Mapping regulatory variants controlling gene expression in drought response and tolerance in maize

生物 基因 遗传学 基因表达 耐旱性 遗传建筑学 表型 调节顺序 基因表达调控 表达数量性状基因座 计算生物学 单核苷酸多态性 基因型 植物
作者
Shengxue Liu,Cuiping Li,Hongwei Wang,Shuhui Wang,Shiping Yang,Xiaohu Liu,Jianbing Yan,Bailin Li,Mary Beatty,Gina Zastrow‐Hayes,Shuhui Song,Feng Qin
出处
期刊:Genome Biology [Springer Nature]
卷期号:21 (1) 被引量:99
标识
DOI:10.1186/s13059-020-02069-1
摘要

Abstract Background Gene expression is a key determinant of cellular response. Natural variation in gene expression bridges genetic variation to phenotypic alteration. Identification of the regulatory variants controlling the gene expression in response to drought, a major environmental threat of crop production worldwide, is of great value for drought-tolerant gene identification. Results A total of 627 RNA-seq analyses are performed for 224 maize accessions which represent a wide genetic diversity under three water regimes; 73,573 eQTLs are detected for about 30,000 expressing genes with high-density genome-wide single nucleotide polymorphisms, reflecting a comprehensive and dynamic genetic architecture of gene expression in response to drought. The regulatory variants controlling the gene expression constitutively or drought-dynamically are unraveled. Focusing on dynamic regulatory variants resolved to genes encoding transcription factors, a drought-responsive network reflecting a hierarchy of transcription factors and their target genes is built. Moreover, 97 genes are prioritized to associate with drought tolerance due to their expression variations through the Mendelian randomization analysis. One of the candidate genes, Abscisic acid 8′-hydroxylase , is verified to play a negative role in plant drought tolerance. Conclusions This study unravels the effects of genetic variants on gene expression dynamics in drought response which allows us to better understand the role of distal and proximal genetic effects on gene expression and phenotypic plasticity. The prioritized drought-associated genes may serve as direct targets for functional investigation or allelic mining.
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