Hybrid performance in maize predicted with combinations of omics data

ABSTRACT: We explored genomics, transcriptomics (mRNA and sRNA) and metabolomics of maize parent lines as predictors for agronomic performance of single-cross hybrids. Our results indicate that the merit of any individual predictor is trait dependent and that combining predictors has advantages for application across traits. We conclude that downstream “omics” can complement genomics for hybrid prediction and thereby contribute to more efficient selection of hybrid candidates.

ORGANISM(S): Zea mays

PROVIDER: GSE106098 | GEO | 2017/10/31

SECONDARY ACCESSION(S): PRJNA416346

REPOSITORIES: GEO