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The relationships among microRNA regulation, intrinsically disordered regions, and other indicators of protein evolutionary rate.


ABSTRACT: Many indicators of protein evolutionary rate have been proposed, but some of them are interrelated. The purpose of this study is to disentangle their correlations. We assess the strength of each indicator by controlling for the other indicators under study. We find that the number of microRNA (miRNA) types that regulate a gene is the strongest rate indicator (a negative correlation), followed by disorder content (the percentage of disordered regions in a protein, a positive correlation); the strength of disorder content as a rate indicator is substantially increased after controlling for the number of miRNA types. By dividing proteins into lowly and highly intrinsically disordered proteins (L-IDPs and H-IDPs), we find that proteins interacting with more H-IDPs tend to evolve more slowly, which largely explains the previous observation of a negative correlation between the number of protein-protein interactions and evolutionary rate. Moreover, all of the indicators examined here, except for the number of miRNA types, have different strengths in L-IDPs and in H-IDPs. Finally, the number of phosphorylation sites is weakly correlated with the number of miRNA types, and its strength as a rate indicator is substantially reduced when other indicators are considered. Our study reveals the relative strength of each rate indicator and increases our understanding of protein evolution.

SUBMITTER: Chen SC 

PROVIDER: S-EPMC3163433 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

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The relationships among microRNA regulation, intrinsically disordered regions, and other indicators of protein evolutionary rate.

Chen Sean Chun-Chang SC   Chuang Trees-Juen TJ   Li Wen-Hsiung WH   Li Wen-Hsiung WH  

Molecular biology and evolution 20110311 9


Many indicators of protein evolutionary rate have been proposed, but some of them are interrelated. The purpose of this study is to disentangle their correlations. We assess the strength of each indicator by controlling for the other indicators under study. We find that the number of microRNA (miRNA) types that regulate a gene is the strongest rate indicator (a negative correlation), followed by disorder content (the percentage of disordered regions in a protein, a positive correlation); the str  ...[more]

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