.6 to 43.00 days after transplanting. Average single fruit weight ranged from 9.70 g
(Byadagi Kaddi) to 7.83 g (‘VR-325’). Highest green fruit yield recorded in ‘VR-378’ was
mainly due to highest fruit yield per plant (746.67 g), highest single fruit weight (7.83 g) as
well as highest number of fruits per plant (66.22).
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Genetic and phenotypic correlations between productivity
components of sweet pepper
L. Khotyleva, L. Tarutina, L. Mishin, M. Shapturenko
Institute of Genetics and Cytology, National Academy of Sciences of Belarus, 27 Akademycheskaya st.,
220072 Minsk, Belarus. Contact: [email protected]
Abstract
Genetic and phenotypic correlations were studied among 9 basic productivity components
(weight, number of fruits per plant and average weight of a fruit in early crop, the same
traits in general crop, length of a fruit, diameter of a fruit, pericarp thickness) of sweet
peppers. In this study were included 13 lines produced from different cultivars, adapted to
growing under Belarus conditions, as well as 40 topcrossing and 30 diallel hybrids F1 were
taken as parental material. The experiment was performed in unheated greenhouses under
Minsk conditions. General tendencies of linked variability in quantitative traits observed in
the lines remained in hybrids. Genetic correlations, as a rule, were pronounced stronger
than phenotypic ones. Productivity of one plant correlated positively with the number of
fruits per plants (r= 0.68) and negatively with fruits weight (r= –0.54), fruits diameter (r=
–0.55) and pericarp thickness (r= –0.30). High genetic correlations were observed between
the mean fruit weight and fruit diameter (r= 0.88), and between the mean fruit weight and
pericarp thickness (r= 0.70). No genetic relationship was revealed between productivity per
plant and other traits. It testifies that productivity is a complex trait. Selection for one of
its components will not give improvement as a whole, and, on the contrary, can worsen
population quickly. Hence, selection should be conducted for two and more traits to
increase productivity.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Assessing genetic variation by thermogravimetric analysis to predict
heterosis of sweet pepper lines
M. Shapturenko1, L. Tarutina1, L. Mishin2, L. Shostak3, L. Khotyleva1
1
Institute of Genetics and Cytology National Academy of Sciences of Belarus, 27 Academic str.,
220072 Minsk, Belarus. Contact: [email protected]
2
Institute of Vegetable Growing, 220028 Minsk, Belarus
3
The Belarus State Technological University, 220050 Minsk, Belarus
Abstract
The objective of this study was to evaluate the usefulness of thermogravimety and differential
scanning calorimetry for selection of the best parents for breeding of hybrid Capsicum
annuum L. Phenotypic characteristic was measured for 6 agronomic traits in 13 parents and
28 F1 hybrids. Diversity of the lines was measured by kinetic parameters (Δm, Ea) thermo­
destruction of seeds. The possibility of using kinetic parameters of seed destruction for
predicting a yield potential of sweet pepper was considered. Coefficient of correlation of
diversity with mid parent heterosis of fruit weight per plant was positive and significant
(r=0.52). It is shown that the value Ea can be used for analysing heterogeneity of parent
breeding material and developing heterotic groups.
Keywords: sweet pepper (Capsicum annuum L.), heterosis, kinetic parameters of seed, ge­
netic diversity.
Introduction
Thermoanalysis methods are widely used in scientific researches and an industrial
practice, owing to high sensitivity and objectivity in assessing thermal characteristics of
substances. They make it possible to obtain valuable data on structure, composition and
properties of both inorganic and organic materials, including polymers, provide
quantitative and qualitative information about physical and chemical changes that
involve endothermic or exothermic processes.
In recent time methods of the thermal analysis, such as thermogravimetry and differential
scanning calorimetry, are successfully used for studying properties of high-molecular
compounds, and allow to solve practical and fundamental problems (Karaosmanoglu F.
et al. 2001, Dimitrakopoulos A. et al., 2001). These give the information on thermal
stability, endo- and exothermal effects caused by changes in enthalpy and allows
estimate of heterogeneity of composition under study (Topor N., 1987).
In researches of biological objects thermal methods are used rather recently. The most
part of investigations is directed on studying of a fiber and oil quality of technical and
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Advances in Genetics and Breeding of Capsicum and Eggplant
food plants (Bartkowiak M. and R.Zakrzewski, 2004, Hernández-Montoya V. et al., 2009).
There are no data about a prediction of productive potential of agricultural plants on
the basis of seed’s kinetic parameters by methods TG and DSC.
However, the biochemical structure and balance of the reserved substances of a plant’s
seeds can provide the superiority of some genotypes in growth and development.
Therefore, research of thermal characteristics of seeds for selection of genotypes with
high genetic potential can be useful.
The objectives of the present study were to evaluate the relationship between kinetic
parameters of seeds and breeding value of sweet pepper.
Material and methods
Plant material and growing conditions
Thirteen lines of sweet pepper from the selection program of Institute of Vegetable
Growing (Belarus) and 28 hybrids (24 test-cross hybrids, 4 singl-cross hybrids) were
analyzed in this study. All peppers were grown up in unheated greenhouse of the Institute
of Genetics and Cytology NASB with three replications in a randomised blok with an area
per plant 35×50 cm.
Thermogravimetric analysis
Thermogravimetric (TG) analysis of sweet pepper seeds (5.0-5.1mg) was made with
thermoanalyser TA-4000 (modulus TG-50 Mettler Toledo STARe System, Switzerland) in
the temperature range of 25-5500C at heating rate of 50C/min and air flush rate of 200
ml/min. The DTG curve and the TG weight loss data were calculated using Graphware
(STARe System). Each sample was analyzed three times.
Kinetic parameters TG and DSC estimated by modified double logs method Broido (Broido
A. and H.Yow, 1977). Activation energy (Еа) was used as criterion of heterogeneity of a
chemical compound in reserve seed components.
The loss of sample weight and activation energy were evaluated at the following stage:
(I) 230-3000C, (II) 300-3500C, (III) 350-4700C, (IV) 470-5500C. Destruction of proteins (I
stage), fatty acids (II stage), nucleotides and nucleic acids (III-IV stages) took place step
by step during TG and DSC.
Data analyses
Quantitative analysis was carried out for early and total yield (fruit per plant, number
of fruits per plant, average weight of one fruit). Mean values of the agronomic traits
and its significance for parents and hybrids were carried out by standard methods (Sne­
decor G., 1967).
High parents heterosis (HPH) was calculated as superiority of the F1 hybrid over best of
parents (Pbest) in percent: i.e. HPH=100 × (F1-Pbest)/Pbest. Negative heterosis counted in
relation to worst of parents. Mid parents heterosis (MPH) was calculated as excess of the
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F1 hybrid over that mean of both parents trait in percent: MPH=100 × [(F1-(P1+P2)/2)/
(P1+P2)/2].
Cluster analysis and genetic distances (GDs) were performed with Statistica (Stat Soft
Inc.) computer package version 6.1. Correlation coefficients (r) were calculated for GDs
with F1 performance and heterosis.
Results and discussion
Phenotypic traits
The analysis of morphological traits has shown that the lines differ in productivity, early
ripeness, shape and color of fruit. Trial of F1 hybrids and analysis of the heterosis effect
have revealed combination with a high degree of heterosis for productivity (Table 1). In
nine combinations out of twenty eight, the hybrids were significantly superior to the
best parent in fruit weight per plant by 10-80%. The value of MPH reached 22-116%.
High parameters of the heterosis effect were detected among hybrids produced in
combinations where the lines L620, L542, L620 were used as a sire components ( ). The
highest number of heterotic hybrids were produced with L586 ( ). In five hybrid
combinations, the value of HPH exceeded 40% and nine F1s were significantly superior to
parents by 10-40%.
Analysis of the MPH level has shown that 15 hybrids were significantly superior to parents
in fruit weight per plant in total yied, with the heterosis value being above 70% in four
F1 combinations. A great part of hybrids with a high MPH was also obtained in cross with
L542 and L620.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Table 1. Mean, High parent (HPH) and mid parent (MPH) heterosis for traits
in total yield in 28 sweet pepper F1s.
fruit weight per plant
average weight of one fruit
number of fruit per plant
MPH,
%
Mean,
(g)
HPH, %
MPH,%
Mean
HPH,
%
MPH, %
-28,4*
-27,92**
124.3
-21.8*
-7.9
4.6
-30.3**
-16.4*
1245
-11,7
17,18*
121.9
-1.2
4.1
10.4
-11.9
13.0*
888
24,2*
29,07*
143.0
22.6*
25.4*
6.4
-3.0
1.6
1053
45,2**
87,70**
109.2
-1.5
24.8*
9.8
48.5**
48.5**
Hybrid F1
Mean,
(g)
HPH,
%
L579×L602
519
×L605
×L620
×L542
L582×L602
963
-5,8
10,25
103.5
-34.9**
-23.7*
7.6
-15.5*
12.6*
×L605
1196
-15,2*
-1,64
119.9
-2.8
1.61
10.4
-11.9*
5.0
×L620
837
-18,1*
-0,53
122.3
4.3
6.4
7.0
-22.2*
0.0
×L542
875
10,1*
22,46*
98.2
-12.8*
11.1
9.0
0.0
15.4*
L585×L602
977
22,9*
28,55**
147.3
-7.3
-0.3
6.6
13.8*
28.2*
×L605
1164
-17,4*
5,58
122.3
-10.6
-6.0
9.6
18.6*
9.1
×L620
732
1,0
0,55
130.0
-4.9
2.4
5.6
-6.7
5.1
×L542
685
-13,8*
13,98*
109.1
-20.2*
8.7
6.2
-6.1
0.0
L586×L602
1225
69,0**
83,25**
145.6
-8.4
-3.1
8.4
86.7**
88.8**
×L605
1006
-13,4*
-0,49
142.1
0.4
7.3
7.0
-40.7**
-13.6*
×L620
958
44,9**
50,51**
127.5
9.9
-1.39
7.6
26.7*
46.1**
×L542
1105
80,6**
116,88**
115.7
-18.2*
12.5*
9.6
45.4**
75.5**
L588×L602
758
4,6
19,65*
151.3
-4.8
0.73
5.6
24.4*
34.9*
×L605
1045
-25,9*
7,07
136.2
-3.8
2.87
8.0
-32.2-
2.6
×L620
725
9,7
20,53*
122.7
-13.3*
-5.1
6.0
0.0
22.4*
19.2*
×L542
728
34,3*
53,42**
119.5
-15.6*
16.2*
6.2
-6.1
L601×L602
883
-0,6
9,49
154.7
-2.6
5.2
5.8
12.1
5.4
×L605
1380
-2,1
20,10*
162.5
20.1*
25.7*
8.6
-27.1*
-6.5
×L620
772
-13,1*
-0,32
132.4
-2.14
6.1
6.0
-9.1
-4.8
×L542
669
-24,7*
3,32
119.5
-11.7
30.2*
5.6
-15.1*
-15.1*
L587×L603
605
-19,0*
-1,79
142.0
-12.7*
8.7
4.3
-14.0*
-11.3*
×L615
713.3
-19,6*
3,94
128.0
-3.8
10.5*
5.7
-18.6*
-5.0
×L620
686.7
3,9
19,90*
141.4
20.6*
31.1*
5.0
-16.7*
-9.1
×L542
773.3
59,4**
73,32**
106.2
7.7
30.6*
7.7
16.7*
32.7*
* Indicates significance at P≤0.05
** Indicates significance at P≤0.01
Thermogravimetric analysis of sweet pepper seed destruction
Analysis of kinetic parameters of reserve components thermodestruction in sweet pepper
seed has revealed differences between lines in the value of activation energy which is
one of the parameters of seed qualitative composition in the accessions under study
(Table 2).
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The lines L602 (76kJ/mole) and L582 (75kJ/mole) have exhibited high Ea at the first
stage (proteine thermodestruction), whereas the lines L586 (66kJ/mole) and L620 (68kJ/
mole) have shown the lowest value Ea
Assessment of kinetic parameters at the second termodestruction stage (310-3600C) has
not revealed substanial differences between the lines – Ea value varied within the range
of 31-36kJ/mole. The line L605 showed low Ea parameters (35kJ/mole) and L620 did high
ones (46 kJ/mole) in the range of 350-4700C (tgermodestruction of fatty acids). At the
fourth stage (470-5500C) optimum values of Ea observed in L582 (28kJ/mole) and L603
(40kJ/mole).
Based on the data obtained by TG and DSC analysis, heterogeneity level and clusterization
of the line collection were performed by Ward’s method (Ward J.H. 1963). Mutual
relationships between lines are presented on a dendrogram (Fig. 1).
Table 2. Kinetic parameters of thermodestruction of sweet pepper
seeds (significant at P≤0.05).
