Genomic prediction with genotype by environment interaction analysis for kernel zinc concentration in tropical maize germplasm

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cg.authorship.typesCGIAR and developing country instituteen
cg.contributor.crpAgriculture for Nutrition and Healthen
cg.contributor.donorIowa State Universityen
cg.contributor.donorCGIAR Trust Funden
cg.identifier.doihttps://doi.org/10.1534/g3.120.401172en
cg.identifier.projectIFPRI - HarvestPlusen
cg.isijournalISI Journalen
cg.issn2160-1836en
cg.issue8en
cg.journalG3: Genes Genomes Geneticsen
cg.reviewStatusPeer Reviewen
cg.volume10en
dc.contributor.authorMageto, Edna K.en
dc.contributor.authorCrossa, Joséen
dc.contributor.authorPérez-Rodríguez, Paulinoen
dc.contributor.authorDhliwayo, Thandaen
dc.contributor.authorPalacios-Rojas, Nataliaen
dc.date.accessioned2025-01-29T12:58:06Zen
dc.date.available2025-01-29T12:58:06Zen
dc.identifier.urihttps://hdl.handle.net/10568/171386
dc.titleGenomic prediction with genotype by environment interaction analysis for kernel zinc concentration in tropical maize germplasmen
dcterms.abstractZinc (Zn) deficiency is a major risk factor for human health, affecting about 30% of the world’s population. To study the potential of genomic selection (GS) for maize with increased Zn concentration, an association panel and two doubled haploid (DH) populations were evaluated in three environments. Three genomic prediction models, M (M1: Environment + Line, M2: Environment + Line + Genomic, and M3: Environment + Line + Genomic + Genomic x Environment) incorporating main effects (lines and genomic) and the interaction between genomic and environment (G x E) were assessed to estimate the prediction ability (rMP) for each model. Two distinct cross-validation (CV) schemes simulating two genomic prediction breeding scenarios were used. CV1 predicts the performance of newly developed lines, whereas CV2 predicts the performance of lines tested in sparse multi-location trials. Predictions for Zn in CV1 ranged from -0.01 to 0.56 for DH1, 0.04 to 0.50 for DH2 and -0.001 to 0.47 for the association panel. For CV2, rMP values ranged from 0.67 to 0.71 for DH1, 0.40 to 0.56 for DH2 and 0.64 to 0.72 for the association panel. The genomic prediction model which included G x E had the highest average rMP for both CV1 (0.39 and 0.44) and CV2 (0.71 and 0.51) for the association panel and DH2 population, respectively. These results suggest that GS has potential to accelerate breeding for enhanced kernel Zn concentration by facilitating selection of superior genotypes.en
dcterms.accessRightsOpen Accessen
dcterms.available2020-08-01en
dcterms.bibliographicCitationMageto, Edna K.; Crossa, Jose; Pérez-Rodríguez, Paulino; Dhliwayo, Thanda; Palacios-Rojas, Natalia; et al. 2020. Genomic prediction with genotype by environment interaction analysis for kernel zinc concentration in tropical maize germplasm. G3 Genes Genomes Genetics 10(8): 2629–2639. https://doi.org/10.1534/g3.120.401172en
dcterms.extentpp. 2629-2639en
dcterms.issued2020-08-01en
dcterms.languageenen
dcterms.licenseCopyrighted; all rights reserveden
dcterms.publisherOxford University Pressen
dcterms.subjectgeneticsen
dcterms.subjectbreedingen
dcterms.subjectzincen
dcterms.subjectforecastingen
dcterms.subjectmaizeen
dcterms.typeJournal Articleen

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