Evidence map›Paper›PMID 35180226›Full record

ArticlePLoS computational biology2022

Phylogenetic inference of changes in amino acid propensities with single-position resolution.

Galya V Klink, Olga V Kalinina, Georgii A Bazykin

Abstract read
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Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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.

Galya V KlinkInstitute for Information Transmission Problems (Kharkevich Institute) of the Russian Academy of Sciences, Moscow, Russia.ORCID 0000-0001-8466-6958
Olga V KalininaHelmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research (HZI), Saarbrücken, Germany; Medical Faculty, Saarland University, Homburg, Germany.ORCID 0000-0002-9445-477X
Georgii A BazykinInstitute for Information Transmission Problems (Kharkevich Institute) of the Russian Academy of Sciences, Moscow, Russia.ORCID 0000-0003-2334-2751

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fitness conferred by the same allele may differ between genotypes and environments, and these differences shape variation and evolution. Changes in amino acid propensities at protein sites over the course of evolution have been inferred from sequence alignments statistically, but the existing methods are data-intensive and aggregate multiple sites. Here, we develop an approach to detect individual amino acids that confer different fitness in different groups of species from combined sequence and phylogenetic data. Using the fact that the probability of a substitution to an amino acid depends on its fitness, our method looks for amino acids such that substitutions to them occur more frequently in one group of lineages than in another. We validate our method using simulated evolution of a protein site under different scenarios and show that it has high specificity for a wide range of assumptions regarding the underlying changes in selection, while its sensitivity differs between scenarios. We apply our method to the env gene of two HIV-1 subtypes, A and B, and to the HA gene of two influenza A subtypes, H1 and H3, and show that the inferred fitness changes are consistent with the fitness differences observed in deep mutational scanning experiments. We find that changes in relative fitness of different amino acid variants within a site do not always trigger episodes of positive selection and therefore may not result in an overall increase in the frequency of substitutions, but can still be detected from changes in relative frequencies of different substitutions.

Indexed as

Amino AcidsInfluenza, HumanAmino Acid SubstitutionEvolution, MolecularHumansPhylogenySequence AlignmentAmino Acids

Identifiers

PMID35180226
PMCPMC9106220

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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.