Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel.

Autor: LaPorte MF; Department of Plant Sciences, University of California, Davis, Davis, CA 95616, USA., Suwarno WB; Department of Agronomy and Horticulture, Faculty of Agriculture, IPB University, Bogor 16680, Indonesia., Hannok P; Division of Agronomy, Faculty of Agricultural Production, Maejo University, Chiang Mai 50200, Thailand.; Plant Breeding and Plant Genetics Program, University of Wisconsin-Madison, Madison, WI 53706, USA., Koide A; Department of Plant Sciences, University of California, Davis, Davis, CA 95616, USA., Bradbury P; United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY 14853, USA., Crossa J; International Maize and Wheat Improvement Center (CIMMYT), Km 45 Carretera Mexico-Veracruz, Texcoco 56130, Mexico., Palacios-Rojas N; International Maize and Wheat Improvement Center (CIMMYT), Km 45 Carretera Mexico-Veracruz, Texcoco 56130, Mexico., Diepenbrock CH; Department of Plant Sciences, University of California, Davis, Davis, CA 95616, USA.
Jazyk: angličtina
Zdroj: G3 (Bethesda, Md.) [G3 (Bethesda)] 2024 May 07; Vol. 14 (5).
DOI: 10.1093/g3journal/jkae044
Abstrakt: 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 (β-carotene, β-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 β-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.
Competing Interests: Conflicts of interest The authors declare no conflicts of interest.
(© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.)
Databáze: MEDLINE
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