pag xxii 2014 – genomic resources applied to marker-assisted breeding in cowpeas – bl huynh
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Genomic resources applied to marker-assisted breeding in cowpea
GCP Tropical Legumes 1: “Improve cowpea productivity for marginal environments in sub-Saharan Africa”
Philip Roberts, Timothy Close, Bao Lam Huynh
Mitchell Lucas, Arsenio Ndeve, Steve Wanamaker – UC Riverside
Ousmane Boukar, Christian Fatokun, Sam Ofodile – IITA, Nigeria
Ndiaga Cisse, Penda Sarr – ISRA, Senegal
Issa Drabo, Jean-Baptiste Tignegre – INERA, Burkina Faso
Rogerio Chiulele – E. Mondlane U, Mozambique
Batieno T. Benoît Joseph – WACCI, Ghana
Ndeye N. Diop, Xavier Delannay et al. – IBP, CIMMYT, Mexico
PAG XXII – GCP Workshop, Jan 2014
Cowpea – Vigna unguiculata
• Tropical legume.
• Nutritious, high-protein food.
• Major food crop in sub-Saharan Africa.
• Nitrogen fixation to enrich soil fertility.
• Tolerance to drought, heat, poor soils.
Yard-long bean/asparagus bean
Blackeye bean
Diverse seed types
Cowpea production zones in Africa
200mm
800mm ISRA INERA
IITA
EMU
200mm
800mm
Yield constraints
Seedling Flowering Pod filling Post-harvest
Aphids Flower thrips
Drought
Pod-sucking bugs
Striga
Root-knot nematodes
Weevils
Heat
African cowpea varieties yield ~20% of potential
Pod borer
Macrophomina
Bacterial blight
Viruses
Genetic variation – basis for QTL discovery and marker-assisted breeding
Heat
Striga
Root-knot
nematodes
Aphid
T S
R
S R S
R S
Jean-Baptiste, Burkina Faso
V1: 2009 PNAS 106:18159-18164
V4: 2011 Plant Genome 4:218-225
V6: 2013 http://harvest.ucr.edu/
QTLs for biotic and abiotic traits
Cowpea consensus genetic map
LG1 LG2 LG3 LG4 LG5 LG6 LG7 LG8 LG9 LG10 LG11
11 RIL populations, 1091 SNPs, 815 bins, 680 cM
1536 SNPs
> 400 accessions from Africa and the world
SNP TVu-9522 TVu-9556 TVu-9557 TVu-9620 TVu-9651 TVu-969 TVu-972 TVu-9749 TVu-9761 TVu-9801 TVu-9820
1_1431 GG GG GG GG GG AA GG GG GG AA AA
1_0721 CC CC CC CC CC CC CC CC CC CC CC
1_1392 GG GG GG GG GG GG GG GG GG GG GG
1_1157 AA AA AA AA AA AA AA AA AA GG GG
1_0595 GG GG GG GG CC CC CC CC CC CC CC
1_0741 AA AA AA AA AA AA GG AA AA AA AA
1_0482 GG CC CC GG CC CC GG CC CC GG GG
1_0791 AA AA AA AA AA AA GG AA AA GG GG
1_1490 GG GG GG GG GG GG CC GG GG GG GG
1_1033 GG GG GG GG GG GG AA GG GG GG AA
1_0144 GG GG GG GG GG GG AA GG GG AA AA
1_0328 GG GG GG GG GG GG GG GG GG GG AA
1_0240 CC CC CC CC CC CC CC CC CC CC CC
1_0985 AA TT TT TT TT AA AA TT AT AA AA
1_0041 GG GG AA GG GG AA GG GG GG GG GG
1_1470 AA AA AA AA AA AA AA AA AA GG GG
1_1535 GG GG GG GG GG GG GG -- GG AA AA
1_1230 AA AA AA AA AA AA AA AA AA AA AA
1_1108 CC CC CC CC CC CC AA CC CC CC AA
1_0670 AA GG GG AA AA AA GG GG AG AA AA
SNP database for germplasm collection
2013 The Plant Genome 6(3)
BreedIt (breedit.org), GDMS (IBP tool, ICRISAT)
Select informative SNPs for a MAS project Consensus map SNP genotypes of parents SNPs selected for MAS QTL
Selection Crossing Planting
New genotyping
1 2 3
4
5 6 7
8
SNP genotyping (KASP platform-LGC Genomics)
