Genome-Wide Identification of differently expressed lncRNAs, mRNAs, and circRNAs in patients with osteoarthritis

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Author(s): Yeqing Sun*, Lei Chen, Yingqi Zhang, Jincheng Zhang, Shashi Ranjan Tiwari

Journal Name: Current Bioinformatics

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Abstract:

Background: Osteoarthritis (OA), one of the most important causes leading to joint disability, was considered as an untreatable disease. A series of genes were reported to regulate the pathogenesis of OA, including microRNAs, Long non-coding RNAs and Circular RNA. So far, the expression profiles and functions of lncRNAs, mRNAs, and circRNAs in OA are not fully understood.

Objective: The present study aimed to identify differently expressed genes in OA.

Method: The present study conducted RNA-seq to identify differently expressed genes in OA. Ontology (GO) analysis was used to analysis the Molecular Function and Biological Process. KEGG pathway analysis was used to perform the differentially expressed lncRNAs in biological pathways.

Results: Hierarchical clustering revealed a total of 943 mRNAs, 518 lncRNAs, and 300 circRNAs were dysregulated in OA compared to normal samples. Furthermore, we constructed differentially expressed mRNAs mediated proteinprotein interaction network, differentially expressed lncRNAs mediated trans regulatory networks, and competitive endogenous RNA (ceRNA) to reveal the interaction among these genes in OA. Bioinformatics analysis revealed these dysregulated genes were involved in regulating multiple biological processes, such as wound healing, negative regulation of ossification, sister chromatid cohesion, positive regulation of interleukin-1 alpha production, sodium ion transmembrane transport, positive regulation of cell migration, and negative regulation of inflammatory response. To the best of our knowledge, this study for the first time revealed the expression pattern of mRNAs, lncRNAs and circRNAs in OA.

Conclusion: This study provided novel information to validate these differentially expressed RNAs may be as possible biomarkers and targets in OA.

Keywords: Osteoarthritis, RNAs, RNA-seq, Bioinformatics analysis, signaling pathway

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Article Details

(E-pub Ahead of Print)
DOI: 10.2174/1574893615999200706002907
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