GRM 2011: Improving cowpea productivity in Africa - J Ehlers

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GRM 2011: Improving cowpea productivity in Africa - J Ehlers

  1. 1. Phase II Activities and HighlightsTropical Legume 1: Objective 2Improving cowpea productivity for marginalenvironments in AfricaJeff Ehlers, Phil Roberts, Tim Close, Zhiqiu Hu - UC RiversideNdiaga Cisse, ISRA SenegalIssa Drabo, Jean-Baptist Tignegre - INERA, Burkina FasoRogerio Chiulele - Eduardo Mondlane Univ., MozambiqueOusmane Boukar, Jorge Franco, Sam Ofodile- IITA, NigeriaGCP-GRM, ICRISAT, Hyderabad, September 25,2011
  2. 2. Building on Phase I Key Outputs• 4 Key Resources for Modern Breeding Developed– 1. high-throughput genotyping platform• Based on Illumina 1536 GoldenGate Assay– 2. high quality consensus genetic map• 6 RILs, 741 lines, 928 markers– 3. fingerprints of >500 parental lines• 370 IITA/GCP mini-core• 200 IITA, West African lines/cultivars– 4. QTL and trait-linked markers• Drought tolerance• Resistance to flower and foliar thrips, ashy-stem blight, bacterialblight, root-knot nematodes
  3. 3. Phase II Activities, Highlights• Activity 1: Develop MAGIC population• Activity 2: Develop genomic resources insupport of marker-assisted breeding• Activity 3: Employ MARS and MABC to developimproved breeding lines• Activity 4: Capacity Building• Activity 5: Curate and Store Phase I and II Data
  4. 4. 2 DC; 360 double cross seed each4-way (ABCD and EFGH); Fall 20104 single crosses; Spring 2010Develop MAGIC population300+ 8-way individuals formed,being intercrossed now8 diverse parents chosen- NJ analysis- traits
  5. 5. Available onwww.HarvEST:cowpea; Lucas et alThe Genome (in press)New CowpeaConsensus Map• 11 RILs, 2 F4• 1293 genotyped• 1107 mappedSNPs,• 856 bins• 33% more bins• 19% more markers• improved order
  6. 6. 1_0502 1_1360 1_0504 1_1499 1_1138 1_1413 1_0847 1_0774 1_1221 1_0027 1_0153 1_0535 1_1092 1_0646AA AA CC CC AA TT -- TT AA AA AA GG AA TTGG TT TT TT GG GG -- CC GG GG GG AA GG AAAA AA CC CC AA TT AA TT AA AA AA GG AA TTGG TT TT TT GG GG TT CC GG GG GG AA GG AALinkage group3 4 5 6LOD0246810(c-1)Linkage group3 4 5 60246810(c-2)(a-1)(a-2)(b)‘Phase Checker’ software to improve map and QTL IDBioinformatics(submitted)GenomeStudioOutput 5 linesCorrectedOutputInferredparentalParentaldata
  7. 7. Selecting customized sets of markers for KASPAR• With high density genotyping– Many markers polymorphic ina given cross are tightly linked– no need to genotype all inbreeding• Marker selection by hand – slow &laborious when 200+ candidatemarkers• How to efficiently choose‘background’ and trait-linkedmarkers for given cross to get acost-optimized marker set forKASPAR genotyping?SNP LG cM IT93K-503-1 IT84S-2246 Polymorphic1_0190 4 6.83 AA AA 01_0502 4 10.27 BB AA 11_1148 4 10.36 AA AA 01_0382 4 10.66 AA AA 01_1360 4 12.23 BB AA 11_0504 4 12.76 AA BB 11_1499 4 13.69 AA BB 11_1138 4 14.09 BB AA 11_0155 4 15.56 BB BB 01_0082 4 17.97 AA AA 01_0756 4 18.37 AA AA 01_1413 4 18.38 BB AA 11_1445 4 19.1 BB BB 01_0847 4 19.48 -- -- 01_0774 4 20.16 BB AA 11_1221 4 20.16 BB AA 11_1242 4 20.72 BB BB 01_0027 4 21.49 BB AA 11_0153 4 21.49 BB AA 11_0535 4 22.85 AA BB 11_1261 4 22.92 BB BB 01_1092 4 23.66 BB AA 11_0646 4 24.12 BB AA 11_0874 4 24.4 AA BB 11_1264 4 24.43 -- -- 01_0826 4 24.55 BB AA 11_0692 4 25 AA BB 11_0403 4 25.31 -- AA 01_0106 4 25.57 AA BB 11_0678 4 27.6 BB AA 11_1209 4 27.9 -- BB 0