Lines
∆m, %
(230310°C)
Ea
kJ/
mole
∆m, %
(310360°C)
Ea
kJ/
mole
∆m, %
(360470°C)
Ea
kJ/
mole
∆m, %
(470550°C)
Ea
kJ/
mole
L 542
L 579
L 582
L 585
L 586
L 587
L 588
L 601
L 602
L 603
L 605
L 615
L 620
16.94
17.58
14.36
14.42
15.46
18.28
16.30
17.88
15.86
17.46
19.44
14.74
15.07
70
71
75
72
66
68
71
74
76
74
72
73
68
8.94
12.29
13.38
10.83
9.04
13.29
9.24
11.76
12.56
12.92
9.76
10.56
11.20
33
35
36
34
35
36
36
33
37
35
31
33
36
37.89
32.05
35.18
38.28
38.75
29.73
36.32
32.3
35.08
33.9
31.38
36.6
35.57
42
38
42
43
44
34
41
39
38
39
35
42
46
19.73
22.34
18.56
19.29
21.06
20.2
19.65
14.07
18.5
22.97
20.97
20.15
20.45
31
36
28
32
39
29
31
32
34
40
36
32
34
According to the performed clusterisation the lines were distributed into three clusters.
The first consists of L542, L620,and L586. The second cluster was formed by L603, L605,
L587 and L579. In it L579 and L603 are located a common subcluster while the rest of
the lines formed external branches with L587 in the distance. The third cluster consisted
of L582, L601, L615, L588 and L585. In this, the lines L585 and L615 were most closely
spaced and L582 was the most distant.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 1. Dendrogram for 13 sweet pepper lines based on kinetic parameters
of seed’s thermodestruction by Ward’s method.
Correlations between kinetic parameters, productivity of lines and heterosis F1
Study of the possibility to use kinetic parameters of seed thermodestruction for predicting
plant productivity has shown that not all the parameters obtained at various thermo­
destruction stages are related to productivity (Table 3).
The kinetic parameters at II, III, IV stages of thermodestruction do not correlate to plant
productivity in both the early and total yields and cant’s be used for predicting yield
potential in sweet pepper lines.
Table 3. Coefficient of correlation of genetic distances based on TG and DSC
with some agronomic traits of pepper lines.
Early yield
fruit weight per
plant, (g)
number of fruit per
plant
fruit weight per
plant, (g)
number of fruit per
plant
I
0,42*
0,22
0,36
-0,04
II
-0,47*
-0,42*
-0,51**
0,19
III
-0,03
-0,02
-0,34
0,05
IV
0,10
-0,23
0,12
-0,21
*P<0.05; **P<0.01
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Total yield
Stage
thermodes
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Advances in Genetics and Breeding of Capsicum and Eggplant
The results of the thermogravimetric analysis indicate that the content and composition
of seed proteins are of a determinative value in formation and development of plants
among the analysed components. Decrease of the relation to the total yield may result
from the influence of exogenous factors.
Analysis of the relationship between the heterogeneity level of sweet pepper and the
heterosis effect of F1 hybrids has shown that there are highly significant positive co­
rrelations (Fig. 2).
Figure 2. Linear correlation of the values of genetic distances with heterosis
for fruit weight per plant: (a) MPH, (b) HPH.
Minimization of intracluster variability by k-means (Statistica, 99) allowed division of
the line collection into three groups (Fig. 4). The lines were distributed as follows: I –
L542, L620, L586; II – L579, L603, L605, L602, L587; III – L582, L585, L615, L588, L601.
According to scheme (Fig. 3) intragroup distances were less than intergroup ones.
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Distances between the groups I-II were more than I-III. Intergroup distances between
II-III were less than I-III.
Analysis of heterosis effect in hybrids produced by intergroup crosses has shown that use
of one of the I-group lines enable production of high-heterotic generation. The highest
HPH for fruit weight per plant was observed just among hybrids produced with
involvement of the lines L620( ), L542( ), L586( ) (Table 3). The MPH value reached
117% in some crosses, also with I-group lines.
Figure 3. Three-clyster model of heterogeneity of a collection of pepper sweet,
constructed by the analysis k-means with minimization of intragroup distances.
Intracluster crosses in the group II and III (L579×L602, L579×L605, L587×L603, L587×L615)
did not result in an increase in the expression of fruit weight per plant – the observed
effects were primarily negative. Significant positive heterosis was not observed, too,
in intercluster crosses II×III where distances did not exceed 10 geometric values (Eucli­
dian distances).
In the conducted investigation, high-heterotic progeny was produced by using lines from
various groups (intercluster crosses) in hybridization with the distance - 17 geometric
values and more.
Conclusions
The result our investigation indicates a positive relationship between kinetic parameters
heterogeneity of parents and their hybrids performance. The correlation for fruit weight
per plant was positive and significant (r(MPH)=0.52**, r(HPH)=0.44*). This suggests that crossing
diverse parents could give high heterotic performance in hybrids. Therefore, TG and DSC
can be used for selection parent breeding material and creation heterotic groups.
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Acknowledgements
This research has been financed by Byelorussian Republican Foundation of Fundamental
Investigations (BRFFI).
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of straw and stalk of rapeseed using thermogravimetric analysis. Energy Sources
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Topor N.D.; Ogorodov L.P.; Melchakova L.V. 1987. Thermal analysis of minerals and inor­ga­
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Reconstruction of regulatory feedback of global gene network of
economically valuable characters of Capsicum annuum L.
O.O. Timina1, A.S. Ryabova2, O.Yu. Timin3
1
Transnistrian University, Bioinformatics Research Laboratory, Transnistria Moldova, Tiraspol, 25 October St.,
128, Building B, 3300. Contact: [email protected]
2
Ershov Institute of Informatics Systems, Siberian Division of Russian Academy of Sciences,6, Lavrentiev ave.,
Novosibirsk, 630090. Contact: [email protected] 3Government Institution, Republican Botanical Garden,
Transnistria Moldova, Tiraspol, Mira St, 50, 3300. Contact: [email protected]
Abstract
Correlations between identity of the dominant alleles of key marketable characters and
their heterosis effect have been determined and visualized in pepper (Capsicum annuum
L.). Found correlations formed the pattern of the feedback of the studied polygenic traits
which generated their global gene network. The functional analysis of the set feedback of
the studied traits has been determined in order to predict the yield`s heterosis effect.
Keywords: Capsicum annuum, correlations, gene networks, heterosis.
Introduction
Research of plant economically valuable characters and their identification are the key
stage for landmark creation of new varieties and hybrids. It is obvious that investigation
in that direction will be successful if different approaches are used for solving challenges.
The economically valuable characters were determined from the position of gene
networks which demonstrate the mechanism of the organisms’ integral functioning. Gene
networks are used to study homeostasis, organism’s stress reactions, differentiation
process, control morphogenesis of tissues and organs, organism’s growth and development
and some others (Kolchanov et al., 2000; Ananko et al., 2002; Ananko, 2008). But there is
too little data about gene networks of plant economically valuable characters and there
is not systematized information. Our research task was the reconstruction of regulatory
feedback of global gene networks of economically valuable characters of C. annuum and
its application to selection for heterosis.
Materials and methods
Plant material
We used C. annuum varieties and lines of our own selection: Dobryinya Nikitich (DN), L
49, Prometei, L 48 and also Kolobok (K). The latter is a variety of the Transnistrian Re­
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search Agricultural Institute (Tiraspol). This plant material was chosen for representing
different varietal types of economically valuable characters.
Genetic statistical evaluation
We crossed the five genotypes according to a diallel crossing system [½р(р+1)] in the
cold plastic houses, and performed regression-cluster analysis for determining identity
of dominant alleles of 16 economically valuable characters (Timina et al., 2004; Timina,
Ryabova, 2010). Parental lines and F1hybryds were grown according to standard methods
and recommendations. According to randomized blocks design, 50 plantlets were planted
out in the open ground and cold plastic house in two replications and 10 plants per
replicate. The effect of heterosis of every character was calculated as a mean of parental
lines in accordance with Dascalov et al., 1978. We used the module model of organization
of quantitative traits (Dragavtsev et al., 1984; Dragavtsev, 2002; Dragavtsev, 2003) and
the theory of gene networks (Kolchanov et al., 2000, Ananko et al., 2002; Ananko, 2008).
The packet of Correlation matrices according Statistica 6.0 has been used for determining
correlation between effect of heterosis and calculated identity parameters of dominant
alleles for every condition and for its partial visualization. For the complete visualization
of the interaction of effect of heterosis and the degree of the identity of dominant
alleles gene networks, a graph was constructed. Edges of the graph connect those genes
and traits whose interaction values were within 20% from extremes of the whole
interaction matrix. The correlation table of heterosis effect of quantitative traits and
the identity degree of dominant alleles’ in both conditions were used as matrix. The
graph was created with dot layout algorithm of the open source graph visualization
software Graphviz, available over the internet at http://www.graphviz.org/ . Dashed
edges represent negative values in matrix and solid edges stands for positive ones. If it
is possible for the layout, the algorithm sets more straight and short edges for more
significant correlation values from the matrix.
Results and discussion
According to the gene networks theory plant economically valuable characters are
considered to be polygenic forming global gene network which consists of hierarchically
interacted separate ones for a particular trait. That is why every economically valuable
character is considered to be the resulting function of particular gene network of such
character according the condition. In order to reconstruct peppers regulatory feedback
of global gene networks, the key alleles of economically valuable characters have been
identified in conformity with their norm of reaction in different conditions (Timina and
Ryabova, 2010) and the heterosis effect has been also refined (Table 1). Comparison of
alleles identity and the effect of heterosis depending on their correlation made it
possible to reconstruct the regulatory feedback graph of global gene network of
economically valuable characters (Fig. 1).
350
Clusters allele’s identity parameters in the plasthouse (Var1-Var9) and open ground (Var181-Var189): Var1, Var 181- the length and the fruit index; Var2,
Var182 total and marketable yield and the fruit number per plant; Var3, Var183 – the fruit diameter; Var4, Var184 – the plant height; Var5, Var185 –fruit
rot; Var6, Var186 – middle and marketable fruit mass; Var7, Var187 – the duration of the 2-d and 3-d vegetation period; Var8, Var188 – the pericarp wall
thickness and verticillium wilting; Var9, Var189 – the duration of the 1-t vegetation period and the fruit number locule;
The heterosis effect in plasthouse (Var 10, NewVar1-NewVar6, NewVar) and open ground (Var1810 – Var1817) according to characters: Var10, Var1810 – the
fruit length; NewVar1, Var1811 – the fruit diameter; NewVar2, Var1812 – the fruit index, Var 3, Var1813 – the pericarp wall thickness, NewVar4, Var1814 –
marketable yield, NewVar5, Var1815 – the fruit number per plant, NewVar6, Var1816 – marketable fruit mass, NewVar, Var1817 – the plant height
Figure 1. Visualized interaction of key alleles of sweet pepper’s economically valuable
characters and effect of heterosis in open ground and cold plastic house.
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Literature data show that there is a strong heterosis effect on such peppers traits as the
duration of vegetation period, yield, resistance to diseases, number of fruits and seeds,
height of plant, and some others. (Dascalov et al., 1978; Pandey et al., 2007). Our data
(Table 1) confirm heterosis on fruit yield, number of fruits per plant, plant height and
fruit mass. But one should take into account that marketable yield is the resulting
character which is determined by the contribution of component ones according to the
model of polygenic plants characters, and in case of pepper correspond to the product
of marketable fruits number per plant on one fruit mass. In turn the fruit mass is the
resultant of the product of the unit weight on its volume. In turn the volume is the
resultant of the pericarp thickness its length and diameter and etc. Thus the number of
key genes which determine resulting character may be not so large. Data obtained
present evidence of possible absence of specific yield and mass genes because of
resulting characters seem to be virtual ones. Wall thickness of the pericarp, length,
diameter and number of the marketable fruits, their unit mass and their correlative
interaction with condition the expression of the characters are the most actual traits for
the yield module. Data both in cold plasthouse and in open ground showed also the
existence of the mediated interactions too except the linear one. Interaction also gives
the resulting effect of heterosis on specific character. The significant correlation
between the identity degree of dominant alleles and the heterosis effect of the character
was found but it was not one to one correspondents (Fig. 1). Taking into account the
contribution of every component of gene network, the role of key elements for the yield
heterosis prediction are as follow for cold plastic house: the presence, degree of the
identity and type of the feedback in the clusters length – fruit index; fruit rot; the
duration of the 1–t vegetation period – the number of fruits locule. Figure 2 demonstrates
interaction of separate elements of gene network in the yield module.
3D Surface: Var1 vs. NewVar5 vs. NewVar4
(Casewise deletion of missing data)
Z = Distance Weighted Least Squares
Figure 2. Visualization of the interaction of heterosis effect
among yield marketable characters.
352
0
0
0
0
0
0
0
0
100
0
0
66,6
33,3
66,6
0
100
0
0
0
100
0
0
0
0
100
0
0
0
0
0
0
0
0
100
0
0
Var3
0
0
0
0
100
0
0
0
0
0
0
0
0
0
0
100
0
0
0
0
Var4,
100
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
100
Var5
0
0
100
0
100
100
0
100
100
100
0
100
0
100
0
100
50
50
50
50
Var6
0
0
0
Var7
0
0
0
0
0
50
0
0
50
50
0
100
0
0
50
0
100
Note: Explanation of the clusters and the effect of heterosis as in figure 1.
