Evidence map›Paper›PMID 38415754›Full record

ArticleeLife2024

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

Jordan Little, Maria Chikina, Nathan L Clark

Abstract read
In one paragraph

Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jordan LittleDepartment of Human Genetics, University of Utah, Salt Lake City, United States.ORCID https://orcid.org/0000-0002-8590-9357
Maria ChikinaDepartment of Computational Biology, University of Pittsburgh, Pittsburgh, United States.
Nathan L ClarkDepartment of Human Genetics, University of Utah, Salt Lake City, United States.ORCID https://orcid.org/0000-0003-0006-8374

Funding

Title: Functional Annotation of Genomes via Phenotypic Convergence within Large Multi-species AlignmentsR01HG009299 · NHGRI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Maria D Chikina, Nathaniel L Clark · 2017 to 2026
$4.1M
NHGRI NIH HHS R01 HG009299NIH HHS HG009299
6 · The paper itself

Abstract

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.

Indexed as

Gene Regulatory NetworksMutationPhylogenyProtein Domainsevolutionary biologyevolutionary rateevolutionary ratesfunctional inferencephylogenetic correlationsprotein co-evolutionprotein interactionsyeast

Identifiers

PMID38415754
PMCPMC10942632

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.