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Novel metrics for quantifying bacterial genome composition skews
BACKGROUND: Bacterial genomes have characteristic compositional skews, which are differences in nucleotide frequency between the leading and lagging DNA strands across a segment of a genome. It is thought that these strand asymmetries arise as a result of mutational biases and selective constraints,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042203/ https://www.ncbi.nlm.nih.gov/pubmed/29996771 http://dx.doi.org/10.1186/s12864-018-4913-5 |
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author | Joesch-Cohen, Lena M. Robinson, Max Jabbari, Neda Lausted, Christopher G. Glusman, Gustavo |
author_facet | Joesch-Cohen, Lena M. Robinson, Max Jabbari, Neda Lausted, Christopher G. Glusman, Gustavo |
author_sort | Joesch-Cohen, Lena M. |
collection | PubMed |
description | BACKGROUND: Bacterial genomes have characteristic compositional skews, which are differences in nucleotide frequency between the leading and lagging DNA strands across a segment of a genome. It is thought that these strand asymmetries arise as a result of mutational biases and selective constraints, particularly for energy efficiency. Analysis of compositional skews in a diverse set of bacteria provides a comparative context in which mutational and selective environmental constraints can be studied. These analyses typically require finished and well-annotated genomic sequences. RESULTS: We present three novel metrics for examining genome composition skews; all three metrics can be computed for unfinished or partially-annotated genomes. The first two metrics, (dot-skew and cross-skew) depend on sequence and gene annotation of a single genome, while the third metric (residual skew) highlights unusual genomes by subtracting a GC content-based model of a library of genome sequences. We applied these metrics to 7738 available bacterial genomes, including partial drafts, and identified outlier species. A phylogenetically diverse set of these outliers (i.e., Borrelia, Ehrlichia, Kinetoplastibacterium, and Phytoplasma) display similar skew patterns but share lifestyle characteristics, such as intracellularity and biosynthetic dependence on their hosts. CONCLUSIONS: Our novel metrics appear to reflect the effects of biosynthetic constraints and adaptations to life within one or more hosts on genome composition. We provide results for each analyzed genome, software and interactive visualizations at http://db.systemsbiology.net/gestalt/skew_metrics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-4913-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6042203 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60422032018-07-13 Novel metrics for quantifying bacterial genome composition skews Joesch-Cohen, Lena M. Robinson, Max Jabbari, Neda Lausted, Christopher G. Glusman, Gustavo BMC Genomics Methodology Article BACKGROUND: Bacterial genomes have characteristic compositional skews, which are differences in nucleotide frequency between the leading and lagging DNA strands across a segment of a genome. It is thought that these strand asymmetries arise as a result of mutational biases and selective constraints, particularly for energy efficiency. Analysis of compositional skews in a diverse set of bacteria provides a comparative context in which mutational and selective environmental constraints can be studied. These analyses typically require finished and well-annotated genomic sequences. RESULTS: We present three novel metrics for examining genome composition skews; all three metrics can be computed for unfinished or partially-annotated genomes. The first two metrics, (dot-skew and cross-skew) depend on sequence and gene annotation of a single genome, while the third metric (residual skew) highlights unusual genomes by subtracting a GC content-based model of a library of genome sequences. We applied these metrics to 7738 available bacterial genomes, including partial drafts, and identified outlier species. A phylogenetically diverse set of these outliers (i.e., Borrelia, Ehrlichia, Kinetoplastibacterium, and Phytoplasma) display similar skew patterns but share lifestyle characteristics, such as intracellularity and biosynthetic dependence on their hosts. CONCLUSIONS: Our novel metrics appear to reflect the effects of biosynthetic constraints and adaptations to life within one or more hosts on genome composition. We provide results for each analyzed genome, software and interactive visualizations at http://db.systemsbiology.net/gestalt/skew_metrics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-4913-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-11 /pmc/articles/PMC6042203/ /pubmed/29996771 http://dx.doi.org/10.1186/s12864-018-4913-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Joesch-Cohen, Lena M. Robinson, Max Jabbari, Neda Lausted, Christopher G. Glusman, Gustavo Novel metrics for quantifying bacterial genome composition skews |
title | Novel metrics for quantifying bacterial genome composition skews |
title_full | Novel metrics for quantifying bacterial genome composition skews |
title_fullStr | Novel metrics for quantifying bacterial genome composition skews |
title_full_unstemmed | Novel metrics for quantifying bacterial genome composition skews |
title_short | Novel metrics for quantifying bacterial genome composition skews |
title_sort | novel metrics for quantifying bacterial genome composition skews |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042203/ https://www.ncbi.nlm.nih.gov/pubmed/29996771 http://dx.doi.org/10.1186/s12864-018-4913-5 |
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