50
0
Kolobok Х Promrtei
Promrtei Х Л 48
0
Kolobok Х Л 49
100
0
Dobryinya Nikitich Х Л 48
Л 49 Х Л 48
0
Dobryinya Nikitich Х Promrtei
0
0
Dobryinya Nikitich Х Л 49
50
0
Dobryinya Nikitich Х Kolobok
Л 49 Х Promrtei
50
Promrtei Х Л 48 Open ground
Kolobok Х Л 48
100
Л 49 Х Л 48
33,3
0
0
Kolobok Х Promrtei
50
0
Kolobok Х Л 49
Kolobok Х Л 48
50
Dobryinya Nikitich Х Л 48
Л 49 Х Promrtei
66,6
0
Dobryinya Nikitich Х Promrtei
33,3
0
50
66,6
Var2
Dobryinya Nikitich Х Л 49
Var1
Dobryinya Nikitich Х Kolobok
Cold plastic house
Cross combination, F1
Identity of the key alleles in clusters, %
50
50
100
0
50
50
50
100
100
50
0
0
0
0
50
0
0
50
0
0
Var8
0
0
100
100
0
0
0
100
100
0
100
100
100
100
100
100
50
50
50
50
Var9
105
117
100
96
77
84
121
98
103
90
108
104
108
85
92
86
115
114
108
110
Var10
95
102
97
112
100
105
103
97
92
109
99
107
105
114
108
123
105
106
117
129
110
115
101
83
79
77
116
102
110
82
113
101
100
77
85
67
114
108
91
85
NewVar1 NewVar2
84
87
84
82
82
98
97
91
83
85
88
99
95
93
95
108
96
101
112
109
Var 3
151
195
77
127
87
81
115
131
88
95
125
213
159
127
97
217
168
148
337
228
90
113
95
91
121
90
71
96
86
73
122
173
124
104
84
131
121
88
206
116
48
111
99
111
86
96
112
102
78
106
97
107
128
105
111
161
118
128
136
166
NewVar4, NewVar5 NewVar6
The fruit
The heterosis effect of economical valuable characters, %
Table 1. The key allele’s identity interaction of economically valuable characters and their heterosis effects according
of plants growing conditions, 2003-2005.
133
120
97
106
90
100
101
121
160
126
125
141
112
106
98
113
109
110
154
131
NewVar
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Obtained data indicate curvilinear (although only up to certain limit) rising of heterosis
effect of marketable yield and the number of fruits per plant and linear rising of the
plant height heterosis with simultaneous increasing of identity parameter of the dominant
alleles’ in the cluster of the length and fruit index. Curvilinear connection shows the
considerable contribution of genotypic background on the expression of heterosis yield
effect and confirms the existence of gene interactions.
Decreasing expression of some characters and replacement of several dominant groups of
them on others which form the yield module has been observed during environment
change (Table 1; Fig. 1). Thanks to available models of polygenic characters in a correspon­
den­ce with the conditions of gene set over determination (switch on the new one and
switch off functioning earlier genes) takes place which determine the character. Such over
deter­mination of the expression initiates coordinated changes in the conjugated traits
which also provoke alterations of feedback types in gene network of the yield module and
functionally the organisms answer towards the condition is over determined. Thus, the
whole function must be marked out in order to see and forecast the effect but not the
separate characters and this analysis can be done by the functional module approach of
the polygenic traits determination.
According to obtained data the question is to be solved about the heterosis prediction
for both conditions and possibility to create the universal hybrid on the base of used
genotypes. Figure 1 shows the interesting internal closed chain which possibly being
ruled can influence the appearance of the marketable yield heterosis in both conditions.
Characters and their dominant alleles are correlated in chain and that is why the resulted
effect may be reversible. The chain includes the following members: (Var1814) – heterosis
of marketable yield in the open ground – (Var181) - alleles identity in the cluster of the
length of the fruit in the open ground – (Var 1) alleles identity in the cluster of the length
of the fruit in the plastic house – (NewVar 5) - heterosis of the fruit number per plant in
the plastic house – (NewVar 4) – heterosis of marketable yield in the plastic house – (Var
187) - alleles identity in the cluster of the duration of the 2 –d and 3 –d vegetation period
– (Var1814) – heterosis of marketable yield in the open ground. According this part of the
gene network the increasing of marketable yield heterosis simultaneously in open ground
and plastic house conditions is correlated positively with alleles identity in the cluster
of the length and the fruit index, but this correlation become differentiated while being
compared with the alleles identity in the cluster of the 2 – d and 3 – d duration of the
vegetation period. Particularly this interaction is positive and significant (r=0.78) in the
plastic house conditions and negative and not significant in the open ground (r=-0,49).
But the presence of some more other correlated interactions initiates over determination
of the resulted effects in the gene chain. Visualization of some separate nodes elements
of this gene network is shown on the Figure 3. This figure represents the forecast of
heterosis effect of yield in both conditions taking into consideration the curvilinear and
straight interactions with alleles’ identity in the clusters of the length and the fruit
index and the 2 – d and 3 – d duration of the vegetation period. Received data indicate
one-way type of correlation between module heterosis effects of marketable yield and
the degree of identity of marker alleles. That is why the universal hybrid for both
conditions may be forecasted. To our opinion obtained data point out the key role of one
locus allele’s interaction for heterosis effect. But change of the conditions switches on
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the functioning of new gene chains thus over determining the effect thanks feedback
and indirect genes interactions.
So, the effect of heterosis is the complex functional reaction of genotype on the
differential impact of the condition which is the cause of not only the one locus allele’s
interactions but also modulated function of genes interactions. One more effect from
received data is that over determining of identifiable genes during the conditional change
supposes the existence of gene regulators in genotypes possibly triggers or switch off
ones. Such regulation of genes polygenic functioning of lower fungi has been described by
Litvin et al. (2008). But on our opinion such type of regulators switch on or switch off not
only separate genes or genes groups of economically valuable characters in accordance
with modern theory of polygene’s functioning.
A) 3D Surface: Var1814 vs. NewVar4 vs. 187
(Casewise deletion of missing data)
Z = Distance Weighted Least Squares
C) 3D Surface: Var181 vs. NewVar4 vs. 1814
(Casewise deletion of missing data)
Z = Distance Weighted Least Squares
B) 3D Surface: Var1814 vs. Var7 vs. NewVar4
(Casewise deletion of missing data)
Z = Distance Weighted Least Squares
D) 3D Surface: Var1814 vs. NewVar4 vs. Var1
(Casewise deletion of missing data)
Z = Distance Weighted Least Squares
Figure 3. Interaction of the marketable yield heterosis effect in the open ground
(a, c) and plastic house (в,d) and the allelic identity in the clusters of the 2 –d and the 3 –d
(a, в) duration of the vegetable period and the fruit length and the fruit index (c, d).
But switch on or block the function of organized coordinated genes chain which determines
specified function in specified conditions. Possibly such plants polygenes functioning of
the cyclic process may be usual and trivial. For example such triggers regulation of
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function “switching-over the way of development from gametophyte type to sporophyte
one” thanks to 4 changer genes in C.annuum have been shown by us earlier by means of
regression-cluster analysis (Timina et al., 2004). And probably thanks to that regulators
rice molecular research has revealed 12 constantly registrable locus’s of polygenic
characters without connection with changing conditions (Dragavtsev, 2003).
So, obtained data refine the allele’s content which determined the marketable yield
module, the character and the degree of the over determination of these alleles in new
conditions and thank to that the occurrence and the type of correlation between
variability of the yield heterosis effect and the degree of functional identity with genes
alleles that encode them. Findings confirm and refine the module organization hypothesis
of polygenic plants characters and on its base supplement it with possible type of
regulation of polygenic functioning and the heterosis phenomenon from these approaches
is the only special case of the total function of the gene network.
References
Ananko, E.A.; Podkolodny, N.L.; Stepanenko, I.L; Ignatieva, E.V.; Podkolodnaya, O.A.;
Kolchanov, N.A. 2002. GeneNet: a database on structure and functional organization
of gene networks. Nucleic Acids Res., 30 (1):398-401.
Ananko, E.A. 2008. Development of the reconstruction technology and computer analysis
of gene networks and it’s applied in biological research. Dissertation PhD, Novosibirsk,
RAS, Siberian Division, Institute of Cytology and Genetics,1-229 (In Russ).
Daskalov, H.; Mihov, H.; Minkov, I.; et al. 1978. Heterosis and it’s applied in vegetable
growing. Ear Press, Moscow, 1-309 (In Russ.).
Dragavtsev, V.A.; Litun, P.P.; Shkel, N.M.; Nechiporenko, N.N. 1984. The model of
ecology-genetic control of plants quantitative characters. Proceedings of Russian
Academy of Science, 274 (3):720-723 (In Russ.).
Dragavtsev, V.A. 2002. Algorithms of an ecology-genetic survey of the genofond and
methods of creating the varieties of crop plants for yield, resistance and quality.
St. Petersburg, VIR, 1-50.
Dragavtsev, V.A. 2003. Towards the problem of genetic analysis of plants polygenic
quantitative characters. St. Petersburg, VIR, 1-35 (In Russ.).
Kolchanov, N.A.; Ananko, E.A.; Kolpakov, F.A.; Podkolodnaya, O.A.; Ignatieva, E.V.;
Goryachkovskaya, T.N.; Stepanenko, I.L.2000. Gene networks. Molecular Biology
(Msk), 34 (4): 449-460.
Litvin, O.; Causton, H.C.; Bo-Juen, C.; Pe ‘er, D. Modularity and interection in the genetics
of gene expression. www.pnas.org/cgi/doi/10,1073/pnas.0810208106,1.6.
Pandey, J.; Singh, J.; Verma, A.; Singh, A.K.; Rai, M.; Kumar, S. 2007. Heterosis studies
in CMS hybrids of chilli (Capsicum annuum L.) for yield and quality parameters. In:
Niemirowicz-Szczytt, K. (Ed.), Progress in Research on Capsicum & Eggplant.
Warsaw University of Life Sciences Press, Warsaw, Poland, pp. 211-220.
Timina, O.O.; Tsykaliuk, R.A.; Orlov, P.A. 2004. The identification of genotypes quantitative
cha­racters by regressive cluster analysis. Capsicum and Eggplant Newsletter, 23:37-40
Timina, O.O.; Ryabova, A.S. 2010. Identification of key alleles of peppers Capsicum annuum
L. economically valuable characters. Agricultural biology, 1: 40-50 (In Russ.).
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SESSION V.
DEVELOPMENT OF MOLECULAR
AND OTHER
BIOTECHNOLOGICAL TOOLS
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Construction of an intra-specific linkage map in eggplant
(Solanum melongena L.)
L. Barchi1, S. Lanteri1, E. Portis1, A. Stagel1, L. Toppino2, G.P. Valè3, N. Acciarri4,
G.L. Rotino2
DIVAPRA, Genetica Agraria, Università di Torino, Grugliasco (TO), Italy. Contact: [email protected]
CRA-ORL Unità di Ricerca per l’Orticoltura, Montanaso Lombardo (LO), Italy
3
CRA-CRA-GPG, Centro di Ricerca Genomica e Postgenomica, Fiorenzuola d’Arda (PC), Italy
4
CRA-ORA. Unità di Ricerca per l’Orticoltura, Monsampolo del Tronto (AP), Italy
1
2
Abstract
An anther-derived doubled haploid (DH) and an F2 mapping population were developed from
an intraspecific hybrid between the eggplant breeding lines ‘305E40’ and ‘67/3’. The former
carries the locus Rfo-sa1 which confers resistance to Fusarium oxysporum. Initially, 28 AFLP
primer combination (PCs) were applied to a sample of 93 individuals of both the DH and F2
populations from which 170 polymorphic AFLP fragments were identified. In the DH population,
the segregation of 117 of these markers was substantially distorted, while in the F2 population,
segregation distortion was restricted to just ten markers. A set of 141 F2 individuals was
chosen for map construction and genotyped with 73 AFLP PCs, 32 SSRs, four tomato RFLPs and
three CAPS markers linked to Rfo-sa1. The framework map covered 718.7cM, comprising 238
markers (212 AFLPs, 22 SSRs, one RFLP and the Rfo-sa1 CAPS marker).
Keywords: eggplant, AFLPs, SSRs, CAPSs, RFLPs, Fusarium oxysporum.
Introduction
Eggplant (Solanum melongena L.) is cultivated worldwide and is susceptible to several
fungal pathogens among which Fusarium oxysporum f. sp. melongenae, which causes
vascular wilt. Sources of genetic resistance have been identified in S. aethiopicum L.
group gilo and S. aethiopicum L. gr. aculeatum (= S. integrifolium) and it has been
suggested that a major gene (Rfo-sa1), tightly linked to a number of CAPS (cleaved
amplified polymorphic sequence), is responsible for much of the resistance (Toppino
et al., 2008).
The eggplant genome has been rather less intensively explored than those of other Sola­
naceae crops (Tanksley et al., 1992; Paran et al., 2004; Frary et al., 2005; Barchi et al.,
2007; Wu et al., 2009a). The earliest eggplant genetic map was based on 58 F2 individuals
derived from the interspecific cross S. linneanum x S. melongena (Doganlar et al., 2002),
and the quality of this map has since been improved by the addition of conserved ortholog
set (COS) markers (Wu et al., 2009b). An intraspecific map was developed by Nunome et
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al. (2001; 2003) and has been recently updated by the addition of a large number of SSRs
(Nunome et al., 2009).
Here we report on (i) the development of two mapping populations: an anther-derived
doubled haploid (DH) and an F2, obtained from parental lines which differ markedly from
one another for both productive and morphological traits, as well for the presence/
absence of Rfo-sa1; (ii) the identification of the most suitable population for mapping
purposes and (iii) the construction of an intraspecific genetic map.
