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16th - 17th November 2015
Clermont-Ferrand, FranceInternational
Wheat
Innovation
Workshop
Genomic selection in a real
wheat breeding programmes
Gilles Charmet – INRA UMR GDEC
Jérôme Auzanneau, Ari-Obtentions
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Wheat in France: a strategic crop
Breeding goals-high yield
-Lodging tolerance
-Disease resistance
-Protein content
-High test weight
-High bread making grade
40000 hectares organic
farming
Average yield: ~7.5 t/ha
9 t/ha Pas de Calais
5 t/ha Gers
~5 millions hectares
« conventionnal
farming »
On average 6.3 pesticide
Tilling (55%), No-till
(45%)
# 165 kg/ha mineral N
DURUM
Worldwide ranking 5th (1st in EU)2015 highest harvest: 40.8 Mt on 5.1 Mha
average yield 7.9 t/ha)
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Typical wheat breeding scheme: long cycles
F1
F2
F3
F4
F5
F6
F7
F8
F9
lines
10
years
Crosses: 10²
105
104
103
102
101
100
F2 bulks
F3 bulks
REGISTRATION
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Typical wheat breeding scheme:
Crosses: 10²
105
104
103
102
101
100
F2 bulks
F3 bulks
Experiment /traits
Loc No remarks
Single plantsVisual trait
One Low h²# random selection
1-3 rowsVisual+diseases
1-2 Negative selection of worse rows/plants
Yield plots¨%protein
2-3, 1 rep
Low h²
Yield plot % protIndirect Q test
5-82-4 rep
Accurate yield evaluation+ GxL
Yield plot % protBread making
8-104 reps
Accurate yield + BM tests + G x Y
Official registration trials
12-15 4 repsT NT,LI
2 year official trialsBM test on year 1 harvest
(Relatively) inefficient for complextraits in early generations
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Genomic selection: how does it work
BWGS pipeline V2.0: General structure
Dimentional
reduction
Dimentional
reduction
Imputation of
genotypes
Imputation
Comparison
of models
(cross-
validation)
Optimal
models GEBV
Training
genotypic
data
Training
phenotypic
data
Target
phenotypic
data
Cor (y, GEBV)
MSEP, SD
(yhat)Cor (y, GEBV)
bwgs.selgen.cv(…)
bwgs.predict(…)
quality indicators
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Advantages of GS over phenotypic selection
DG = i h sG / L
Selection intensity: Can be increased if Genotyping cost < phenotyping
Cycle length: can beShortenned by juvenilSelection and intermating
h or prediction accuracyGenetic variability: can bemonitored by markers
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Where to insert GS in a wheat breeding scheme ?
Where to insert GS in a wheat
breeding scheme ?
Crosses: 10²
105
104
103
102
101
100
F2 bulks
F3 bulks
REGISTRATION
DG = i h sG / L
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Propose new schemes
Crosses: 10²
105
104
103
102
101
100
F2 bulks
F3 bulks
REGISTRATION
DG = i h sG / L
Select parents
crosses
F2 or DH
Apply GS
2-3 yearsCycles
GS
Adapted from J HickeyEUCARPIA Biometrics in Plant Breeding 2015
Use historicaldata for training
Select parents on GEBV per se of expected
progeny BV
Re-invent short cycle Recurrent selection
An application to INRA-AO real winterwheat breeding programme:
Preliminary results
Jérôme AUZANNEAU
AGRI OBTENTIONS
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Genotyping: The BW420K SNP Axiom chip
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Use of historical dataCrossa et al 2010, Dawson et al 2013, Rutkoski et al 2015)
• Yield, protein: 35 298 records/ 1589 lines (760 Genotyped)• Fusarium HB: 27 135 records, 1705 lines (672 G)• Bread-making traits: 5887records / 526 lines (357 G)
F7 issued in 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
year of trial
2002 F7: 184
2003 F8: 64 F7: 186
2004 F9: 4 F8: 72 F7: 221
2005 F9: 6 F8: 93 168
2006 F9: 11 72 161
2007 8 65 183
2008 5 77 176
2009 7 66 172
2010 8 54 176
2011 4 56 178
2012 6 66 147
2013 8 73 177
2014 9 88 176
2015 ? ?
