期刊
NUCLEIC ACIDS RESEARCH
卷 50, 期 4, 页码 1849-1863出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkac050
关键词
-
资金
- Korean National Research Foundation [2021R1A2B5B01001903, 2020R1A6A1A03047902, 2017M3C9A604765]
- Ministry of Oceans and Fisheries [20150242]
- IITP [2019-0-01906]
- National Research Foundation of Korea [2020R1A6A1A03047902, 2021R1A2B5B01001903] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
By investigating the evolutionary divergence of regulatory relationships between transcription factors and target genes, the study finds that the rewiring of gene regulatory networks contributes to phenotypic discrepancies between humans and mice, which may explain the failure of mouse models to accurately mimic human diseases.
Mouse models have been engineered to reveal the biological mechanisms of human diseases based on an assumption. The assumption is that orthologous genes underlie conserved phenotypes across species. However, genetically modified mouse orthologs of human genes do not often recapitulate human disease phenotypes which might be due to the molecular evolution of phenotypic differences across species from the time of the last common ancestor. Here, we systematically investigated the evolutionary divergence of regulatory relationships between transcription factors (TFs) and target genes in functional modules, and found that the rewiring of gene regulatory networks (GRNs) contributes to the phenotypic discrepancies that occur between humans and mice. We confirmed that the rewired regulatory networks of orthologous genes contain a higher proportion of species-specific regulatory elements. Additionally, we verified that the divergence of target gene expression levels, which was triggered by network rewiring, could lead to phenotypic differences. Taken together, a careful consideration of evolutionary divergence in regulatory networks could be a novel strategy to understand the failure or success of mouse models to mimic human diseases. To help interpret mouse phenotypes in human disease studies, we provide quantitative comparisons of gene expression profiles on our website (http://sbi.postech.ac.kr/w/RN).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据