Download Yield and protein content

E.P.S.O
Genetic improvement of wheat
quality for animal feeding
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
World cereal production and uses
• Wheat is the most widely grown
worldwide
• Its use for animal feeding is about
10% wordlwide, but 30% in Europe
Alim. animale
Semences
Alim. humaine
Exportations
Stock
Source : ONIC
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Animal feeding requirements
• Cereals are primarily a source of ENERGY (starch),
mostly for monogastics (unable to use cellulose). Animal
production (profitability) is correlated to
•Low cost = yield, low inputs
•High digestibility: problem of viscosity for poultry
• Protein content may be of interest (depending of the
price/availability of other sources): if not conflicting with
yield
• Protein quality (composition): lysin and methionin
• Mineral availability: phytase activity
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Yield and protein content
How to deal with the
(genetic) negative correlation
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
RENDEMENT-TENEUR EN PROTEINES SUR VALEURS MOYENNES
essais avec bles ameliorants
FERTILISATION N+: correlation = -0.83
FERTILISATION N: correlation = -0.85
Comparaison des 2 regressions : F(2,25) = 50 (P<0.001)
13
CF511
EC511
Courtot
12
CF503
EC511
CF511
EC506
EC513
Monopol
Renan
CF407
Qualital
Alidos
Busard
EC514
Courtot
11
EC514
EC513
EC506
Monopol
Alidos
Renan
Recital
CF407
Busard
Qualital
Soissons
Soissons
Recital
10
teneur en proteines (%)
14
CF503
70
75
NUTRITION
- FOOD
80
AGRICULTURE
rendement (q/ha)
E N V I R O N NM E N T
85
COMBINED INDEX SELECTION ON YIELD AND PROTEIN
Up to now, protein % has rarely been used as selection criterion.
Use of quantitative genetics tools to predict the expected response to
index selection with various economic weights W given to Yield vs
Protein
- Genetic material: breeding lines of INRA programme. Genetic
correlation -0.75
- Selection intensity = 20% (best lines crossed).
- Expected response to selection estimated from G and P
variance-covariance matrices. Gain = i * P-1 * G * W
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
SELECTION SUR RENDEMENT ET TENEUR EN PROTEINES
With current payment for extra-protein % (bread-wheat: 3€/T)
prise en compte des 2 caracteres dans un index de selection
Optimum economic weight leads to improve only yield (0.4T/cycle)
Scenario 1: prix de base = 90 E/t + 1.5 E par demi-point de proteines au-dela de 10.5%
Correlative
response of protein content is -0.4% per cycle
Gains a l'optimum: rendement = 0.53 proteines = -0.41 revenu = 39.2
gain attendu pour le revenu par hectare (optimum = 78)
40
0.4
80
poids du rendement dans
l'index de selection
0
40
Euros
0
20
-0.4
tonne/hectare
gain attendu pour le rendement
-20
0.4
-0.4
pourcent
gain attendu pour
la teneur en proteines
0
40
80
poids du rendement dans
l'index de selection
0
20NUTRITION
40 - FOOD60
AGRICULTURE
80
poids
donne
ENVIR
O N NMau
E Nrendement
T
dans l'index de selection
100
SELECTION SUR RENDEMENT ET TENEUR EN PROTEINES
To achieve a balanced response on both yield and protein content,
prise en compte des 2 caracteres dans un index de selection
Extra payment for protein should be 12€/T/%
2: prix de base = 90 E/t + 6 E par demi-point de proteines au-dela de 10.5%
Yet Scenario
the expected
response would be limited (0.25T/ha and 0.3% prot)
Gains a l'optimum: rendement = 0.12 proteines = 0.18 revenu = 31.1
25
poids du rendement dans
l'index de selection
-0.4
10
0.4
gain attendu pour
la teneur en proteines
20
80
15
40
Euros
0
pourcent
gain attendu pour le revenu par hectare (optimum = 50)
30
0.4
-0.4
tonne/hectare
gain attendu pour le rendement
0
40
80
poids du rendement dans
l'index de selection
0
20NUTRITION
40 - FOOD
60
AGRICULTURE
80
poids
E N V I donne
R O N NMau
E Nrendement
T
dans l'index de selection
100
How to conciliate
yield
and protein
INTER-STATIONS
1991-2002
(moyennes
sur aucontent?
