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Genomic prediction and QTL discovery in a cassava training population constructed from multiple breeding stages

dc.contributor.authorSomo, M.
dc.contributor.authorKulembeka, H.
dc.contributor.authorMtunda, K.
dc.contributor.authorMrema, E.
dc.contributor.authorSalum, K.
dc.contributor.authorWolfe, M.
dc.contributor.authorRabbi, I.Y.
dc.contributor.authorEgesi, C.
dc.contributor.authorKawuki, R.
dc.contributor.authorOzimati, A.
dc.contributor.authorLozano, R.
dc.contributor.authorJannink, J.
dc.date.accessioned2020-05-28T12:04:19Z
dc.date.available2020-05-28T12:04:19Z
dc.date.issued2020
dc.identifier.citationSomo, M., Kulembeka, H., Mtunda, K., Mrema, E., Salum, K., Wolfe, M. D., ... & Jannink, J.L. (2020). Genomic prediction and QTL discovery in a cassava training population constructed from multiple breeding stages. Crop Science, 1-42.
dc.identifier.issn0011-183X
dc.identifier.urihttps://hdl.handle.net/20.500.12478/6847
dc.description.abstractAssembly of a training population (TP) is an important component of effective genomic selection‐based breeding programs. In this study, we examined the power of diverse germplasm assembled from two cassava (Manihot esculenta Crantz) breeding programs in Tanzania at different breeding stages to predict traits and discover quantitative trait loci (QTL). This is the first genomic selection and genome‐wide association study (GWAS) on Tanzanian cassava data. We detected QTL associated with cassava mosaic disease (CMD) resistance on chromosomes 12 and 16; QTL conferring resistance to cassava brown streak disease (CBSD) on chromosomes 9 and 11; and QTL on chromosomes 2, 3, 8, and 10 associated with resistance to CBSD for root necrosis. We detected a QTL on chromosome 4 and two QTL on chromosome 12 conferring dual resistance to CMD and CBSD. The use of clones in the same stage to construct TPs provided higher trait prediction accuracy than TPs with a mixture of clones from multiple breeding stages. Moreover, clones in the early breeding stage provided more reliable trait prediction accuracy and are better candidates for constructing a TP. Although larger TP sizes have been associated with improved accuracy, in this study, adding clones from Kibaha to those from Ukiriguru and vice versa did not improve the prediction accuracy of either population. Including the Ugandan TP in either population did not improve trait prediction accuracy. This study applied genomic prediction to understand the implications of constructing TP from clones at different breeding stages pooled from different locations on trait accuracy.
dc.description.sponsorshipBill & Melinda Gates Foundation
dc.description.sponsorshipDepartment for International Development, United Kingdom
dc.format.extent1-42
dc.language.isoen
dc.subjectCassava
dc.subjectBreeding
dc.subjectAfrican Cassava Mosaic Virus
dc.subjectFood Security
dc.subjectGermplasm
dc.subjectGenomics
dc.titleGenomic prediction and QTL discovery in a cassava training population constructed from multiple breeding stages
dc.typeJournal Article
cg.contributor.crpRoots, Tubers and Bananas
cg.contributor.affiliationCornell University
cg.contributor.affiliationTanzania Agricultural Research Institute
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationNational Crops Resources Research Institute, Uganda
cg.contributor.affiliationUnited States Department of Agriculture
cg.coverage.regionAfrica
cg.coverage.regionEast Africa
cg.coverage.countryTanzania
cg.coverage.countryUganda
cg.coverage.hubEastern Africa Hub
cg.researchthemeBiotech and Plant Breeding
cg.identifier.bibtexciteidSOMO:2020
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectAgronomy
cg.iitasubjectCassava
cg.iitasubjectDisease Control
cg.iitasubjectFood Security
cg.iitasubjectGenetic Improvement
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Diseases
cg.iitasubjectPlant Genetic Resources
cg.iitasubjectPlant Production
cg.journalCrop Science
cg.notesOpen Access Article; Published online: 11 Dec 2019
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.1002/csc2.20003
cg.iitaauthor.identifierIsmail Rabbi: 0000-0001-9966-2941
cg.iitaauthor.identifierChiedozie Egesi: 0000-0002-9063-2727
cg.noniitaauthor.identifierJean-Luc Jannink: 0000-0003-4849-628X


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