v More than 200 breeders and agriculturistsfromNARStrainedtousemodernbreedingmanagementanddecisiontool(Fig.1)
v Establishment of nodes and migra@on ofhistorical data from several breedingprogramsinAfricaintotheBMStool
v 15researchscien@ststrainedinDemand-ledvarietydesignapproach
v SSR genotyping of tubers (yam, cassava),cereals (rice, maize), tree crops (mango,eucalyptus), vegetable (biJer leaf), forage,fish and livestock (caJle, goat) from subSaharanAfrica,USAandEcuador(Fig2)
v SNP genotyping of 3230 samples includingforage,maize,rice,sorghum,fishandsheepfromCGcenters(70%),Na@onalAgriculturalResearch System (NARS) (15%) and theProgram for African Seed System (PASS)(15%)(Fig.3).
v Genomic ass isted breeding jo int lyimplementedwithpartnersinTanzaniaandEritrea
MolecularBreedingPla0ormattheBecA-ILRIHub:Suppor>ngbreedersintheregion
*NasserYao,MaryWambugu,FrancescaStomeo,MarkWamalwa,AppolinaireDjikengand*JosephineBirungiBioscienceseasternandcentralAfrica-InternaFonalLivestockResearchInsFtute,(BecA-ILRI)Hub,Nairobi,Kenya
AbouttheMolecularBreedingPla0ormTheBreedingplaWormattheBecA-ILRIHubaimsatenhancingplantbreedingandlivestockresearchusingmodernbreedingtools.TheplaWormisbuiltaroundthreekeycomponents:theBreedingManagementSystem(BMS),theIntegratedGenotypingServiceandSupport(IGSS)andtheDemand-ledvarietydesign.BMS is a suiteof comprehensive tools, embedded in a singleplace, and commonlyusedbybreeders for their day todaybreedingac@[email protected]@vegenotypingserviceandsupporttolocalplant/livestockbreedingprogramsandsmallandmediumenterprisesinsub-SaharanAfricatoacceleratetherateofgene@cgain,developmentandreleaseofnewcropvarie@esandimprovedlivestock.Throughthedemand-ledvarietydesignapproach,thebreedingplaWormaimsatmakingplantbreedinginAfricaabusinessmodelresponsivetomarketdemand.TheplaWormalsogeneratesandmanagesgenomicandmarkerdataandprovidessupport tobreedersandotherscien@sts in integra@ngDNAmarkerassaysandgenomic tools into theirbreedingprogramand researchac@vi@es forboth cul@vatedandorphan cropsand livestock species.Majorfields coveredundertheplaWorminclude:1)trainingofbreederstomakeefficientuseofbreedingdecisionsupporttools(BMSandIGSS),2)provisionofadviceandguidanceinelabora@nganholis@cbreedingstrategies(demand-ledvarietydesign)usingmodernbreedingtools,3)genomesequencing-basedgene@cprofiling and genera@on of various genotyping data types from low to high throughput facili@es, 4) support in popula@on development and datamanagementfollowedbyrequiredanalyses,interpreta@onofresultandsuppor@ngscien@ststogetthesuitablebreedingdecisionforthenextstep,5)genomewideassocia@onstudyand6)genomicselec@on.
*Formoreinforma@oncontactDrNasserYao/[email protected]/[email protected]●hub.africabiosciences.orgFunding:BillandMelindaGatesFounda@on(BMGF)SyngentaFounda@onforSustainableAgriculture(SFSA)ThisdocumentislicensedforuseunderaCrea@veCommonsAJribu@on–Noncommercial-ShareAlike3.0UnportedLicenseFebruary2016
Partnerships
Outputsv Modernbreedingtooladoptedandused
inseveralbreedingprograms ineastern,central and southern Africa includingEthiopia, Uganda, Tanzania, Sudan andKenya
v Breeders and agriculturists beJerintegra@ng historical and manual datadirectly intoBMStoacceleratebreedingefforts
v Major QTL for Maize Lethal Necrosis(MLN) iden@fied and used to developmaizeMLNresistantlines
v Gene@c profiling of 350 rice accessions,comprising a unique collec@on of theAfrican Oryza and key rice germplasmsused by the rice community as parentallines or elite material, now servingseveral breeding purposes at the AfricaRiceCentre
v Ins@tu@ons (Naliendele AgriculturalResearchIns@tute(NARI)inTanzaniaandthe Hamalmelo College of Agriculture,Eritrea) implemen@ng genomic-based/molecularassistedbreeding
Outcomes
• Gene@c profiling of key crop and livestock commodi@es from breedingprogramsinEthiopia,Kenya,Rwanda,TanzaniaandUganda
• Designofproductprofilesformajorcrops/livestock
• Developmentofcul@vardevelopmentpipelinesformajorcrop/livestock
• Linkage with the Global Open-source Breeding and Informa@cs Ini@a@ve(GOBII)andDiversitySeek(DivSeek)ini@a@ves
Poten>altoscale-up
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Figure1:Numberoftraineespercountryandperins>tu>on
Figure 3: Number of samples processed per commodity and perins>tu>onunderIGSS
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Figure2:SSRgenotypingserviceprovisionandtrendfrom2009to2014
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