Materials and methods
Plant material, DNA isolation and genotyping
F1 hybrids were obtained by crossing the two S. melongena breeding lines ‘305E40’
(female parent) and ‘67/3’ (male parent). The line ‘305E40’ is a doubled haploid (DH)
obtained through anther culture of an advanced introgression line (BC7) derivative of an
interspecific somatic hybrid Solanum aethiopicum gr. Gilo (+) S. melongena cv. Dourga
(Rizza et al., 2002), selected to include Rfo-sa1 and characterized by elongated fruit
(Toppino et al., 2008). The line ‘67/3’ is a selection from the intraspecific cross cv.
‘Purpura’ x cv.‘CIN2’ followed by seven cycles of selfing, it is characterized by round
fruit type and lacks Rfo-sa1. A DH population, consisting of 300 individuals, was developed
from these F1 plants using anther culture (Rotino, 1996) while an F2 population of size
230 was obtained by selfing. A set of 93 randomly chosen individuals from both populations
was subjected to a preliminary round of AFLP profiling. Afterwards 141 F2 individuals
were randomly chosen for the construction of the genetic map. Genomic DNA was
extracted from young leaves, using the Gene EluteTM Plant Genomic DNA Miniprep kit
(Sigma, St. Louis, MO).
AFLP reactions were performed as described by Vos et al. (1995). For the identification of
the most suitable segregating population 28 EcoRI/TaqI primer combination (PCs) were
applied (Tab.1). Later this set of PCs was extended by including further enzyme combinations
(EcoRI/MseI, PstI/TaqI, or PstI/MseI); in all, 73 PCs were employed to generate genotypic
data for the construction of the genetic map (Tab.1). Each AFLP marker was named using
the Keygene PC code with a suffix indicating the estimated size of the fragment in bp and
the identity of the donor parent (‘305’ for ‘305E40’, ‘67’ for ‘67/3’). In addition, a panel
of 210 microsatellite (SSR) primers was screened for informativeness between the mapping
parents (Nunome et al., 2003; Stagel et al., 2008; Nunome et al., 2009), among which 41
were designed from tomato sequence (Frary et al., 2005). PCR amplifications were carried
out as described by Stagel et al. (2008). The developer’s nomenclature for SSR loci was
adopted and, where known, included their linkage group (LG) number in parenthesis.
Three CAPS markers linked to Rfo-sa1 were assayed as described by Toppino et al. (2008).
Finally four tomato RFLP loci (CT232, CT204, TG460, CT167) represented in Doganlar et al.
(2002) map, were assayed following Bernatzky and Tanksley (1986).
Linkage analysis and map construction
Observed segregations were tested for any deviation from Mendelian expectation.
Goodness-of-fit between observed and expected segregation patterns was assessed using
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Advances in Genetics and Breeding of Capsicum and Eggplant
the χ2 test. Only those markers fitting (χ2 ≤ χ2α=0.1), or at most deviating only slightly
from expectation (χ2α=0.1 < χ2 ≤ χ2α=0.01) were used for map construction. The genotypic
data were analysed with JoinMap v4.0 software (van Ooijen, 2006). LGs were accepted
at a LOD threshold of 4.0 and above. To determine marker order within an LG, JoinMap
parameters were set at Rec = 0.40, LOD = 1.0 and Jump = 5. Map distances were converted
to centiMorgans (cM) using the Kosambi mapping function (Kosambi, 1944). The LGs were
numbered serially in descending order of their genetic length.
Results and discussion
The suitability of the populations for linkage analysis
The parents used for the F1 development represent a material of high relevance to the
gene pool used by eggplant breeders, enriched by the locus Rfo-sa1 introgressed from S.
aethiopicum. The sample of 28 AFLP PCs applied to 93 randomly chosen individuals of
the DH and F2 mapping populations delivered 170 informative markers. In the DH
population, 117 (68%) showed segregation distortion (α>10%), with most (76%) of the
distortion in the direction of parent ‘67/3’. In the F2 population, however, distortion
only affected ten markers (7%). Given the problem of extensive segregation distortion in
the DH population, a full genotypic analysis was only applied to the F2 population.
Linkage analysis in the F2 population
The full set of 73 AFLP PCs (Table 1) amplified 406 informative fragments among 141 F2
individuals. Only 32 of the 210 SSR loci were polymorphic between the parental lines. In
all, genotypic data relating to 438 markers were entered into the mapping program,
which assembled 348 markers (322 AFLPs, 22 SSRs, one RFLP and the three Rfo-sa1 CAPS
markers) into 12 LGs each comprising four or more loci; of the remaining markers, 25 (19
AFLPs, three RFLPs and three SSRs) were grouped as either triplets or doublets, and the
remaining 65 markers were unlinked.
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Table 1. AFLP PCs used for linkage analysis. PCs used to initially identify segregation
distortion in the mapping populations are shown in bold.
Eco/Taq template
code
Eco/Mse template
code
Eco+ACA
e35t79
e35t80
e35t81
e35t82
e35t83
e35t84
e35t85
e35t86
e35t87
e35t88
e35t89
e35t90
e35t91
e35t93
e35t94
e36t80
e36t83
e36t84
e36t86
e36t87
e36t89
e36t91
e36t92
e36t94
e37t81
e37t83
e37t84
e37t88
e37t89
e37t90
e38t80
e38t81
e38t83
e38t84
e38t86
e38t87
e38t89
e38t90
e38t91
e38t94
Eco+ACA
e35m48
e35m61
e35m62
e36m47
e36m48
e36m61
e38m50
e38m59
e38m60
e38m61
e38m62
Eco+ACC
Eco+ACG
Eco+ACT
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Taq+TAA
Taq+TAC
Taq+TAG
Taq+TAT
Taq+TCA
Taq+TCC
Taq+TCG
Taq+TCT
Taq+TGA
Taq+TGC
Taq+TGG
Taq+TGT
Taq+TTA
Taq+TTG
Taq+TTT
Taq+TAC
Taq+TCA
Taq+TCC
Taq+TCT
Taq+TGA
Taq+TGG
Taq+TTA
Taq+TTC
Taq+TTT
Taq+TAG
Taq+TCA
Taq+TCC
Taq+TGC
Taq+TGG
Taq+TGT
Taq+TAC
Taq+TAG
Taq+TCA
Taq+TCC
Taq+TCT
Taq+TGA
Taq+TGG
Taq+TGT
Taq+TTA
Taq+TTT
Eco+ACC
Eco+ACT
Mse+CAC
Mse+CTG
Mse+CTT
Mse+CAA
Mse+CAC
Mse+CTG
Mse+CAT
Mse+CTA
Mse+CTC
Mse+CTG
Mse+CTT
Pst/Taq template
Pst+ACA
Taq+TAA
Taq+TAC
Pst+ACC
Taq+TAC
Taq+TAG
Taq+TAT
Pst+ACG
Taq+TAA
Taq+TAC
Taq+TAG
Pst+ACT
Taq+TAA
Taq+TAC
Taq+TAG
code
p35t79
p35t80
p36t80
p36t81
p36t82
p37t79
p37t80
p37t81
p38t79
p38t80
p38t81
Pst/Mse template
Pst+ACA
Mse+CAA
Mse+CAT
Pst+ACC
Mse+CAT
Mse+CTG
Mse+CTA
Mse+CTC
Pst+ACG
Mse+CAA
Mse+CAT
Mse+CTC
Pst+ACT
Mse+CAG
Mse+CTT
code
p35m47
p35m50
p36m50
p36m61
p36m59
p36m60
p37m47
p37m50
p37m60
p38m49
p38m62
Advances in Genetics and Breeding of Capsicum and Eggplant
Figure 1. Genetic map of eggplant. Marker names are shown to the right of each LG,
with map distances (in cM) to the left. Markers showing a significant level of segregation
distortion are indicated by asterisks (0.1 > α > 0.05: *; 0.05 > α > 0.01: **).
A subset of 238 of the markers constituted the ‘framework’ map (Fig. 1) and 110 ‘accessory’
markers were clustered within a small region of LG1. The genetic length of the map was
718.7 cM, and the global mean inter-marker separation was 3.0 cM. Individual LG length
ranged between 27.3 cM (LG12) and 82.2 cM (LG1) (mean 59.9 cM). LG1 incorporated 51
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loci, while LG10 had just four (mean 19.7 loci per LG). The three Rfo-sa1 CAPS markers
co-segregated and were mapped to LG1 (Fig. 1). Of the 22 SSR markers developed by
Nunome et al. (2003; 2009) which segregated in the mapping population, 20 mapped to 11
of the 12 major LGs. The use of a common set of SSRs allowed for the present map to be
aligned with that recently published by Nunome et al. (2009) (data not reported).
Of the 438 markers mapped in the F2 population, only 6.5% showed any segregation distortion
when tested against the expectation of 3:1. This level is less than the 16% reported for an
interspecific cross by Doganlar et al. (2002), but is comparable to that experienced by
Nunome et al. (2001) as a consequence of the use of intraspecific populations.
The number of markers placed on the framework map was 238, similar to that assigned
by Doganlar et al. (2002) and Nunome et al. (2009), but higher than that assigned by
Nunome et al. (2003) and somewhat lower than that reported by Wu et al. (2009b). The
genetic length of the present map is comparable to the estimate provided by Nunome et
al. (2001; 2003), even though these latter maps were based on both fewer F2 individuals
and fewer markers, but shorter than the inter-specific one, based on RFLPs markers,
reported by Doganlar et al. (2002). This, presumably, might be due to the lower level of
polymorphism present in our parental lines as well as the higher tendency to clustering
of AFLP markers compared to RFLPs. The number of major LGs identified was 12, so we
anticipate that the minor groups and the singlet will be integrated given a larger
genotyping effort.
LG1 includes a notable cluster of AFLP loci. Marker clustering is a well documented
phenomenon and has been associated with the highly heterochromatic, relatively genefree centromeric regions of the chromosomes, (Tanksley et al., 1992; Qi et al., 1998;
Pradhan et al., 2003). In eggplant, a pronounced clustering of SSR markers was also
observed in several LGs by Nunome et al. (2009) who attributed this to the use of genomic
SSR loci, which tend to mark heterochromatin-rich, non-genic regions of the genome.
In a previous work Toppino et al. (2008) were able to demonstrate that the resistance to
Fusarium inherited from S. aethiopicum / S. integrifolium is under monogenic control,
and went on to develop a set of co-segregating CAPS markers tightly linked to this gene.
A second source of resistance to Fusarium has recently been described by Mutlu et al.
(2008), but no markers for this resistance are as yet available. Here, we have been able
to show that the CAPS markers, and hence Rfo-sa1, is located on of LG1.
Acknowledgements
This research was partially supported by the Italian Ministry of Agricultural Alimentary
and Forest Politics in the framework of its “PROM” and “AGRONANOTECH” projects. We
thank MG Tacconi, G Grazioli, P Rinaldi, G Caponetto and E Leone and for their technical
assistance.
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Advances in Genetics and Breeding of Capsicum and Eggplant
References
Barchi, L.; Bonnet, J.; Boudet, C.; Signoret, P.; Nagy, I.; Lanteri, S.; Palloix, A.; Lefebvre,
V. 2007. A high-resolution, intraspecific linkage map of pepper (Capsicum annuum
L.) and selection of reduced recombinant inbred line subsets for fast mapping.
Genome 50:51-60.
Bernatzky, R.; Tanksley, S. 1986. Toward a saturated linkage map in tomato based on
isozymes and random CdnaSequences. Genetics 112:887-898.
Doganlar, S.; Frary, A.; Daunay, M.; Lester, R.; Tanksley, S. 2002. A comparative genetic
linkage map of eggplant (Solanum melongena) and its implications for genome
evolution in the Solanaceae. Genetics 161:1697-1711.
Frary, A.; Xu, Y.; Liu, J.; Mitchell, S.; Tedeschi, E.; Tanksley, S. 2005. Development of a
set of PCR-based anchor markers encompassing the tomato genome and evaluation
of their usefulness for genetics and breeding experiments. Theoretical and Applied
Genetics 111:291-312.
Kosambi, D. 1944. The estimation of map distance from recombination values. In: Annals
of Eugenics, pp. 172-175.
Mutlu, N.; Boyaci, F.; Gocmen, M.; Abak, K. 2008. Development of SRAP, SRAP-RGA, RAPD
and SCAR markers linked with a Fusarium wilt resistance gene in eggplant.
Theoretical and Applied Genetics 117:1303-1312.
Nunome, T.; Ishiguro, K.; Yoshida, T.; Hirai, M. 2001. Mapping of fruit shape and color
development traits in eggplant (Solanum melongena L.) based on RAPD and AFLP
markers. Breeding Science 51:19-26.
Nunome, T.; Suwabe, K.; Iketani, H.; Hirai, M. 2003. Identification and characterization
of microsatellites in eggplant. Plant Breeding 122:256-262.
Nunome, T.; Negoro, S.; Kono, I.; Kanamori, H.; Miyatake, K.; Yamaguchi, H.; Ohyama, A.;
Fukuoka, H. 2009. Development of SSR markers derived from SSR-enriched genomic
library of eggplant (Solanum melongena L.). Theoretical and Applied Genetics 119:
1143-1153.
