Integrated analysis of long noncoding RNA‐associated competing endogenous RNA network in periodontitis. (8th March 2018)

• Record Type: Journal Article
• Authors: Li, S.; Liu, X.; Li, H.; Pan, H.; Acharya, A.; Deng, Y.; Yu, Y.; Haak, R.; Schmidt, J.; Schmalz, G.; Ziebolz, D.
• Is Part Of: Journal of periodontal research. Volume 53:Number 4(2018)
• Page Start: 495
• Page End: 505
• Publication Date: 2018-03-08
• Subjects: ceRNA -- gene expression data -- lncRNA -- miRNA -- mRNA -- periodontitis -- regulatory network; Periodontics -- Periodicals; 617.632
• DOI: 10.1111/jre.12539
• Languages: English
• ISSNs: 0022-3484

Abstract

Abstract : 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.