Download Development and validation of SNP

Mol Breeding (2015)35:129
DOI 10.1007/s11032-015-0323-4
Development and validation of SNP-based functional
codominant markers for two major disease resistance genes
in rice (O. sativa L.)
G. Ramkumar . G. D. Prahalada .
Sherry Lou Hechanova . Ricky Vinarao .
Kshirod K. Jena
Received: 13 November 2014 / Accepted: 8 May 2015
! Springer Science+Business Media Dordrecht 2015
Abstract Blast and bacterial leaf blight are major
diseases of rice that limit grain yield significantly.
These two devastating biotic stresses have to be
controlled to meet the demand for 23 % more rice
production by 2035 to feed the increasing number of
rice consumers. Incorporating appropriate disease
resistance genes into elite varieties is considered as
the best method to enhance crop resistance. Molecular
markers play an important role in multiple gene
pyramiding programs to select desirable genotypes
with targeted genes. Two major resistance genes, Pita
and xa5, for blast and bacterial leaf blight races,
respectively, have been used in many gene pyramiding
programs. However, simple PCR-based functional
codominant markers have not been reported for these
genes. Hence, in the present study, time- and costeffective codominant markers for Pita and xa5 have
been developed and validated in segregating populations. High-throughput screening has been demonstrated using parallel capillary electrophoresis to
Electronic supplementary material The online version of
this article (doi:10.1007/s11032-015-0323-4) contains supplementary material, which is available to authorized users.
G. Ramkumar ! G. D. Prahalada ! S. L. Hechanova !
R. Vinarao ! K. K. Jena (&)
Novel Gene Resources Laboratory, Plant Breeding,
Genetics, and Biotechnology Division, International Rice
Research Institute, DAPO Box 7777, Metro Manila,
Philippines
e-mail: [email protected]
replace laborious gel-based electrophoresis. Additionally, the presence of Pita and xa5 alleles was evaluated
with 260 diverse rice varieties that were collected from
different parts of the world. Of the 260 cultivars tested,
55 were identified with the Pita resistance allele while
all the tested cultivars had the susceptible Xa5 allele.
The identified Pita allele-derived cultivars can be used
as an alternative resistance source for blast disease.
The newly developed Pita and xa5 functional markers
will help toward tracking the two target genes for blast
and bacterial leaf blight resistance in breeding
programs.
Keywords Rice blast ! Bacterial leaf blight !
Codominant marker ! Pita ! xa5
Introduction
Rice is an important cereal crop that feeds more than
half of the world population (Wang and Li 2005).
Demand for rice is steadily increasing, as the number
of rice consumers is increasing, especially in developing countries (Khush and Jena 2009). However, rice
production is severely affected by biotic and abiotic
stresses. Among the biotic stresses, rice blast and
bacterial leaf blight (BB) are major devastating
diseases that limit rice yield significantly (Ou 1985;
Mew et al. 1993). Enhancement of host plant
resistance is one of the best methods to control these
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two major biotic stresses. Pyramiding of multiple
disease resistance genes into elite cultivars could
provide durable and broad-spectrum resistance.
Among the biotic stresses, blast is the most
devastating disease. It is caused by the filamentous
ascomycete fungus Magnaporthe oryzae (anamorph
Pyricularia oryzae), which leads to multiple social
crises. Yield losses from this fungal disease were
estimated to be 157 million tons per year (Lin et al.
2007). Nearly 100 resistance genes have been reported
and 19 of these genes have been cloned and characterized at the molecular level (Ramkumar et al. 2014).
Among the resistance genes, Pita is one of the major
genes that was characterized by a map-based cloning
strategy (Bryan et al. 2000). Pita is a single-copy gene,
located on rice chromosome 12, where a few other
blast resistance genes are also located (Jia et al. 2003).
The Pita resistance allele has three exons and encodes
for 928 amino acids; a single amino acid change
(serine instead of alanine) at the 918 amino acid
position leads to the susceptible pita allele (Bryan
et al. 2000). Since the gene provides broad-spectrum
resistance against different blast isolates, it is used to
control blast disease worldwide (Lee et al. 2011).