Paran, I.; van der Voort, J.; Lefebvre, V.; Jahn, M.; Landry, L.; van Schriek, M.; Tanyolac, B.;
Caranta, C.; Ben Chaim, A.; Livingstone, K.; Palloix, A.; Peleman, J. 2004. An integrated
genetic linkage map of pepper (Capsicum spp.). Molecular Breeding 13:251-261.
Pradhan, A.; Gupta, V.; Mukhopadhyay, A.; Arumugam, N.; Sodhi, Y.; Pental, D. 2003. A
high-density linkage map in Brassica juncea (Indian mustard) using AFLP and RFLP
markers. Theoretical and Applied Genetics 106:607-614.
Qi, X.; Stam, P.; Lindhout, P. 1998. Use of locus-specific AFLP markers to construct a highdensity molecular map in barley. Theoretical and Applied Genetics 96:376-384.
Rizza, F.; Mennella, G.; Collonnier, C.; Shiachakr, D.; Kashyap, V.; Rajam, M.; Prestera,
M.; Rotino, G. 2002. Androgenic dihaploids from somatic hybrids between Solanum
melongena and S-aethiopicum group gilo as a source of resistance to Fusarium
oxysporum f. sp melongenae. Plant Cell Reports 20:1022-1032.
Rotino, G. 1996. Haploidy in eggplant. In: Jain SM SS, Veillux RE (eds) ed. In vitro
production of haploids in higher plants: Kluwer Academic Publishers, Amsterdam,
pp. 115-124.
Stagel, A.; Portis, E.; Toppino, L.; Rotino, G.; Lanteri, S. 2008. Gene-based microsatellite
development for mapping and phylogeny studies in eggplant. BMC Genomics
9:357.
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Tanksley, S.; Ganal, M.; Prince, J.; Devicente, M.; Bonierbale, M.; Broun, P.; Fulton, T.;
Giovannoni, J.; Grandillo, S.; Martin, G.; Messeguer, R.; Miller, J.; Miller, L.; Paterson,
A.; Pineda, O.; Roder, M.; Wing, R.; Wu, W.; Young, N. 1992. High-density molecular
linkage maps of the tomato and potato genomes. Genetics 132:1141-1160.
Toppino, L.; Vale, G.; Rotino, G. 2008. Inheritance of Fusarium wilt resistance introgressed
from Solanum aethiopicum Gilo and Aculeatum groups into cultivated eggplant (S.
melongena) and development of associated PCR-based markers. Molecular Breeding
22:237-250.
van Ooijen, J. 2006. JoinMap ® 4, Software for the calculation of genetic linkage maps in
experimental populations.In: Kyazma B.V., Wageningen, Netherlands.
Vos, P.; Hogers, R.; Bleeker, M.; Reijans, M.; Vandelee, T.; Hornes, M.; Frijters, A.; Pot,
J.; Peleman, J.; Kuiper, M.; Zabeau, M. 1995. AFLP - A new technique for DNAfingerprinting. Nucleic Acids Research 23:4407-4414.
Wu, F.; Eannetta, N.; Xu, Y.; Durrett, R.; Mazourek, M.; Jahn, M.; Tanksley, S. 2009a. A
COSII genetic map of the pepper genome provides a detailed picture of synteny with
tomato and new insights into recent chromosome evolution in the genus Capsicum.
Theoretical and Applied Genetics 118:1279-1293.
Wu, F.; Eannetta, N.; Xu, Y.; Tanksley, S. 2009b. A detailed synteny map of the eggplant
genome based on conserved ortholog set II (COSII) markers. Theoretical and Applied
Genetics 118:927-935.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Identification of molecular markers linked to ms8 gene in sweet
pepper (Capsicum annuum L.)
G. Bartoszewski1, I. Stepien1, P. Gawronski1, C. Waszczak1, V. Lefebvre2, A. Palloix2,
A. Kilian3, K. Niemirowicz-Szczytt1
1
Department of Plant Genetics Breeding and Biotechnology, Warsaw University of Plant Sciences (SGGW),
Nowoursynowska 159, 02-776 Warsaw, Poland. Contact: [email protected]
2
Unité de Génétique et Amélioration des Fruits et Légumes, UR 1052, INRA, Domaine Saint-Maurice BP 94,
84143 Montfavet Cedex, France
3
Diversity Arrays Technology P/L, 1 Wilf Crane Crescent, Yarralumla, Canberra, ACT, 2600, Australia
Abstract
Nuclear ms8 gene is a single recessive gene which can be used to develop the male sterility
system, applicable in sweet pepper hybrid seed production. Such a nuclear male sterility
system would be more effective if molecular markers of ms8 gene were available. Thus we
have made an attempt to find molecular markers linked to ms8 locus. A male sterile plant
of line 320 was crossed with Elf variety in order to develop F2 mapping population 320 x Elf.
Line 320 is a male sterile Bulgarian-type red fruited line and Elf is a blocky-type yellow
fruited sweet pepper variety. RAPD and DArT technologies combined with BSA (Bulked
Segregant Analysis) were used to identify molecular markers of ms8 gene. Seven RAPD
markers linked to ms8 gene were identified and converted to dominant SCAR markers. Two
developed SCAR markers were segregating in the doubled haploid population from the F1
(Yolo Wonder x Perennial) and were mapped on the lower arm of the pepper chromosome
P4. COSII markers available for lower arm of chromosome P4 were tested in 320 x Elf
population and two markers were segregating showing rather weak linkage with ms8 locus.
DArT BSA analysis resulted in the identification of seven DArT markers potentially linked to
ms8 locus. The applicability of the identified markers in the breeding programmes will be
subject to further studies.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Improvement in doubled haploids production through in vitro
culture of isolated eggplant microspores
P. Corral-Martínez, J.M. Seguí-Simarro
Instituto para la Conservación y Mejora de la Agrodiversidad Valenciana (COMAV). Universidad Politécnica de
Valencia. Ciudad Politécnica de la Innovación (CPI), Edificio 8E-Escalera I. Camino de Vera s/n, 46022 Valencia.
SPAIN. Contact: [email protected]
Abstract
Production of androgenic doubled haploids by means of isolated microspore cultures is a
promising alternative to classic breeding techniques to obtain pure lines with fewer
resources. But unfortunately, this technique is not optimized in eggplant and there is only a
previous published work, where doubled haploids are obtained from calli, not embryos.
In this work we have improved this existing procedure, increasing significantly the number
of calli by two ways: the co-culture with Brassica napus induced microspores and the
disruption of calli through different mechanical methods. We have also analyzed the ploidy
of the calli and regenerants obtained by flow cytometry. The calli were fundamentally
mixoploids, although haploid and doubled haploid calli were also observed. Nevertheless,
the majority of the regenerants studied were doubled haploids, with only few haploid and
mixoploid individuals.These results open new ways to improve the efficiency of isolated
microspore cultures in eggplant.
Keywords: androgenesis, Brassica napus, co-culture, haploid, microspore embryogenesis,
So­la­num melongena.
Introduction
The production of doubled haploids by means of androgenesis allows for the shortening
of breeding programs, obtaining pure lines in much less time and with fewer resources,
both human and material (Forster et al., 2007; Seguí-Simarro and Nuez, 2008). This is
the reason why these methods are the alternative of choice in those crops where the
technique is optimized. Eggplant (Solanum melongena L.) is a crop of great interest for
the Spanish agriculture. In spite of it, in eggplant only one of the two techniques for
induction of androgenesis, the culture of anthers, is well set up. The second one, the
culture of isolated microspores, although technically more complex, presents a number
of practical advantages that makes it worth to investigate on its optimization. Up to
date, there is only a previous study published on regeneration of plants from cultures of
isolated microspores (Miyoshi, 1996).
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We have previously designed a method for the culture of eggplant isolated microspores
which overperforms the previous report in terms of number of calli and doubled haploids
obtained (Corral-Martínez et al., 2008). In addition, Miyoshi (1996) described only
formation of callus from isolated microspores, whereas we have observed that globular
embryos are formed prior to their transformation into microcalli.
In this work, we have studied the variation in ploidy level of the calli and the regenerants
obtained from microspore cultures using flow cytometry.
Rapeseed (Brassica napus) is a model system for microspore embryogenesis where
doubled haploids embryo can be easily obtained. We have also evaluated in this work the
possible effect of co-culturing eggplant microspores with those of rapeseed, in order to
evaluate their possible effect in the improvement of the efficiency of our system.
Finally, we have assessed different methods to multiply the number of calli in the cul­
tures, in order to have more material to further optimize the protocol in a genotypeindependent manner. Our results may represent an important advance in the development
of a highly efficient microspore culture system in eggplant for the production of andro­
genic doubled haploids.
Material and methods
Plant material and growing conditions
We have used individuals of a commercial hybrid of eggplant, Bandera, as donor plants.
They were obtained from the COMAV germplasm collection. Plants were grown in the COMAV
glasshouses at the Universidad Politécnica de Valencia, under 18ºC and natural light.
In vitro isolated microspores culture, co-culture with Brassica napus and plant
regeneration
Flower buds at the appropriate stage (anther lengh about 6 mm with microspores at the
vacuolated stage) were excised and surface sterilized. With this size the microspores
were mainly at vacuolated stage. Microspores were isolated, placed in a 6 cm petri dish
with sterile distilled water and pretreated according to Miyoshi, 1996. Later on, plates
were transferred in NLN medium at 25ºC (Miyoshi, 1996) and incubated into a growth
chamber at 25ºC and 16/8 h photoperiod. Induced calli were transferred to solid MS
medium a month later, where they regenerated shoots and then full plantlets. For the
co-culture with rapeseed microspores, after the application of the inductive treatment
separately for both microspore types, they were mixed and equally distributed in plates
either with eggplant or rapeseed culture medium. The culture medium for rapeseed
microspores was prepared according to Custers, (1994).
Flow cytometry
Small pieces of green calli and young leaves from regenerated plants were analyzed
using the CyStain UV Precise P Kit (Partec). The plant material was crushed on ice for 1
minute with 500 µl of NEB (nuclei extraction buffer). Then, 2 ml of DAPI were added and
incubated for 5 minutes. The obtained extract was filtered away with 30 µm cell Tricks
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filters and immediately analyzed. Young leaf samples from the donor plants were used
as standards for the 2C DNA content.
Multiplication of the number of cultured calli.
Calli were isolated and subjected to four different mechanical methods for disgregation:
(1) two or (2) seven days in constant agitation (200 rpm), (3) crushing the calli with a
syringe piston in sterile conditions, and (4) agitation for 3 minutes in a vortex. To determine
which was the most effective of them, the callus viability, defined as the number of calli
with normal appearance (whitish colour) a month after the procedure, was measured.
Results
A month after the initiation of the isolated microspore culture, microcalli were observed.
These microcalli were transferred from liquid culture to solid MS medium for growth and
differentiation. Calli were maintained in the solid medium until apical shoots were
developed. In some cases, shoots rooted spontaneously. In the cases where rooting was
not spontaneous, they were transferred to V3 medium (Dumas de Vaulx and Chambonet,
1982) to induce rooting. Next, in vitro regenerated plantlets were acclimatized.
Flow cytometric analysis of androgenic calli and regenerated plants.
Calli were analyzed through flow cytometry to characterize the ploidy level. A total of
41 different calli were analyzed (Figure 1A). 36 calli (88% of the total) were mixoploid,
presenting three different DNA contents: 27 presented a 2C+4C content (Figure 1A), 8
presented a C+2C+4C content and 1 presented a C+ 2C content. On the other hand, 3
calli (7% of the total) were tetraploid, 2 of them (5%) were doubled haploid and none
presented a haploid content (Figure 1A).
Fully regenerated plants were also analyzed through flow cytometry. A total of 20 plants
were analyzed. The frequency of mixoploidy was lower than in calli. Only 3 plants (15%)
were mixoploids, all of them presenting the same DNA content: 2C+4C (Figure 1B). Four
of them (20%) were haploid and 1 (5%) was tetraploid (Figure 1B). The majority of plants
(60%) showed a DNA content equivalent to the donor plants (2C).
Figure 1. Flow cytometric analysis of eggplant androgenic calli (A) and regenerants (B).
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Multiplication of microspore-derived calli
Figure 2. A: Example of callus cells disgregated after processing. B: Disgregated cultured,
callus cell one week after disgregation. C: Number of calli obtained using the four
different methodologies described in material and methods. D: Comparison of the
viability of the calli measured one month after disgregation.
After isolating the calli, they were subjected to several mechanical procedures to dis­
gregate their cells and increase the number of microcalli clones. These procedures
allowed for the disgregation of cells or groups of cells (Figure 2A). When those cells were
transferred to fresh culture medium for calli regeneration, a week later the cells
presented a normal, undisturbed appearance (Figure 2B). Each method yielded different
efficiencies in terms of number of calli (Figure 2C). The highest number of calli was
obtained by crushing the original calli with a syringe piston in sterile conditions. But in
this case, the viability of calli was lower than 10% (Figure 2D). The second highest
number of calli was obtained incubating them for seven days under constant agitation in
fresh liquid medium. In this case, the viability was very low too (Figure 2D). In the other
two cases the number of calli obtained were very similar (Figure 2C). The viability of
calli obtained after two days in constant agitation in liquid medium was approximately
60%, while after 3 minute vortexing, the viability was higher, nearly 80% (Figure 2D). Our
results indicated that the best procedure for disgregation is 3 minutes in vortex.
