Protein evolution is structure dependent and non-homogeneous across the tree of life

6Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Protein sequence evolution is a complex process that varies across the tree of life and among-sites within proteins. Comparing evolutionary rate matrices for specific taxa ('clade-specific models') can reveal this variation and provide information about the basis for changes in the paterns of protein evolution over time. However, clade-specific models can only provide this information if the variation among taxa exceeds the variation among proteins. We showed this to be the case by demonstrating that clade-specific model fit could distinguish among proteins from the four taxa that we examined (vertebrates, plants, oomycetes, and yeasts). Model fit classified proteins correctly by clade of origin >70% of the time. A relatively small number of dimensions can explain differences among models. If model parameters are averaged across all sites ∼80% of the variance among models reflects clade; for models that consider protein structure ∼50% of the variance reflected relative solvent accessibility and ∼25% reflected clade. Relaxed purifying selection in taxa with smaller long-Term effective population sizes appears to explain much of the among clade variance. Relaxed selection on solvent-exposed sites was correlated with the degree of change in amino acid side-chain volume for substitutions; other differences among models were more complex. Beyond the information they reveal about protein evolution, our clade-specific models also represent tools for phylogenomic inference. Availability: model files are available from htps://github.com/ebraun68/clade_specific_prot_models.

Cite

CITATION STYLE

APA

Pandey, A., & Braun, E. L. (2020). Protein evolution is structure dependent and non-homogeneous across the tree of life. In Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2020. Association for Computing Machinery, Inc. https://doi.org/10.1145/3388440.3412473

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free