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A graph-based approach for the visualisation and analysis of bacterial pangenomes

BACKGROUND: The advent of low cost, high throughput DNA sequencing has led to the availability of thousands of complete genome sequences for a wide variety of bacterial species. Examining and interpreting genetic variation on this scale represents a significant challenge to existing methods of data...

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Autores principales: Harling-Lee, Joshua D., Gorzynski, Jamie, Yebra, Gonzalo, Angus, Tim, Fitzgerald, J. Ross, Freeman, Tom C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548110/
https://www.ncbi.nlm.nih.gov/pubmed/36209064
http://dx.doi.org/10.1186/s12859-022-04898-2
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author Harling-Lee, Joshua D.
Gorzynski, Jamie
Yebra, Gonzalo
Angus, Tim
Fitzgerald, J. Ross
Freeman, Tom C.
author_facet Harling-Lee, Joshua D.
Gorzynski, Jamie
Yebra, Gonzalo
Angus, Tim
Fitzgerald, J. Ross
Freeman, Tom C.
author_sort Harling-Lee, Joshua D.
collection PubMed
description BACKGROUND: The advent of low cost, high throughput DNA sequencing has led to the availability of thousands of complete genome sequences for a wide variety of bacterial species. Examining and interpreting genetic variation on this scale represents a significant challenge to existing methods of data analysis and visualisation. RESULTS: Starting with the output of standard pangenome analysis tools, we describe the generation and analysis of interactive, 3D network graphs to explore the structure of bacterial populations, the distribution of genes across a population, and the syntenic order in which those genes occur, in the new open-source network analysis platform, Graphia. Both the analysis and the visualisation are scalable to datasets of thousands of genome sequences. CONCLUSIONS: We anticipate that the approaches presented here will be of great utility to the microbial research community, allowing faster, more intuitive, and flexible interaction with pangenome datasets, thereby enhancing interpretation of these complex data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04898-2.
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spelling pubmed-95481102022-10-10 A graph-based approach for the visualisation and analysis of bacterial pangenomes Harling-Lee, Joshua D. Gorzynski, Jamie Yebra, Gonzalo Angus, Tim Fitzgerald, J. Ross Freeman, Tom C. BMC Bioinformatics Research Article BACKGROUND: The advent of low cost, high throughput DNA sequencing has led to the availability of thousands of complete genome sequences for a wide variety of bacterial species. Examining and interpreting genetic variation on this scale represents a significant challenge to existing methods of data analysis and visualisation. RESULTS: Starting with the output of standard pangenome analysis tools, we describe the generation and analysis of interactive, 3D network graphs to explore the structure of bacterial populations, the distribution of genes across a population, and the syntenic order in which those genes occur, in the new open-source network analysis platform, Graphia. Both the analysis and the visualisation are scalable to datasets of thousands of genome sequences. CONCLUSIONS: We anticipate that the approaches presented here will be of great utility to the microbial research community, allowing faster, more intuitive, and flexible interaction with pangenome datasets, thereby enhancing interpretation of these complex data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04898-2. BioMed Central 2022-10-08 /pmc/articles/PMC9548110/ /pubmed/36209064 http://dx.doi.org/10.1186/s12859-022-04898-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Harling-Lee, Joshua D.
Gorzynski, Jamie
Yebra, Gonzalo
Angus, Tim
Fitzgerald, J. Ross
Freeman, Tom C.
A graph-based approach for the visualisation and analysis of bacterial pangenomes
title A graph-based approach for the visualisation and analysis of bacterial pangenomes
title_full A graph-based approach for the visualisation and analysis of bacterial pangenomes
title_fullStr A graph-based approach for the visualisation and analysis of bacterial pangenomes
title_full_unstemmed A graph-based approach for the visualisation and analysis of bacterial pangenomes
title_short A graph-based approach for the visualisation and analysis of bacterial pangenomes
title_sort graph-based approach for the visualisation and analysis of bacterial pangenomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548110/
https://www.ncbi.nlm.nih.gov/pubmed/36209064
http://dx.doi.org/10.1186/s12859-022-04898-2
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