Evolutionary rate covariation is a reliable predictor of co-functional interactions but not necessarily physical interactions.

evolutionary biology evolutionary rate evolutionary rates functional inference phylogenetic correlations protein co-evolution protein interactions yeast

Journal

eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614

Informations de publication

Date de publication:
28 Feb 2024
Historique:
medline: 28 2 2024
pubmed: 28 2 2024
entrez: 28 2 2024
Statut: epublish

Résumé

Co-functional proteins tend to have rates of evolution that covary over time. This correlation between evolutionary rates can be measured over the branches of a phylogenetic tree through methods such as evolutionary rate covariation (ERC), and then used to construct gene networks by the identification of proteins with functional interactions. The cause of this correlation has been hypothesized to result from both compensatory coevolution at physical interfaces and nonphysical forces such as shared changes in selective pressure. This study explores whether coevolution due to compensatory mutations has a measurable effect on the ERC signal. We examined the difference in ERC signal between physically interacting protein domains within complexes compared to domains of the same proteins that do not physically interact. We found no generalizable relationship between physical interaction and high ERC, although a few complexes ranked physical interactions higher than nonphysical interactions. Therefore, we conclude that coevolution due to physical interaction is weak, but present in the signal captured by ERC, and we hypothesize that the stronger signal instead comes from selective pressures on the protein as a whole and maintenance of the general function.

Identifiants

pubmed: 38415754
doi: 10.7554/eLife.93333
pii: 93333
doi:
pii:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NIH HHS
ID : HG009299
Pays : United States

Informations de copyright

© 2023, Little et al.

Déclaration de conflit d'intérêts

JL, MC, NC No competing interests declared

Auteurs

Jordan Little (J)

Department of Human Genetics, University of Utah, Salt Lake City, United States.

Maria Chikina (M)

Department of Computational Biology, University of Pittsburgh, Pittsburgh, United States.

Nathan L Clark (NL)

Department of Human Genetics, University of Utah, Salt Lake City, United States.
Department of Biological Sciences, University of Pittsburgh, Pittsburgh, United States.

Classifications MeSH