  8. 8. ‘BreedIt’• Program to choose a marker set for a given cross– Input SNP data table (genotype or locus file)– Input trait (QTL, markers) and map files– Program Options• Choose 2 parents• Choose cM interval for background selection• Choose cM interval for markers flanking traits• Output list of SNPs for KBiosciences assay• Can quickly compare cost versus marker density
  9. 9. SNP SNP_ID LG cM IT93K-503-1IT84S-2246 Polymorphic Trait Selected Reason Distance1_0190 16480_663 4 6.83 AA AA 0 01_0502 5268_412 4 10.27 BB AA 1 1 Every 5 cM1_1148 10853_451 4 10.36 AA AA 0 01_0382 6867_337 4 10.66 AA AA 0 01_1360 12393_305 4 12.23 BB AA 1 01_0504 14303_873 4 12.76 AA BB 1 01_1499 12324_917 4 13.69 AA BB 1 1 Flanking 3.411_1138 17303_348 4 14.09 BB AA 1 Flower Thrips 1 Trait 0.41_0155 474_351 4 15.56 BB BB 0 01_0082 13873_544 4 17.97 AA AA 0 01_0756 14622_2490 4 18.37 AA AA 0 01_1413 1078_282 4 18.38 BB AA 1 1 Flanking 4.291_1445 13794_319 4 19.1 BB BB 0 01_0847 8899_1022 4 19.48 -- -- 0 01_0774 16646_118 4 20.16 BB AA 1 01_1221 1202_1215 4 20.16 BB AA 1 1 Flanking 1.771_1242 4217_685 4 20.72 BB BB 0 Foliar Thrips 01_0027 3683_549 4 21.49 BB AA 1 1 Flanking 1.341_0153 14462_1712 4 21.49 BB AA 1 01_0535 1808_342 4 22.85 AA BB 1 01_1261 11736_560 4 22.92 BB BB 0 01_1092 5061_428 4 23.66 BB AA 1 01_0646 12854_535 4 24.12 BB AA 1 01_0874 7102_965 4 24.4 AA BB 1 01_1264 11709_707 4 24.43 -- -- 0 01_0826 9147_1655 4 24.55 BB AA 1 01_0692 8273_1205 4 25 AA BB 1 01_0403 4774_665 4 25.31 -- AA 0 01_0106 8625_1231 4 25.57 AA BB 1 01_0678 13269_270 4 27.6 BB AA 1 1 Every 5 cM 6.11BreedItoutputfile formarkerselection
  10. 10. Activity 3. Main MARS Breeding Effort• F1 made (March –June 2010)• F1 grown out to produce F2 (Sept. – Nov. 2010)• F2 seed (500/cross) sent to partners, Feb. 2011• Harvested ~300 plants/popln– Tissue samples taken, mailed to KBioCurrently F3s being phenotyped (Senegal, Burkina, IITA,January 2012-Mozambique)Fall 2011 - Calculate breeding values with OptiMAS• Apply 10% selection intensity, genotype 10individuals/family and intermate
  11. 11. MABC to develop improved breeding lines Made F1 - Spring 2010 and BC1F1 Fall 2010 Made BC2F1 and BC1F2 – Spring 2011 Currently Phenotyping BC1F2 families for Striga tolerance (IITAand BF) Genotype at KBio – Dec. 2011CrossnumberCrossNo.BC1F1Donor Traits2011-052 IT84S-2246/IT93K-503-1//IT84S-2246 48 Drought Tol. , Striga2011-053 IT84S-2246/IT98K-1111-1//IT84S-2246 48 Heat Tol., Striga2011-054 SuVita 2/IT93K-503-1//SuVita 2 48 Drought Tol., Striga2011-055 SuVita 2/IT97K-499-35//SuVita 2 48 Drought Tol., StrigaSeveral other MABC efforts at BC1F1 stage
  12. 12. QTL Discovery in Elite RILs• Heat Tolerance Phenotyping– Greenhouse Aug. – Oct. 2010 and 2011– RIL CB27 x IT82E-18• Aphid Resistance Phenotyping– Field hotspot, Calif., Summer 2010 &11– RIL CB27 x IT97K-556-6• Anthracnose Phenotyping• Burkina Faso, RIL 524B/IT84S-2049Aphid Resistance QTL
