An expression quantitative trait loci-guided co-expression analysis for constructing regulatory network using a rice recombinant inbred line population.
An expression quantitative trait loci-guided co-expression analysis for constructing regulatory network using a rice recombinant inbred line population.
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表达数量性状位点引导的共表达分析，用于利用水稻重组自交系群体构建调控网络
DOI：
10.1093/jxb/ert464
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发表时间：
2014-03
影响因子：
6.9
通讯作者：
Zhang Q
中科院分区：
文献类型：
--
作者：
Wang J;Yu H;Weng X;Xie W;Xu C;Li X;Xiao J;Zhang Q
通过构建调控网络在全基因组水平上揭示基因调控体系的能力，对于理解生物的生物学过程和发育计划至关重要。在这里，我们进行了eQTL引导的功能相关共表达分析，以确定可能的调控因子，并构建基因调控网络。利用水稻抽穗期剑叶RNA样品与Affymetrix全基因组芯片杂交获得的数据，对来自两个优质杂交稻亲本珍珊97和明恢63的210个重组自交系进行了eQTL分析。利用群体测序构建的超高密度单核苷酸多态结合图，共检测到10725个e性状的13647个eQTL，其中顺式eQTL 5079个(37.2%)，反式eQTL 8568个(62.8%)。分析发现了138个反式eQTL热点，每个热点都明显调控着许多基因的表达差异。在eQTL概述的调控-靶关系框架内对功能相关基因的共表达分析导致了系统中可能的调控因子的识别。已知的与开花有关的基因证明了这一策略的有效性。我们还将这一策略应用于产量性状的QTL分析，也提出了可能的候选基因。EQTL引导的共表达分析可能为勾勒生物体复杂调控网络的框架提供一个有前途的解决方案。
The ability to reveal the regulatory architecture of genes at the whole-genome level by constructing a regulatory network is critical for understanding the biological processes and developmental programmes of organisms. Here, we conducted an eQTL-guided function-related co-expression analysis to identify the putative regulators and construct gene regulatory network. We performed an eQTL analysis of 210 recombinant inbred lines (RILs) derived from a cross between two indica rice lines, Zhenshan 97 and Minghui 63, the parents of an elite hybrid, using data obtained by hybridizing RNA samples of flag leaves at the heading stage with Affymetrix whole-genome arrays. Making use of an ultrahigh-density single-nucleotide polymorphism bin map constructed by population sequencing, 13 647 eQTLs for 10 725 e-traits were detected, comprising 5079 cis-eQTLs (37.2%) and 8568 trans-eQTLs (62.8%). The analysis revealed 138 trans-eQTLs hotspots, each of which apparently regulates the expression variations of many genes. Co-expression analysis of functionally related genes within the framework of regulator–target relationships outlined by the eQTLs led to the identification of putative regulators in the system. The usefulness of the strategy was demonstrated with the genes known to be involved in flowering. We also applied this strategy to the analysis of QTLs for yield traits, which also suggested likely candidate genes. eQTL-guided co-expression analysis may provide a promising solution for outlining a framework for the complex regulatory network of an organism.
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