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Evolutionary rewiring of regulatory networks contributes to phenotypic differences between human and mouse orthologous genes

Abstract 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...

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Bibliographic Details
Published in:Nucleic acids research 2022-02, Vol.50 (4), p.1849-1863
Main Authors: Ha, Doyeon, Kim, Donghyo, Kim, Inhae, Oh, Youngchul, Kong, JungHo, Han, Seong Kyu, Kim, Sanguk
Format: Article
Language:English
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Summary:Abstract 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).
ISSN:0305-1048
1362-4962
1362-4962
DOI:10.1093/nar/gkac050