Evidence map›Paper›PMID 39724093›Full record

ArticlePLoS genetics2024

Estimating the proportion of beneficial mutations that are not adaptive in mammals.

Thibault Latrille, Julien Joseph, Diego A Hartasánchez, Nicolas Salamin

Abstract read
In one paragraph

Article in PLoS genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. In silico prediction of variant effects: promises and limitations for precision plant breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Review
  3. 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

4 authors.

Thibault LatrilleDepartment of Computational Biology, Université de Lausanne, Lausanne, Switzerland.ORCID 0000-0002-9643-4668
Julien JosephLaboratoire de Biométrie et Biologie Evolutive, UMR5558, Université Lyon 1, Villeurbanne, France.ORCID 0009-0002-1312-9930
Diego A HartasánchezDepartment of Computational Biology, Université de Lausanne, Lausanne, Switzerland.ORCID 0000-0003-2596-6883
Nicolas SalaminDepartment of Computational Biology, Université de Lausanne, Lausanne, Switzerland.ORCID 0000-0002-3963-4954

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutations can be beneficial by bringing innovation to their bearer, allowing them to adapt to environmental change. These mutations are typically unpredictable since they respond to an unforeseen change in the environment. However, mutations can also be beneficial because they are simply restoring a state of higher fitness that was lost due to genetic drift in a stable environment. In contrast to adaptive mutations, these beneficial non-adaptive mutations can be predicted if the underlying fitness landscape is stable and known. The contribution of such non-adaptive mutations to molecular evolution has been widely neglected mainly because their detection is very challenging. We have here reconstructed protein-coding gene fitness landscapes shared between mammals, using mutation-selection models and a multi-species alignments across 87 mammals. These fitness landscapes have allowed us to predict the fitness effect of polymorphisms found in 28 mammalian populations. Using methods that quantify selection at the population level, we have confirmed that beneficial non-adaptive mutations are indeed positively selected in extant populations. Our work confirms that deleterious substitutions are accumulating in mammals and are being reverted, generating a balance in which genomes are damaged and restored simultaneously at different loci. We observe that beneficial non-adaptive mutations represent between 15% and 45% of all beneficial mutations in 24 of 28 populations analyzed, suggesting that a substantial part of ongoing positive selection is not driven solely by adaptation to environmental change in mammals.

Indexed as

Evolution, MolecularGenetic FitnessMammalsMutationSelection, GeneticAdaptation, PhysiologicalAnimalsGenetic DriftHumansModels, GeneticPolymorphism, Genetic

Identifiers

PMID39724093
PMCPMC11709321

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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.