BLUE lmer(Y~geno+(1|year:site:trial:bloc)+(1|year:site:geno),data=…)
BLUP lmer(Y~(1|year:site:trial:bloc)+(1|geno)+(1|year:site:geno),data=Y)
Cor (YieldBLUP, YieldBLUE)=0.97
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Heritability and prediction accuracy
(GBLUP – 10 000 random markers)
TRAIT h² = s2G/(s2G+s2
GE+s2
e) r = cor(GEBV, y) r/sqrt(h²)
Yield and protein %:
Yield 0,307 0,558 1,007
Protein 0,513 0,557 0,778
Alveograph:
dough strength W 0,705 0,536 0,638
tenacity P 0,757 0,622 0,715
extensibility L 0,564 0,574 0,764
P / L 0,062 0,301 1,209
Bread making
dough score 0,392 0,404 0,645
crumb score 0,371 0,448 0,736
bread score 0,275 0,405 0,772
total score 0,433 0,452 0,687
loaf volume 0,44 0,427 0,644
Other:
heading date 0,787 0,38 0,428
plant height 0,296 0,353 0,649
hagberg FN 0,505 0,427 0,601
dietary fibre (visco) 0,908 0,68 0,714
Fusarium HB score 0,563 0,63 0,84
GS accuracy is good enough for most traits to enable genetic progress
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Comparing accuracy among methods
Yield, N=760, 10 000 markersMETHOD r = cor(GEBV, y)
MKRKHS 0.5698 a
RKHS 0.5688 a
Bayesian LASSO 0.5646 a
RF regression 0.5628 a
Bayes B 0.5618 a
EGBLUP 0.5606 a
Bayes A 0.5560 a b
Bayes C(p) 0.5514 a b
Bayesian RR 0.5508 a b
GBLUP 0.5452 b
LASSO 0.5316 b
Elastic net 0.5282 b
SVM 0.2882 c
NK homogeneous groups
Various prediction methods giveconsistent results: GS is robust
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Application to real breeding linesDoubled haploïde production from 14 crosses (1000 DH)Year 1
CTPS1
Genotyping (WP1)
2nd generation crosses
Genomic
Selection
DH production
Phenotypic
Selection
Genotyping WP1
Genomic
Selection
2
3
4
5
6
7
8
Yie
ld:
Tre
ate
d v
s
Un
tre
ate
d
Yield + quality test
(7 to 9 locations)
CTPS2
registration
?
CTPS1
Yie
ld:
Tre
ate
d v
s
Un
tre
ate
d
Yiled + quality test
(7 to 9 locations)
CTPS2
regisration
?Phenotypic
Selection
(Classic selection)
1st cylcle of GSY
iled
:
Tre
ate
d v
s
Un
tre
ate
d
Yield + quality test
(7 to 9 locations)
2nd cycles of
GS
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Phenotypic selection
DH
• 1600 haploid plantlets from 14 crosses
• Seed X: 990 DH with > 30 seeds
Nursery
• 990 rows, inoculation Yellow rust
• 140 lines selected
Yield
• Nursery + unreplicated plots x 3 loc
• 35 best lines selected for comparison
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Genomic selection
DNA
• 990 DH lines genotyped with BW420K
• 188 000 polymorphic SNP
training
• Training set = 760 historical lines
• GEBV with GBLUP
GEBV
• Selection on GEBV for yield in H/L input
• 30/990 or 10 /140 for comparison
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
2014 – 2015 Comparison on trials
Qx / ha % Tem Qx / ha % Tem Qx / ha % Tem
Min 72,8 75,8 36,8 45,1 57,7 63,4
Max 98,6 103,6 85,5 104,7 92 103,6
Mean 86,3 89,7 70,1 85,9 78,2 87,8
Genomic selection
Treated Untreated Treated + Untreated
