Harnessing interdisciplinary approaches for germplasm development

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Tools to accelerate efficiency of germplasm improvement,how these tools support breeders

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Harnessing interdisciplinary approaches for germplasm development

  1. 1. “IITA - the appliance of science” Harnessing interdisciplinary approaches for germplasm developmentSarah Hearne International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  2. 2. The bottom lineDevelopment of varieties that are:High yield potentialHigh yielding under farmerconditionsPest and disease resistantResistant to abiotic stressEffective use of nutrientsMarket preferred characteristicsNutritiousDesired duration International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  3. 3. PhysiologyPathologyWeed science BreedingEntomology AgronomyNematology IPMBiotechnologyBiometricsBioinformatics International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  4. 4. Tools to Phenotypingaccelerate / Methodologiesbetter target / Benchmark sitesimproveefficiency of Molecular tools -markersgermplasmimprovement Statistical methodologies Breeding and selection methodologies Data management, analysis and decision support tools International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  5. 5. How these tools Rapid targeted selection of segregants Molecular breedingsupport Rapid integrated data analysisbreeders? Selection of parents Heterotic grouping Diversity assessment – allelic / general Predictive breeding Variety production and seed systems DUS (distinct, uniform, stable)& VCU (value for cultivation and use) Seed purity Impact assessment Stress interactions / host-pest interactions Target breeding for specific stress complexes / pest genotypes International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  6. 6. Three years- Maize molecular breedingoutputs and projects, methodologiesoutcomes applicationsMaize Maize genetic diversityCowpea global diversityCassava StrigaMusa distribution, diversityStriga pathogenicity Resource development and useSome highlights cowpea, cassava and musa Plans for the future International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  7. 7. DTMA Interdisciplinary team with many talents working across centers! International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  8. 8. DTMA Multiple interconnected themes within the initiative Genomics Breeding Seed systems Impact assessment Drought Polygenic with high degree of epistasis GxE issues Phenotyping complexity – precision issues Can’t apply markers across populations for MAS International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  9. 9. Phenotyping Increase throughput Enhance precision Benchmark sites with precision irrigation -Nigeria, Kenya, Zimbabwe, Zambia, Mexico International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  10. 10. Phenotyping Biomass/ senescence Spectroradiometry – NDVI – rapid biomass assessmentNew toolsimplementedCollaboration withbreeders andphysiologists Transpiration Leaf / canopy temperature Water use efficiency / NIRS & ash content effectiveness International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  11. 11. Molecular DTMA- largest public sector molecular breeding project for maize in the worldbreeding Monitor and coordinate phenotyping, genotyping, data analysis and breeding turnaround across projects Work with physiologists on phenotyping methods and site characterization Work with molecular team on genotyping technologies and bottlenecks Work with biometricians on issues of pop size and marker number and on simulations of new approaches using real data Work with bioinformaticians on issues of data handling and processing International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  12. 12. Molecular What strategy to use for molecular breeding?breeding What markers to use? How to do the genotyping? What traits to look at using markers?: Make adapted materials more drought tolerant Make drought tolerant materials more disease tolerant International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  13. 13. Molecular What strategy to use for molecular breeding?breeding Classic QTL ABQTL MARS GWS What markers to use? For breeding - SNP How to do the genotyping? What traits to look at using markers?: Both drought and disease -list of diseases and populations International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  14. 14. Molecular Molecular breeding training course 2008breeding DTMA scientists NARS and private sector partners Side meetings Breeding strategy? Evaluated our own QTL data and looked at necessary population sizes and marker numbers – NO classic QTL Private sector present advising ABQTL and MARS breeding strategies Defined a template for population planning and molecular breeding implementation Worked with breeders to define possible populations – 35 potentials International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  15. 