Evidence map›Paper›PMID 41593609›Full record

ArticleBMC biology2026

Synonymous codon usage defines functional gene families.

Farzan Ghanegolmohammadi, Shinsuke Ohnuki, Shane Byrne, Rahul Raman, Thomas J Begley, Peter C Dedon

Abstract read
In one paragraph

Article in BMC biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Farzan GhanegolmohammadiDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. farazanaa@gmail.com.
Shinsuke OhnukiDepartment of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, 277-8562, Japan.
Shane ByrneDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Rahul RamanDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Thomas J BegleyThe RNA Institute and Department of Biological Sciences, University at Albany, Albany, NY, 12222, USA.
Peter C DedonDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. pcdedon@mit.edu.

Funding

National Research Foundation Singapore SMART AMR IRGNIH HHS ES002109NIH HHS ES026856
6 · The paper itself

Abstract

backgroundThe degeneracy of the genetic code is increasingly recognized for roles in regulating translation rate, protein folding, and cell response. However, the functional genomics of codon usage patterns remains poorly defined. We previously showed that prokaryotic and eukaryotic cells respond to individual stresses by uniquely reprogramming the tRNA pool and the dozens of tRNA modifications comprising the tRNA epitranscriptome to cause selective translation of mRNAs from codon-biased stress response genes. Here, we tested the hypothesis that functional gene families have distinct values of codon bias in the Saccharomyces cerevisiae genome by modeling isoacceptor codon distributions using a new approach-analysis of synonymous codon signatures (ASCS).

resultsApplication of ASCS to the S. cerevisiae genome revealed linear relationships between patterns of codon bias and gene function using canonical correlation analysis. By mapping codon-biased open reading frames (ORFs) onto a functional network of gene ontology (GO) categories, we identified 91 gene families distinguished by unique codon usage signatures. The codon usage patterns were found to strongly predict functional clusters of genes, such as translational machinery, transcription, and metabolic processes.

conclusionsThe ASCS-derived model of codon usage patterns in S. cerevisiae reveals functional codon bias signatures and captures more biologically meaningful information when compared to other codon analytical approaches.

Indexed as

CodonCodon UsageMultigene FamilySaccharomyces cerevisiaeGenome, FungalOpen Reading FramesCodonCodon analyticsCodon metricFunctional networksIsoacceptor codon frequencySaccharomyces cerevisiaeSynonymous codonsTranslational regulation

Identifiers

PMID41593609
PMCPMC12918127

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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.