Identification of global mRNA expression profiles and comprehensive bioinformatic analyses of abnormally expressed genes in cholestatic liver disease

生物 基因 转录组 小桶 下调和上调 胆汁淤积 Wnt信号通路 基因表达谱 代谢途径 基因表达 遗传学 计算生物学 内分泌学
作者
Jie Sun,Jing Wang,Na Zhang,Renjun Yang,Keyang Chen,Derun Kong
出处
期刊:Gene [Elsevier BV]
卷期号:707: 9-21 被引量:9
标识
DOI:10.1016/j.gene.2019.04.078
摘要

Cholestatic liver disease (CLD) is a highly heterogeneous hepatobiliary disease with various causes. The purpose of this research was to explore the gene expression changes throughout the course of CLD revealing potential causative molecular mechanisms and therapeutic targets.We established two animal models of cholestasis: 3,5-diethoxycarbonyl-1,4-dihydrocollidine feeding for 2, 4 and 6 weeks and bile duct ligation for 14 days. Using these two models, we identified differentially expressed genes (DEGs) by RNA-Seq analysis and used the newly-found knowledge of DEGs in comprehensive bioinformatic analyses to investigate key molecular events. Sequencing results were confirmed by experimental verification.Our study detected overlapping DEGs in the two models, of these 568 genes were upregulated and 117 genes were downregulated. Gene Ontology analysis demonstrated that the upregulated genes were associated with the biological processes of cell adhesion, cell migration and cell motility, while the metabolic processes of various substances were enriched for the downregulated genes. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the upregulated pathways were mainly distributed in focal adhesion, ECM-receptor interaction and amoebiasis, while downregulated pathways focused on peroxisome proliferator-activated receptor signaling pathway, metabolic pathways and primary bile acid biosynthesis. These findings were further confirmed by protein-protein interaction network modeling. Hub genes Src, Pdgfb, Col15a1, Mmp9, Egfr were selected using centralities analyses and verified by qRT-PCR.We profiled a global mRNA landscape in CLD to promote a complete understanding of transcriptomic events of this disease, offering candidate biomarkers and therapeutic targets for the clinic.

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