An atlas of the human liver diurnal transcriptome and its perturbation by hepatitis C virus infection

表观基因组 转录组 生物 肝癌 肝病 表观遗传学 小RNA 基因 遗传学 癌症研究 癌症 生物信息学 基因表达 DNA甲基化 生物化学
作者
Atish Mukherji,Frank Jühling,Yogy Simanjuntak,Émilie Crouchet,Fabio Del Zompo,Yuji Teraoka,Alexandre Haller,Philippe Baltzinger,Soumith Paritala,Fahmida Rasha,Naoto Fujiwara,Cloé Gadenne,Nevena Slovic,Marine Oudot,Sarah Durand,Clara Ponsolles,Catherine Schuster,Xiaodong Zhuang,Jacinta A. Holmes,Ming‐Lun Yeh,Hiromi Abe‐Chayama,Mathias Heikenwälder,A. Sangiovanni,Massimo Iavarone,M. Colombo,Steven K. H. Foung,Jane A. McKeating,Irwin Davidson,Ming‐Lung Yu,Raymond T. Chung,Yujin Hoshida,Kazuaki Chayama,Joachim Lupberger,Thomas F. Baumert
出处
期刊:Nature Communications [Springer Nature]
卷期号:15 (1) 被引量:2
标识
DOI:10.1038/s41467-024-51698-8
摘要

Chronic liver disease and cancer are global health challenges. The role of the circadian clock as a regulator of liver physiology and disease is well established in rodents, however, the identity and epigenetic regulation of rhythmically expressed genes in human disease is less well studied. Here we unravel the rhythmic transcriptome and epigenome of human hepatocytes using male human liver chimeric mice. We identify a large number of rhythmically expressed protein coding genes in human hepatocytes of male chimeric mice, which includes key transcription factors, chromatin modifiers, and critical enzymes. We show that hepatitis C virus (HCV) infection, a major cause of liver disease and cancer, perturbs the transcriptome by altering the rhythmicity of the expression of more than 1000 genes, and affects the epigenome, leading to an activation of critical pathways mediating metabolic alterations, fibrosis, and cancer. HCV-perturbed rhythmic pathways remain dysregulated in patients with advanced liver disease. Collectively, these data support a role for virus-induced perturbation of the hepatic rhythmic transcriptome and pathways in cancer development and may provide opportunities for cancer prevention and biomarkers to predict HCC risk.
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