Moreover, it is one of the most common genes used in
blast gene pyramiding programs (Hittalmani et al.
2000; Hayashi et al. 2006) and allele mining studies
(Jia et al. 2003; Wang et al. 2008; Ramkumar et al.
2010a; 2014).
BB disease caused by Xanthomonas oryzae pv.
oryzae (Xoo) limits rice production up to 81 %
(Kumar et al. 2012). Thirty-eight different resistance
genes have been identified to combat this serious
disease of rice (Suh et al. 2013). Among them, xa5 is
one of the major recessive resistance genes that
provide a high degree of resistance to a wide range
of Xoo races (Suh et al. 2013). The xa5 gene was
cloned and characterized by Iyer and McCouch
(2004), and it encodes a small subunit of transcription
factor IIA. This gene is located on rice chromosome 5
and has four exons and three introns. Two nucleotide
substitutions at the second exon lead to one amino acid
change (valine to glutamic acid at position 39), which
leads to the resistance allele xa5 locus. It has also been
observed that the reported amino acid change is
consistent among all 27 different resistant rice varieties tested and nine susceptible ones belonging to the
Aus-Boro group (Iyer and McCouch 2004). This gene
is also used in many bacterial resistance gene
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Mol Breeding (2015)35:129
pyramiding programs worldwide (Sundaram et al.
2008; 2009; Kottapalli et al. 2010; Suh et al. 2013).
Recessive resistance genes are preferable, as those
genes provide resistance to different pathogenic races
with mechanisms of action different from those of the
dominant resistance genes. A high degree of durable
resistance could be achieved by using recessive genes
in breeding programs (Li et al. 2012).
Molecular markers play a significant role in gene
pyramiding programs, and the availability of appropriate and functional gene-derived markers facilitates
tracking the target alleles in segregating populations.
Dominant molecular markers were reported for the
blast resistance gene Pita (Jia et al. 2002; Hayashi
et al. 2006). However, these markers could not
differentiate the homozygous and heterozygous status
of the alleles in the segregating populations, which is a
significant limitation of the dominant markers. CAPS
markers were reported to track BB resistance gene
xa5, which was functional and could differentiate the
allelic homo-/heterozygous status (Iyer and McCouch
2007). However, genotyping with CAPS markers
involves many additional steps, that is, confirmation
of success of the PCR amplification, digestion of
amplicons with restriction enzymes, and incubation of
digestion mixture for a proper enzymatic reaction, and
the digested products have to be usually separated in a
high percentage of agarose or polyacrylamide gels.
These additional steps make the genotyping process
costly, time-consuming, and laborious (Ramkumar
et al. 2010b).
High-throughput screening for traits is preferred in
the molecular marker development process. Screening
of PCR products is one of the crucial steps in genotyping
samples. Conventional agarose/acrylamide gel-based
electrophoresis is linked with considerable time, cost,
and labor. Moreover, this method of electrophoresis is
associated with mutagens and carcinogens such as
ethidium bromide and acrylamide. Hence, the demonstrated applicability of markers using recent technology
such as parallel capillary electrophoresis is appropriate
to avoid gel-based genotyping.
Information regarding the number of genes present/
absent in a given rice cultivar is often lacking, which is
critical for rice breeding programs. It is often difficult
to screen plant materials in the field because of
quarantine restrictions that inhibit the exchange of
different M. oryzae races (Wang et al. 2007). However, the availability of functional markers helps
Mol Breeding (2015)35:129
immensely to screen a wide range of diverse plants to
detect the presence of particular genes with less cost
and effort (Ramkumar et al. 2011).
Based on the status of Pita and xa5 resistance genes
and the available molecular markers, this study was
designed with the following objectives: 1. Development of simple PCR-based functional codominant
molecular markers for Pita and xa5; 2. validation of
accuracy and usability of the markers in crosssegregating populations; 3. applicability of the markers in high-throughput genotyping; and 4. analysis of
Pita and xa5 distribution in a wide range of diverse
rice cultivars collected from different parts of the
world. The newly developed Pita and xa5 functional
markers will help to track the favorable alleles in
disease resistance breeding programs, while the identified 55 Pita alleles can be used as new sources for
blast resistance.