  13. 13. IT93K-503xCB46 RIL2006CVS(57)2006UCR(57)2007CVS(57)2007CVS(124)2007UCR(57)2008CVS(91)2008UCR(108)VuLG4VuLG2VuLG8VuLG10Foliar Thrip Res. QTL Validation LOD>8.4LOD>6.8LOD>4LOD>3.2Validating withCB27/IT82E-18 RIL
  14. 14. SNP SNP SNP SNPLine Rank All Weight UC No(+/+) No(-/-) No(+/-) 1_0589 1_0853 1_0604 1_148205066-004 1 1 1 4 4 0 0 1 1 1 105066-065 2 1 1 4 4 0 0 1 1 1 105066-109 3 0.875 0.94 4 3 0 1 1 1 1 0.505066-001 4 0.75 0.88 3 3 1 0 1 1 1 005066-073 5 0.75 0.88 3 3 1 0 1 1 1 005066-087 6 0.75 0.88 3 3 1 0 1 1 1 005066-045 7 0.75 0.87 3.71 2 0 2 0.5 1 1 0.505066-103 8 0.75 0.87 3 3 1 0 0 1 1 105066-015 85 0.25 0.12 1 1 3 0 1 0 0 0Mouride 86 0.25 0.12 1 1 3 0 1 0 0 005066-002 87 0.25 0.12 1.71 0 2 2 0.5 0 0 0.505066-034 88 0.25 0.12 1 1 3 0 0 0 0 105066-054 89 0.125 0.06 1 0 3 1 0 0 0 0.505066-100 90 0 0 0 0 4 0 0 0 0 005066-129 91 0 0 0 0 4 0 0 0 0 0%PV 4.665 19.05 10.15 4.57Favorable DT SNPsDrought QTL ValidationOptiMAS Results - one Pilot MARS Popln10 best and worst lines from 3 HixHi populationsBeing phenotyped now
  15. 15. Bayesian QTL detection methodsbeing tried• Improved QTL estimation when QTLs• PROC QTL softwarehttp://statgen.ucr.edu/download/software/PROC%20QTL.pdf• Better markers and marker effects forcalculating selection index weights• Redoing QTL estimates with new map
  16. 16. Bayesian vs Interval Mapping2010 MARS Pilot Project Data Senegal - 100 grain weightInterval mapping1 2 3 4 5 6 7 8 9 10 11LODscore0.01.02.03.04.05.0Bayesian analysisChromosome1 2 3 4 5 6 7 8 9 10 11Effectestimate-0.4-0.20.00.20.4
  17. 17. Activity 4. Capacity Building• Two PhD students Senegal (Penda Sarr - English at UCR Spring 2010; nowenrolled at Anta Diop Chiekh University, Dakar, Senegal) Mozambique (Arsenio Ndeve - English at UCR Spring 2010,accepted for Winter 2012 enrollment at UCR) MABC and MARS breeding• PhD student at WACCI (started Sept. 2009) Burkina Faso (Joseph Batieno) Supported by GCP Capacity Building funds• Mentoring Rogerio Chiulele (Mozambique – PhD completed ACCI May2011)
  18. 18. Mentoring WACCI PhDs• WACCI Cowpea PhD students– Joseph Batieno – INERA-Burkina Faso; PhD started 2009– Maureen Nkoumki –IRAD-Cameroon; PhD started 2010– Mohamad Lawan – IAR-Nigeria; PhD started 2010– Fafa Egbadzor – Univ. of Ghana; PhD started 2010• Presented Breeding Training Module March 21 – 25,2011 at WACCI• Reviewing WACCI Student PhD Proposals• Assisting with GCP-GSS Proposal Development
  19. 19. Thank YouUniversity of California,RiversideMuchero, WellingtonPottorff, MartiWanamaker, SteveEhlers, Jeffrey D.Roberts, Philip A.Close, Timothy J.Lucas, MitchellXu, ShizhongHu, Zhiqui19National Agricultural Research System(NARS)Cisse, Ndiaga, ISRA-SenegalDrabo, Issa, INERA-Burkina FasoTignegre, Jean-Baptist, INERA, Burkina FasoRogerio Chiulele, Eduardo Mondlane U,MozambiqueInternational Institute ofTropical Agriculture (IITA)Muranaka, SatoruBoukar, OusmaneFatokun, ChristianFranco, JorgeSam Ofodile

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