Macroevolutionary divergence of gene expression driven by selection on protein abundance

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.

Authors

Institutions

Publication Details

Journal
Science
Published
2025-03-06
DOI
https://doi.org/10.1126/science.ads2658
Citations
15
Primary Topic
RNA Research and Splicing
Type
article
Field-Weighted Citation Impact
12.09
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Macroevolutionary divergence of gene expression driven by selection on protein abundance

Alexander L. Cope, Joshua G. Schraiber, Matthew W. Pennell
15 citations
Science
RNA Research and Splicing
12.09
article

Macroevolutionary divergence of gene expression driven by selection on protein abundance

Alexander L. Cope, Joshua G. Schraiber, Matthew W. Pennell
article en
15 citations

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.

ScienceVol. 387(6738)
Rutgers, The State University of New Jersey (US), University of Southern California (US), Vanderbilt University (US), Cornell University (US), Johnson University (US)
Life in Land
Openalex Percentile: Top 1%
RNA Research and Splicing
12.09
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.