Quantification of codon selection for comparative bacterial genomics

BMC Genomics

Methodology Article

Jeffrey G Lawrence¹  Adam C Retchless² 

[1] Department of Biological Sciences, University of Pittsburgh, 15260, Pittsburgh, PA, USA;Department of Biological Sciences, University of Pittsburgh, 15260, Pittsburgh, PA, USA;Department of Environmental Science, Policy and Management, University of California, 94720, Berkeley, CA, USA;

关键词: Codon;    Codon Usage;    Synonymous Codon;    Codon Usage Bias;    Synonymous Codon Usage;   

DOI  :  10.1186/1471-2164-12-374

 received in 2011-03-23, accepted in 2011-07-25,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundStatistics measuring codon selection seek to compare genes by their sensitivity to selection for translational efficiency, but existing statistics lack a model for testing the significance of differences between genes. Here, we introduce a new statistic for measuring codon selection, the Adaptive Codon Enrichment (ACE).ResultsThis statistic represents codon usage bias in terms of a probabilistic distribution, quantifying the extent that preferred codons are over-represented in the gene of interest relative to the mean and variance that would result from stochastic sampling of codons. Expected codon frequencies are derived from the observed codon usage frequencies of a broad set of genes, such that they are likely to reflect nonselective, genome wide influences on codon usage (e.g. mutational biases). The relative adaptiveness of synonymous codons is deduced from the frequency of codon usage in a pre-selected set of genes relative to the expected frequency. The ACE can predict both transcript abundance during rapid growth and the rate of synonymous substitutions, with accuracy comparable to or greater than existing metrics. We further examine how the composition of reference gene sets affects the accuracy of the statistic, and suggest methods for selecting appropriate reference sets for any genome, including bacteriophages. Finally, we demonstrate that the ACE may naturally be extended to quantify the genome-wide influence of codon selection in a manner that is sensitive to a large fraction of codons in the genome. This reveals substantial variation among genomes, correlated with the tRNA gene number, even among groups of bacteria where previously proposed whole-genome measures show little variation.ConclusionsThe statistical framework of the ACE allows rigorous comparison of the level of codon selection acting on genes, both within a genome and between genomes.

【 授权许可】

CC BY   
© Retchless and Lawrence; licensee BioMed Central Ltd. 2011