Literature DB >> 23943854

Systems genetics of hepatocellular damage in vivo and in vitro: identification of a critical network on chromosome 11 in mouse.

Roman Liebe1, Rabea A Hall, Robert W Williams, Steven Dooley, Frank Lammert.   

Abstract

Quantitative trait locus (QTL) mapping is a powerful method to find modifier loci that influence disease risk and progression without prior knowledge of underlying genetic mechanisms. The aim of this study is to identify gene loci that contribute to individual differences in liver fibrosis following chronic liver damage. For this purpose, we carried out a mapping study across a panel of 21 BXD recombinant inbred strains using primary hepatocytes challenged with transforming growth factor (TGF)-β for 48 h. We identified a 6 Mb interval on chromosome 11 that is a major modifier of TGF-β-induced hepatocyte injury. Corresponding in vivo genetic analysis of fibrosis after chronic hepatotoxic injury by carbon tetrachloride (CCl4 ip for 6 wk) highlighted the same locus. Expression QTL (eQTL) analysis in liver tissues in the BXD family identified six polymorphisms in this region that are associated with strong cis eQTLs and that correlate well with gene expression in liver after both 6 wk CCl4 treatment and acute ethanol damage of the liver. Within this interval we rank two genes containing coding sequence variants as strong candidates that may modulate the severity of liver fibrosis: 1) the extracellular proteinase inhibitor gene Expi (also known as Wdnm1 or Wfdc18) and 2) musashi RNA-binding protein 2 (Msi2). The powerful combination of experimental, genetics, and bioinformatics methods, as well as combined in vitro and in vivo approaches can be used to define QTLs, genes, and even candidate sequence variants linked to hepatotoxicity and fibrosis.

Entities:  

Keywords:  fibrogenesis; hepatocellular damage; murine reference population; quantitative trait locus; recombinant inbred line; systems genetics

Mesh:

Substances:

Year:  2013        PMID: 23943854      PMCID: PMC3798765          DOI: 10.1152/physiolgenomics.00078.2013

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  41 in total

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