Department of Mathematics, Shanghai Normal University, Shanghai 200234, China.
J Plant Physiol. 2011 Apr 15;168(6):611-8. doi: 10.1016/j.jplph.2010.09.010. Epub 2010 Nov 1.
Identification of cis-regulatory elements in Arabidopsis is a key step to understanding its transcriptional regulation scheme. In this study, the Arabidopsis gene coexpression network was constructed using the ATTED-II data, and thereafter a subgraph-induced approach and clique-finding algorithm were used to extract gene coexpression groups from the gene coexpression network. A total of 23 large coexpression gene groups were obtained, with each consisting of more than 100 highly correlated genes. Four classical tools were used to predict motifs in the promoter regions of coexpressed genes. Consequently, we detected a large number of candidate biologically relevant regulatory elements, and many of them are consistent with known cis-regulatory elements from AGRIS and AthaMap. Experiments on coexpressed groups, including E2Fa target genes, showed that our method had a high probability of returning the real binding motif. Our study provides the basis for future cis-regulatory module analysis and creates a starting point to unravel regulatory networks of Arabidopsis thaliana.
鉴定拟南芥的顺式调控元件是理解其转录调控机制的关键步骤。本研究利用 ATTED-II 数据构建了拟南芥基因共表达网络，然后采用子图诱导方法和团块发现算法从基因共表达网络中提取基因共表达群。共获得 23 个大型共表达基因群，每个基因群由 100 多个高度相关的基因组成。使用四种经典工具在共表达基因的启动子区域预测基序。结果检测到大量候选生物相关调控元件，其中许多与 AGRIS 和 AthaMap 中的已知顺式调控元件一致。对共表达基因群（包括 E2Fa 靶基因）的实验表明，我们的方法返回真实结合基序的概率很高。本研究为进一步的顺式调控模块分析提供了基础，并为揭示拟南芥调控网络创造了起点。