Materials and methods
Plant materials
The plant materials used in this study include segregating populations for validating the accuracy and
specificity of newly developed Pita and xa5 functional
markers and a panel of highly diverse plant materials to
analyze the distribution of candidate genes. A BC1F2
segregating population, derived from a cross between
IR95440-1-26-1-4 (possessing Pita-gene-derived blast
resistance) and IR72 (susceptible to blast), was used to
validate the newly developed Pita marker. Another
BC2F2 segregating population, derived from a cross
between IR90751-1-14-1-2 (possessing xa5-derived
BB resistance) and IR72 (susceptible to BB), was used
to validate the newly developed xa5 markers. These
materials were obtained from the Plant Breeding,
Genetics, and Biotechnology Division of the International Rice Research Institute (IRRI), Los Baños,
Laguna, Philippines.
Highly diverse cultivars that were collected from
different parts of the world have been obtained from
the International Rice Genebank collection of IRRI
(Supplementary Table 1). Seed materials were germinated in seedbeds, and 21-day-old seedlings were
transplanted in the field. DNA was extracted using the
standard protocol with minor modifications (Dellaporta et al. 1983).
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Evaluation for BB resistance
A BC2F2 population derived from IR90751-1-14-1-2
and IR72 and the diversity panel were screened with
Xoo race 9A (PX0339) (incompatible with xa5).
Taichung Native 1 (TN 1) was included as a susceptible check. The overnight-grown race 9A culture
(incompatible with xa5) was diluted into 1 9 109 cfu/
ml and was used to inoculate 8–10 leaves of 60-dayold plants by clip inoculation (Kauffman et al. 1973).
The lesions were scored 14 days after inoculation
(IRRI, 2006). The experiments were performed in two
randomized replications.
Development of allele-specific functional markers
The Pita resistance allelic sequence (Acc. No.
AF207842) was obtained from NCBI (http://www.
ncbi.nlm.nih.gov/) and compared with the Nipponbare
genome sequence. The xa5 resistance and susceptible
allelic sequences (Acc. No. AY643716 and
AY643717, respectively) were aligned using the
bioinformatic tool MEGA (Tamura et al. 2011). The
functional polymorphic regions of the Pita and xa5
alleles as reported by Bryan et al. (2000) and Iyer and
McCouch (2004), respectively, were targeted to design
primers by following the strategy as illustrated in
Fig. 1. In brief, external forward and external reverse
primers are not allele-specific and common for both
(resistance and susceptible) alleles; internal forward
and internal reverse primers are allele-specific
(Table 1). In the case of the Pita SNP marker, the
common band of 759 bp was amplified irrespective of
the Pita/pita allele. The internal forward primer and
external reverse primer produce a 302-bp amplicon if
the resistance (Pita) allele is present, and a 500-bp
amplicon is produced by the external forward primer
and internal reverse primer if the susceptible (pita)
allele is present. In the case of the xa5 SNP marker,
primers were designed in such a way that the common
band (873 bp) was produced, irrespective of the (xa5/
Xa5) alleles, while 338- and 577-bp amplicons were
produced for xa5 and Xa5 alleles, respectively. Care
was taken that the size difference between the amplicons was at least 100 bp, so that the amplicons could be
separated in a low-percentage (*1 %) agarose gel.
The PCR conditions were standardized to differentiate the resistance and susceptible alleles with different annealing temperature by gradient PCR. The Pita
