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基于竞争性内源性 RNA 构建 lncRNA-miRNA-mRNA 网络揭示脑梗死中的功能 lncRNAs。

Reconstruction of the lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveal functional lncRNAs in Cerebral Infarction.

机构信息

Shaanxi Province Key Laboratory of New Drugs and Chinese Medicine Foundation Research,Pharmacy College, Shaanxi University of Chinese Medicine, Xianyang, 712046, China.

The first affiliated Hospital of Hunan University of Medicine, Huaihua, 410007, China.

出版信息

Sci Rep. 2019 Aug 21;9(1):12176. doi: 10.1038/s41598-019-48435-3.

Abstract

Functioning as miRNA sponges, long non-coding RNA (lncRNA) exert its pharmacological action via regulating expression of protein-coding genes. However, the lncRNA-mediated ceRNA in cerebral Infarction (CI) remains unclear. In this study, the expression recordsets of mRNA, lncRNA and miRNA of CI samples were obtained from the NCBI GEO datasets separately. The differentially expressed lncRNAs (DELs), miRNAs (DEMis) and mRNAs (DEMs) were identified by limma package in R platform. A total of 267 DELs, 26 DEMis, and 760 DEMs were identified as differentially expressed profiles, with which we constructed the ceRNA network composed of DELs-DEMis-DEMs. Further, clusterProfiler package in R platform is employed for performing Gene Ontology (GO) and KEGG pathway analysis. An aberrant ceRNA network was constructed according to node degrees in CI, including 28 DELs, 19 DEMs and 12 DEMis, from which we extracted the core network, in which 9 nodes were recognized as kernel genes including Tspan3, Eif4a2, rno-miR-208a-3p, rno-miR-194-5p, Pdpn, H3f3b, Stat3, Cd63 and Sdc4. Finally, with the DELs-DEMis-DEMs ceRNA network provided above, we can improve our understanding of the pathogenesis of CI mediated by lncRNA.

摘要

作为 miRNA 的海绵,长链非编码 RNA(lncRNA)通过调节蛋白质编码基因的表达发挥其药理学作用。然而,lncRNA 在脑梗死(CI)中的 ceRNA 仍不清楚。在这项研究中,我们分别从 NCBI GEO 数据集获得了 CI 样本的 mRNA、lncRNA 和 miRNA 的表达记录集。使用 R 平台中的 limma 包鉴定差异表达的 lncRNA(DELs)、miRNA(DEMis)和 mRNA(DEMs)。共鉴定出 267 个 DELs、26 个 DEMis 和 760 个 DEMs 作为差异表达谱,我们构建了由 DELs-DEMis-DEMs 组成的 ceRNA 网络。进一步,我们使用 R 平台中的 clusterProfiler 包进行基因本体(GO)和 KEGG 通路分析。根据 CI 中的节点度构建了异常 ceRNA 网络,包括 28 个 DELs、19 个 DEMs 和 12 个 DEMis,从中提取了核心网络,其中 9 个节点被认为是核心基因,包括 Tspan3、Eif4a2、rno-miR-208a-3p、rno-miR-194-5p、Pdpn、H3f3b、Stat3、Cd63 和 Sdc4。最后,利用上述 DELs-DEMis-DEMs ceRNA 网络,我们可以更好地理解 lncRNA 介导的 CI 发病机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5702/6704173/7ad476949653/41598_2019_48435_Fig1_HTML.jpg

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