Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel
| cg.contributor.affiliation | University of California | en |
| cg.contributor.affiliation | IPB University | en |
| cg.contributor.affiliation | Maejo University | en |
| cg.contributor.affiliation | University of Wisconsin | en |
| cg.contributor.affiliation | United States Department of Agriculture | en |
| cg.contributor.affiliation | International Maize and Wheat Improvement Center | en |
| cg.contributor.donor | United States Department of Energy | en |
| cg.contributor.donor | CGIAR Trust Fund | en |
| cg.contributor.initiative | Accelerated Breeding | |
| cg.creator.identifier | Mary-Francis LaPorte: 0000-0001-5856-2901 | |
| cg.creator.identifier | Willy Bayuardi Suwarno: 0000-0002-7189-7906 | |
| cg.creator.identifier | Pattama Hannok: 0000-0002-7381-182X | |
| cg.creator.identifier | Peter Bradbury: 0000-0003-3825-8480 | |
| cg.creator.identifier | Jose Crossa: 0000-0001-9429-5855 | |
| cg.creator.identifier | natalia palacios rojas: 0000-0002-3072-4611 | |
| cg.creator.identifier | Christine Diepenbrock: 0000-0001-8411-0343 | |
| cg.howPublished | Formally Published | en |
| cg.identifier.doi | https://doi.org/10.1093/g3journal/jkae044 | en |
| cg.isijournal | ISI Journal | en |
| cg.issn | 2160-1836 | en |
| cg.journal | G3: Genes, Genomes, Genetics | en |
| cg.reviewStatus | Peer Review | en |
| dc.contributor.author | LaPorte, Mary-Francis | en |
| dc.contributor.author | Suwarno, Willy Bayuardi | en |
| dc.contributor.author | Hannok, Pattama | en |
| dc.contributor.author | Koide, Akiyoshi | en |
| dc.contributor.author | Bradbury, Peter | en |
| dc.contributor.author | Crossa, José | en |
| dc.contributor.author | Palacios-Rojas, Natalia | en |
| dc.contributor.author | Diepenbrock, Christine | en |
| dc.date.accessioned | 2024-11-21T15:24:39Z | en |
| dc.date.available | 2024-11-21T15:24:39Z | en |
| dc.identifier.uri | https://hdl.handle.net/10568/162526 | |
| dc.title | Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel | en |
| dcterms.abstract | Vitamin A deficiency remains prevalent on a global scale, including in regions where maize constitutes a high percentage of human diets. One solution for alleviating this deficiency has been to increase grain concentrations of provitamin A carotenoids in maize (Zea mays ssp. mays L.)-an example of biofortification. The International Maize and Wheat Improvement Center (CIMMYT) developed a Carotenoid Association Mapping panel of 380 inbred lines adapted to tropical and subtropical environments that have varying grain concentrations of provitamin A and other health-beneficial carotenoids. Several major genes have been identified for these traits, 2 of which have particularly been leveraged in marker-assisted selection. This project assesses the predictive ability of several genomic prediction strategies for maize grain carotenoid traits within and between 4 environments in Mexico. Ridge Regression-Best Linear Unbiased Prediction, Elastic Net, and Reproducing Kernel Hilbert Spaces had high predictive abilities for all tested traits (beta-carotene, beta-cryptoxanthin, provitamin A, lutein, and zeaxanthin) and outperformed Least Absolute Shrinkage and Selection Operator. Furthermore, predictive abilities were higher when using genome-wide markers rather than only the markers proximal to 2 or 13 genes. These findings suggest that genomic prediction models using genome-wide markers (and assuming equal variance of marker effects) are worthwhile for these traits even though key genes have already been identified, especially if breeding for additional grain carotenoid traits alongside beta-carotene. Predictive ability was maintained for all traits except lutein in between-environment prediction. The TASSEL (Trait Analysis by aSSociation, Evolution, and Linkage) Genomic Selection plugin performed as well as other more computationally intensive methods for within-environment prediction. The findings observed herein indicate the utility of genomic prediction methods for these traits and could inform their resource-efficient implementation in biofortification breeding programs. | en |
| dcterms.accessRights | Open Access | |
| dcterms.available | 2024-03-01 | |
| dcterms.bibliographicCitation | LaPorte, M. F., Suwarno, W. B., Hannok, P., Koide, A., Bradbury, P., Crossa, J., Palacios-Rojas, N., & Diepenbrock, C. (2024). Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel. G3: Genes, Genomes, Genetics, 14(5), jkae044. https://doi.org/10.1093/g3journal/jkae044 | en |
| dcterms.hasVersion | https://hdl.handle.net/10883/23155 | en |
| dcterms.issued | 2024-05 | |
| dcterms.language | en | |
| dcterms.license | CC-BY-4.0 | |
| dcterms.publisher | Oxford University Press | en |
| dcterms.subject | genomics | en |
| dcterms.subject | maize | en |
| dcterms.subject | provitamins | en |
| dcterms.subject | carotenoids | en |
| dcterms.subject | biofortification | en |
| dcterms.type | Journal Article |