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Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes

INTRODUCTION: Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon...

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Autores principales: Bohlin, Jon, Brynildsrud, Ola, Vesth, Tammi, Skjerve, Eystein, Ussery, David W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3724673/
https://www.ncbi.nlm.nih.gov/pubmed/23922837
http://dx.doi.org/10.1371/journal.pone.0069878
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author Bohlin, Jon
Brynildsrud, Ola
Vesth, Tammi
Skjerve, Eystein
Ussery, David W.
author_facet Bohlin, Jon
Brynildsrud, Ola
Vesth, Tammi
Skjerve, Eystein
Ussery, David W.
author_sort Bohlin, Jon
collection PubMed
description INTRODUCTION: Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon frequencies were distributed in over 2000 microbial genomes and how these distributions were affected by base compositional changes. In addition, we wanted to know how genome-wide amino acid usage was biased in the different genomes and how changes to base composition and mutations affected this bias. To carry this out, we used a Generalized Additive Mixed-effects Model (GAMM) to explore non-linear associations and strong data dependences in closely related microbes; principal component analysis (PCA) was used to examine genomic amino acid- and codon frequencies, while the concept of relative entropy was used to analyze genomic mutation rates. RESULTS: We found that genomic amino acid frequencies carried a stronger phylogenetic signal than codon frequencies, but that this signal was weak compared to that of genomic %AT. Further, in contrast to codon usage bias (CUB), amino acid usage bias (AAUB) was differently distributed in AT- and GC-rich genomes in the sense that AT-rich genomes did not prefer specific amino acids over others to the same extent as GC-rich genomes. AAUB was also associated with relative entropy; genomes with low AAUB contained more random mutations as a consequence of relaxed purifying selection than genomes with higher AAUB. CONCLUSION: Genomic base composition has a substantial effect on both amino acid- and codon frequencies in bacterial genomes. While phylogeny influenced amino acid usage more in GC-rich genomes, AT-content was driving amino acid usage in AT-rich genomes. We found the GAMM model to be an excellent tool to analyze the genomic data used in this study.
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spelling pubmed-37246732013-08-06 Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes Bohlin, Jon Brynildsrud, Ola Vesth, Tammi Skjerve, Eystein Ussery, David W. PLoS One Research Article INTRODUCTION: Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon frequencies were distributed in over 2000 microbial genomes and how these distributions were affected by base compositional changes. In addition, we wanted to know how genome-wide amino acid usage was biased in the different genomes and how changes to base composition and mutations affected this bias. To carry this out, we used a Generalized Additive Mixed-effects Model (GAMM) to explore non-linear associations and strong data dependences in closely related microbes; principal component analysis (PCA) was used to examine genomic amino acid- and codon frequencies, while the concept of relative entropy was used to analyze genomic mutation rates. RESULTS: We found that genomic amino acid frequencies carried a stronger phylogenetic signal than codon frequencies, but that this signal was weak compared to that of genomic %AT. Further, in contrast to codon usage bias (CUB), amino acid usage bias (AAUB) was differently distributed in AT- and GC-rich genomes in the sense that AT-rich genomes did not prefer specific amino acids over others to the same extent as GC-rich genomes. AAUB was also associated with relative entropy; genomes with low AAUB contained more random mutations as a consequence of relaxed purifying selection than genomes with higher AAUB. CONCLUSION: Genomic base composition has a substantial effect on both amino acid- and codon frequencies in bacterial genomes. While phylogeny influenced amino acid usage more in GC-rich genomes, AT-content was driving amino acid usage in AT-rich genomes. We found the GAMM model to be an excellent tool to analyze the genomic data used in this study. Public Library of Science 2013-07-26 /pmc/articles/PMC3724673/ /pubmed/23922837 http://dx.doi.org/10.1371/journal.pone.0069878 Text en © 2013 Bohlin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Bohlin, Jon
Brynildsrud, Ola
Vesth, Tammi
Skjerve, Eystein
Ussery, David W.
Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes
title Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes
title_full Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes
title_fullStr Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes
title_full_unstemmed Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes
title_short Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes
title_sort amino acid usage is asymmetrically biased in at- and gc-rich microbial genomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3724673/
https://www.ncbi.nlm.nih.gov/pubmed/23922837
http://dx.doi.org/10.1371/journal.pone.0069878
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