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Improving Prediction of Agronomic Traits in Hybrid Maize

In a paper published in the May 2020 issue of Genetics, Buckler Lab members Guillaume Ramstein and Cinta Romay investigate the relevance of dominance and functional classes of variants in genomic models, for agronomic traits in diverse populations of hybrid maize.



Single-cross hybrids have been critical to the improvement of maize (Zea mays L.), but the characterization of their genetic architectures remains challenging. Previous studies of hybrid maize have shown the contribution of within-locus complementation effects (dominance) and their differential importance across functional classes of loci. However, they have generally considered panels of limited genetic diversity and have shown little benefit from genomic prediction based on dominance or functional enrichments.


The results of this study suggest dominance and gene annotations improve genomic prediction across diverse populations in hybrid maize.


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