Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/6381
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dc.contributor.authorClever Mukuzeen_US
dc.contributor.authorUlemu M. Msiskaen_US
dc.contributor.authorAfang Badjien_US
dc.contributor.authorTonny Obuaen_US
dc.contributor.authorSharon V. Kweyuen_US
dc.contributor.authorSelma N. Nghituwamhataen_US
dc.contributor.authorEvalyne C. Ronoen_US
dc.contributor.authorMcebisi Maphosaen_US
dc.contributor.authorFaizo Kasuleen_US
dc.contributor.authorPhinehas Tukamuhabwaen_US
dc.date.accessioned2024-12-11T11:13:05Z-
dc.date.available2024-12-11T11:13:05Z-
dc.date.issued2023-09-24-
dc.identifier.urihttps://cris.library.msu.ac.zw//handle/11408/6381-
dc.description.abstractSoybean is a globally important industrial, food, and cash crop. Despite its importance in present and future economies, its production is severely hampered by bruchids (Callosobruchus chinensis), a destructive storage insect pest, causing considerable yield losses. Therefore, the identification of genomic regions and candidate genes associated with bruchid resistance in soybean is crucial as it helps breeders develop new soybean varieties with improved resistance and quality. In this study, 6 multi-locus methods of the mrMLM model for genome-wide association study were used to dissect the genetic architecture of bruchid resistance using 5 traits: percentage adult bruchid emergence (PBE), percentage weight loss (PWL), growth index (GI), median development period (MDP), and Dobie susceptibility index (DSI) on 100 diverse soybean genotypes, genotyped with 14,469 single-nucleotide polymorphism (SNP) markers. Using the best linear unbiased predictors (BLUPs), 13 quantitative trait nucleotides (QTNs) were identified by the mrMLM model, 3 of which, rs16_14976250, rs1_22916615, and rs16_14975721, were associated with more than 1 bruchid resistance trait. As a result, the identified QTNs linked with resistance traits can be employed in marker-assisted breeding for the accurate and rapid screening of soybean genotypes for resistance to bruchids. Moreover, a gene search on the Phytozome soybean reference genome identified 27 potential candidate genes located within a window of 478.45 kb upstream and downstream of the most reliable QTNs. These candidate genes exhibit molecular and biological functionalities associated with various soybean resistance mechanisms and, therefore, could be incorporated into the farmers’ preferred soybean varieties that are susceptible to bruchids.en_US
dc.language.isoenen_US
dc.publisherCold Spring Harbor Laboratoryen_US
dc.relation.ispartofbioRxiven_US
dc.subjectCallosobruchus chinensisen_US
dc.subjectGlycine maxen_US
dc.subjectsingle-nucleotide polymorphismen_US
dc.subjectGWASen_US
dc.subjectquantitative trait loci (QTL)en_US
dc.subjectcandidate genesen_US
dc.titleGenome-wide association mapping of bruchid resistance loci in soybeanen_US
dc.typepreprinten_US
dc.identifier.doihttps://doi.org/10.1101/2023.09.22.559046-
dc.contributor.affiliationDepartment of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere University, Kampala 7062, Uganda; Department of Crop Science and Post-Harvest Technology, Chinhoyi University of Technology, Private Bag 7724, Chinhoyi, Zimbabween_US
dc.contributor.affiliationDepartment of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere University, Kampala 7062, Uganda;Department of Agri-Sciences, Faculty of Environmental Sciences, Mzuzu University, Luwinga Private Bag 201, Malawien_US
dc.contributor.affiliationDepartment of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere University, Kampala 7062, Ugandaen_US
dc.contributor.affiliationDepartment of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere University, Kampala 7062, Ugandaen_US
dc.contributor.affiliationDepartment of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere University, Kampala 7062, Ugandaen_US
dc.contributor.affiliationDepartment of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere University, Kampala 7062, Ugandaen_US
dc.contributor.affiliationDepartment of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere University, Kampala 7062, Ugandaen_US
dc.contributor.affiliationDepartment of Crop and Soil Science, Faculty of Agricultural Sciences, Lupane State University, Lupane P.O. Box 170, Zimbabwe.en_US
dc.contributor.affiliationNational Agricultural Research Organization (NARO), National Semi-Arid Resources Research Institute, Soroti P.O. Box 56, Ugandaen_US
dc.contributor.affiliationDepartment of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere University, Kampala 7062, Ugandaen_US
dc.description.startpage1en_US
dc.description.endpage27en_US
item.languageiso639-1en-
item.openairetypepreprint-
item.openairecristypehttp://purl.org/coar/resource_type/c_816b-
item.grantfulltextopen-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
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