牙周炎中长链非编码 RNA 相关竞争性内源性 RNA 网络的综合分析。
Integrated analysis of long noncoding RNA-associated competing endogenous RNA network in periodontitis.
机构信息
Department of Cariology, Endodontology and Periodontology, University of Leipzig, Leipzig, Germany.
Shanghai Genomap Technologies, Yangpu District, Shanghai, China.
出版信息
J Periodontal Res. 2018 Aug;53(4):495-505. doi: 10.1111/jre.12539. Epub 2018 Mar 8.
BACKGROUND AND OBJECTIVES
Long noncoding RNAs (lncRNAs) play critical and complex roles in regulating various biological processes of periodontitis. This bioinformatic study aims to construct a putative competing endogenous RNA (ceRNA) network by integrating lncRNA, miRNA and mRNA expression, based on high-throughput RNA sequencing and microarray data about periodontitis.
MATERIAL AND METHODS
Data from 1 miRNA and 3 mRNA expression profiles were obtained to construct the lncRNA-associated ceRNA network. Gene Ontology enrichment analysis and pathway analysis were performed using the Gene Ontology website and Kyoto Encyclopedia of Genes and Genomes. A protein-protein interaction network was constructed based on the Search Tool for the retrieval of Interacting Genes/Proteins. Transcription factors (TFs) of differentially expressed genes were identified based on TRANSFAC database and then a regulatory network was constructed.
RESULTS
Through constructing the dysregulated ceRNA network, 6 genes (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL) and 3 miRNAs (miR-125a-3p, miR-200a, miR-142-3p) were detected. Three lncRNAs (MALAT1, TUG1, FGD5-AS1) were found to target both miR-125a-3p and miR-142-3p in this ceRNA network. Protein-protein interaction network analysis identified several hub genes, including VCAM1, ITGA4, UBC, LYN and SSX2IP. Three pathways (cytokine-cytokine receptor, cell adhesion molecules, chemokine signaling pathway) were identified to be overlapping results with the previous bioinformatics studies in periodontitis. Moreover, 2 TFs including FOS and EGR were identified to be involved in the regulatory network of the differentially expressed genes-TFs in periodontitis.
CONCLUSION
These findings suggest that 6 mRNAs (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL), 3 miRNAs (hsa-miR-125a-3p, hsa-miR-200a, hsa-miR-142-3p) and 3 lncRNAs (MALAT1, TUG1, FGD5-AS1) might be involved in the lncRNA-associated ceRNA network of periodontitis. This study sought to illuminate further the genetic and epigenetic mechanisms of periodontitis through constructing an lncRNA-associated ceRNA network.
背景与目的
长链非编码 RNA（lncRNA）在调控牙周炎的各种生物学过程中发挥着关键而复杂的作用。本生物信息学研究旨在通过整合高通量 RNA 测序和牙周炎 microarray 数据，构建一个基于 lncRNA、miRNA 和 mRNA 表达的假定竞争性内源 RNA（ceRNA）网络。
材料与方法
从 1 个 miRNA 和 3 个 mRNA 表达谱中获取数据，构建 lncRNA 相关的 ceRNA 网络。通过 Gene Ontology 网站和京都基因与基因组百科全书进行基因本体论富集分析和通路分析。根据 Search Tool for the Retrieval of Interacting Genes/Proteins 构建蛋白质-蛋白质相互作用网络。根据 TRANSFAC 数据库识别差异表达基因的转录因子（TF），然后构建调控网络。
结果
通过构建失调的 ceRNA 网络，检测到 6 个基因（HSPA4L、PANK3、YOD1、CTNNBIP1、EVI2B、ITGAL）和 3 个 miRNA（miR-125a-3p、miR-200a、miR-142-3p）。在这个 ceRNA 网络中，发现 3 个 lncRNA（MALAT1、TUG1、FGD5-AS1）可以同时靶向 miR-125a-3p 和 miR-142-3p。蛋白质-蛋白质相互作用网络分析确定了几个枢纽基因，包括 VCAM1、ITGA4、UBC、LYN 和 SSX2IP。三个通路（细胞因子-细胞因子受体、细胞黏附分子、趋化因子信号通路）被鉴定为与牙周炎的先前生物信息学研究重叠的结果。此外，鉴定出 2 个转录因子 FOS 和 EGR 参与牙周炎差异表达基因-TFs 的调控网络。
结论
这些发现表明，6 个 mRNA（HSPA4L、PANK3、YOD1、CTNNBIP1、EVI2B、ITGAL）、3 个 miRNA（hsa-miR-125a-3p、hsa-miR-200a、hsa-miR-142-3p）和 3 个 lncRNA（MALAT1、TUG1、FGD5-AS1）可能参与牙周炎的 lncRNA 相关 ceRNA 网络。本研究通过构建 lncRNA 相关 ceRNA 网络，旨在进一步阐明牙周炎的遗传和表观遗传机制。
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