moins 8 resultats)
Identification of breeding lines or cultivars with positive
seuil = 1.96 effectif = 54 ; coeff. de correlation = -0.71
grain
deviation
moyenne rdt = protein
91.9 moyenne
prot = 11.8 (GPD)
y = 21.06 + -0.101 x
CF99351
RE9209
VM9207
RE9201
CF99102
CF9107
RE9205
CF9309
RE9204
CF9103
CF99105
CF99075
12
EM99012
VM9203
CF9414
VM9209
VM9205
DI9714
RE9819
CF99031RE99017
DI9304
VM9014
CF00189
RE01002
EM00002
DI9812
CF99005
DI00024
DI00010
DI9404
CF9825
EM00015
EM00018
DI9403
DI9428
EM99006CF9621
EM99017
RE99001
CF9703
VM9516
RE99009
RE9707
CF9804 CF9717
11
apache
RE99003
RE99004
RE9510
RE9607
CF9608
VM9409
VM9517
isengrain
VM9510
VM9509
VM9401
VM9402
10
teneur en proteines (%)
13
CF00193
VM9202
VM9601
VM9601
80
85
90
NUTRITION - FOOD
AGRICULTURE
95
E N V I R O N NM E N T
rendement (q/ha)
100
DIGESTIBILITY
Problems with pentosan
viscosity in poultry
Genetics of cell walls
composition
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Factors affecting starch digestion
Starch granule structure
Protein matrix Access
problems
.
. . .. ... ... .. ......... ... .... Cell walls in particles
. . .. . . .. .. .... .
.. . ... . . .. . . ... . . . .
. . . .. .. ...... ... ... . . ... ..
.
. . .. . .. .... ................ ....... ..
Viscosity
. ..
..... . .. ...... . . . .
. . α-amylase
. . .. . . ..... ........ .. . .......... .. . . . ..... .
. . .. .
... . ......... .
.
.
.
.
.
.... ... . . .......... ... ... ..... .... . .
. . . . ....... ... . .. . . . .
Tannins
.
.. . .. .....
.
..
α-amylase inhibitors
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Effect of kernel hardness
Carré et al 2005, British poultry Sci 46:66-74
• Particle size ranges from ~500 µm (soft varieties) to
~900 µm (hard wheats).
• As expected, starch digestibility is negatively
correlated to grain hardness (r=-0.56)
• Consequently, Apparent Metabolisable Energy
(AMEN) is also negatively correlated
• However, grain hardness is strongly correlated to
pellet durability (r=0.84), which is often considered
as a desired trait to reduce food spillage
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Relationship between wheat starch digestibility
and particle size of wheat flours before pelleting
Starch digestibility
%
97
y = 95.5 - 0.41x ; R^2 = 0.42
95
93
91
89
87
0
2
4
6
8
10
% coarse particles (>1600 μ m)
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
After Carré et al. 2002
5 DS
Xmta9
Xfba393b
Xfbb238b
Xksud30
Xcdo412b
Xbcd1874
Xcdo1508
Xbcd450a
A major gene for
kernel hadness
Xbcd1103
Sourdille et al 1996 TAG
Xfbb100
Xbcd1670b
Xbcd1421
Xfba11a
Xcdo506
5 DL
0
10
20
30
40
r2 VALUE ( % )
50
60
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Effect of viscosity (RAV) of wheats (55% in diets) on
starch digestibility in 3 w. broiler chickens.
Digestibility %
90
Effect of wheat RAV:
P = 0.008
80
70
Assay 1
Assay 2
60
After Carré et al. 2002
0
1
2
3
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
RAV (mL/g DM)
Problems with viscosity in birds diet
• A high dietary viscosity reduces the
digestibility of the various components
• Causes inflammation of the intestinal mucosa,
and induces over-consumption of water in
birds (Carré et al, 1994).
• This over-consumption leads to more aqueous
excreta which exacerbate both sanitary and
environmental pollution problems (Carré et al,
1995).
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Arabinoxylans and β-D-glucans are the major
components of wheat endosperm cell walls and
have impacts on processing and nutrition
% cell wall
arabinoxylan
70
(1→3)(1→4)β-glucan
20
glucomannan
2-7
cellulose
2-4
ferulic acid
X-X-X-X–X
AA
A
A A A
F
X X X
•
•
are polymers of Mr 104-106
•
•
•
have high affinity for water
•
F
A
Cell wall fibre
A
A
X
occur in water-soluble and
water insoluble (ferulic acid
cross-linked) forms
form viscous solutions
affect intestinal absorption of
lipids
have other effects on colon
bacteria and composition
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
60
50
40
30
20
10
0
Fréquence
30
Fréquence
20
10
s.
