Time-resolved multiomics analysis of the genetic regulation of maize kernel moisture

Abstract

Maize kernel moisture content (KMC) at harvest greatly affects mechanical harvesting, transport and storage. KMC is correlated with kernel dehydration rate (KDR) before and after physiological maturity. KMC and KDR are complex traits governed by multiple quantitative trait loci (QTL). Their genetic architecture is incompletely understood. We used a multiomics integration approach with an association panel to identify genes influencing KMC and KDR. A genome-wide association study using time-series KMC data from 7 to 70 days after pollination and their transformed KDR data revealed respectively 98 and 279 loci significantly associated with KMC and KDR. Time-series transcriptome and proteome datasets were generated to construct KMC correlation networks, from which respectively 3111 and 759 module genes and proteins were identified as highly associated with KMC. Integrating multiomics analysis, several promising candidate genes for KMC and KDR, including Zm00001d047799 and Zm00001d035920, were identified. Further mutant experiments showed that Zm00001d047799, a gene encoding heat shock 70 kDa protein 5, reduced KMC in the late stage of kernel development. Our study provides resources for the identification of candidate genes influencing maize KMC and KDR, shedding light on the genetic architecture of dynamic changes in maize KMC.

Keywords

• Maize
• Kernel moisture
• Kernel dehydration rate
• GWAS
• Multiomics