Employ marker-assisted backcrossing (MABC) to improve local cowpea varieties
Country 11 MABC populations (Recurrent/Donor) Main donor Traits
Nigeria IT93K-452-1/IT97K-499-35 IT89KD-288/IT97K-499-35 SuVita 2/IT97K-499-35
Striga Striga Drought, Striga
Burkina Faso Moussa/IT93K-693-2 KVX745-11P/KVX414-22
Striga Striga, Large Seed
Senegal Melakh/IT97K-499-39 Striga
Mozambique IT85F-3139/CB27 CB27/INIA-41
Large seed, Heat Nematode, Drought
USA/ Mozambique
CB27/IT97K-556-6 CB46/IT97K-556-6 CB50/IT97K-556-6
Aphid
MABC example – Aphid resistance
IT97K-556-6 (resistant)
Blackeyes (susceptible)
Aphid resistance screening
Big Buff
Recombinant inbred lines CB27 (S) x IT97K-556-6 (R)
R S
Big Buff
Kearney, CA
Aphid-resistance QTLs
LG1 LG2 LG3 LG4 LG5 LG6 LG7 LG8 LG9 LG10 LG11
Major QTL 66% phenotypic variance
Minor QTL 9% phenotypic variance
QTL IciMapping: http://www.isbreeding.net/
04 05 11 12 24 26 35 38 40 46 48 53 57 62 63 66 67 69 71 79 80 CB46A
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AB AB AA AB AA AB AB AB AB AB AB AB AB AA AB AB AB AB AB AB AB AA
AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AA
AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AA
AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AB AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AB AB AB AB AA AB AA AA AA AA AA AB AB AA AA AB AB AB AA AA AA AA
AA AB AB AB AA AA AB AA AB AA AA AA AB AA AA AB AB AB AA AB AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AB AB AB AB AA AA AA AA AA AA AA AA AB AA AA AB AB AB AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AB AB AB AA AB AB AB AB AA AA AA AA AB AB AA AB AB AB AA AA
AB AA AB AA AB AA AB AB AB AB AA AA AA AA AB AB AB AB AB AB AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AB AB AA AB AB AA AB AB AA AA AB AA AA AA AA AB AB AA AB AA AA AA
AB AB AA AA AB AB AB AB AA AA AB AA AA AA AA AB AB AA AB AB AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA -- AA AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA AA
QTL introgression
2 3
4 5 6
1
BCnF1 plants Leaf sampling SNP genotyping
Backcrossing Background selection Foreground selection
Resistant genotypes
Resistant RIL x Recurrent P
Employ marker-assisted recurrent selection (MARS) to develop improved breeding lines P
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TL
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Lin
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Cycle 1
Multilocation phenotyping
Parent 1 × Parent 2 F1
F2
F3 Genotyping
Multilocation phenotyping
A B C D E F G H
F1 F1 F1 F1
F1 F1
F1
F2
F3
F3:4
QTL detection –estimate marker effects
Cycle 2
Cycle 3
4 populations Traits
Burkina Faso (Issa Drabo et al.)
Yield, Drought, Striga, Macrophomina
Nigeria (Ousmane Boukar et al.)
Earliness, Striga, Heat
Senegal (Ndiaga Cisse et al.)
Drought, Striga, Nematode, Macrophomina
Mozambique (Rogerio Chiulele et al.)
Heat, Large seed, Grain quality
Ideotype
Single seed descent
• Developed F2 from elite parents (Suvita 2, IT97K-499-35).
• Genotyped 300 F2s with 164 poly SNPs every 2 cM interval.