15. Marker assisted recurrent selection: MARS -new lines Select Genotype populations parents Using 200-300 polymorphic Make SNP markers populations Phenotype test cross populations in 3 or more Genotype parents multilocation trials Find marker traitUsing ~1500 SNP markers associations for drought tolerance Recombine the best materials using marker data to stack or Isolate new lines Use lines to pyramid favorable markers and phenotype create new for two or more cycles under drought drought tolerant (no phenotyping) varietiesSeed based DNA extraction International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  16. 16. Y1MolecularbreedingPower of MARS Y2 Sel C0 Breeder lines Y3 MARS C2S1 lines mid p If you have 20 regions under selection, freq of optimum genotype goes from 1 per trillion in cycle 0 to 1 in 5 in cycle 3 International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  17. 17. Marker assisted recurrent selection: MARS -new lines Select Genotype populations parents Using 200-300 polymorphic Make SNP markers populations Phenotype test cross populations in 3 or more Genotype parents multilocation trials Find marker traitUsing ~1500 SNP markers associations for drought tolerance Recombine the best materials using marker data to stack or Isolate new lines Use lines to pyramid favorable markers and phenotype create new for two or more cycles under drought drought tolerant (no phenotyping) varietiesSeed based DNA extraction International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  18. 18. Molecular Annual meeting 2008breeding Scheduling of phenotyping and genotyping and cost of genotyping Some seasons ~6500 individuals to genotype 3 weeks to extract DNA and genotype Genotyping option Illumina golden gate – 1536 SNP markers International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  19. 19. Illumina golden gate – 1536 SNP markersMolecularbreeding International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  20. 20. Molecular Workshop Feb 2009breeding SNPlex no longer an option BeadXpress Illumina system 384 markers Single plex assays – KBiosciences DTMA – buy BeadXpress Analysis of throughput and cost Discussion with private sector Visit to KBioscience Presented data at 2009 DTMA annual meeting in Zim - use KBiosciences International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  21. 21. Molecular DTMA – 20 molecular breeding projects. 18 MARS/GWS (explained in next slide), 2 ABQTL (linebreeding conversion) – WA had 5 MARS/GWS populations Two genotyping platforms- Illumina golden gate- One diverse 1536 illumina OPA, 1330 good SNP KASPar – single plex primer extension based assays designed for 1111 SNP Will be using new 60k infinium assay in 2010 Genotyping by sequencing under evaluation International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  22. 22. Building on MARS Some of the hit list:-populationsWe have high MSVbreeding valuesegregating Striga hermonthicapopulationsWe have GLSgenotype data NematodesWhat other highvalue traits wecan phenotypefor… International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  23. 23. Molecular Tolerance to MSVbreeding Breeder, Virologist, Biometrician and Mol Geneticist Abebe + – populations, field phenotyping Lava – Screenhouse phenotyping and indexing, field phenotyping Sarah – Candidate marker identification, population genotyping, tracking, data curation Guy – Data handling and manipulation Sarah and Jose – Data analysis and marker identification Contribute knowledge and markers for simple traits to incorporate into breeding work International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  24. 24. Molecular Resistance and tolerance to Strigabreeding Breeders, Physiologist, Biometrician and Mol Geneticist Abebe and Baffour – populations, field phenotyping Sarah – Screenhouse phenotyping Sarah – Candidate marker identification, population genotyping, tracking, data curation Sarah and Jose – Data analysis and marker identification Contribute knowledge and markers for identified traits to incorporate into breeding work International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  25. 25. GLS Field phenotyping issues - Reliability Not a simple trait – or a single species (Lava) Development of improved phenotyping e.g. HTP detached leaf assay for GLS evaluations with pathologist - Ranajit Enable controlled infestation with different genotypes of pathogen (pathotypes / species with agroecological niches) International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  26. 26. CML 488 maize inbred lineNematodesPratylenchusMeloidogyne Black Lesions Reduced root mass “Root galling” Un-infected Meloidogyne infested International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  27. 