Genome Technology Center

Maximum likelihood estimation of codon usage bias

Morten Kloster

Abstract

The genetic code is degenerate; most amino acids can be encoded by from two to as many as six different codons. While one might expect synonymous codons to occur with equal frequency, that is usually not the case---not only are some codons favored over others, but their usage can vary significantly between different genes in the same organism. Known causes of codon bias include differences in mutation rates as well as selection pressure related to the expression level of a gene, but the standard analysis methods can explain only a fraction of the observed codon usage variation. We here introduce an explicit model of codon usage bias, inspired by statistical physics. Combining this model with a maximum likelihood approach, we are able to clearly identify up to four different sources of bias in various genomes. We have applied the algorithm to Saccharomyces cerevisiae as well as 325 bacterial genomes, and in most cases our model explains essentially all observed variance.

 

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