卵巢早衰患者颗粒细胞关键LncRNAs的生物信息学分析

Bioinformatics analysis of key LncRNAs in granulosa cells of patients with premature ovarian failure

目的通过生物信息学分析筛选卵巢早衰(premature ovarian failure,POF)患者的差异表达长链非编码RNA(long non-coding RNA,LncRNAs),研究POF病理机制,预测潜在治疗靶点。方法选取GEO数据库中与POF相关的基因芯片,利用GEO2R在线分析软件筛选颗粒细胞中差异表达LncRNAs。通过mircode数据库和miRNA靶基因预测网站预测靶基因,采用Cytoscape 3.7.2软件绘制基因交互作用网络模型。在DAVID数据库进行基因本体论(gene ontology,GO)和京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)富集分析。结果共筛选出1110个差异表达LncRNAs(P<0.01,|log_(2)FC|≥1.0,FC为差异倍数),其中上调基因905个,下调基因205个,其靶基因主要与金属离子跨膜转运蛋白活性、DNA与转录因子结合能力、蛋白质丝氨酸/苏氨酸激酶活性相关,并且主要富集于PI3K-Akt、MAPK、Rap1、Ras、钙离子信号通路中。结论利用生物信息学分析差异表达LncRNAs的靶基因功能和通路,进一步探讨POF的病理机制,为寻找新的治疗靶点提供启发。

Objective To study the molecular mechanism and potential therapeutic targets of premature ovarian failure(POF)by screening the differentially expressed genes(DEGs)through bioinformatics analysis.Methods The gene microarrays related with POF were selected from GEO database,the GEO2R online analysis tool was used to screen for DEGs.Target genes were predicting from the mircode database and miRNA-target genes predicting website,network model of gene interaction was constructed by the Cytoscape 3.7.2.GO and KEGG analysis of target genes were performed on DAVID database.Results A total of 1110 DEGs were screened(P<0.01,|log_(2)FC|≥1.0),including 905 up-regulated genes and 205 down-regulated genes,target genes of which mainly associated with metal ion transmembrane transporter activity,DNA and transcription factor binding ability,protein serine/threonine kinase activity were involved in PI3K-Akt、MAPK、Rap1、Ras and Ca^(2+)signal pathways.Conclusion This study indicates that screening for DEGs then analyzing pathways and functions of target genes could help to understand the molecular mechanism of POF,and provide with new therapeutic targets for POF.