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Genome Complexity Browser: Visualization and quantification of genome variability

Comparative genomics studies may be used to acquire new knowledge regarding genome architecture, which defines the rules for combining sets of genes in the genome of living organisms. Hundreds of thousands of prokaryotic genomes have been sequenced and assembled. However, computational tools capable...

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Detalles Bibliográficos
Autores principales: Manolov, Alexander, Konanov, Dmitry, Fedorov, Dmitry, Osmolovsky, Ivan, Vereshchagin, Rinat, Ilina, Elena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577506/
https://www.ncbi.nlm.nih.gov/pubmed/33035207
http://dx.doi.org/10.1371/journal.pcbi.1008222
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author Manolov, Alexander
Konanov, Dmitry
Fedorov, Dmitry
Osmolovsky, Ivan
Vereshchagin, Rinat
Ilina, Elena
author_facet Manolov, Alexander
Konanov, Dmitry
Fedorov, Dmitry
Osmolovsky, Ivan
Vereshchagin, Rinat
Ilina, Elena
author_sort Manolov, Alexander
collection PubMed
description Comparative genomics studies may be used to acquire new knowledge regarding genome architecture, which defines the rules for combining sets of genes in the genome of living organisms. Hundreds of thousands of prokaryotic genomes have been sequenced and assembled. However, computational tools capable of simultaneously comparing large numbers of genomes are lacking. We developed the Genome Complexity Browser, a tool that allows the visualization of gene contexts, in a graph-based format, and the quantification of variability for different segments of a genome. The graph-based visualization allows the inspection of changes in gene contents and neighborhoods across hundreds of genomes, simultaneously, which may facilitate the identification of conserved and variable segments of operons or the estimation of the overall variability associated with a particular genome locus. We introduced a measure called complexity, to quantify genome variability. Intraspecies and interspecies comparisons revealed that regions with high complexity values tended to be located in areas that are conserved across different strains and species.
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spelling pubmed-75775062020-10-26 Genome Complexity Browser: Visualization and quantification of genome variability Manolov, Alexander Konanov, Dmitry Fedorov, Dmitry Osmolovsky, Ivan Vereshchagin, Rinat Ilina, Elena PLoS Comput Biol Research Article Comparative genomics studies may be used to acquire new knowledge regarding genome architecture, which defines the rules for combining sets of genes in the genome of living organisms. Hundreds of thousands of prokaryotic genomes have been sequenced and assembled. However, computational tools capable of simultaneously comparing large numbers of genomes are lacking. We developed the Genome Complexity Browser, a tool that allows the visualization of gene contexts, in a graph-based format, and the quantification of variability for different segments of a genome. The graph-based visualization allows the inspection of changes in gene contents and neighborhoods across hundreds of genomes, simultaneously, which may facilitate the identification of conserved and variable segments of operons or the estimation of the overall variability associated with a particular genome locus. We introduced a measure called complexity, to quantify genome variability. Intraspecies and interspecies comparisons revealed that regions with high complexity values tended to be located in areas that are conserved across different strains and species. Public Library of Science 2020-10-09 /pmc/articles/PMC7577506/ /pubmed/33035207 http://dx.doi.org/10.1371/journal.pcbi.1008222 Text en © 2020 Manolov 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Manolov, Alexander
Konanov, Dmitry
Fedorov, Dmitry
Osmolovsky, Ivan
Vereshchagin, Rinat
Ilina, Elena
Genome Complexity Browser: Visualization and quantification of genome variability
title Genome Complexity Browser: Visualization and quantification of genome variability
title_full Genome Complexity Browser: Visualization and quantification of genome variability
title_fullStr Genome Complexity Browser: Visualization and quantification of genome variability
title_full_unstemmed Genome Complexity Browser: Visualization and quantification of genome variability
title_short Genome Complexity Browser: Visualization and quantification of genome variability
title_sort genome complexity browser: visualization and quantification of genome variability
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577506/
https://www.ncbi.nlm.nih.gov/pubmed/33035207
http://dx.doi.org/10.1371/journal.pcbi.1008222
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