Evidence map›Paper›PMID 40799605›Full record

ArticlebioRxiv : the preprint server for biology2025

Protein language models reveal evolutionary constraints on synonymous codon choice.

Helen Sakharova, Liana F Lareau

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Helen SakharovaCenter for Computational Biology, University of California, Berkeley, CA 94720, USA.
Liana F LareauCenter for Computational Biology, University of California, Berkeley, CA 94720, USA.ORCID 0000-0003-3223-3426

Funding

Determinants and consequences of translation elongation rateR01GM132104 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI LAREAU, LIANA FAYE · 2019 to 2023
$1.6M
Pacific Biosciences PacBio RS Single Molecule Real Time SequencerS10OD018174 · OD · UNIVERSITY OF CALIFORNIA BERKELEY · PI ROKHSAR, DANIEL SOLEYMAN · 2014 to 2014
$600k
NIGMS NIH HHS R01 GM132104NIH HHS S10 OD018174
6 · The paper itself

Abstract

Evolution has shaped the genetic code, with subtle pressures leading to preferences for some synonymous codons over others. Codons are translated at different speeds by the ribosome, imposing constraints on codon choice related to the process of translation. The structure and function of a protein may impose pressure to translate the associated mRNA at a particular speed in order to enable proper protein production, but the molecular basis and scope of these evolutionary constraints have remained elusive. Here, we show that information about codon constraints can be extracted from protein sequence alone. We leverage a protein language model to predict codon choice from amino acid sequence, combining implicit information about position and protein structure to learn subtle but generalizable constraints on codon choice in yeast. In parallel, we conduct a genome-wide screen of thousands of synonymous codon substitutions in endogenous loci in yeast, reliably identifying a small set of several hundred synonymous variants that increase or decrease fitness while showing that most positions have no measurable effect on growth. Our results suggest that cotranslational localization and translational accuracy, more than cotranslational protein folding, are major drivers of selective pressure on codon choice in eukaryotes. By considering both the small but wide-reaching effects of codon choice that can be learned from evolution and the strong but highly specific effects determined via experiment, we expose unappreciated biological constraints on codon choice.

Identifiers

PMID40799605
PMCPMC12340807

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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.