基于生物信息学构建阿尔茨海默病内源竞争RNA调控网络
曲浩宁, 朱文韬, 何群中国医科大学生命科学学院生物信息学教研室, 沈阳 110122
收稿日期:
2021-04-22出版日期:
2022-02-28发布日期:
2022-01-05通讯作者:
何群E-mail:qunh@cmu.edu.cn作者简介:
曲浩宁(2000-),男,本科在读.基金资助:
辽宁省大学生创新创业基金(S202010159033)关键词: 阿尔茨海默病, 内源竞争RNA, 长链非编码RNA, 生物信息学
Abstract: Objective To explore the interaction between differential long noncoding RNA (lncRNA) and targeted microRNA (miRNA) and messenger RNA (mRNA) in Alzheimer's disease (AD) and AD pathogenesis. Methods The data were downloaded from the GEO database. Differentially expressed lncRNA and mRNA in the early, middle, and late stages of AD were screened. The targeted miRNA of lncRNA was predicted using the RegRNA web server. The targeted mRNA of miRNA was predicted using TargetScan, TargetMiner, and miRDB. DAVID was used for mRNA enrichment and KEGG pathway analyses. The resulting network was constructed using Cytoscape. Protein-protein interaction analysis of differentially expressed mRNA was performed. The key genes were identified using Cytoscape. Results Select LINC02047, LINC01124, LINC00582, LINC02478 from the pDEFs differentially expressed in the early, mid-late and late stages in the data set GSE28146. Predict the downstream target miRNA of the differential lncRNA, and then predict the downstream mRNA of the target miRNA and construct the lncRNA-miRNA-mRNA regulatory network of AD. Conclusion LINC02047, LINC01124, LINC02478 may influence the occurrence and development of AD through the regulation of miR-4060, miR-4090, miR-4786, miR-3612, miR-1254, and miR-132.
Key words: Alzheimer's disease, competing endogenous RNAs, long non-coding RNA, bioinformatics
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