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Genomic prediction of the performance of tropical doubled haploid maize mines under artificial Striga hermonthica (Del.) Benth. infestation

dc.contributor.authorKimutai, J.J.C.
dc.contributor.authorMakumbi, D.
dc.contributor.authorBurgueno, J.
dc.contributor.authorPerez-Rodriguez, P.
dc.contributor.authorCrossa, J.
dc.contributor.authorGowda, M.
dc.contributor.authorMenkir, A.
dc.contributor.authorPacheco, A.
dc.contributor.authorIfie, B.E.
dc.contributor.authorTongoona, P.
dc.contributor.authorDanquah, E.Y.
dc.contributor.authorPrasanna, B.M.
dc.date.accessioned2024-10-02T09:56:23Z
dc.date.available2024-10-02T09:56:23Z
dc.date.issued2024-08-12
dc.identifier.citationKimutai, J.J.C., Makumbi, D., Burgueño, J., Pérez-Rodríguez, P., Crossa, J., Gowda, M., ... & Prasanna, B.M. (2024). Genomic prediction of the performance of tropical doubled haploid maize lines under artificial Striga hermonthica (Del.) Benth. infestation. G3: Genes, Genomes, Genetics, 1-13.
dc.identifier.issn2160-1836
dc.identifier.urihttps://hdl.handle.net/20.500.12478/8564
dc.description.abstractStriga hermonthica (Del.) Benth., a parasitic weed, causes substantial yield losses in maize production in sub-Saharan Africa. Breeding for Striga resistance in maize is constrained by limited genetic diversity for Striga resistance within the elite germplasm and phenotyping capacity under artificial Striga infestation. Genomics-enabled approaches have the potential to accelerate identification of Striga resistant lines for hybrid development. The objectives of this study were to evaluate the accuracy of genomic selection for traits associated with Striga resistance and grain yield (GY) and to predict genetic values of tested and untested doubled haploid maize lines. We genotyped 606 doubled haploid lines with 8,439 rAmpSeq markers. A training set of 116 doubled haploid lines crossed to 2 testers was phenotypes under artificial Striga infestation at 3 locations in Kenya. Heritability for Striga resistance parameters ranged from 0.38–0.65 while that for GY was 0.54. The prediction accuracies for Striga resistance-associated traits across locations, as determined by cross-validation (CV) were 0.24–0.53 for CV0 and from 0.20 to 0.37 for CV2. For GY, the prediction accuracies were 0.59 and 0.56 for CV0 and CV2, respectively. The results revealed 300 doubled haploid lines with desirable genomic estimated breeding values for reduced number of emerged Striga plants (STR) at 8, 10, and 12 weeks after planting. The genomic estimated breeding values of doubled haploid lines for Striga resistance-associated traits in the training and testing sets were similar in magnitude. These results highlight the potential application of genomic selection in breeding for Striga resistance in maize. The integration of genomic-assisted strategies and doubled haploid technology for line development coupled with forward breeding for major adaptive traits will enhance genetic gains in breeding for Striga resistance in maize.
dc.description.sponsorshipBill & Melinda Gates Foundation
dc.description.sponsorshipUS Foundation for Food and Agriculture Research
dc.description.sponsorshipUnited States Agency for International Development
dc.format.extent1-13
dc.language.isoen
dc.subjectStriga Hermonthica
dc.subjectMaize
dc.subjectBreeding
dc.subjectGenomics
dc.subjectPhenotypes
dc.titleGenomic prediction of the performance of tropical doubled haploid maize mines under artificial Striga hermonthica (Del.) Benth. infestation
dc.typeJournal Article
cg.contributor.crpMaize
cg.contributor.affiliationInternational Maize and Wheat Improvement Center
cg.contributor.affiliationUniversity of Ghana
cg.contributor.affiliationEstadística e Informática, Colegio de Postgraduados, Mexico
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationAberystwyth University
cg.coverage.regionAfrica
cg.coverage.regionEast Africa
cg.coverage.countryKenya
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeBiotech and Plant Breeding
cg.identifier.bibtexciteidKIMUTAI:2024
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectAgronomy
cg.iitasubjectFood Security
cg.iitasubjectGenetic Improvement
cg.iitasubjectMaize
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Production
cg.journalG3-Genes Genomes Genetics
cg.notesOpen Access Journal
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://doi.org/10.1093/g3journal/jkae186
cg.iitaauthor.identifierAbebe Menkir: 0000-0002-5907-9177
cg.futureupdate.requiredNo


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