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Mol Breeding (2015)35:129
Fig. 1 Primer designing strategy to develop codominant
molecular markers for Pita and xa5 genes. External forward
and external reverse primers are not allele-specific and common
for both (resistance and susceptible) alleles; internal forward
and internal reverse primers are allele-specific. In case of Pita, a
common band (759 bp) will be amplified irrespective of the
Pita/pita allele. The internal forward primer and external
reverse primer will produce a 302-bp amplicon if a resistance
(Pita) allele is present, and a 500-bp amplicon is produced by the
external forward primer and internal reverse primer if a
susceptible (pita) allele is present. For xa5, primers were
designed in such a way that the common band (873 bp) will be
produced, irrespective of the (xa5/Xa5) alleles, while 338- and
577-bp amplicons will be produced for xa5 and Xa5 alleles,
respectively
Table 1 Primers used to develop Pita and xa5 molecular markers
S. no.
Primer name
Primer sequence
Annealing
temperature ("C)
Role
1
Pita Ext F
TGCGCAAAGAATCGTCGCTGC
62
Pita external forward
2
Pita Ext R
TCTTTGATCCAAGTGTTAGGGCC
62
Pita external reverse
3
Pita Int F
CCGTGGCTTCTATCTTTACCTG
62
Pita internal forward
4
Pita Int R
AGTCAGGTTGAAGATGCATAGA
62
Pita internal reverse
5
xa5 Ext F
CGGATAGCAGCATTTCCAAGAG
57
xa5 external forward
6
7
xa5 Ext R
xa5 Int F
GGAGAAATTACATCACAAGCGC
GCTCGCCATTCAAGTTCTTGAG
57
57
xa5 external reverse
xa5 internal forward
8
xa5 Int R
GTAGATACCTTATCAAACTGGA
57
xa5 internal reverse
and xa5 markers’ PCR was performed in a 15 ll PCR
mix containing 1X buffer (20 mM Tris–HCl (pH 8.8
at 25 "C), 10 mM (NH4)2SO4, 10 mM KCl, 0.1 mg/
mL BSA, 0.1 % (v/v) Triton X-100, 2 mM MgSO4,
0.25 mM of each dNTPs, 5 pM of each primer, and 1
U of DNA polymerase (Invitrogen, USA). Template
quantity was *50 ng of genomic DNA per PCR. PCR
was performed with the following thermal profile:
initial denaturation at 94 "C for 5 min followed by 35
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cycles of denaturation at 94 "C for 30 s, primer
annealing at 62 "C (for Pita)/57 "C (for xa5) for
30 s, and extension at 72 "C for 1 min, followed by
final extension at 72 "C for 7 min.
Comparative genotyping of gene-specific markers
Genotyping data of the newly developed Pita SNP
marker were compared with those of the Pita
Mol Breeding (2015)35:129
dominant marker (Jia et al. 2002). The new xa5 marker
genotypic results were also compared with those of the
xa5 CAPS marker 10603.T10Dw (Suh et al. 2013) and
phenotypic results of the BC2F2 population. The
BC2F2 DNA samples were amplified with
10603.T10Dw primers, and the amplicons were
digested with the RsaI restriction enzyme and incubated for 3 h; the digested products were resolved
through 8 % polyacrylamide/3 % agarose gel
electrophoresis.
Application in high-throughput genotyping
To test the applicability of newly developed Pita and
xa5 markers in high-throughput genotyping, and to
lower the cost and time of the laborious gel electrophoresis process, the amplicons were analyzed with
Fragment Analyzer (Ames, Iowa, USA), which works
by parallel capillary electrophoresis. The experiment
was performed following the manufacturer’s instructions, with 35 and 1500 bp as lower and upper limits,
respectively.
Results
Based on the Pita- and xa5-gene-derived resistance and
susceptible allelic sequence information, primers were
designed targeting the reported functional polymorphism of the genes (Table 1) and PCR conditions of
those primers have been standardized. The SNP marker
for the Pita gene could differentiate the parental
genotypes (IR95440-1-26-1-4 and IR72). To check the
accuracy and reliability of the newly developed Pita
marker, a BC1F2 population derived from crosses
among IR95440-1-26-1-4 and IR72 was screened with
the new Pita allele-specific marker. The genotyping
analysis revealed that, among the 200 genotypes
analyzed, 48 had Pita alleles, 56 had pita alleles, and
96 had Pita/pita (heterozygous) alleles (Fig. 2a). In
order to confirm the results of the newly developed Pita
marker, the same samples were screened with the Pita
dominant marker (Jia et al. 2002), and the genotyping
results of the dominant Pita marker showed agreement
with the new Pita marker. However, the dominant
marker could not differentiate the homozygous/
heterozygous conditions of the Pita allele, and, for the
susceptible pita allele, the marker did not produce any
amplicons (Supplementary Fig. 1).
