Enhanced effective codon numbers to understand codon usage bias

Codon usage bias is a well recognized phenomenon but the relative influence of its major causes: G+C content, mutational biases, and selection, are often difficult to disentangle. This paper presents methods to calculate modified effective codon numbers that allow the investigation of the sources of codon bias and how genes or organisms have their codon biases shaped. In particular, it demonstrates that variation in codon usage bias across organisms is likely driven more by likely mutational forces while the variation in codon usage bias within genomes is likely driven by codon selectional forces. Author summaryA new method of disaggregating codon bias influences is described where I show how that different values of the effective codon number, following Wrights Nc, can be used as ratios to demonstrate the similar or different causes of codon biases across genes or organisms. By calculating ratios of the different types of effective codon numbers, one can easily compare organisms or different genes while controlling for gene G+C content or codon nucleotide G+C content. The driving forces determining the variations in codon usage bias across or within organisms thus become much clearer.