• Phenotyped F2:3 families
₋ Pobe (low-yielding site)
₋ Saria (high-yielding site)
Pope
Saria
Burkina Faso – MARS example
300 mm
1000 mm
QTL detection
VuLG1 VuLG2 VuLG3 VuLG4 VuLG5 VuLG6 VuLG7 VuLG8 VuLG9 VuLG10 VuLG11
Yield Yield
Yield Grain size
Grain size
Favorable alleles from IT97K-499-35
Favorable alleles from Suvita 2
QTL IciMapping: http://www.isbreeding.net/
Striga
YLD-4 YLD-6 YLD-8 GDW-3 GDW-11 Rsg 3
243 0.83 1.00 0.50 0.50 1.00 1.00 1.00 Yes
71 0.83 1.00 1.00 0.50 1.00 0.50 1.00 Yes
281 0.79 1.00 0.50 0.98 0.50 1.00 0.73 Yes
51 0.75 1.00 0.50 1.00 1.00 0.50 0.50 Yes
190 0.75 0.50 1.00 0.98 0.50 1.00 0.50 Yes
154 0.71 0.50 1.00 1.00 0.50 0.50 0.73 Yes
112 0.42 1.00 0.50 0.50 0.50 0.00 0.00 No
235 0.42 0.50 0.00 0.50 0.50 0.50 0.50 No
251 0.42 0.50 0.00 0.50 0.50 0.50 0.50 No
199 0.19 0.62 0.00 0.00 0.00 0.50 0.00 No
285 0.17 0.00 0.00 0.50 0.00 0.00 0.50 No
99 0.17 0.00 0.00 0.00 0.00 0.00 1.00 No
SelectedF2:3
family
Molecular
score
Yield QTLs Kernel-size QTLs
Select best families with OptiMAS (IBP tool, INRA)
The striga QTL is incorporated from prior publication 2002 Genome 45:787-793 (Ouédraogo et al.)
(Example list)
Striga
YLD-4 YLD-6 YLD-8 GDW-3 GDW-11 Rsg 3
71 F2 0.83 1.00 1.00 0.50 1.00 0.50 1.00
71-03 F4 0.92 1.00 1.00 0.50 1.00 1.00 1.00 Yes
71-02 F4 0.92 1.00 1.00 1.00 1.00 0.50 1.00 Yes
71-10 F4 0.92 1.00 1.00 1.00 1.00 0.50 1.00 Yes
71-01 F4 0.75 1.00 1.00 0.52 1.00 0.00 1.00 No
71-04 F4 0.75 1.00 1.00 0.00 1.00 0.50 1.00 No
71-05 F4 0.75 1.00 1.00 0.50 1.00 0.00 1.00 No
71-07 F4 0.67 1.00 1.00 0.00 1.00 0.00 1.00 No
SelectedPlant ID Cycle MSYield QTLs Kernel-size QTLs Plant Cycle 1_0853 1_0447 1_0146 1_0937 1_0031
2010-057-190 F2 GG GG AA GG GG
2010-057-190-01 F4 GG GG AA GG GG
2010-057-190-02 F4 GG -- AA -- GG
2010-057-190-03 F4 GG GG AA GG GG
2010-057-190-04 F4 GG GG AA GG GG
2010-057-190-05 F4 GA GC GA GC GA
2010-057-190-06 F4 GG GG AA GG GG
2010-057-190-07 F4 GG GG AA GG GG
2010-057-190-08 F4 GG GG AA GG GG
2010-057-190-09 F4 GG GG AA GG GG
2010-057-190-10 F4 GA GC GA GC GA
QTL combination
2 3
4 5 6
1
10 members per family/cross Leaf sampling KASP genotyping
Intercrossing OptiMAS to select best plants Outcrosses eliminated
OptiMAS summary: Frequency of favorable alleles at different selection steps in Burkina Faso MARS (on average and for each QTL)
P F1
F2
F4 F5
C1
C2
“Ideotype” Local check
Intercross to
recombine QTLs
Intercross progeny
MARS activities in Burkina Faso (Issa Drabo et al.)
Leaf sample
for genotyping
Acknowledgements University of California, Riverside
Roberts, Philip A.
Close, Timothy J.
Huynh, Bao Lam
Wanamaker, Steve
Lucas, Mitchell
Ndeve, Arsenio
Jansen Santos
Xu, Shizhong
Ehlers, Jeff D.
Diop, Ndeye N.
Muchero, Wellington
Pottorff, Marti
Hu, Zhiqiu
22
National Agricultural Research System (NARS)
Cisse, Ndiaga, ISRA-Senegal
Drabo, Issa, INERA-Burkina Faso
Tignegre, Jean-Baptiste, INERA-Burkina Faso
Joseph, Batieno T. Benoît – WACCI
Chiulele , Rogerio, EMU-Mozambique
International Inst. of Tropical Agriculture (IITA)
Boukar, Ousmane
Fatokun, Christian
Ofodile, Sam
LGC Genomics
Vyas, Darshna et al.
IBP-GCP
Delannay, Xavier et al.