Qx / ha % Tem Qx / ha % Tem Qx / ha % Tem
Min 87,3 89,7 65,6 80,5 79 87,7
Max 106,6 109,5 89,2 109,5 97,9 109,5
Mean 94,4 97,3 75,9 93,1 85,2 95,2
Treated + Untreated
Phenotypic selection
Treated Untreated
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
PS vs GS comparison: top lines
PS only
PS x GS
GS only 30/990
GS only 10/140
line %Tem moy T+NT %Tem T % Tem NT line %Tem moy T+NT %Tem T % Tem NT line %Tem moy T+NT %Tem T % Tem NT
09BH040H047 109,5 109,5 109,5 AREZZO 96,3 97,8 94,9 09BH032H071 90,2 93,8 86,6
09BH025H051 106,1 104,6 107,6 09BH009H020 96,3 98,3 94,2 09BH019H026 89,9 93,2 86,6
RUBISKO 104,8 104,2 105,4 09BH032H013 96,2 96,0 96,5 09BH007H054 89,4 94,3 84,4
RUBISKO 104,4 103,2 105,7 09BH032H024 96,0 99,4 92,6 09BH032H066 89,3 97,3 81,3
09BH007H065 103,6 102,6 104,7 09BH019H048 95,4 101,8 89,0 09BH039H027 89,1 96,2 82,0
CELLULE 102,4 101,8 103,0 AREZZO 94,8 97,1 92,5 09BH009H032 89,1 90,9 87,2
CELLULE 101,8 100,3 103,2 09BH032H031 94,8 94,1 95,5 09BH009H001 88,7 88,5 88,8
09BH018H017 101,1 101,9 100,3 09BH032H006 94,8 94,8 94,7 09BH009H035 88,6 89,7 87,4
09BH040H076 100,9 100,5 101,3 09BH007H043 94,6 93,1 96,2 09BH006H074 88,1 90,7 85,5
09BH002H065 99,1 97,0 101,3 09BH025H030 94,4 91,9 97,0 09BH038H039 87,7 94,9 80,5
09BH037H013 99,0 99,6 98,4 09BH039H029 94,4 97,7 91,1 09BH007H023 86,7 84,8 88,6
09BH002H062 98,9 98,2 99,7 09BH032H043 94,0 91,3 96,7 09BH009H036 85,2 90,4 79,9
BERMUDE 98,7 98,4 98,9 09BH038H001 93,9 99,5 88,4 09BH009H075 84,9 86,1 83,7
09BH002H001 98,3 94,7 102,0 09BH032H039 92,7 95,9 89,5 09BH009H081 83,0 81,1 84,9
09BH040H026 98,3 99,3 97,3 09BH006H066 92,6 89,7 95,6 09BH025H015 82,2 82,0 82,4
09BH019H024 98,0 101,2 94,7 09BH007H074 92,0 102,8 81,3 09BH006H047 81,5 86,8 76,3
09BH009H079 96,9 96,9 97,0 09BH009H007 91,6 92,3 91,0 09BH009H063 79,8 79,3 80,3
09BH019H016 96,9 97,7 96,1 09BH002H047 91,4 92,9 89,9 09BH009H078 79,5 83,1 75,9
09BH019H034 96,9 99,0 94,8 09BH019H045 91,1 97,3 84,8 09BH009H028 76,9 75,8 78,0
BERMUDE 96,9 97,3 96,5 09BH018H050 90,9 94,9 86,8 09BH025H067 67,8 77,1 58,5
09BH032H004 96,8 98,1 95,4 09BH009H054 90,5 88,3 92,7 09BH002H071 63,4 81,7 45,1
International Wheat Innovation Workshop - 16th & 17th November 2015 - Clermont-Ferrand, France
Take home messages
• Marker coverage in large enough in Breeding pop
• Historical data are powerful for training
• GEBV are accurate enoughto enable efficient GS
• Variuos prediction modelsgive consistent results
• First field comparisons are encouraging
• Cost of genotyping: stillunafordable on 105
candidates
• New schemes to be explored
• Maintainance of accuracyacross # germplasms?
• Multiple traits MUST beconsidered
• GxE and multitrait methods to be further developped (e.g.
Jarquin et al 2014, Heslot et al 2014)
Aknowledgements
Van Giang Tran INRA for BWGS pipeline programmingJérôme Auzanneau AO for field experiments and data analyses
All partners in BW-WP4 for helpful discussion
THANK YOU FOR YOUR ATTENTION