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

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 98and 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.

Genome assembly of KA105,a new resource for maize molecular breeding and genomic research

Superior inbred lines are central to maize breeding as sources of natural variation.Although many elite lines have been sequenced,less sequencing attention has been paid to newly developed lines.We constructed a genome assembly of the elite inbred line KA105,which has recently been developed by an arti-ficial breeding population named Shaan A and has shown desirable characteristics for breeding.Its pedigree showed genetic divergence from B73 and other lines in its pedigree.Comparison with the B73 reference genome revealed extensive structural variation,58 presence/absence variation(PAV)genes,and 1023 expanded gene families,some of which may be associated with disease resistance.A network-based integrative analysis of stress-induced transcriptomes identified 13 KA105-specific PAV genes,of which eight were induced by at least one kind of stress,participating in gene modules responding to stress such as drought and southern leaf blight disease.More than 200,000 gene pairs were differentially correlated between KA105 and B73 during kernel development.The KA105 reference genome and transcriptome atlas are a resource for further germplasm improvement and surveys of maize genomic variation and gene function.