..
pl
u
ou
0.
54
0.
47
0.
41
0.
35
60
50
40
30
20
10
0
Flour TAXI equivalents (ppm)1
s.
..
pl
u
ou
0.
13
41
0.
10
83
0.
08
25
0.
05
67
Fréquence
0.
03
09
0.
00
51
ou
pl
u
s.
..
10
0.
8
85
69
.2
53
.4
Fréquence
A/X in WE-AX
Fréquence
37
.6
0.
28
5
0.
22
ou
pl
u
s.
..
1.
17
9
0.
97
8
0.
77
6
0.
57
5
40
35
30
25
20
15
10
5
0
21
.8
40
0
WE-AX (% )
Fréquence
Fréquence
50
0.
37
0.
17
Fréquence
Range of variation in bread wheat
core- collection
Flour Xylanase activity (EU/g)
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
INTER-STATIONS 1999
4.5
Choice of two contrasted breeding
lines
to develop doubled haploids
effectif = 33
r2 = 0.87
moyenne
x = 3.1= 0.87,
moyenne
y = 2.5 high h²
NB r² between
years
means
3.5
RE99018
DI9714
DI9812
3.0
CF99003
RE9819
EM99006
CF99031
CF9804
CF99027
EM99003
2.0
2.5
CF9825
AO99001
EM99027
EM99002
EM99001
CF99009
RE99016
Soissons
RE99009
1.5
viscosite potentielle Le Moulon
4.0
CF99007
h² estimates
0.75 +-0.10
Martinant et al 1999
J Cereal Sc 30:45-48
CF99016
EM99017
RE99001
RE99002
CF99005
RE99004
EM99021
CF9717
EM99012
RE99007
RE99014
RE99003
RE99006
2.0
2.5
3.0
- FOOD
3.5 NUTRITION4.0
AGRICULTURE
viscosite potentielleEClermont
N V I R O N NM E N T
4.5
5.0
POPULATION RE99006 x CF99007 (annee 2003)
40
Distribution of potential viscosity in R6C7 DH population (harvest 2004)
0
10
CF99007
RE99006
20
30
DNAchip hybridization to
find differentially expressed
ESTs between high vs low
pentonan lines
1
2
NUTRITION
- FOOD
3
AGRICULTURE
viscosite potentielle
E N V I R O N NM E N T
4
1B
1B
QTL analyses
7A
gpw2067d**
16.1
gwm260
gwm413
18
10
37
9
19
gwm456**
gwm131a
cfa2028
gwm060
39
gpw2233
gwm403a
17
18.8
gwm233
SPA (GluB1)
39
23.2
gwm268**
gwm471
18
cfa2219
20.5
7.9
13.9
gpw1077**
cfa2292***
gwm259**
gwm063
viscosity
r²=18%
28.5
cfa2019
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
viscosity
h²=18%
Search for candidate genes of
endosperm cell wall composition
►
UDP - D - Gal
GAE
UDP - D - Glc
UGD
UDP - D - GlcA
UXS
UDP - D - GlcA
AXS
UXS
UDP - D - Api
UDP - D - Xyl
UDP - D - Xyl
Phenylalanine
or tyrosine
Caffeoyl CoA
Lignin
pathway
XS
UXE
CCoAOMT
UDP - L - Ara
COMT
Feruloyl CoA
?
Feruloyl Glc
FCoApSFt
Xylan
AT
AX
?
CCR
Conifer
aldehyde
Peroxidases
ME
Conifer aldehyde
Dehydro
genase
?
Ferulic
acid
F - AX
Golgi
F - AX
Cytoplasm
Cell wall
Figure 1. An overview of the pathway of AX synthesis in plant (from P.E. Sado). GT involved in this pathway
are in pink boxes. Enzymes involved in early step of the AX synthesis and studied are in yellow boxes.
NUTRITION - FOOD
Epimerases studied in the year 1 are not represented.