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The newly developed xa5 SNP marker could
differentiate the parental genotypes, that is,
IR90751-1-14-1-2 and IR72. The xa5 marker was
also validated in a BC2F2 segregating population
(derived from crosses of IR90751-1-14-1-2 and IR72).
The xa5 allele-specific marker identified 54 Xa5, 97
Xa5/xa5 (heterozygous), and 49 xa5 alleles from the
BC2F2 population of 200 genotypes (Fig. 2b). A
comparison of genotype and phenotype data revealed
a perfect co-segregation among them. To confirm the
accuracy of the xa5 marker further, the BC2F2 samples
were screened with the reported CAPS marker
(10603.T10Dw; Suh et al. 2013) and the results of
10603.T10Dw perfectly matched with the newly
developed xa5 marker.
Applicability in high-throughput genotyping
The applicability of the newly developed Pita and xa5
markers was checked by analyzing the amplicons with
Fragment Analyzer (Ames, Iowa, USA) to replace the
cumbersome gel-based electrophoresis as an optional
choice. This experiment clearly distinguished the
specific resistance and susceptible amplicons. In the
case of the Pita-resistant genotype, the Fragment
Analyzer detected two peaks: one peak for the
resistance allele-specific band (302 bp) and the other
one for the common band (759 bp). In the susceptible
genotype, it detected two bands again, but of different
sizes, one of 500 bp (susceptible allele-specific) and
the other a common band. For the heterozygous
genotype, it detected three peaks: one each for the
resistance and susceptible allele-specific band and
another for a common band (Fig. 3).
In the case of xa5 also, the Fragment Analyzer was
used and could differentiate the resistance and
susceptible-specific amplicons clearly. In the resistant
genotypes, it detected two different amplicons of 338
and 873 bp band sizes, which are resistance allelespecific and a common band, respectively. In the case
of susceptible samples, it also detected two different
amplicons of different sizes: a 577-bp band (susceptible allele-specific band) and the other a common
band. For heterozygous samples, all three peaks (for
resistance, susceptible, and common bands) were
found at the respective bp lengths (Fig. 3). The
analysis was performed with five replications, and
similar results were obtained in all the replications.
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Mol Breeding (2015)35:129
Fig. 2 Amplification pattern of newly developed Pita and xa5
gene markers in segregating populations. a A set of BC1F2
populations derived from crosses among IR95440-1-26-1-4
(possessing Pita and resistant to blast) and IR72 (susceptible to
blast) was screened with the new Pita marker. 1 IR95440-1-261-4, 2 IR72. b The new xa5 marker was also validated in a
BC2F2 segregating population derived from crosses of IR907511-14-1-2 (possessing xa5; resistant to bacterial blight) and IR72
(susceptible to bacterial blight). 1 IR72, 2 IR90751-1-14-1-2.
RR homozygous resistant, Rr heterozygous allele, S homozygous susceptible
Screening of diverse plant materials
agreement with genotype data. However, 68 cultivars
showed resistance against race 9A, while the marker
revealed a susceptible Xa5 allele for those genotypes.
The resistance of these exceptional cultivars might be
due to the presence of BB resistance genes other than
the xa5 gene.
A set of 260 highly diverse materials collected from 32
different countries were screened using the standardized new Pita and xa5 markers. Among the diverse
cultivars, 55 showed the presence of the Pita resistance allele (Table 2), which can be used as an
alternative source of the Pita gene for blast resistance,
while 205 showed the susceptible pita allele (Supplementary Table 1). Though the highest number of
entries was collected from the Philippines (36), the
highest number of 13 Pita-derived resistant entries
was found in the germplasm from China (Supplementary Fig. 2). This was followed by six Pita-resistant
cultivars from Vietnam (Supplementary Table 2). In
order to confirm the genotyping data, the Pita
dominant marker was also used for genotyping and
the results were in agreement with those of the newly
developed Pita marker.
