胆道闭锁相关基因的生物信息学分析和功能预测

Bioinformatics analysis and function prediction of biliary atresia-related genes

目的运用生物信息学技术分析胆道闭锁发生、发展的潜在生物学过程和关键基因。方法从公共数据库平台(GEO)下载胆道闭锁相关的基因芯片数据,运用R语言分析与胆道闭锁高度相关的差异基因;对差异基因进行KEGG分析后,阐述其主要参与的信号通路。对差异基因构建蛋白质相互作用网络,从中筛选出主要的信息模块。同时,运用GSEA筛选出胆道闭锁中差异较显著的两条信号通路,富集出Core Enrichment Gene与主要模块中的基因做交集,检测不同基因对胆道闭锁诊断的准确度。结果一共筛选出了146个与胆道闭锁紧密相关的差异基因,KEGG分析指出其主要与细胞外基质-受体相互作用及黏附等信号通路相关。构建蛋白质相互作用网络后,从中筛选出含有21个差异基因的模块。GSEA筛选结果指出,在胆道闭锁中差异较显著的两条信号通路为细胞外基质-受体相互作用及黏附。富集出79个Core Enrichment Gene与21个差异基因做交集后得到11个差异基因,其中JUN联合LAMC2在肝组织中的表达诊断胆道闭锁的准确度为96.4%。结论生物信息学分析表明,细胞外基质-受体相互作用及黏附可能与胆道闭锁的发生、发展密切相关,有11个关键差异基因可能在该过程中起到了重要作用,且JUN和LAMC2对于诊断胆道闭锁具有重要意义。

Objective This paper aims to analyze potential biological processes and key genes for the development of biliary atresia by using bioinformatics techniques.Methods The gene chip related to biliary atresia from public database platform(GEO)was downloaded and R software packages were used to analyze differentially expressed genes highly correlated with biliary atresia.After the KEGG analysis of differentially expressed genes,the main signaling pathways involved were described.Then,a protein-protein interaction network was constructed and the main modules were screened out.Meanwhile,GSEA was used to screen the top two signal pathways related to biliary atresia and Core Enrichment Gene was enriched,which were intersected with the genes in the main module to measure the accuracy of different genes in the diagnosis of biliary atresia.Results A total of 146 differentially expressed genes were screened out which were closely related to biliary atresia.The KEGG analysis showed that this was mainly involved in biological processes such as ECM-receptor interaction and focal adhesion.After constructing a protein-protein interaction network,a main module we found including 21 differentially expressed genes.The GSEA indicated that the top two signal pathways related to biliary atresia were ECM-receptor interaction and focal adhesion.Seventy-nine Core Enrichment Genes were enriched and 21 differential genes were intersected to obtain 11 differential genes,of which,the accuracy of JUN combined with LAMC2 expression in the diagnosis of biliary atresia was 96.4%.Conclusions The bioinformatics analysis demonstrates that ECM-receptor interaction and focal adhesion may play an important role in the development of biliary atresia,the 11 differential genes may play an important role in this process,and JUN and LAMC2 are important for the diagnosis of biliary atresia.