AGRICULTURE
E N V I R O N NM E N T
Identification of candidate genes involved in arabinoxylans (AX) biosynthesis
Find matching EST contigs (eventually assignation NSF)
Design of specific primers
Assignation in deletion bin of CS
Polymorphism between parents of populations
Genes mapping and/or Difference in gene expression
Allelic variant in core collection
NUTRITION
- FOOD
Association SNP polymorphism / trait
variation
for validation
AGRICULTURE
E N V I R O N NM E N T
Candidate genes on
chromosome
7A
7A
gwm260
18
10
Assignation on the deletion bin of CS
cfa2028
gwm060
39
gpw2233
17
gwm233
39
gwm471
gwm063
28.5
4 genes in the bin C7AL1-0.39
QTL
ITMI
7 genes in the bin AL-0.39-0.71
viscosity
h²=18%
cfa2019
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
COMT
GT14
Epi7
GH28
Nepi7-1
GH17
TT1
Nepi7-2a
Nepi7-2b
NEpi7-3
GH16
Genome and allele specific markers
► Design of specific allele primers for genotyping HG core-collection
Allele 1 primer
Allele 2 primer
► PCR on HG core-collection
SNP1
SNP2
With allele 1 primer
HGW32
SNP used to genotype HG collection
With allele 2 primer
HGW32
Amplification = Allele 1
HGW47
No amplification = Allele 1
HGW47
NUTRITION - FOOD
AGRICULTURE
No amplification = Allele 2
E N V I R O NAmplification
NM E N T
= Allele 2
post GENOMICS
(Perfect) Marker Assisted
Selection
Inducing new variation
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Bioavailability of
minerals
Phytic acid and phytasic
activity
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Genotype and environment main effects on
mineral content (ANOVA: F values)
ASG-2
IS
Df
Yield
Magnesium
Zinc
Iron
Year
2
5.9 **
5.5 *
1.7 NS
6.6 **
Génotype
10
7.7 ****
13.7 ****
3.1 *
2.1 NS
Error
20
Location
2
708 ****
71.8 ****
95.4 **** 28.1 ****
Génotype
50
3.2 ****
4.8 ****
2.8 ****
Error
100
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
1.4 NS
RELATIONSHIP BETWEEN THE 3 MINERALS CONTENTS
Relationship
between the 3 minerals contents
1000
40
34
28
CF99351
DI02008
CF99102
DI02006CF00193
CF01196
CF99105
EM01024
RE01086
Soissons
EM01288
RE01092
RE01037
EM99006
CF00108
CF01216
RE99132
EM01216
EM01328 CF00060 DI01016
EM00018 EM01063CF99005EM01150
CF00116
CF01184
DI02001
EM01325
RE02101
EM01271
EM00074
DI01022
EM00264
DI00010
EM01324
DI02028
CF01085
RE01015
CF01043
EM00107
RE01002DI02032 EM99017
EM00072
EM01023
DI02021
DI00024EM01062
1200
EM01214
EM00002
800
1000
magnesium content (ppm)
magnesium content (ppm)
34
40
n = 51
correlation = 0.53 ****
Fe = 15.858 + 0.921 * Zn
28
800
iron content (ppm)
22
EM01024
CF99351
CF01196
CF00193 CF99102
DI01016 CF01184
EM01325 EM01328
EM01288
EM99006
DI02008
CF99105
CF01216
CF00108
EM01150
RE99132
EM01023
EM00107
CF00060
DI02006
CF00116
Soissons
EM99017
CF01043
EM00072
DI02028
EM00264
EM01062
DI01022
EM00074
CF99005
RE01037
EM01216 EM01271
RE01092
RE01086
EM01214
EM00002
RE01002
CF01085
EM00018
DI00024
RE02101EM01324
EM01063
DI00010
RE01015
DI02021
DI02032
iron content (ppm)
n = 51
correlation = 0.49 ***
Fe = 19.629 + 0.015 * Mg
DI02001
16
zinc content (ppm)
n = 51
correlation = 0.64 ****
Zn = 9.03 + 0.011 * Mg
DI02008 CF99351
CF99102
CF00193
EM01214
DI02006
CF99105 CF01196
EM01024
RE01086
Soissons
EM01288
RE01092
RE01037
EM99006
CF00108
CF01216
RE99132
EM01216
EM01328
CF00060
DI01016
EM00018
CF99005
CF00116
CF01184
EM01150 EM01325
EM01063
RE02101
EM01271
EM00074
DI01022
EM00264
DI00010
EM01324
DI02028
CF01085
RE01015
CF01043
EM00107
EM99017
RE01002
EM00072
DI02032
EM01023
DI02021 DI00024EM01062
DI02001
EM00002
16
18
20
- FOOD
22 NUTRITION
24
26
AGRICULTURE
zinc content (ppm)
E N V I R O N NM E N T
1200
RANGE OF VARIATION OF MODERN LINES VERSUS COLLECTIONS
Range of variation of modern lines vs collections
BdDAMAR
JF-H4
50
modern lines
YUKICHABO
BGW 76
JF-H4
TIBET26
40
NSA-1
BNChinois
TEZ.PINTOSp
BGW-76
CARALA
BdDomes
US67115 Mexique11
Azteca67
CARALA
EXCELSIOR YUKICHABO
30
NSA-1
Soissons
CHARTER
BdPOLOGNEr
BdDAMAR
CONSUL
LOVRIN25
BINGZHOU95-18
BGW76
Azakaze-K
Mexique11
Apache
Vilmorin27
THATCHER
BdDAMAR
EAP63A
BANKUTI1201
BdDomes
KLEIN66
BUCK-ATL.
