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dc.contributor.authorAgre, A.P.
dc.contributor.authorNorman, P.E.
dc.contributor.authorAsiedu, R.
dc.contributor.authorAsfaw, A.
dc.date.accessioned2022-01-25T11:42:59Z
dc.date.available2022-01-25T11:42:59Z
dc.date.issued2021
dc.identifier.citationAgre, A.P., Norman, P.E., Asiedu, R. & Asfaw, A. (2021). Identification of quantitative trait nucleotides and candidate genes for tuber yield and mosaic virus tolerance in an elite population of white guinea yam (Dioscorea rotundata) using genome-wide association scan. BMC Plant Biology, 21(1), 1-16.
dc.identifier.issn1471-2229
dc.identifier.urihttps://hdl.handle.net/20.500.12478/7322
dc.description.abstractBackground Improvement of tuber yield and tolerance to viruses are priority objectives in white Guinea yam breeding programs. However, phenotypic selection for these traits is quite challenging due to phenotypic plasticity and cumbersome screening of phenotypic-induced variations. This study assessed quantitative trait nucleotides (QTNs) and the underlying candidate genes related to tuber yield per plant (TYP) and yam mosaic virus (YMV) tolerance in a panel of 406 white Guinea yam (Dioscorea rotundata) breeding lines using a genome-wide association study (GWAS). Results Population structure analysis using 5,581 SNPs differentiated the 406 genotypes into seven distinct sub-groups based delta K. Marker-trait association (MTA) analysis using the multi-locus linear model (mrMLM) identified seventeen QTN regions significant for TYP and five for YMV with various effects. The seveteen QTNs were detected on nine chromosomes, while the five QTNs were identified on five chromosomes. We identified variants responsible for predicting higher yield and low virus severity scores in the breeding panel through the marker-effect prediction. Gene annotation for the significant SNP loci identified several essential putative genes associated with the growth and development of tuber yield and those that code for tolerance to mosaic virus. Conclusion Application of different multi-locus models of GWAS identified 22 QTNs. Our results provide valuable insight for marker validation and deployment for tuber yield and mosaic virus tolerance in white yam breeding. The information on SNP variants and genes from the present study would fast-track the application of genomics-informed selection decisions in breeding white Guinea yam for rapid introgression of the targeted traits through markers validation.
dc.description.sponsorshipBill & Melinda Gates Foundation
dc.format.extent1-16
dc.language.isoen
dc.subjectGenetic Diversity
dc.subjectPopulation Structure
dc.subjectYams
dc.subjectVarieties
dc.subjectNigeria
dc.subjectQuantitative Trait Loci
dc.titleIdentification of quantitative trait nucleotides and candidate genes for tuber yield and mosaic virus tolerance in an elite population of white guinea yam (Dioscorea rotundata) using genome-wide association scan
dc.typeJournal Article
cg.contributor.crpRoots, Tubers and Bananas
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationSierra Leone Agricultural Research Institute
cg.coverage.regionAfrica
cg.coverage.regionWest Africa
cg.coverage.countryNigeria
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeBiotech and Plant Breeding
cg.identifier.bibtexciteidAGRE:2021a
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectAgronomy
cg.iitasubjectFood Security
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Production
cg.iitasubjectYam
cg.journalBMC Plant Biology
cg.notesOpen Access Journal; Published online: 22 Nov 2021
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.1186/s12870-021-03314-w
cg.iitaauthor.identifierPaterne AGRE: 0000-0003-1231-2530
cg.iitaauthor.identifierRobert Asiedu: 0000-0001-8943-2376
cg.iitaauthor.identifierAsrat Asfaw: 0000-0002-4859-0631
cg.futureupdate.requiredNo
cg.identifier.issue1: 552
cg.identifier.volume21


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