利用WGCNA鉴定非生物胁迫相关基因共表达网络

加权共表达网络分析(Weighted Gene Co-expression Network Analysis, WGCNA)是用来描述不同样品之间基因关联模式的系统生物学方法,可以用来鉴定高度协同变化的基因集。本研究利用正常水稻组织共47份转录组数据,通过冷胁迫、干旱胁迫、盐胁迫不同的处理方式,使用WGCNA方法,根据已克隆基因的报道与以上3种胁迫相关的关键基因,探究不同逆境下基因之间的调控关系。通过对低表达量基因的过滤,最终利用筛选的30,339个表达的基因来构建共表达矩阵,得到15个模块。分析发现已知的水稻3种相关基因在各个模块均有存在,于是对预测到的靶基因进行GO富集分析。对3种胁迫下处理的转录组数据进行差异表达基因分析,结合已报道与胁迫相关的基因,选取各胁迫相关的2个模块进行了基因调控网络的构建。鉴于3种胁迫相关基因在green模块中大量分布,通过对green模块下各自特有的基因和共有的基因的GO功能富集分析,并对共有的基因构建调控网络,挖掘到2599个与3种胁迫都相关的基因,并预测出25个抗逆相关的关键基因,为水稻的抗逆及综合抗逆能力等研究提供了新思路。

Identification of rice stress-related gene co-expression modules by WGCNA

Weighted Gene Co-expression Network Analysis (WGCNA) is a systematic biological method describing gene association patterns among different samples. It can be used to identify synergistically altered gene sets. In this study, 47 transcriptome data of rice tissues specimens were used to explore the regulation relationship between genes under harsh environmental conditions (cold, drought, and salt) try WGCNA method. By filtering the low expressed genes, the co-expression matrix was finally constructed using the screened 30,339 expressed genes. Subsequently, 15 modules were obtained. The reports of cloned key genes under those three stresses existed in each module, so the GO enrichment analysis was performed on the predicted target genes. The differentially expressed genes were analyzed by transcriptome data under harsh conditions, and combined with the reported stress-related genes, two stress-related modules were selected to construct the gene regulatory network. In consideration of a large number of genes related to the mentioned harsh situations in the green module, the GO functional enrichment analysis was carried out for the three kinds of stress genes under the green module, and the gene regulatory network was constructed for the common genes. In summary, 2599 harsh environmental situations-related genes were mined. Meanwhile, 25 key genes related to stress resistance were predicted. Our results on stress resistance and comprehensive stress resistance open a new window for future studies.