Kernel size-related genes revealed by an integrated eQTL analysis during early maize kernel development

文献类型： 外文期刊

第一作者： Pang, Junling

作者： Pang, Junling;Zong, Na;Wang, Jing;Song, Dandan;Zhang, Xia;Fan, Yunliu;Zhao, Jun;Fu, Junjie;He, Cheng;Fang, Ting;Zhang, Hongwei;Wang, Guoying

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关键词： expression quantitative trait loci; complex trait; m(6)A RNA modification; kernel development; Zea mays L

期刊名称：PLANT JOURNAL （ 影响因子：6.417； 五年影响因子：7.627 ）

ISSN： 0960-7412

年卷期： 2019 年 98 卷 1 期

页码：

收录情况： SCI

摘要： In maize, kernel traits strongly impact overall grain yields, and it is known that sophisticated spatiotemporal programs of gene expression coordinate kernel development, so advancing our knowledge of kernel development can help efforts to improve grain yields. Here, using phenotype, genotype and transcriptomics data of maize kernels at 5 and 15 days after pollination (DAP) for a large association mapping panel, we employed multiple quantitative genetics approaches-genome-wide association studies (GWAS) as well as expression quantitative trait loci (eQTL) and quantitative trait transcript (QTT) analyses-to gain insights about molecular genetic basis of kernel development in maize. This resulted in the identification of 137 putative kernel length-related genes at 5 DAP, of which 43 are located in previously reported QTL regions. Strikingly, we identified an eQTL that overlaps the locus encoding a maize homolog of the recently described m(6)A methylation reader protein ECT2 from Arabidopsis; this putative (epi)eQTL is associated with 53 genes and may represent a master epi-transcriptomic regulator of kernel development. Notably, among the genes associated with this (epi)eQTL, 10 are for the main storage proteins in the maize endosperm (zeins) and two are known regulators of zein expression or endosperm development (Opaque2 and ZmICE1). Collectively, beyond cataloging and characterizing genomic attributes of a large number of eQTL associated with kernel development in maize, our study highlights how an eQTL approach can bolster the impact of both GWAS and QTT studies and can drive insights about the basic biology of plants.

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