Evidence map›Paper›PMID 40493494›Full record

ArticleMolecular biology and evolution2025

High Gene Expression Predicts Extremely Low Segregation of Deleterious Mutations in Large Penguin Populations.

Emiliano Trucchi, Piergiorgio Massa, Francesco Giannelli, Thibault Latrille, Marco Gargano, Flavia A Nitta Fernandes, Lorena Ancona, Nils Chr Stenseth, Joan Ferrer Obiol, Josephine Paris and 2 more

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Emiliano TrucchiDepartment of Life and Environmental Sciences, Marche Polytechnic University, Ancona, Italy.ORCID 0000-0002-1270-5273
Piergiorgio MassaDepartment of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, Ravenna, Italy.ORCID 0009-0007-8683-7264
Francesco GiannelliDepartment of Life and Environmental Sciences, Marche Polytechnic University, Ancona, Italy.ORCID 0000-0002-7706-151X
Thibault LatrilleDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.ORCID 0000-0002-9643-4668
Marco GarganoDepartment of Life and Environmental Sciences, Marche Polytechnic University, Ancona, Italy.ORCID 0000-0003-0073-9094
Flavia A Nitta FernandesDepartment of Life and Environmental Sciences, Marche Polytechnic University, Ancona, Italy.ORCID 0000-0001-7897-6976
Lorena AnconaDepartment of Life and Environmental Sciences, Marche Polytechnic University, Ancona, Italy.ORCID 0000-0001-7174-3918
Nils Chr StensethCentre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Oslo, Norway.ORCID 0000-0002-1591-5399
Joan Ferrer ObiolDepartment of Environmental Science and Policy, University of Milan, Milan, Italy.ORCID 0000-0002-1184-5434
Josephine ParisDepartment of Life and Environmental Sciences, Marche Polytechnic University, Ancona, Italy.ORCID 0000-0001-6868-3416
Giorgio BertorelleDepartment of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy.ORCID 0000-0002-2498-2702
Céline Le BohecUniversité de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France.ORCID 0000-0003-0149-6477

Funding

Centre National de la Recherche ScientifiqueCentre Scientifique de MonacoInstitut Polaire Français Paul Emile Victor
6 · The paper itself

Abstract

Purifying selection is the most pervasive type of selection, as it constantly removes deleterious mutations arising in populations, directly scaling with population size. Highly expressed genes appear to accumulate fewer nonsynonymous mutations between divergent species' lineages (known as E-R anticorrelation), pointing toward gene expression as an additional component modulating the selection coefficient of protein-coding mutations. However, estimates of the effect of gene expression on segregating deleterious variants in natural populations are scarce, as is an understanding of the relative contribution of population size and gene expression to purifying selection. Here, we analyze genomic and transcriptomic data from two natural populations of closely related sister species with different demographic histories, the Emperor penguin (Aptenodytes forsteri) and the King penguin (Aptenodytes patagonicus), and show that purifying selection at the population level depends on gene expression rate, resulting in very high selection coefficients at highly expressed genes. Leveraging realistic forward simulations, we estimate that the top 10% of the most highly expressed genes in a genome experience a selection pressure corresponding to an average selection coefficient of -0.1, which decreases to a selection coefficient of -0.01 for the top 50%. Gene expression rate can be regarded as a fundamental parameter of protein evolution in natural populations, maintaining selection effective even at small population size. We suggest gene expression could be considered as a major component of gene-specific selection coefficients, which are notoriously difficult to derive in nonmodel species under real-world conditions.

Indexed as

Gene ExpressionMutationSpheniscidaeAnimalsEvolution, MolecularSelection, GeneticTranscriptomeforward simulationsgene expressionpopulation sizeprotein evolutionpurifying selection

Identifiers

PMID40493494
PMCPMC12199756

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