Codon Usage Bias Measured Through Entropy Approach

TL;DR

This paper introduces an entropy-based method to quantify codon usage bias by comparing real codon frequencies with various quasi-equilibrium models, applied to 125 bacterial genomes.

Contribution

It presents a novel entropy approach to measure codon bias and compares different quasi-equilibrium models for a comprehensive analysis.

Findings

Quantified codon bias across 125 bacterial genomes

Compared three models of quasi-equilibrium frequency distributions

Provided insights into codon usage patterns in bacteria

Abstract

Codon usage bias measure is defined through the mutual entropy calculation of real codon frequency distribution against the quasi-equilibrium one. This latter is defined in three manners: (1) the frequency of synonymous codons is supposed to be equal (i.e., the arithmetic mean of their frequencies); (2) it coincides to the frequency distribution of triplets; and, finally, (3) the quasi-equilibrium frequency distribution is defined as the expected frequency of codons derived from the dinucleotide frequency distribution. The measure of bias in codon usage is calculated for 125 bacterial genomes.