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Utility of Ugandan genomic selection cassava breeding populations for prediction of cassava viral disease resistance and yield in West African clones

dc.contributor.authorOzimati, A.
dc.contributor.authorEzuma, W.
dc.contributor.authorManze, F.
dc.contributor.authorIragaba, P.
dc.contributor.authorKanaabi, M.
dc.contributor.authorAno, C.U.
dc.contributor.authorEgesi, C.
dc.contributor.authorKawuki, R.S.
dc.date.accessioned2023-01-05T07:59:26Z
dc.date.available2023-01-05T07:59:26Z
dc.date.issued2022-11-23
dc.identifier.citationOzimati, A.A., Esuma, W., Manze, F., Iragaba, P., Kanaabi, M., Ano, C.U., ... & Kawuki, R.S. (2022). Utility of Ugandan genomic selection cassava breeding populations for prediction of cassava viral disease resistance and yield in West African clones. Frontiers in Plant Science, 13:1018156, 1-12.
dc.identifier.issn1664-462X
dc.identifier.urihttps://hdl.handle.net/20.500.12478/7998
dc.description.abstractCassava (Manihot esculenta Crantz) is a staple crop for ~800 million people in sub-Saharan Africa. Its production and productivity are being heavily affected by the two viral diseases: cassava brown streak disease (CBSD) and cassava mosaic disease (CMD), impacting greatly on edible root yield. CBSD is currently endemic to central, eastern and southern Africa, if not contained could spread to West Africa the largest cassava producer and consumer in the continent. Genomic selection (GS) has been implemented in Ugandan cassava breeding for accelerated development of virus resistant and high yielding clones. This study leveraged available GS training data in Uganda for pre-emptive CBSD breeding in W. Africa alongside CMD and fresh root yield (FRW). First, we tracked genetic gain through the current three cycles of GS in Uganda. The mean genomic estimated breeding values (GEBVs), indicated general progress from initial cycle zero (C0) to cycle one (C1) and cycle two (C2) for CBSD traits and yield except for CMD. Secondly, we used foliar data of both CBSD and CMD, as well as harvest root necrosis and yield data to perform cross-validation predictions. Cross-validation prediction accuracies of five GS models were tested for each of the three GS cycles and West African (WA) germplasm as a test set. In all cases, cross-validation prediction accuracies were low to moderate, ranging from -0.16 to 0.68 for CBSD traits, -0.27 to 0.57 for CMD and -0.22 to 0.41 for fresh root weight (FRW). Overall, the highest prediction accuracies were recorded in C0 for all traits tested across models and the best performing model in cross-validation was G-BLUP. Lastly, we tested the predictive ability of the Ugandan training sets to predict CBSD in W. African clones. In general, the Ugandan training sets had low prediction accuracies for all traits across models in West African germplasm, varying from -0.18 to 0.1. Based on the findings of this study, the cassava breeding program in Uganda has made progress through application of GS for most target traits, but the utility of the training population for pre-emptive breeding in WA is limiting. In this case, efforts should be devoted to sharing Ugandan germplasm that possess resistance with the W. African breeding programs for hybridization to fully enable deployment of genomic selection as a pre-emptive CBSD breeding strategy in W. Africa.
dc.description.sponsorshipBill & Melinda Gates Foundation
dc.format.extent1-12
dc.language.isoen
dc.subjectCassava
dc.subjectGenomics
dc.subjectViroses
dc.subjectFood Security
dc.subjectClimate Change
dc.subjectModels
dc.subjectUganda
dc.subjectBreeding
dc.titleUtility of Ugandan genomic selection cassava breeding populations for prediction of cassava viral disease resistance and yield in West African clones
dc.typeJournal Article
cg.contributor.crpRoots, Tubers and Bananas
cg.contributor.affiliationNational Crops Resources Research Institute, Uganda
cg.contributor.affiliationMakerere University
cg.contributor.affiliationCornell University
cg.contributor.affiliationNational Root Crops Research Institute, Nigeria
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.coverage.regionAfrica
cg.coverage.regionEast Africa
cg.coverage.countryUganda
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeBiotech and Plant Breeding
cg.identifier.bibtexciteidOZIMATI:2022
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectAgronomy
cg.iitasubjectCassava
cg.iitasubjectFood Security
cg.iitasubjectGenetic Improvement
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Diseases
cg.iitasubjectPlant Genetic Resources
cg.iitasubjectPlant Production
cg.journalFrontiers in Plant Science
cg.notesOpen Access Journal; Published online: 23 Nov 2022
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.3389/fpls.2022.1018156
cg.iitaauthor.identifierChiedozie Egesi: 0000-0002-9063-2727
cg.futureupdate.requiredNo
cg.identifier.issue1018156
cg.identifier.volume13


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