Analyzing Gene Expression and Codon Usage Bias in Diverse Genomes Using a Variety of Models

Title:Analyzing Gene Expression and Codon Usage Bias in Diverse Genomes Using a Variety of Models

Volume: 9 Issue: 2

Author(s): Satyabrata Sahoo and Shibsankar Das

Affiliation:

Keywords: Archaea, bacteria, codon usage, eukaryotes, GC content, gene expression, highly expressed genes predicted.

Abstract: Synonymous codon usage has long been known as a factor that affects the average expression level of proteins in microorganisms. A systematic approach to study the role of codon usage bias underlying gene expression has been described. Facts and ideas presented in this short review are to derive biological information from genome sequences by means of various statistical analyses and appropriate design of algorithms. Using codon usage bias as a numerical estimator of gene expression, a comparative analysis of predicted highly expressed (PHE) genes was performed in bacteria, cyanobacteria, archaea, lower eukaryotes and higher eukaryotes. Here, it is suggested that both codon usage and as well as base compositions at three codon sites regulate the individual gene expression. Any correlation between gene length and expression level, however, remains unexplained. Relationship between gene expression levels and synonymous codon usage provides an important line of evidence for translational selection and suggests some general mechanism underlying protein evolution.

Cite this article as:

Sahoo Satyabrata and Das Shibsankar, Analyzing Gene Expression and Codon Usage Bias in Diverse Genomes Using a Variety of Models, Current Bioinformatics 2014; 9 (2) . https://dx.doi.org/10.2174/1574893608999140109114247