Evidence map›Paper›PMID 40048509›Full record

ArticleScience (New York, N.Y.)2025

Macroevolutionary divergence of gene expression driven by selection on protein abundance.

Alexander L Cope, Joshua G Schraiber, Matt Pennell

Abstract read
In one paragraph

Article in Science (New York, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Quantitative system drift.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. 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.

Alexander L Cope *Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA.ORCID 0000-0002-5756-7812
Joshua G Schraiber *Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.ORCID 0000-0002-7912-2195
Matt PennellDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.ORCID 0000-0002-2886-3970

Funding

IRACDA at Rutgers: INSPIRE Postdoctoral Training ProgramK12GM093854 · NIGMS · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI Detlev Boison, Gary A. Brewer · 2010 to 2026
$14.7M
Leveraging phylogenetic approaches to investigate the evolution of geneexpressionR35GM151348 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Matthew Wesley Pennell · 2023 to 2026
$1.6M
NIGMS NIH HHS K12 GM093854NIGMS NIH HHS R35 GM151348
6 · The paper itself

Abstract

The regulation of messenger RNA (mRNA) and protein abundances is well-studied, but less is known about the evolutionary processes shaping their relationship. To address this, we derived a new phylogenetic model and applied it to multispecies mammalian data. Our analyses reveal (i) strong stabilizing selection on protein abundances over macroevolutionary time, (ii) mutations affecting mRNA abundances minimally impact protein abundances, (iii) mRNA abundances evolve under selection to align with protein abundances, and (iv) mRNA abundances adapt faster than protein abundances owing to greater mutational opportunity. These conclusions are supported by comparisons of model parameters with independent functional genomic data. By decomposing mutational and selective influences on mRNA-protein dynamics, our approach provides a framework for discovering the evolutionary rules that drive divergence in gene expression.

Indexed as

Evolution, MolecularGene Expression RegulationMammalsProteinsRNA, MessengerSelection, GeneticAnimalsHumansModels, GeneticMutationPhylogenyProteinsRNA, Messenger

Identifiers

PMID40048509
PMCPMC12314801

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Registered trials

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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.