Increase in number of calli through co-culture of eggplant with rapeseed microspores.
In order to improve the efficiency of the culture of eggplant isolated microspores, we
have co-cultured them with isolated and induced rapeseed microspores (Figure 3).
After two weeks of co-culture, some initial divisions of eggplant were observed when the
co-culture was carried out in rapeseed medium (Figure 3A). In these conditions, rapeseed
embryos were not induced. In the eggplant medium, calli of eggplant could be identified
but rapeseed embryos or dividing microspores were not observed (Figure 3B).
After a month of culture, a significant increase in the number of total eggplant calli was
observed in the culture with eggplant medium compared to the eggplant microspores
alone (Figure 3C). An increase in the mean size of the calli compared to the control
experiments was also observed (data not shown). However, neither calli nor embryos
were observed, either for rapeseed or for eggplant in the rapeseed medium (Figure 3D).
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Figure 3. Co-culture with Brassica napus. A: Mixed microspores of eggplant and rapeseed
in rapeseed medium. Two weeks after the culture, the first dividing eggplant microspores
were observed. B: Mixed microspores of eggplant and rapeseed in eggplant medium.
After two weeks of culture, calli of eggplant could be identified. C: Comparison of the
efficiency between the co-culture with rapeseed (left dish) and the culture of eggplant
microspores alone (right dish).D: Number of eggplant calli obtained by the culture of eggplant
microspores alone (control), and obtained by the co-culture of both microspore types.
Discussion
In this work, the analyses of the calli ploidy level revealed that not all of the cells undergo
genome duplications. This heterogeneity is the responsible of the mixoploidy observed.
This does not seem to be an important problem, since a high percentage of doubled
haploids (60%), more genetically stable, are obtained. In tomato, it was described that
mixoploidy is frequent in young calli and regeneration is favoured over the 2C regions
(Seguí-Simarro and Nuez, 2007). This spontaneous genome doubling may be due to the
effects of the in vitro culture conditions, and more specifically, to the effect of the growth
regulators added to the medium.
In this system, the disruption of microcalli supposes an effective method to increase
considerably the material, obtaining clonic calli and regenerant lines useful to evaluate
the effect of different factors regardless of genotype. Among the procedures used in this
work to disgregate the cells, the most efficient in terms of number of calli obtained was
crushing, but viability was the lowest. This might be due to the aggressive disruption of
the calli in individual cells, killing or damaging many of them. By means of a soft and
continued agitation, we obtained the highest number of microcalli. Two days of agitation
is better because, although we obtained the lowest number of calli, the damage to the
cells was minimized and the calli regenerated from them had higher size and viability.
By vortexing, we obtained the lowest number of calli, but they are the biggest in size,
and the highest in viability. In addition, it is the most rapid and simple method. Vortexing
released a sufficient number of cells that proliferated and regenerated shoots, probably
due to reduced damage they have suffered.
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We have shown that the co-culture of isolated eggplant and rapeseed microspores can
help to improve the efficiency of the system. In the co-culture in eggplant medium, the
number of calli obtained was almost twice than the control culture. This allows to
increase number and size of the calli. Our results suggest that rapeseed secretes to the
culture medium something that favours the proliferation of eggplant calli. On the
contrary, when the co-culture is in rapeseed medium neither eggplant calli nor rapeseed
embryos were observed. The absence of eggplant calli could to be due to the lack of
hormones in the culture medium, while the absence of rapeseed embryos could be due
to the secretion of some inhibitory substance by the eggplant microspore. Further
experiments will help to elucidate this hypothesis.
Ackowledgements
We want to acknowledge the staff of the COMAV greenhouses for their valuable help.
P.C-M is a FPI predoctoral fellow from Spanish Generalitat Valenciana. This work was
supported by grants AGL2006-06678 from the Spanish Ministry of Education and Science
(MEC) and ACOMP/2007/148 from Spanish Generalitat Valenciana to JMSS.
References
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crospoea cultures for production of androgenic double haploids, pp. 104-108. In:
Prohens, J.; Badenes, M.L. (eds.) Modern variety breeding for present and future
needs, Editorial de la Universidad Politécnica de Valencia, Valencia, Spain.
Custers, J.B.M.; Cordewener, J.H.G.; Nöllen, Y.; Dons, H.J.M.;Van Lockeren Campagne
M.M.1994. Temperature controls both gametophytic and sporophytic development
in microspore cultures of Brassica napus. Plant Cell Reports. 13:267-271.
Dumas de Vaulx, R.; Chambonnet, D. 1982. Culture in vitro d’anthères d’aubergine
(Solanum melongena L.): stimulation de la production de plantes au moyen de
traitements à 35ºC associés à de faibles teneurs en substances de croissance.
Agronomie 2:983-988.
Forster, B.P.; Heberle-Bors, E.; Kasha, K.J.; Touraev, A. 2007. The resurgence of haploids
in higher plants. Trends in Plant Science 12:368-375.
Miyoshi, K. 1996. Callus induction and plantlet formation through culture of isolated
microspores of eggplant (Solanum melongena L). Plant Cell Rep. 15: 391-395.
Seguí-Simarro, J.M.; Nuez, F. 2007. Embryogenesis induction, callogenesis, and plant
regeneration by in Vitro culture in tomato isolated microsporas and whole anthers.
Journal of Experimental Botany 58:1119-1132.
Seguí-Simarro, J.M.; Nuez, F. 2008. How microspores transform into haploid embryos:
changes associated with embryogenesis induction and microspore-derived embryo­
genesis. Physiologia Plantarum 134:1–12.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Development of an integrated linkage map using genomic SSR
and gene-based SNPs markers in eggplant
H. Fukuoka, K. Miyatake, T. Nunome, S. Negoro, H. Yamaguchi, A. Ohyama
National Institute of Vegetable and Tea Science (NIVTS), NARO, 360 Kusawa, Ano, Tsu, Mie 514-2392, Japan.
Contact: [email protected]
Abstract
An integrated DNA marker linkage map of eggplant was constructed using DNA marker
segregation datasets obtained from two independent intra-specific F2 populations. The
linkage map consisted of 12 linkage groups and encompassed 1,480 cM in total. The 985 DNA
markers were mapped including 313 genomic SSR markers developed by random sequencing
of SSR-enriched genomic libraries (Nunome et al. 2009) and 656 SNPs found in eggplant ESTs
(Fukuoka et al. 2010) and related genomic sequences (introns and UTRs) mainly genotyped
using modified Tm-shift PCR method (Fukuoka et al. 2008). Because of their highly
polymorphic and multi-allelic nature, the SSR markers should be more versatile than SNP
markers for map-based genetic analysis of any traits of interest using arbitrary segregating
populations derived from intra-specific crosses of practical breeding materials. It was
found, however, that distribution of genomic SSR markers was biased in some extent and
therefore, considerable genomic regions were identified only by mapping of gene-related
SNP markers. Out of 656 SNP markers, 306 markers were mapped commonly on a tomato
linkage map EXPEN2000 (Wu et al. 2006). These eggplant-tomato common markers will be
informative landmarks for transfer of more saturated genomic information of tomato to
eggplant and will also provide comparative information of the genome organization of the
two solanaceous species. The data will be available from the DNA marker database of
vegetables, ‘VegMarks’ (http://vegmarks.nivot.affrc.go.jp).
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
New perspective: microspore culture as new tool
in paprika breeding
A. Gémes Juhász1, Cs. Lantos2, J. Pauk 2
1
2
Medimat Ltd., 1224 Budapest, XIV utca 37, Hungary. Contact: [email protected]
Cereal Research Non-Profit Ltd., Department of Biotechnology, 6721 Szeged, P.O. Box 391, Hungary
Abstract
The use of in vitro anther culture has the advantage that it can now be applied routinely for
all types of varieties (as the result of 15 years of developments). Disadvantage of this
technique, that it is extremely labour-intensive and generally resulting in an average of 1/3
spontaneous diploids and 2/3 haploids. In addition, selection is not possible at the cell level.
In order to accelerate the development of hybrid varieties of sweet and spice peppers, an
attempt was made to improve the efficiency of the haploid technique by elaborating an in
vitro isolated microspore culture. Among the factors that influence efficiency we investigated
preliminary treatment of the anthers, isolation procedure of the microspores, collection of
viable cells, media composition for embryo induction and plant regeneration.
Keywords: sweet and spice paprika, doubled haploids, anther and microspore culture.
Introduction
The production of doubled haploid plants has become a key tool in advanced plant
breeding. Plant breeders are increasingly using this system in their mainstream pure-line
programs to reduce the number of years needed from crosses to commercial variety
registration.
Anther culture protocol (optimized anther donor plants condition, elimination methods,
optimized protocols, economic methods for in vitro genome duplication of haploids,
checking genetic purity of spontaneous diploids using microsatellite markers) and trial
results achived in the last twenty years we summarized in 2006 (Mitykó and Gémes
Juhász; 2006).
In laboratory of Medimat Ltd. over the past five years more than 2200 different genotypes
originating from Hungarian sweet pepper types (Cecei, tomato-shaped, apple-shaped,
white blocky, light green and dark green blocky, green spice), Hungarian spice pepper
genotypes, Dutch blocky types, Spanish types (Dolce Italiano, Lamuyo, red blocky) and
Turkish types (e.g. Dolma, Charliston) have been tested and developed DH plants using
in vitro anther culture (Gémes Juhász et al. 2009). More than twenty thousand pure
lines has been built in the breeding programmes.
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Isolated microspore culture are intensively employed in numerous species, so this technique
is an attractive solution for production huge amount of doubled haploid paprika plants. So
far this technique did not used successfully in paprika breeding programmes only the
anther culture. The first successful microspore culture-derived haploids were published in
2006 (Supena et al.). Later, Kim et al. (2008) reported on establishing haploids from the
hot pepper ‘Milyang-jare’ using microspore culture, other genotypes were not tested.
Studies on factors such as stage of isolated microspore, isolation procedure of the
microspores, co-culture and media composition were carried out in microspore culture of
Hungarian sweet and spice pepper genotypes (Gémes et al. 2009; Lantos et al. 2009) in
order to develop en efficient protocol to regenerate fertile DH plants.
Material and methods
Plant material and growing conditions
The donor plants of genotypes were used in anther and microspore culture experiments
to induce haploid plants and DH lines were grown in glasshouse (automatic temperature
control, ventilation and shadowing). The donor plants were grown under a natural
photoperiod condition without additional light. In the glasshouse the plants were kept
at 25-32o C day and 15-20o C night time temperature. The donor plants were fed with
Volldünger® (N:P:K:Mg/14:7:21:1, plus 1% microelements, as B, Cu, Fe, Mn, Zn) fertilizer
every 2 weeks and watered with standard tap water when required.
Isolation protocol and culture of pepper microspores
Microspore isolation protocol was based on (Lantos et al. 2009).
Investigated factors in microspore culture
To improve efficiency the following factors were investigated:
—effect of microspore developmental stage
—role of ovary co-culture of paprika and foreign species
—role of exogenous growth regulators (media composition) on quantity and quality
of embryo yield
Plantlet regeneration
When the microspore derived embryo reached the bipolar developmental stage, 8-10
individual structures were transferred into 55 mm Ø Petri dishes containing R1 regeneration
medium (Dumas de Vaulx et al. 1981). The regeneration experiment was carried out in
culture room at 24 ˚C in a 16/8 hour day/night photoperiod at a light intensity of 100
μmol m2 s-1. When the plantlets reached the 1-2 leaf stage with roots, the plantlets were
transferred into glass tubes containing growth regulator-free half-strength MS (Murashige
and Skoog 1962) medium with 2% sucrose.
Ploidy level determination and chromosome doubling
The ploidy level of the well-rooted plantlets with 3-4 leaves was tested by flowcytometry. For the chromosome determination and doubling used the protocol described
by Gémes Juhász et al. (2006).
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Advances in Genetics and Breeding of Capsicum and Eggplant
Results and discussion
Effect of microspore developmental stage on efficiency
The effect of microspore developmental stage was determined for isolated microspore
culture. The donor anthers containing 80% uni-nucleated and 20% bi-nucleated mi­
crospores gave the superior results.
Role of ovary co-culture of paprika and foreign species
Ovary co-culture of wheat and durum wheat was effective to improve embryo production
(Fig. 1). Presence of wheat ovaries we detected up-to 23 embryos/ Petri-dish (Table 1),
and sufficient plant development. Presence of paprika ovaries we observed up-to 2
embryos/ Petri-dish, but any regenerated plants.
Figure 1. Development of microspore-derived embryoids
in the presence of wheat ovaries.
Media composition
The heat pre-treatment in 0.3 M mannitol had an important effect on microspore deve­
lopment, because treated microspores were better developed (Lantos et al. 2009).
The effects of growth regulators in the induction medium were also tested. Growth
regulator-free medium, 5 mg/l phenylacetic acid (PAA) and a combination of 0.5 mg/l
2,4-dichlorophenoxyacetic acid (2,4-D) and 0.5 mg/l kinetin were compared: the best
results were achieved with the combination of 2,4-D and kinetin contained medium.
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Table 1. Effect of different ovary co-culture on pepper embryo formation
in isolated microspore culture.