27. Nematodes Nematode and drought interaction Breeders, Nematologist, Physiologist,Interaction Biometrician and Mol Geneticistbetween drought Abebe and Baffour – lines – parents of MARSand nematode – populationsflowering date Danny – Screenhouse phenotyping-and ASI nematodes Sarah – Screenhouse phenotyping- drought Sarah and Jorge – Data analysis Contribute knowledge and markers for identified traits to incorporate into breeding work International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  28. 28. What other Selection of parentsapplications to Heterotic groupingsupport Diversity assessment – allelic / general Predictive breedingbreeders? Genotyping of potential parents Variety production and seed systems DUS (distinct, uniform, stable)& VCU (value for cultivation and use) Seed purity Impact assessment Testing the quality of outgrower produced hybrid seed in Zimbabwe Genotyping IITA released maize lines using 60k SNP chip to facilitate tracking of IITA germplasm for impact assessment International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  29. 29. Numbers, Molecular breeding is a balancingnumbers acteverywhere… $ How do we balance competing demands for funds and optimize genetic gain? International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  30. 30. A MD= 5 cM B MD= 5 cM 0.70 0.50 PVE=1% Standard error of estimated effect 0.65 0.45 PVE=2% 0.60 Estimated genetic effect 0.40 PVE=3% 0.55 0.50 0.35 PVE=4% 0.45 0.30 PVE=5% 0.40 0.25 PVE=10% 0.35 0.20 PVE=20% 0.30 0.15 PVE=30% 0.25 Analysis of pop 0.20 0.15 0.10 0.10 0.05 0.00 size and marker 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600 Population size Population size C MD= 10 cM D MD= 10 cM 0.70 0.50 density on QTL PVE=1% Standard error of estimated effect 0.65 0.45 PVE=2% 0.60 Estimated genetic effect 0.40 PVE=3% 0.55 0.35 PVE=4% detection 0.50 0.45 0.40 0.30 0.25 PVE=5% PVE=10% 0.35 0.20 PVE=20% 0.30 0.15 PVE=30% 0.25 0.20 0.10 0.15 0.05 0.10 0.00 20 40 60 80 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600 Population size Population size 100 E F 0.70 MD= 20 cM 0.50 MD= 20 cM 90 PVE=1% Standard error of estimated effect 0.65 0.45 MD=5 cM PVE=2% 0.60 80 Estimated genetic effect 0.40 PVE=3% 0.55 0.35 PVE=4% 70 0.50 Power (%) 0.45 0.30 PVE=5% 60 0.40 0.25 MD=10 cM PVE=10% 0.35 0.20 PVE=20% 50 0.30 0.15 PVE=30% 0.25 40 0.20 0.10 MD=20 cM 0.15 0.05 30 0.10 0.00 20 20 40 60 80 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600 10 Population size Population size MD=40 cM G MD= 40 cM H MD= 40 cM 0.70 0.50 0 PVE=1% Standard error of estimated effect 0.65 0.45 PVE=2% 0.60 40 40 40 40 40 40 40 40 440 240 440 240 540 140 340 540 140 340 240 440 240 440 140 340 540 140 240 340 540 140 340 540 140 340 440 240 440 240 440 540 140 340 540 140 340 540 240 440 Estimated genetic effect 0.40 PVE=3% 0.55 0.50 0.35 PVE=4% 0.45 0.30 PVE=5% PVE=1% PVE=2% PVE=3% PVE=4% 0.40 PVE=5% PVE=10% PVE=20% 0.25 PVE=30% PVE=10% 0.35 PVE=20% Population size 0.30 0.20 0.15 PVE=30% 0.25 0.20 0.10 0.15 0.05 0.10 0.00 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600 Zhonglai Li, Institute of Wang, Agriculture – Institut international d’agriculture tropicale – www.iita.org Population size Population sizeHuihui Li, Sarah Hearne, Yunbi Xu, Marianne Bänziger,International & JiankangTropicalHeredity in press
  31. 31. MAS versus MASGWS Only track significant markers GWS All markers have value Which is optimal? How many cycles of selection? Best estimate? BLUE (GxE), BLUP (no GxE but marker by marker) Selection index? International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  32. 32. MAS versus Simulations GWS Fig.1 1a Fig. 360 YB 400MM BLUE YB 40MM BLUE 30 YA 400MM BLUE YB 400MM BLUP YB 40MM BLUP YA 400MM BLUP EPP (number) 355 25 P 350 EP 20 GY (grams per plot) 345 15 340 10 Y G 335 5 ASI (days) ASI 330 0 325 -5 0 1 2 3 4 5 6 Cycle of selectionCerón-Rojas, J. J., Crossa, J., Alvarado, G., Burgueño, International Institute of Tropical Agriculture – S. J. & Davenport, G., F., Sub Crop Sci – www.iita.org J., Wang, J., Atlin, G., Bänziger, M., Hearne, Institut international d’agriculture tropicale