In the case of xa5, other than the known resistant
controls, interestingly, all the 260 cultivars showed
susceptible Xa5 alleles with the new marker. The
diverse genotypes were screened with race 9A
(incompatible with xa5 and Xa21) to know their
phenotypic reaction to BB resistance. Most of the
phenotypic reactions of the cultivars were in
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Discussion
Biotic stresses caused by fungal and bacterial diseases
are serious threats to rice crop production and
productivity. Among the biotic stresses, blast and
BB are the most devastating diseases that lead to
severe yield and economic losses (Ou 1985; Mew et al.
1993; Lin et al. 2007; Kumar et al. 2012). Enhancement of host plant resistance by means of incorporating resistance genes is the best strategy to control
biotic stresses. The incorporation of major resistance
genes will enhance the durability and degree of
resistance of the crop, in which molecular markers
play a vital role for the rapid selection of genotypes
having the targeted genes (Jena and Mackill 2008).
The Pita gene is one of the major blast resistance
genes as it provides resistance against a wide range of
blast isolates (Bryan et al. 2000; Jia et al. 2003), and
Mol Breeding (2015)35:129
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Fig. 3 Applicability of new Pita and xa5 markers in highthroughput genotyping. The experiment was performed with
Fragment Analyzer (Ames, USA) by following the manufacturer’s
instructions, with 35 and 1500 bp as lower and upper limits,
respectively. R = resistant allele; S = susceptible allele
hence, this gene has been used in many resistance
breeding programs for more than a decade (Hittalmani
et al. 2000; Hayashi et al. 2006). However, to select the
favorable Pita gene-specific allele in segregating
breeding populations, appropriate codominant functional molecular markers are not yet reported even
though the gene has been cloned and characterized. A
fluorescence primer-based non-functional marker (targeting the intronic region of the allele) was reported
(Jia et al. 2004), which needs expensive primers and
chemicals and a costly instrument to resolve single
nucleotide differences in amplicon length (Wang et al.
2007), which may not be practical and affordable for
most of the laboratories in developing countries.
Though normal PCR-based dominant markers are
reported, those markers are not appropriate for a
molecular breeding program as the dominant marker
cannot differentiate homozygous and heterozygous
Pita alleles (Jia et al. 2002; Hayashi et al. 2006). For
instance, in a segregating population, if the target is
the homozygous Pita allele, it is not possible with a
dominant marker to select the Pita/Pita allele accurately. As the phenotypic reaction also cannot differentiate the heterozygous and homozygous condition of
a dominant gene, selection of a Pita/pita genotype
leads to additional time and cost to achieve the target
(Pita/Pita). Moreover, for a susceptible genome, the
marker would not produce any amplicons, which
could lead to ambiguity of PCR failure (Wang et al.
2007). Hence, the development of a codominant Pita
marker is imperative to enhance molecular breeding
efficiency.
The BB resistance gene xa5 is also one of the most
used resistance genes in rice breeding programs. The
recessive resistance gene is preferable in gene pyramiding programs, as it provides a wide range of
resistance to different races by a different mechanism
(Li et al. 2012). The availability of an appropriate
marker system enhances the efficiency of a markerassisted breeding program. Though CAPS markers
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Table 2 List of diverse cultivars possessing Pi-ta resistance allele
S.
no.
IRGC
no.
Variety name
Source
country
S.
no.
IRGC no.