287 genotypes
Embryo/Petri dish
callus/Petri dish
without ovaries
0
0
paprika
2
1
barley
12,8
1,8
wheat
23
3
17,5
2,5
291 genotypes
Embryo/Petri dish
callus/Petri dish
without ovaries
0
0
paprika
1
0
barley
0,2
0
wheat
4,2
0
durum wheat
12
3
durum wheat
Conclusions
In order to increase the cost effectiveness, in the past years we improved a new method,
isolated microspore culture. This technique provide an attractive solution for production
huge amount of pure breeding lines and new paprika varieties.
Acknowledgements
This research has been financed by Medimat Ltd.
References
Dumas de Vaulx, R.; Chambonnet, D.; Pochard, E. 1981. Culture in vitro d’anthères du
pi­ment (Capsicum annuum L.): amélioration des taux d’obtention de plantes chez
différents génotypes par des traitements à + 35 C. Agronomie 1:859-864.
Gémes Juhász, A.; Venczel, G.; Sági, Zs.; Gajdos L.; Kristóf Z.; Vági P.; Zatykó L. 2006.
Production of doubled haploid breeding lines in case of paprika, eggplant, cucumber,
zucchini and onion. Acta Horticulture 725:845-854.
Gémes Juhász A.; Kristóf Z.; Vági P.; Lantos Cs.; Pauk, J. 2009. In vitro anther and iso­la­
ted microspore culture as tools in sweet and spice pepper breeding. Acta Horti­
culture 829:61-65.
Kim, M.; Jang, I.C.; Kim, J.A.; Park, E.; Yoon, M.; Lee, Y. 2008. Embryogenesis and plant
regeneration of hot pepper (Capsicum annuum L.) through isolated microspore
culture. Plant Cell Reports 27:425-434.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Lantos, C.; Gémes Juhász, A.; Somogyi, Gy.; Ötvös, K.; Vági, P.; Mihály, R.; Kristóf, Z.;
Somogyi, N.; Pauk, J. 2009. Improvement of isolated microspore culture of pepper
(Capsicum annuum L.) via co-culture with ovary tissues of pepper or wheat.
Plant Cell Tissue and Organ Culture 97:285-293
Mitykó, J.; Gémes Juhász, A. 2006. Improvement in the haploid technique routinely used
for breeding sweet and spice peppers in Hungary. Acta Agronomica Hungarica
54:203-219.
Murashige, T.; Skoog, F. 1962. A revised medium for rapid growth and bioassays with to­
bacco tissue cultures. Physiolia Plantarum 15:473-497.
Supena, E.D.J.; Suharsono, S.; Jacobsen, E.; Custers, J.B.M. 2006. Successful development
of a shed-microspore culture protocol for doubled haploid production in Indonesian
hot pepper (Capsicum annuum L.). Plant Cell Reports 25:1-10.
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Eds. J. Prohens & A. Rodríguez-Burruezo
Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
SSR Markers Derived from EST Database in Capsicum spp.
H. Huang, Z. Zhang, S. Mao, L. Wang, B. Zhang
Key Laboratory of Vegetable Genetics and Physiology of Ministry of Agriculture, Institute of Vegetables and
Flowers, Chinese Academy of Agricultural Sciences, Zhongguancun South Street No.12, Beijing100081, China.
Contact: [email protected]
Abstract
SSR markers are useful in pepper linkage mapping and gene locating. Several hundred (446)
SSR makers have been reported, but they are insufficient. It is a costly way to develop SSR
marker from DNA library, whereas it seems much easy to find in EST sequences in the Genbank
of pepper through internet. We try to develop SSR markers in the EST sequences by using
bioinformatics. EST sequences were trimmed by est-trimmer.pl’ software, while 116915 EST
sequences were obtained without poly ‘A’ or poly ‘T’, ranging between 100 and 700 bp.
Using ‘e-PCR’ and ‘del.pl’ software, SSR sequences were identified. 2508 Microsatellite loci
(larger than 20 repeats) were established and 755 SSR primers were designed using ‘SSR
finder’ software and ‘Primer 3’ software. There were 498 (0.43%) mono-, 1 026(0.89%) di-,
518(0.45%) tri-, 245(0.21%) tetra-, 114(0.10%) penta- and 107(0.09%) hexa-nucleotide SSRs.
The estimated frequency of SSRs was approximately 1/25.12 kb. According to the distribution
of SSRs in pepper, the mean length of pepper SSRs was 22.68 bp and the adenine rich repeats
such as A/T, AG, AT, AAG, AAAT and AAAC were predominant in each type of SSRs (mono-, di-,
tri-, tetra-, penta- and hexa-), whereas the C/G, CG, CCG repeats were less abundant. 210
primers were tested in 8 pepper cultivars and the PCR result revealed the existence of
polymorphism among 127(60.48%) SSR primers within 8 pepper cultivars. It confirmed that
pepper EST database could be efficiently exploited for available SSR markers.
Keywords: pepper, expressed sequence tags, microsatellite, polymorphism, bioinformatics,
e-PCR.
Introduction
Pepper (Capsicum annuum L.) derived from tropic regions of America, is now cultivated
in many countries over the world, especially in China. In the recent years, genetic map
location and molecular genetic researches in pepper have made marked progress, and so
far approximately twenty genetic maps have been established (Wang, et al., 2005).
While saturation of intraspecific maps is relatively low in comparison with other
solanaceae crops (http://solgenomics.net), different molecular markers are increasing
gradually, nevertheless new markers still need to be developed and applied to obtain
high-density maps of pepper (Wu et al., 2006; 2009).
Microsatellites or simple sequence repeats (SSRs) are tandemly repeated DNA with re­
peats length of one to six base pairs. SSR markers, with good stability, high polymorphism
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and easy operation, have been widely used in many researches including genetic variation,
linkage map construction and others. However, traditional methods of developing SSR
markers are laborious and expensive (Nagy et al., 2007).
To develop SSR markers from Genbank is an effective approach, since the number of
expressed sequence tags (ESTs) is increasing considerably in public databases with the
development of the sequencing. The EST databases provide a new source for developing
SSR markers in a rapid and cost effective manner. Up to now, the EST-SSR markers have
been developed and validated in crops such as barly (Thiel et al., 2003; Pillen et al.,
2000), rice (Miyao et al., 2000), rye (Hackauf et al., 2002), grap (Scott et al., 2000) and
others. In this way, Huang Sanwen (2001) and his colleagues searched 58 SSRs and
developed 12 SSR markers in 302 sequences from database comprising 12 ESTs. Nagy and
his coworkers (Portis et al., 2007) succeeded to have developed a set of 50 polymorphic
SSRs from a collection of about 23000 Capsicum sequences. 783 SSRs were found in
about 8000 Capsicum ESTs and 348 SSR primer pairs were designed and used in the
classification of different Capsicum species (Aniko Stagel et al., 2007).
At least 117616 pepper EST have now been developed in the Genbank (http://solgenomics.
net, August 20th, 2009), which represents a much larger figure than that reported in 2007
(Aniko Stagel et al., 2007). It seems desirable to develop new SSR markers from the EST
database. However, how to take off the sequences reported before seems difficult but
necessary. The Electronic PCR (e-PCR) as a computational procedure for searching DNA
sequences for sequence tagged sites (STSs). STSs are defined by a pair of primer sequences
and an expected PCR product size (Schuler G.D., 1997; 1998). e-PCR is a useful tool to
compare the chosen primers to the genomic sequence. It has increasingly important
applications to the process of designing new PCR primer pairs. Primers that match multiple
locations in the genome and can be discarded before using them in an experiment (Kirill
et al., 2004).The DNA sequences for reported primers also can be removed before
designing new primers.
In this article, we tryed to use the pepper EST database to derive new SSRs and eliminate
EST sequences containing SSR sequences using e-PCR.
Material and Methods
Source of EST sequences of pepper
All the EST sequences used in this study were retrieved from dbEST/Genbak (http://
www.ncbi.nlm.nih.gov) on August 20th, 2009. A total of 117616 pepper EST sequences
from organs and tissues of different growth and development stages of various pepper
cultivars.
Deriving available EST sequences
Quality control of EST sequences was first carried out using est-trimmer.pl (jttp://pgrc.
ipk-gatersleben.de/misa/misa.html). The EST sequences shorter than 100 bp were exclu­
ded and those longer than 700 bp were clipped at their 5′ end to preclude the inclusion of
low-quality sequences (Thiel et al., 2003). The remaining polyA and polyT stretches
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Advances in Genetics and Breeding of Capsicum and Eggplant
corresponding to polyA-tails of mRNA were removed so that there was no stretch of (T)5
and (A)5 in a window of 50bp on the 5′ or 3′ end.
Eliminating EST sequences containing SSR sequences reported
SSR sequence tagged sits based on SSR markers reported were obtained by using
Electronic PCR (e-PCR, http://www.ncbi.nlm.nih.gov/sutils/e-pcr/). They were elimi­
nated from the irredundant EST sequences by using del.pl written in Perl language. The
remaining EST sequences were used to explore SSRs.
Exploring EST sequences for SSRs
SSR Finder, a Perl script (http;//maizonemap.org/bioinformatics/SSRFINDER), was run
to search the remaining EST sequences for mi­crosatellites on a personal computer with
Linux system. A repeat motif was defined if the size of the repeat unit was between one
and six nucleotides (1–6 bp). The minimum length criteria was 12 repeat units for a
mononucleotide, 10 repeats for a dinucleo­tide, 7 repeats for a trinucleotide and 5
repeats for other microsatellites(Kijas et al., 1995; Mauricio et al., 2005).
EST-SSRs markers development and PCR verification of their polymorphism
EST-SSRs were designed for the EST sequences containing SSR loci by SSR Finder and
Primer 3.0 (http://primer3.sourceforge.net/releases.php) in batch processing. Parame­
ters for primers pairs were described as follows: size of primer products ranged from 100
to 500 bp; primers size were from 20 to 24 bp; TM of primers ranged between 60 and
65ºC; and the genomic DNA was extracted from eight pepper culti­vars (Table).
Table 1. Plant materials used in SSR markers polymorphism investigations.
Materials
Name
Species
Variety
83-60
Capsicum annuum L.
Sweet pepper
83-58
Capsicum annuum L.
Sweet pepper
93-100
Capsicum annuum L.
Hot pepper
Qiemen
Capsicum annuum L.
Sweet pepper
Perennial
Capsicum annuum L.
Hot pepper
H3
Capsicum annuum L.
Hot pepper
PI 15225
Capsicum chinense J.
Hot pepper
PI235047
Capsicum pubescens
R&P.
Hot pepper
Donors
Institute of Vegetables and
Flowers (IVF), Chinese Academy of
Agricultural Sciences (CAAS), China.
Dr. Alain Palloix, National Institute_
of Agricultural Research (INRA),
France.
Dr. Miller Sally, Oregon State
University, USA.
PCR conditions were as follows: 30 ng of DNA, 2.5 mmol/L of MgCl2, 0.2 µmol/L of each
primer, 0.2 mmol/L of dNTPs and1 unit of Taq DNA enzyme. Reaction volumes were set
at 25 µL, and the mixture was first denatured at 94ºC for 1 min, then cycled 30 times at
94ºC for 40 sec, annealing temperature for 1 min, and 72ºC for 1 min and finally extended
at 72ºC for 5 min. The annealing temperatures were adjusted depending on different
primer pairs. The PCR products were electrophoresed on 4% polyacrylamide gels and
stained by Silver.
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Advances in Genetics and Breeding of Capsicum and Eggplant
Results and Discussion
Occurrences of different SSRs in pepper ESTs
A total of 116915 irredundant EST sequences cor­responding to approximately 63.73 Mb
were obtained from 117616 EST sequences published on Genbank, and 2137 SSR sequences
tagged sits were obtained from SSR markers reported by using Electronic PCR (e-PCR),
of which 1304 SSR sequences tagged sits corresponded with irredundant EST sequences
and were eliminated from the irredundant EST sequences by using del.pl. Then the
115611(62.99 Mb) remaining EST sequences were searched for microsatellites, and as a
result, 2508 Microsatellite loci (larger than 20 repeats) were identified in 2419 ESTs. The
frequency was 2.17%, but the proportion of different SSR among 2508 SSRs was not
evenly distributed (Table 2). The estimated frequency of SSRs was approximately 1/25.12
kb. It was found that the Dinucleotide SSRs were the most abundant repeat motifs and
the trinu­cleotide SSRS were the second most abundant ones.
Table 2. Number, percentage, frequency mean distance and length of EST-SSRs
developed in pepper.
Repeat types
Number
Percentage Frequency
/%
/%
Mean
distance
/Kb
Length of
repeats/bp
Average
length
Mononucleotide
498
19.86
0.43
126.48
12-57
13.18
Dinucleotide
1026
40.90
0.89
61.39
10-25
22.42
Trinucleotide
518
20.65
0.45
121.59
7-12
22.71
Tetranucleotide
245
9.77
0.21
257.08
5-10
21.03
Pentanucleotide
114
4.55
0.10
552.51
5-8
26.27
Hexanucleotide
107
4.27
0.09
588.65
5-7
31.23
Total
2508
100.00
2.17
25.12
12-30
22.68
Note: Percentage= Total different repeat SSRs / Total SSRs; Frequency= Total different repeat SSRs /
Total irredundant ESTs; Mean distance=Total length of irredundant ESTs/Total different repeat SSRs.
