Genetic basis of maize resistance to multiple insect pests: integrated genome-wide comparative mapping and candidate gene prioritization

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dc.creatorBadji, Arfang
dc.creatorKwemoi, Daniel Bomet
dc.creatorMachida, Lewis
dc.creatorOkii, Dennis
dc.creatorMwila, Natasha
dc.creatorAgbahoungba, Symphorien
dc.creatorKumi, Frank
dc.creatorIbanda, Angele
dc.creatorBararyenya, Astere
dc.creatorSolemanegy, Marta
dc.creatorOdong, Thomas L.
dc.creatorWasswa, Peter
dc.creatorOtim, Michael
dc.creatorAsea, Godfrey
dc.creatorOchwo-Ssemakula, Mildred
dc.creatorTalwana, Herbert A.L.
dc.creatorKyamanywa, Samuel
dc.creatorRubaihayo, Patrick
dc.date2020-12
dc.date2021-01-11T08:49:27Z
dc.date2021-01-11T08:49:27Z
dc.date.accessioned2026-06-27T13:21:30Z
dc.descriptionSeveral species of herbivores feed on maize in field and storage setups, making the development of multiple insect resistance a critical breeding target. In this study, an association mapping panel of 341 tropical maize lines was evaluated in three field environments for resistance to fall armyworm (FAW), whilst bulked grains were subjected to a maize weevil (MW) bioassay and genotyped with Diversity Array Technology’s single nucleotide polymorphisms (SNPs) markers. A multi-locus genome-wide association study (GWAS) revealed 62 quantitative trait nucleotides (QTNs) associated with FAW and MW resistance traits on all 10 maize chromosomes, of which, 47 and 31 were discovered at stringent Bonferroni genome-wide significance levels of 0.05 and 0.01, respectively, and located within or close to multiple insect resistance genomic regions (MIRGRs) concerning FAW, SB, and MW. Sixteen QTNs influenced multiple traits, of which, six were associated with resistance to both FAWandMW, suggesting a pleiotropic genetic control. Functional prioritization of candidate genes (CGs) located within 10–30 kb of the QTNs revealed 64 putative GWAS-based CGs (GbCGs) showing evidence of involvement in plant defense mechanisms. Only one GbCG was associated with each of the five of the six combined resistance QTNs, thus reinforcing the pleiotropy hypothesis. In addition, through in silico co-functional network inferences, an additional 107 network-based CGs (NbCGs), biologically connected to the 64 GbCGs, and di erentially expressed under biotic or abiotic stress, were revealed within MIRGRs. The provided multiple insect resistance physical map should contribute to the development of combined insect resistance in maize.
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/110812
dc.identifier.urihttp://hdl.handle.net/123456789/56838
dc.languageen
dc.publisherMDPI
dc.rightsOpen Access
dc.sourceBadji, A.; Kwemoi, D.; Bomet; Machida, L.; Okii, D.; Mwila, N.; Agbahoungba, S.; Kumi, F.; Ibanda, A.; Bararyenya, A.; Solemanegy, M.; Odong , T.; Wasswa, P.; Otim, M.; Asea, G.; Ochwo-Ssemakula, M.; Talwana, H.; Kyamanywa, S.; Rubaihayo, P. (2020) Genetic basis of maize resistance to multiple insect pests: integrated genome-wide comparative mapping and candidate gene prioritization. Genes 11(6) p. 689 ISSN: 2073-4425
dc.subjectpest insects
dc.subjectgenomes
dc.subjectpest resistance
dc.subjectcontrol methods
dc.subjectiinsectos dañinos
dc.subjectgenomas
dc.subjectresistencia a las plagas
dc.subjectgenetics
dc.titleGenetic basis of maize resistance to multiple insect pests: integrated genome-wide comparative mapping and candidate gene prioritization
dc.typeJournal Article

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