利用WGCNA方法分析稻瘟病抗性相关的基因共表达网络

Analysis of Gene Co-expression Network Related to Rice Blast Resistance Using WGCNA Method

加权基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)常用于分析多样本(>15)数据,鉴定协同表达的基因模块,探索共表达模块与目标性状的相关性。为探究携带不同广谱抗性基因的水稻近等基因系(near iso-genic lines,NIL)在应对稻瘟菌(Magnaporthe oryzae)侵染时基因的共表达网络。本研究以GEO数据库中的RNA-seq数据GSE117030为基础,利用WGCNA方法分析携带不同广谱抗性基因的水稻近等基因系在应对稻瘟菌侵染时的基因表达情况,构建加权基因共表达网络,共得到23个共表达模块。根据表达模式差异并结合抗性表型,本试验选择tan模块和midnightblue模块作为目标模块。GO富集分析表明,两个目标模块内的基因大多富集在细胞成分(Cellular component)层面。分别对两个目标模块内的基因进行共表达网络构建,从共表达网络中筛选出了部分核心基因,如LOC_Os01g03880.1。本研究结果为进一步理解水稻广谱抗性基因的抗性机制、选育抗稻瘟病新品种提供了参考。

Weighted gene co-expression network analysis(WGCNA)is often used to analyze multi-sample(>15)data,identify co-expressed gene modules,and explore the relationship between co-expression modules and target traits in systematic biology.In order to explore the gene co-expression network in response to Magnaporthe oryzae infection in rice near iso-genic lines(NIL)carrying different broad-spectrum resistance genes.We analyzed the expression pattern of genes by WGCNA based on the data of GSE117030 form the GEO database and identified 23co-expression modules.Combining expression patterns with phenotypes,we chose tan module and midnightblue module as target modules.GO enrichment analysis showed that most of the genes in the target module were related to cell components.A co-expression network was constructed for the genes in the target module,and some hub genes were screened out.These results provide reference into further understanding the mechanism of broad-spectrum resistance genes and breeding rice varieties with disease resistance.