摘要
通过生物信息学方法预测hsa-miR-342-3p靶基因及其功能机制。检索Pub Med有关hsa-miR-342-3p的研究报道并进行功能分析;检索miRBase获取hsa-miR-342-3p序列;通过Target Scan,Pictar和PITA数据库预测靶基因并取交集,对其进行组织和疾病特异性表达谱分析、功能富集分析(GO enrichment analysis)、信号转导通路富集分析(Pathway enrichment analysis)和蛋白质相互作用网络分析(PPI analysis)。结果发现:hsa-miR-342-3p序列在多物种间具有高度保守性;hsa-miR-342-3p在肾脏组织和急性淋巴细胞性白血病、乳腺癌疾病中表达水平较高(RPM≥1 000);预测得到14个hsa-miR-342-3p靶基因;靶基因分子功能分别富集于转化生长因子活性、DNA结合和蛋白激酶激活等(P<0.05);hsa-miR-342-3p靶基因GO生物学过程主要集中于大分子代谢抑制,肺部组织发育、呼吸系统发育及管状组织发育建成(P<0.05);细胞信号通路主要富集于TGF-Beta信号通路、细胞因子、受体作用信号通路及前列腺疾病信号通路(P<0.01)。hsa-miR-342-3p在体内分布广泛,预测的靶向TGF-Beta信号通路可能在疾病发生中发挥重要调控作用,是具有潜在研究价值的生物学靶标。
To predict the target genes of the hsa-miR-342-3p and its function by bioinformatics analysis. All relevant studies of hsa-miR-342-3p were searched in Pub Med and reviewed. The sequence of hsa-miR-342-3p was obtained from miRBase. Target Scan,Pictar and PITA were used to do intersection dataset of the target genes of hsa-miR-342-3p. The bioinformatics analysis of the target genes of hsa-miR-342-3p involved tissue and disease specific expression profile analysis,enrichment( gene ontology,GO),signal transduction pathway enrichment and protein interaction network analyses. The results showed that hsa-miR-342-3p sequences were highly conserved in various species. hsamiR-342-3p had relatively high expression in kidney and disease of ALL,breast cancer( RPM≥1 000). There were14 target genes of hsa-miR-342-3p identified. GO analyses showed that hsa-miR-342-3p target genes were enriched in growth factor activity,DNA binding and protein kinase activity( GO molecular function,P 0.05),and enriched in positive regulation of macromolecule metabolic process,lung development,tube development and respiratory tube development( GO biology process,P0.05); Pathway analyses showed that the target genes set mainly located in TGF-Beta signaling pathway,cytokine-cytokine receptor interaction signaling pathway and prostate disease pathway( P0.01).The conclusion is hsa-miR-342-3p may be involved in the diseases via TGF-Beta signaling pathway,which might be a potential biological marker for further investigation.
出处
《生物信息学》
2015年第4期212-219,共8页
Chinese Journal of Bioinformatics
基金
宁夏医科大学2014年度校级科研项目(XM201401)