  33. 33. MAS versus GWS better than MAS in all situations GWS 400 markers better than 40 BLUP better than BLUE when looking at Fig.1 1a Fig. well watered environments 360 YB 400MM BLUE YB 40MM BLUE 30 YA 400MM BLUE YB 400MM BLUP YB 40MM BLUP YA 400MM BLUP EPP (number) 355 25 350 EP P 20 BLUE better than BLUP when looking at drought stressed environmentsGY (grams per plot) 345 15 340 10 Y G 335 5 ASI (days) ASI 330 325 0 -5 Genetic gain for grain yield up to cycle six 0 1 2 3 4 5 6 Cycle of selection International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  34. 34. Three years- Maize molecular breedingoutputs and projects, methodologiesoutcomes applicationsMaize Maize genetic diversityCowpea global diversityCassava StrigaMusa distribution, diversityStriga pathogenicity Resource development and useSome highlights cowpea, cassava and musa Plans for the future International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  35. 35. Maize diversity Maize from Americas, Africa, Asia, Europe and teosintes Group of collaborators from ten different institutes Population geneticists, breeders, genebank Curators, molecular geneticists, GIS specialists How has maize migrated across the globe? What is the pattern of global diversity? International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  36. 36. Maize diversity Maize from Americas, Africa, Asia, Europe and teosintes Group of collaborators from ten different institutes Population geneticists, breeders, genebank Curators, molecular geneticists, GIS specialists How has maize migrated across the globe? What is the pattern of global diversity? International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  37. 37. Maize diversity Globally landraces are in general tropical in origin Twelve main landrace clusters exist in the worldAfrica International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  38. 38. Maize diversity Western Sub-Saharan Africa -tropical maize Diversity data strongly supports hypothesis of introduction via Portuguese slave West Africa very distinct - Sao Tome and Cape Verde – groups originating from both can be defined:- rapid differentiation of original gene pools- environment and human usesAfrica East Africa – data suggests direct diffusion of US maize after World War II – potential replacement of tropical landraces International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  39. 39. Mir, C., Warburton, M.L., Taba, S., Bedoya, C., Franco, J.,Zhang, S., Xie, C., Prasanna, B.M., Hearne, S., Muthamia, Z., Yunus, M., Cuong,B.M., and Charcosse. In Prep International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  40. 40. Three years- Maize molecular breedingoutputs and projects, methodologiesoutcomes applicationsMaize Maize genetic diversityCowpea global diversityCassava StrigaMusa distribution, diversityStriga pathogenicity Resource development and useSome highlights cowpea, cassava and musa Plans for the future International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  41. 41. Striga Striga is one of the most significant biotic constraints to maize production in SSA-from the parasite Striga sp., while often lumped together haveperspective distinct and different breeding systems. S. asiatica is inbreeding species while S. hermonthica is self incompatible and is highly outbreeding in nature. These differences have implications on diversity within and between parasite populations per se and also has implications control technology efficacy from region to region – be that host resistance and tolerance to parasite or herbicide tolerant germplasm. Hearne, Pest Mgmt Sci, 65, 2009 International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  42. 42. Striga Surveying Striga endemic areas in Nigeria, DRC and Kenya. In 2011 survey Tanzania.-from the parasiteperspective Taking basic farmer perception data and collecting Striga leaf and seed samples from individuals and populations to assess parasite diversity. Using location data to prepare and atlas of Striga distribution working with GIS International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  43. 43. Striga Pilot project completed assessing diversity of S. hermonthica in Kenya using SSR markers-from the parasiteperspective Within population variation contributed to some 95.89% of the total variance with only 4.11% being due to among populations. High even for an allogamous species. The total heterozygosity observed across all markers and populations was very high at 0.72054, within population heterozygosities ranged from 0.4829 to 0.73988. International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  44. 44. Striga The level of heterozygosity may reflect the obligate out-breeding nature of the species and the level of population diversity needed to ensure-from the parasite fitnessperspective Marker availability for Striga is limited – 8 informative SSR markers Link with evolutionary biologist, Claude de Pamphilis at Penn State on NSF initiative to sequence parasitic plant ESTs Striga tissue collected from diverse sources in Nigeria and sent to US for RNA isolation and sequencing using 454 Titanium sequencing International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  45. 45. Striga Assemblies being constructed – mine for SNP and polymorphic SSR to conduct further studies-from the parasite Claude using data to complete the Striga chloroplast genome and construct a mitochondrialperspective genome – understand evolution of parasitism across parasitic plants – Striga, Alectra, Orobanche Use new markers to evaluate within and between population S. hermonthica diversity. SSR in Ibadan and SNP at Kbiosciences. Data analysis, Sarah, Jorge and GIS International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  46. 