Variety name
Source
country
1
121034
Lal Bagdar
Bangladesh
29
121771
Jamajigi
Mali
2
121035
Lalbajam
Bangladesh
30
122093
IR22/Kulu
Philippines
3
121099
Ray Jazaykayz
Bhutan
31
121591
Peta/Tangkai Rotan
Philippines
4
121701
91-385
Bhutan
32
120984
China 1039 DWF MUT//IR3186864-2-3-3-3/Pinidua
Philippines
5
121161
Zalcha
Bhutan
33
120987
IR64 (WH)/Aday Sel//3IR64
Philippines
6
120972
Hong Zui Zao
China
34
121753
IR4432-53-33/PTB 33//IR36
Philippines
7
121111
San Ri Qi
China
35
121819
Safari
Portugal
8
121040
Liu Xu
China
36
121854
Was 207-B-B-3-1-1
Senegal
9
120861
Ai Lan Ke 1110
China
37
121849
Was 183-B-6-2-3
Senegal
10
121163
Zao Shou 691-11
China
38
121846
Was 169-B-B-4-2-1
Senegal
11
12
121145
120912
Tung Chiu Ai
China 98-45-1::IRGC
1598-1
China
China
39
40
121848
122284
Was 182-B-1-1
Was 170-B-B-1-1
Senegal
Senegal
13
120970
Hong Mi Dong Mao
Zhan
China
41
121011
Karayal
Sri Lanka
14
120925
Da Nuo
China
42
121153
Wanni Dahanala
Sri Lanka
15
121164
Zi Gan Nan Gu
China
43
117525
Madael
Sri Lanka
16
117280
Zhenshan 97B
China
44
121094
Race
Sri Lanka
17
121162
Zao Shao Zhan
China
45
121059
Motta Samba
Sri Lanka
18
19
117881
120979
Shai Kuh
P 738-137-4-1/
P 723-6-3-1
China
Ecuador
46
47
117848
121019
Peh Kuh
Khao Daw Tai
Taiwan
Thailand
20
120998
Jariyu
India
48
122179
Nam Sagui
Thailand
21
122258
Vasistha/Mahsuri
India
49
121662
Daw Leuang Nam Pueng 29-314::IRGC 24301-1
Thailand
22
117817
Garikasannavari
India
50
121642
Som Cau 70 A
Vietnam
23
117501
JC 92
India
51
117682
Chau
Vietnam
24
121418
Madhuri::IRGC
67730-1
India
52
117478
Gie 57
Vietnam
25
117880
Seratoes Hari
Indonesia
53
117589
Tetep
Vietnam
26
121990
Botramaitso
Madagascar
54
121599
Bat DO::IRGC 7014-1
Vietnam
27
121136
Telovolana
Madagascar
55
121919
Khau Muong Pieng::IRGC 78333-1
Vietnam
28
121811
Rojofotsy 693
Madagascar
have been reported (Iyer and McCouch 2007; Suh
et al. 2013), they need laborious additional steps in
comparison with simple PCR-based markers, such as
confirmation of PCR successive amplification and
digestion with a restriction enzyme of the specific
amplicons with incubation of 1–3 h for proper digestion of the amplicons, which requires more cost and
time.
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To overcome these limitations of using Pita and
xa5 markers, we have designed PCR-based codominant markers, targeting the functional polymorphism
of those genes. Also, care was taken to have at least a
100-bp difference between the amplicons so that those
amplicons could be separated in low-percentage
agarose gels in less time. The newly developed
molecular markers for Pita and xa5 genes differentiate
Mol Breeding (2015)35:129
the resistance and susceptible alleles and provide more
details on homozygous and heterozygous status of the
alleles without any restriction digestion. The Pita
marker, which targeted the well-established polymorphic SNP, was validated by comparing with the
reported dominant marker, which revealed that both
marker data were in agreement with each other (Bryan
et al. 2000; Jia et al. 2002). The xa5 marker has been
validated in the segregating population, which revealed that the genotype and phenotype data perfectly
co-segregated. In addition, co-segregation of the
newly developed marker for the xa5 gene and CAPS
marker (10603.T10Dw; Suh et al. 2013) was confirmed, which revealed that the newly developed
marker is accurate and reliable to use in molecular
breeding applications.
High-throughput marker technology is one of the
preferable choices in molecular marker-assisted rice
breeding programs. The reduction in time, cost, and
cumbersome molecular activity can lead to highthroughput screening of the marker. Gel electrophoresis is a time-consuming, cumbersome, and laborious
job, which is vulnerable to manual error. Recent
technology such as capillary electrophoresis facilitates
screening of amplicons without gel electrophoresis.
This method is cheaper and saves significant time and
energy compared with gel electrophoresis in the long
run. We have demonstrated the applicability of the
newly developed markers in recent technology—
capillary electrophoresis, using Fragment Analyzer
(Ames, Iowa, USA). This experiment clearly differentiated the resistance and susceptible alleles and the
homozygous and heterozygous status of the alleles.