Azteca67
Mexique11
EAP63A
TEZ.PINTOSp
MARQUILLO
BdPOLOGNEr
BGW-76 CHARTER
YANFU188
FRONTEIRA
COMANCHES
Azteca67
BANKUTI1201
BGW-76
Bezostaia1
TEZ.PINTOZp
STARING~GB
THATCHER
LAURA EXCELSIOR
RdSABANDO
KLEIN66
FERTODI293
20
zinc content (ppm)
NSA-1
BdDomes
600
800
1000
1200
NUTRITION
- FOOD
1400
1600
AGRICULTURE
magnesium content
E N (ppm)
V I R O N NM E N T
1800
BUCK-ATL.
2000
CONCLUSIONS
• The genetic variability appears to be high for Mg, Zn
and Fe, even in modern cultivars
– experimental cross CF99102 (high-MG) x EM01216 (lowMg)
• Heritability is hiigh for MG, moderate for Zn and low
for Fe, fortunately all these cations are positively
correlated (also with toxic ones?)
• Genetic resources with high mineral content are often
exotic, unadapted lines or old landraces.
– Advanced backcross population developped from Apache
(recurrent) x Azteca67
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Bio-accessibility of Mg in bran:
genetic variability
100
Mg solubilisé
(en % de la teneur totale)
Taldor
(Crouel 2000)
Uli 3 (Allier 2000)
Supersoft
BNC
1999
Sponsor
50
Aligre
(C00)
(Ménétrol 2001)
Bonpain
(M01)
Scipion
(M01)
Soissons
0
0
20
40
60
NUTRITION - FOOD
Duration of solubilisation
(min)
AGRICULTURE
From F. Lenhardt, J. Abecassis
E N V I R O N NM E N T
80
(M01)
(M01)
Problems with Phosphorus in animal feeds
• A total of 50-70% of grain phosphorus is in the form of
phytic acid phosphorus (Reddy et al, 1982).
• This phytic acid phosphorus cannot be used by
monogastric animals (Sauveur, 1989; Pointillart, 1994).
• In consequence, the phytic acid phosphorus is not available
and therefore contributes to the pollution of surface water.
• Wheat, however, contains plant phytase whose activity
varies depending on the variety (Sauveur, 1989; BarrierGuillot et al, 1996a and b).
• This phytase is activated during digestion and liberates a
substantial amount of the grain phosphorus (Frapin and
Nys, 1993).
• A high phytase activity is, therefore, to be sought after in
wheat
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Phytase activity in Triticale
Cultivar
n
Phytasic activity, UP / kg a
DI34-2
4
1012 ± 102 a
Aubrac
6
1320 ± 87 b
Trimaran
6
1424 ± 125 b
Capitale
4
1815 ± 126 c
Calao
6
2146 ± 145 d
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
A low phytic acid mutant in maize
(lpa241)
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Carotenoid Pathway
IPP
βLCY
Lycopene
GGPP
y1
βLCY
εLCY
PSY
Phytoene
vp5
PDS
Phytofluene
2x
ζ- carotene
vp9
β-carotene
OH
β-cryptoxantin
α-carotene
OH
OH
ZDS
Neurosporene 2x
OH
Zeaxanthin
OH
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T
Lutein
Contributions from
• G Charmet, FX Oury UMR1095 Plant Genetics
and breeding Clermont-Ferrand F
• B Carré et al, Poultry Research Unit, Nouzilly F
• L Saulnier et al, UMR Biopolymers Nantes F
NUTRITION - FOOD
AGRICULTURE
E N V I R O N NM E N T