46. Striga Pathogenicity work – implication of diversity? First need a system for maintaining the discrete Striga populations collected in the field Working with Mike Timko, U . Virginia to look at methodologies for inter population mating to maintain population diversity. Working on Nigerian isolates of Striga NSF proposal to sequence Striga genome – great resource to start to understand parasitism and pathogenicity at the genomic level International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  47. 47. Striga-host Field screening $, uses only one or two populations of Striga and does not provide an understanding of theinteractions mechanisms of tolerance / resistance seen Implemented medium and high throughput lab and screenhouse based phenotyping protocols to assess the Striga-host interaction at biochemical, physiological and morphological levels. Assess resistance at germination, haustorial initiation, attachment and post attachment stages Enable improved selection of favorable recombinants and facilitate studies of gene action Integrate these assays with current molecular breeding work to identify molecular markers for key traits of interest International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  48. 48. Three years- Maize molecular breedingoutputs and projects, methodologiesoutcomes applicationsMaize Maize genetic diversityCowpea global diversityCassava StrigaMusa distribution, diversityStriga pathogenicity Resource development and useSome highlights cowpea, cassava and musa Plans for the future International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  49. 49. Marker Program of EST sequencing projects – cowpea, cassava and musadevelopment Generated:- Cowpea-JCVI, ILRI, UC 41949 sequencesRiverside 3367 putative SNP 1805 putative SSR, 916 di- and trinucleotide repeats Cassava 5046 sequences (41173) 2699 putative SSR 2486 putative SNP Musa 5494 sequences (52907) 1937 putative SSR 28815 putative SNP International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  50. 50. Marker development HarvEST cowpea database - 17 libraries - Two IITA libraries, 12 UCR libraries.Consolidation andutilization of EST HarvEST cassava database - 17 libraries - Two IITA libraries, 12 UCR libraries. HarvEST musa database - 17 libraries - Two IITA libraries, 12 UCR libraries. http://harvest.ucr.edu/ International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  51. 51. Marker Developed Illumina Goldengate SNP assay IITA Reference collection, breeders lines, bi-development and parental populationsuse IITA reference collection encompassed genetic diversity assessed using SNPCowpea Ref set and additional germplasm extensively phenotyped – tool for allele mining Development of consensus genetic map of cowpea, and synteny with soybean and Medicago Provides genomic framework for identification of marker trait association, map-based cloning, selection of markers for assessment of genetic diversity, association mapping Muchero, W., Diop, N., Bhat, P., Fenton, R., Pottorff, M., Hearne, S., Ndiaga, C., Fatokun, C., Ehlers, J., Roberts, P., Close,T. 2009. PNAS International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  52. 52. Marker 410 EST derived SSR - Xu et al 2009, Molecular breedingdevelopment Mike Timko’s group compared EST with GSSConsolidation and datautilization of EST Determine the gene discovery rate Timko et al 2008 BMC Genomics Predict open reading frames for the genes (oligos) used to create a cowpea microarray – 385k. Microarray used to study cowpea-Striga interaction- Li et al 2009 Pest Mgmt Sci International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  53. 53. Three years- Maize molecular breedingoutputs and projects, methodologiesoutcomes applicationsMaize Maize genetic diversityCowpea global diversityCassava StrigaMusa distribution, diversityStriga pathogenicity Resource development and useSome highlights cowpea, cassava and musa Plans for the future International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  54. 54. Building on good Breedingfoundations Musa Yam Genome sequence ESTs Cassava TLI TLII DTMA DTMA DTMA DTMA Adapt and apply know how to achieve rapid advances in other IITA crops International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  55. 55. Be brave and In farmers fields plant are subject tolook at multiple stressescomplexity Start looking at the basis of stress tolerance resistance. Then look at complexes of commonly occurring stresses International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org
  56. 56. We have a bright futureThank you International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org

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