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Current Bioinformatics

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ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

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Research Article

Comprehensive Analysis of the Differentially Expressed Transcriptome with ceRNA Networks in a Mouse Model of Liver Cirrhosis

Author(s): Yichi Zhang, Xinsheng Nie, Yanan Jiang, Lijuan Wang, Zhuzhi Wan, Hao Jin, Ronghui Pu, Meihui Liang, Hailong Zhang, Qi Liu, Yuan Chang, Yang Gao, Ningning Yang and Shizhu Jin*

Volume 17, Issue 6, 2022

Published on: 22 July, 2022

Page: [510 - 520] Pages: 11

DOI: 10.2174/1574893617666220426123328

Price: $65

Abstract

Background: Hepatic cirrhosis is the consequence of various chronic liver diseases for which there is no curative treatment. In this study, based on RNA sequencing (RNA-seq) and subsequent bioinformatic analysis, we aim to explore the biological function of non-coding RNAs (ncRNAs) in hepatic cirrhosis.

Methods: The hepatic cirrhosis models were induced by the intraperitoneal injection of carbon tetrachloride (CCl4). The transcriptome profile was acquired by RNA-seq, the results of which were verified by quantitative real-time PCR (qRT-PCR). The competing endogenous RNA (ceRNA) networks were visualized by Cytoscape software. The enrichment analyses of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted.

Results: The differentially expressed transcript of liver cirrhosis consists of 2369 mRNAs, 374 lncRNAs, 91 circRNAs, and 242 miRNAs (|log2(fold change)|≥1 and P<0.05). The RNA-seq results were highly consistent with qRT-PCR validation of DEGs (four upregulated and four down-regulated, including ENSMUSG00000047517, ENSMUST00000217449, novel-circ-001366, miR-383-5p, ENSMUSG00000078683, ENSMUST00000148206, novel-circ-001986 and miR-216a-5p). Based on ceRNA theory, a circRNA-lncRNA co-regulated ceRNA network was established. Enrichment analysis revealed the potential key regulatory process during the liver cirrhosis progression.

Conclusion: In conclusion, the present study comprehensively analyzed differentially expressed transcripts in CCl4-induced liver cirrhosis. Our findings explored the gene signatures for liver cirrhosis’s diagnosis and precise treatment.

Keywords: RNA sequencing, liver cirrhosis, non-coding RNA, competing endogenous RNA, transcriptome, ceRNA Networks, mouse model

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