Synonymous codon usage defines functional gene families

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 genes. Here, we systematically defined distinct values of codon bias in the Saccharomyces cerevisiae genome by modeling isoacceptor codon distributions using a new statistical toolbox - 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 115 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.