Distribution of SSRs in pepper
The minimal length of a SSR varied from 12 to 30 bp according to the set parameter, while
the maximal length ranged from 40 to 120 bp depending on the repeat times of the motif
contained in the SSR. The overall mean length of pepper SSRs was 22.68 bp (Table 2). In
fact, most tri-, tetra-, penta-and hexa-nucleotide SSRs had less than 10 repeats. The
number of mono-nu­cleotide SSRs decreased with the increased number of repeats. Similar
trends were also shown by di-, tri-, tetra-, penta- and hexa-nucleotide SSRs (Figure 1).
Furthermore, the adenine rich repeats, such as A/T, AG, AT, AAG, AAAT, AAAC etc. were
predominant in each type of SSRs (mono-, di-, tri-, tetra-, penta- and hexa-), whereas the
C/G, CG, CCG repeats were less abundant.
The distribution of different types of repeat mo­tifs in dinucleotide and trinucleotide
SSRs is presented in Figure 2. The complementary sequences, for instance AT/TA, AG/
TC, were considered the same motif type. The AT was the most common motif, followed
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Advances in Genetics and Breeding of Capsicum and Eggplant
by AG. In contrast, the CG motif was rare, and found only in 10 SSRs. Among all
trinucleotide motifs, AAT was the predominant motif followed by AAG. ACG was the
rarest motif, whereas CCG was the least motif in pepper.
Figure 1. Number of SSRs developed in different repeat units.
Figure 2. Distribution of dinucleotide and trinucleotide microsatellites.
EST-SSR primers development and evaluation
755 EST-SSR primers were designed in batch processing from 2419 EST sequences containing
SSR loci. 210 primers were chosen at random and were tested against eight pepper culti­
vars. PCR test revealed the existence of polymorphism among 127(60.48%) SSR primers
and no amplification products were detected among 54 (25.71%) SSR primers.
Discussion
The Electronic PCR (e-PCR) has in general Forward e-PCR and Reverse e-PCR, wherein
e-PCR is referred to as Forward e-PCR. e-PCR is used to map sequences in STS database;
re-PCR is used to map STSs or short primers in sequence database and famap and fahash
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Advances in Genetics and Breeding of Capsicum and Eggplant
are used to prepare sequence database for re-PCR searches. e-PCR parses stsfile in unists
format, and then reads nucleotide sequence data in FASTA format from files listed in
command line if any, For input sequences e-PCR finds matches and prints output in one
of the three formats (Schuler G.D., 1997; 1998). In this study, 446 SSR marker primers are
used as STS, and 2137 sequences are obtained by e-PCR, in which 1304(61%) sequences
match with ESTs of pepper. The Electronic PCR (e-PCR is one of the common electronic
tools used for the analysis of nucleotide sequences. It plays an important role in the
chromosomal localizations of the DNA fragments, genomic sequencing, assistance to
genome mapping and PCR primer design, and gene cloning using the Mapviewer software,
Genemap database, and Unigene database, etc.
In this study, 2508 SSRs are obtained from pepper EST database. In addition to SSRs
developed from traditional genetic library screening and other methods, pepper EST
sequences are a rich resource for the rapid discovery of SSRs. However, specific methods
to be applied largely depend on the availability of ESTs. The present study has shown
that the distribution of the different microsatellites exhibits a similar pat­tern in many
crops (Kijas et al., 1995; Mauricio et al., 2005). Generally, adenine-rich repeat motifs,
especially AG/T, AAG/T, AAAG/T, AAAAG/T and AAAAAG/T are com­mon in SSRs. These
adenine-rich repeat motifs are most likely to appear to match with the structure and
frequency of different proteins. The specific reasons yet to be further studied. To test
the possibility of using EST-SSRs to de­velop molecular markers, we have randomly
selected 210 primers, and as shown by the PCR testing 127 primers of them are successful
to reveal the polymorphism of the selected SSRs within eight pepper cultivars. This
finding demonstrates that the EST data­base is an excellent resource for the development
of SSR markers, and that 54 pairs of primers have no amplification products, probably
because of a long intron contained in primer sequences in two exons or in the middle.
Acknowledgments
The work was financed by the National Scientific Research Institutes Fund of China
(Agreement No. 0032007216), Chinese National Science Fund (30800752) and Key Labo­
ratory of Vegetable Genetics and Physiology, Ministry of Agriculture, China.
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Mauricio, L.R.; Ramesh, V.K.; Ju, K.Y.; Mark, E.S. 2005. Nonran­dom distribution and fre­
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Graft-induced genetic variation of fruit color in the progenies
derived from interspecific-grafting in chili pepper
M. Ishimori, C. Yamaguchi, M. Khalaj Amirhosseini, H. Miyazawa, L. Yu,
C.R. Zhao, Y. Hirata
Laboratory of Plant Genetics and Biotechnology, Tokyo University of Agriculture and Technology,
Tokyo 183-8054, Japan. Contact: [email protected]
Abstract
Graft induced change has been already known as genetic phenomena. We carried out
grafting experiments using two peppers, Capsicum annuum (as “scion”) and C. baccatum
(as “stock”). Both species have red fruits at maturity. But the progenies derived from the
scion developed fruits with different colors from the scion and stock. The number of variant
colors was seven in total. We investigated the content of carotenoids in mature fruit and
the carotenoid biosynthetic genes which seemed to be responsible in these variations.
These variations in this study were caused by both quantitative and qualitative changes of
carotenoids. On the basis of this result, three genes involved in carotenoid biosynthesis,
which were capsanthin-capsorubin synthase (Ccs) gene, phytoene synthase (Psy) gene and
zeta-carotene desaturase (Zds) one, were analyzed. While Ccs gene of the scion and stock
functioned normally, Ccs gene of some variants colud not function due to 1 bp deletion. In
Psy gene, two types of variation were found in different variants. Another gene, Zds, was
trancribed in the grafted parents and all variants, however, particular variants had three
fragments by PCR analysis. In conclusion, interspecific-grafting could induce variations of
genes involved in mature fruit color.
Keywords: Capsicum, capsanthin-capsorubin synthase, carotenoid, mature fruit color, phy­
toe­ne synthase, zeta-carotene desaturase.
Introduction
Graft-induced change means that genetic traits in the scion or stock are varied by
grafting. This phenomenon can take place not only in the grafted plants but also in the
progenies (Ohta and Chuong 1975, Hirata 1979a,b). The existence of graft-induced
change has been denied by typical Mendelian, however, some studies are revealed by
partial geneticist or biologist (Stegemann and Bock 2009).
We experimented grafting using two peppers in order to introduce the resistance against
cucumber mosaic virus (CMV) from the stock to the scion. Grafted scions partly obtained
the stronger resistance than original scion and the trait were transmitted to the progenies
derived from grafted scions (Shiiguchi et al. 2004, Miyazawa et al. 2006). Because we
only used two long-distant related species with red fruits, contamination is impossible
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to suppose. But the induced-changes were complicated. The progenies derived from
grafted scions had various traits which original scion did not have (Miyazawa et al.
2006). Both the scion and stock plants had mature fruits with red color. But the progenies
derived from grafted scion had mature fruits with not only red but also orange, paleorange, orange-yellow, variable-yellow, yellow or white (total 7 colors). Quantity and
quality of carotenoids contained in the pericarp is responsible for mature fruit color in
pepper (Thorup et al. 2000).
We analyzed quantitative and qulitative changes of carotenoids in mature fruit and
genes involved in carotenoid biosynthesis so as to explain the nature of these variations
in mature fruit color. Finally, the relationship between interspecific-grafting and these
color changes was discussed.
Material and methods
Plant materials
Capsicum annuum ‘G line’ was used as original scion. C. baccatum ‘LS1205’ was used as
original stock. All variants analyzed in this study were derived from the grafted G line
scion onto LS1205 stock. Variants were classified into seven colors. The seven colors
were red (same as the scion and stock), orange, pale-orange, orange-yellow, variableyellow, yellow and white.
HPLC analysis
All procedures were carried out by the same methods as Watanabe et al. (2009).
DNA and RNA techniques
Extraction of DNA and total RNA, PCR condition, cDNA synthesis and sequencing were
followed by the common method (Gergely 2009).
Results and discussion
The quantification of carotenoids in mature fruit
The scion and stock fruits contained a large carotenoid (Table 1). Especially, capsanthin
and capsorubin with red color in fruits were very abundant. Orange and pale-orange
fruits had also these pigments, but the total contents of carotenoids were much less
than that of grafted parents. On the other hand, orange-yellow and variable-yellow
fruits did not include the red pigments but relatively rich carotenoids as compared with
other variant fruits. Yellow and white fruits contained no red pigments and little
carotenoids. These results indicated that mature fruit color variations in this study were
caused by both quantitative and qualitative changes of carotenoids in mature fruit.
Probably, the expression of carotenoid biosynthesis may alter in these variants.
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Table 1. Quantification of carotenoids in the samples analyzed.
Analysis of capsanthin-capsorubin synthase (Ccs) gene
Ccs gene is essential to the formation of red fruits in pepper. While several SNPs existed in
Ccs gene between the scion and stock, the transcripts were normal in both mature fruits.
But orange-yellow, variable-yellow, yellow and white variants had 1 bp deletion in Ccs exon
among the fruit color variants (Fig. 1). The deletion caused frame-shift in the sequence,
and the formation of early stop codon (TAG). In PCR-RFLP using Alw26I, the band pattern
co-segregated with the mature fruit color. This variation seemed to be induced by
interspecific-grafting because both the scion and stock had no deletion in Ccs gene.
Analysis of phytoene synthase (Psy) gene
Psy gene in the scion and stock had a normal sequence and was transcribed. But many
varinats except orange-yellow had two types of variations in Psy gene. In the variants
with one variation, no amplified products were obtained in PCR and RT-PCR (Fig. 2).
Another variation was found only in variable-yellow. The cDNA sequence had 40 bp of
insert region and 312 bp of deletion region in the 5’ end. The genomic DNA sequence had
more than 500 bp of insert as compared with that of the scion. This inserted sequence
had the homology with partial C. annuum genome sequence. But the origin of the insert
was unknown because the sequence might be conserved in pepper genome. These results
show that two variations in Psy gene must be individually induced via different steps
after interspecific-grafting.
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Figure 1. Frame shift by 1bp deletion and change of protein sequence. Arrow indicates
a position of 1 bp deletion in nucleotide sequence.
Analysis of zeta-carotene desaturase (Zds) gene
Although the polymorphism between the scion and stock was found in the intron regions
of Zds gene, no remarkable differences were found in the exon. The mRNA of Zds gene
with expected size was also observed in mature fruit of both plants. In the variant color
fruits, the transcript of the same size also existed. While genomic sequence of Zds gene
in some variants was highly similar to that of the scion, pale-orange or white fruits had
three fragments of putative Zds gene by PCR. The fragment of middle size (Zds2) was
the same size as that of the scion, however, both the biggest one (Zds1) and the smallest
(Zds3) had a 90 bp insertion in the putative intron 13 as compared with Zds2 (Fig. 3).
Moreover a 174 bp deletion near the region was found in Zds3. This deleted region
essentially existed not in intron 13 of the scion Zds gene but in that of the stock. These
results indicated that Zds2 proved be derived from the scion and Zds3 from the stock.
However a 90 bp insertion in Zds1 and Zds3 did not exist in the stock genome. This
insertion might be derived from other region.
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Figure 2. RT-PCR using Psy primers. RC. Red (scion), RT: Red (stock), Y: Yellow,
Y’: Variable-Yellow, O: Orange, OY: Ornage-Yellow, PO: Pale-Orange, W. White.
Figure 3. Three fragments of putative Zds gene found in the variants
with pale-orange or white fruit and the stock Zds gene.
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Acknowledgements
HPLC analysis in this study was done with the cooperation with Dr. Watanabe (Nihon
University). We’d like to express our sincerest thanks.
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Advances in Genetics and Breeding of Capsicum and Eggplant, (2010)
Editorial de la Universitat Politècnica de València, Valencia, Spain
Evaluation of response to in vitro embryo rescue in Capsicum spp.
J.P. Manzur, J. Herraiz, A. Rodríguez-Burruezo, F. Nuez
Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universidad Politécnica de Valencia,
Camino de vera, sn, CP 46022 Valencia, Spain. Contact: [email protected]
Abstract
Embryo rescue has been found useful for breeding programs, as on one hand allows immature
embryos can be germinated, and on the other it allows overcoming postzygotic incompatibility
barriers, making possible obtaining interespecific hybrids which cannot be obtained simply
by artificial sexual hybridization. Although embryo rescue has been studied in several
solanaceous crops, its knowledge is scarce in genus Capsicum. Therefore, establishing
knowledge and protocols in this topic could be of great interest for Capsicum breeders. This
experiment included several accessions from C. annuum, C. chinense and C. baccatum.
Fruits from self-pollination were sampled at 20, 30, 40, and 50 days after pollination (DAP)
and a total of 820 seeds were removed and evaluated. Embryo presence and stage of
development were recorder for each seed. Efficiency of embryo rescue was evaluated after
10 days of in vitro culture, as germinated embryos vs. total rescued embryos. The results
obtained show that 40 DAP was the best time for embryo rescue. This date had a high
number of embryos and diver