Dominance effects and functional enrichments improve prediction of agronomic traits in hybrid maize

Guillaume P. Ramstein, Sara J. Larsson, Jason P. Cook, Jode W. Edwards, Elhan S. Ersoz, Sherry Flint-Garcia, Candice A. Gardner, James B. Holland, Aaron J. Lorenz, Michael D. McMullen, Mark J. Millard, Torbert R. Rocheford, Mitchell R. Tuinstra, Peter J. Bradbury, Edward S. Buckler, M. Cinta Romay

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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. This study investigates the relevance of dominance and functional classes of variants in genomic models for agronomic traits in diverse populations of hybrid maize. We based our analyses on a diverse panel of inbred lines crossed with two testers representative of the major heterotic groups in the U.S. (1106 hybrids), as well as a collection of 24 biparental populations crossed with a single tester (1640 hybrids). We investigated three agronomic traits: days to silking (DTS), plant height (PH), and grain yield (GY). Our results point to the presence of dominance for all traits, but also among-locus complementation (epistasis) for DTS and genotype-by-environment interactions for GY. Consistently, dominance improved genomic prediction for PH only. In addition, we assessed enrichment of genetic effects in classes defined by genic regions (gene annotation), structural features (recombination rate and chromatin openness), and evolutionary features (minor allele frequency and evolutionary constraint). We found support for enrichment in genic regions and subsequent improvement of genomic prediction for all traits. Our results suggest that dominance and gene annotations improve genomic prediction across diverse populations in hybrid maize.

Original languageEnglish (US)
Pages (from-to)215-230
Number of pages16
JournalGenetics
Volume215
Issue number1
DOIs
StatePublished - May 2020

Bibliographical note

Funding Information:
We thank the editor and two anonymous reviewers for their comments, which contributed to increase the quality of the manuscript. This work was funded by the National Science Foundation Plant Genome Program (IOS-0820619 and 1238014) and the U.S. Department of Agriculture– Agricultural Research Service. Graduate work of S.J.L., work of E.S.E., and IA10 trials were partially funded by Syngenta.

Funding Information:
We thank the editor and two anonymous reviewers for their comments, which contributed to increase the quality of the manuscript. This work was funded by the National Science Foundation Plant Genome Program (IOS-0820619 and 1238014) and the U.S. Department of Agriculture-Agricultural Research Service. Graduate work of S.J.L., work of E.S.E., and IA10 trials were partially funded by Syngenta.

Publisher Copyright:
Copyright © 2020 Ramstein et al.

Keywords

  • Dominance
  • Functional enrichment
  • Genomic features
  • Genomic prediction
  • Hybrid maize

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

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