Integrated analysis of long noncoding RNA-associated competing endogenous RNA network in periodontitis

被引:70
作者
Li, S. [1 ]
Liu, X. [2 ,3 ]
Li, H. [4 ]
Pan, H. [5 ]
Acharya, A. [6 ,7 ]
Deng, Y. [2 ]
Yu, Y. [8 ]
Haak, R. [1 ]
Schmidt, J. [1 ]
Schmalz, G. [1 ]
Ziebolz, D. [1 ]
机构
[1] Univ Leipzig, Dept Cariol Endodontol & Periodontol, Leipzig, Germany
[2] Shanghai Genomap Technol, Shanghai, Peoples R China
[3] Harbin Med Univ, Coll Bioinformat Sci & Technol, Harbin, Heilongjiang, Peoples R China
[4] Univ Leipzig, Saxon Incubator Clin Translat SIKT, Leipzig, Germany
[5] Harvard Univ, Harvard Med Sch, Brigham & Womens Hosp, Dept Orthoped Surg, Boston, MA 02115 USA
[6] Univ Hong Kong, Fac Dent, Hong Kong, Hong Kong, Peoples R China
[7] Dr DY Patil Vidyapeeth, Dr DY Patil Dent Coll & Hosp, Pune, Maharashtra, India
[8] Harbin Med Univ, Stomatol Affiliated Hosp, Dept Periodontol, Harbin, Heilongjiang, Peoples R China
关键词
ceRNA; gene expression data; lncRNA; miRNA; mRNA; periodontitis; regulatory network; ORAL INFLAMMATORY DISEASES; MICRORNA EXPRESSION; POTENTIAL ROLE; GROWTH-FACTOR; DIFFERENTIATION; CANCER; GENES; BONE; PROLIFERATION; MICROARRAY;
D O I
10.1111/jre.12539
中图分类号
R78 [口腔科学];
学科分类号
100302 [口腔临床医学];
摘要
Background and ObjectivesLong 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 MethodsData 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. ResultsThrough 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. ConclusionThese 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.
引用
收藏
页码:495 / 505
页数:11
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