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The Dynamic Codon Biaser: calculating prokaryotic codon usage biases
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 prote...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Microbiology Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627211/ https://www.ncbi.nlm.nih.gov/pubmed/34699346 http://dx.doi.org/10.1099/mgen.0.000663 |
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author | Dehlinger, Brian Jurss, Jared Lychuk, Karson Putonti, Catherine |
author_facet | Dehlinger, Brian Jurss, Jared Lychuk, Karson Putonti, Catherine |
author_sort | Dehlinger, Brian |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8627211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Microbiology Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-86272112021-11-29 The Dynamic Codon Biaser: calculating prokaryotic codon usage biases Dehlinger, Brian Jurss, Jared Lychuk, Karson Putonti, Catherine Microb Genom Methods 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. Microbiology Society 2021-10-26 /pmc/articles/PMC8627211/ /pubmed/34699346 http://dx.doi.org/10.1099/mgen.0.000663 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License. |
spellingShingle | Methods Dehlinger, Brian Jurss, Jared Lychuk, Karson Putonti, Catherine The Dynamic Codon Biaser: calculating prokaryotic codon usage biases |
title | The Dynamic Codon Biaser: calculating prokaryotic codon usage biases |
title_full | The Dynamic Codon Biaser: calculating prokaryotic codon usage biases |
title_fullStr | The Dynamic Codon Biaser: calculating prokaryotic codon usage biases |
title_full_unstemmed | The Dynamic Codon Biaser: calculating prokaryotic codon usage biases |
title_short | The Dynamic Codon Biaser: calculating prokaryotic codon usage biases |
title_sort | dynamic codon biaser: calculating prokaryotic codon usage biases |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627211/ https://www.ncbi.nlm.nih.gov/pubmed/34699346 http://dx.doi.org/10.1099/mgen.0.000663 |
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