Cao Nan-Jue, Liu He-Nan, Dong Feng, Wang Wei, Sun Wei, Wang Gang
Department of Ophthalmology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, Peoples R China.
Department of Ophthalmology, Shengjing Hospital, China Medical University, Shenyang, Liaoning, Peoples R China.
PeerJ. 2020 Jun 29;8:e9452. doi: 10.7717/peerj.9452. eCollection 2020.
Increasing evidence has suggested that non-coding RNAs (ncRNAs) play critical roles in the pathogenesis of diabetic retinopathy (DR), but their underlying mechanisms remain unclear. The purpose of this study was to determine latent key genes and to structure a competing endogenous RNA (ceRNA) regulatory network to discover the potential molecular mechanisms governing the effects of high glucose on human retinal endothelial cells (HRECs).
We obtained microarray data for long non-coding RNA (lncRNA) and mRNA of high-glucose-induced HREC samples from NCBI GEO datasets. The ceRNA network was screened using intersecting prediction results from miRcode, TargetScan, miRTarBase and miRDB. The protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes and hub genes were obtained using the cytoHubba app. The ClusterProfiler package was applied for performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The expression of key RNAs was verified using the qRT-PCR method. A key ceRNA subnetwork was constructed based on the criticality of the genes and its binding sites were verified by luciferase reporter assay. The viability and apoptosis of HRECs were tested using the transfection of the miR-449c inhibitor.
A total of 3,328 lncRNAs and 2,017 mRNAs were screened for differentially expressed (DE) profiles. The newly constructed ceRNA network was composed of 410 lncRNAs, 35 miRNAs and 122 mRNAs. The 10 hub genes were identified through the PPI network. GO and KEGG analysis revealed that DE mRNAs were mainly related to the positive regulation of the mRNA catabolic process, cell polarity, and the G1/S transition of mitotic and cell cycle signaling pathways. QRT-PCR was used to verify RNAs and the most important genes were screened out. A key ceRNA subnetwork OIP5-AS1/miR-449c/MYC was established. The binding site was verified by luciferase reporter assay. The expression levels of OIP5-AS1 and MYC increased after miR-449c inhibitor transfection, miR-449c decreased, HRECs activity increased, and apoptosis decreased, compared with the control group.
We successfully built the key ceRNA subnetwork, OIP5-AS1/miR-449c/MYC, by applying the GEO database for data analysis and mining. The results from the ceRNA network allow us to better understand the effect of ncRNAs on HRECs under hyperglycemic conditions and the pathogenesis of DR.
越来越多的证据表明,非编码RNA(ncRNAs)在糖尿病视网膜病变(DR)的发病机制中起关键作用,但其潜在机制仍不清楚。本研究的目的是确定潜在的关键基因,并构建一个竞争性内源性RNA(ceRNA)调控网络,以发现高糖对人视网膜内皮细胞(HRECs)影响的潜在分子机制。
我们从NCBI GEO数据集中获取了高糖诱导的HREC样本的长链非编码RNA(lncRNA)和mRNA的微阵列数据。使用miRcode、TargetScan、miRTarBase和miRDB的交叉预测结果筛选ceRNA网络。使用基因相互作用检索工具构建蛋白质-蛋白质相互作用(PPI)网络,并使用cytoHubba应用程序获得枢纽基因。应用ClusterProfiler软件包进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)通路分析。使用qRT-PCR方法验证关键RNA的表达。基于基因的关键性构建关键ceRNA子网,并通过荧光素酶报告基因检测验证其结合位点。使用miR-449c抑制剂转染测试HRECs的活力和凋亡。
共筛选出3328个lncRNAs和2017个mRNAs的差异表达(DE)谱。新构建的ceRNA网络由410个lncRNAs、35个miRNAs和122个mRNAs组成。通过PPI网络鉴定出10个枢纽基因。GO和KEGG分析显示,DE mRNAs主要与mRNA分解代谢过程的正调控、细胞极性以及有丝分裂和细胞周期信号通路的G1/S转变有关。使用qRT-PCR验证RNA,并筛选出最重要的基因。建立了关键ceRNA子网OIP5-AS1/miR-449c/MYC。通过荧光素酶报告基因检测验证结合位点。与对照组相比,miR-449c抑制剂转染后,OIP5-AS1和MYC的表达水平升高,miR-449c降低,HRECs活性增加,凋亡减少。
我们通过应用GEO数据库进行数据分析和挖掘,成功构建了关键ceRNA子网OIP5-AS1/miR-449c/MYC。ceRNA网络的结果使我们能够更好地理解ncRNAs在高血糖条件下对HRECs的影响以及DR的发病机制。