The Dynamic Codon Biaser: calculating prokaryotic codon usage biases

Author:

Dehlinger Brian1ORCID,Jurss Jared1,Lychuk Karson1,Putonti Catherine1234ORCID

Affiliation:

1. Bioinformatics Program, Loyola University Chicago, Chicago, IL 60660, USA

2. Department of Microbiology and Immunology, Loyola University Chicago, Stritch School of Medicine, Maywood, IL 60153, USA

3. Department of Biology, Loyola University Chicago, Chicago, IL 60660, USA

4. Department of Computer Science, Loyola University Chicago, Chicago, IL 60660, USA

Abstract

Bacterial genomes often reflect a bias in the usage of codons. These biases are often most notable within highly expressed genes. While deviations in codon usage can be attributed to selection or mutational biases, they can also be functional, for example controlling gene expression or guiding protein structure. Several different metrics have been developed to identify biases in codon usage. Previously we released a database, CBDB: The Codon Bias Database, in which users could retrieve precalculated codon bias data for bacterial RefSeq genomes. With the increase of bacterial genome sequence data since its release a new tool was needed. Here we present the Dynamic Codon Biaser (DCB) tool, a web application that dynamically calculates the codon usage bias statistics of prokaryotic genomes. DCB bases these calculations on 40 different highly expressed genes (HEGs) that are highly conserved across different prokaryotic species. A user can either specify an NCBI accession number or upload their own sequence. DCB returns both the bias statistics and the genome’s HEG sequences. These calculations have several downstream applications, such as evolutionary studies and phage–host predictions. The source code is freely available, and the website is hosted at www.cbdb.info.

Funder

National Science Foundation

Publisher

Microbiology Society

Subject

General Medicine

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