The rice varieties, which were collected from 32
different countries, were screened with the newly
developed markers as well as available markers for
Pita and xa5 genes. This experiment not only revealed
the agreement among the new and available markers
but also revealed 55 genotypes as new sources of Pita
resistance alleles. In a previous study, with Pita
resistance alleles evaluated in 141 rice varieties using
Pita dominant markers, 20 rice accessions possessed
Pita resistance alleles (Wang et al. 2007). However,
the authors used four pairs of markers to screen the
Pita allele-specific to resistance and susceptibility
independently. In the present study, a wide range of
rice varieties was assessed with a single codominant
marker set that detected the presence of Pita and pita
alleles.
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129
Among the 260 diverse rice varieties, the highest
number of entries (36) came from the Philippines,
followed by China (32) and India (28). The Pita alleles
were identified from 55 different cultivars of 15
different countries out of 260 cultivars from 32 countries. The highest number of Pita resistance alleles was
found from cultivars collected from China (13), followed by Vietnam (6) and the Philippines (5). Among
the analyzed cultivars, it was revealed that, though the
Pita resistance alleles were accumulated in Asian
countries, the Pita alleles were distributed throughout
the world, including Africa and South America
(Table 2; Supplementary Fig. 2). This experiment
indicates that the Pita gene might have originated long
ago in Asia and migrated to different parts of the world.
As it is found in a wide range of cultivars, it should be an
important resistance gene that may provide a wide
spectrum of resistance against various blast isolates
(Wang et al. 2008). Moreover, the identified novel Pitaresistant cultivars can be validated and used in blast
resistance breeding programs, and also these novel Pita
alleles open the way for an intensive Pita allele mining
strategy (Ramkumar et al. 2014). The evaluation of xa5
gene-specific alleles reveals that all the diverse materials
have the susceptible Xa5 allele, indicating either its
limited distribution or that it originated recently. Earlier
studies reported that the xa5 resistance allele is limited
to the Aus-Boro group, originating from Bangladesh
and Nepal (Garris et al. 2003; Iyer and McCouch 2007).
Phenotypic screening of diverse cultivars for BB
resistance revealed that most of the cultivars’ phenotype
reaction was in agreement with the genotype of the
respective cultivars. However, 68 cultivars showed
resistance against race 9A, while the marker revealed
those cultivars to have the susceptible Xa5 allele. This
can be explained by the resistance of those exceptional
cultivars perhaps coming from other BB resistance
genes such as Xa21, as race 9A is incompatible with
Xa21. Moreover, the disease reaction pattern of race 9A
with recently identified known resistance genes is
unknown (IRRI 2006). In addition, as the cultivars are
highly diverse, there is a strong possibility that they may
possess novel kinds of genes with disease resistance to
BB pathotypes.
Although the Pita and xa5 genes are used in many
gene pyramiding breeding programs, simple and
appropriate PCR-based codominant markers have
not been reported until this study. Unlike the available
dominant and CAPS markers, the newly developed
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Page 10 of 11
Mol Breeding (2015)35:129
PCR-based codominant Pita and xa5 markers could
differentiate resistant and susceptible genotypes without any further restriction digestion and they provide
more details on the homozygous and heterozygous
status of the alleles. Our study has validated the newly
developed molecular markers in segregating populations, and high-throughput genotyping has also
demonstrated using capillary electrophoresis. The
presence of Pita alleles in diverse rice varieties was
analyzed, and novel Pita resistance sources were
revealed. The cultivars possessing the identified Pitagene-specific allele can be used in resistance breeding
programs. The identified cultivars with BB resistance
to race 9A can be analyzed further to identify novel
BB resistance genes. We strongly believe that the
newly developed Pita and xa5 markers will immensely help molecular breeders to track the targeted Pita
and xa5 gene-specific alleles using a more convenient
and simpler method in blast and bacterial leaf blight
resistance breeding programs.
Acknowledgments We are grateful to the Global Rice
Science Partnership (GRiSP) program of IRRI for financially
supporting this project. We thank Bill Hardy for editing the
manuscript.
Conflict of interest
The authors declare no conflict of interest.
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