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Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads
Whole genome sequencing has revolutionized infectious disease surveillance for tracking and monitoring the spread and evolution of pathogens. However, using a linear reference genome for genomic analyses may introduce biases, especially when studies are conducted on highly variable bacterial genomes...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448961/ https://www.ncbi.nlm.nih.gov/pubmed/37636268 http://dx.doi.org/10.3389/fgene.2023.1225248 |
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author | Yang, Zuyu Guarracino, Andrea Biggs, Patrick J. Black, Michael A. Ismail, Nuzla Wold, Jana Renee Merriman, Tony R. Prins, Pjotr Garrison, Erik de Ligt, Joep |
author_facet | Yang, Zuyu Guarracino, Andrea Biggs, Patrick J. Black, Michael A. Ismail, Nuzla Wold, Jana Renee Merriman, Tony R. Prins, Pjotr Garrison, Erik de Ligt, Joep |
author_sort | Yang, Zuyu |
collection | PubMed |
description | Whole genome sequencing has revolutionized infectious disease surveillance for tracking and monitoring the spread and evolution of pathogens. However, using a linear reference genome for genomic analyses may introduce biases, especially when studies are conducted on highly variable bacterial genomes of the same species. Pangenome graphs provide an efficient model for representing and analyzing multiple genomes and their variants as a graph structure that includes all types of variations. In this study, we present a practical bioinformatics pipeline that employs the PanGenome Graph Builder and the Variation Graph toolkit to build pangenomes from assembled genomes, align whole genome sequencing data and call variants against a graph reference. The pangenome graph enables the identification of structural variants, rearrangements, and small variants (e.g., single nucleotide polymorphisms and insertions/deletions) simultaneously. We demonstrate that using a pangenome graph, instead of a single linear reference genome, improves mapping rates and variant calling for both simulated and real datasets of the pathogen Neisseria meningitidis. Overall, pangenome graphs offer a promising approach for comparative genomics and comprehensive genetic variation analysis in infectious disease. Moreover, this innovative pipeline, leveraging pangenome graphs, can bridge variant analysis, genome assembly, population genetics, and evolutionary biology, expanding the reach of genomic understanding and applications. |
format | Online Article Text |
id | pubmed-10448961 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104489612023-08-25 Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads Yang, Zuyu Guarracino, Andrea Biggs, Patrick J. Black, Michael A. Ismail, Nuzla Wold, Jana Renee Merriman, Tony R. Prins, Pjotr Garrison, Erik de Ligt, Joep Front Genet Genetics Whole genome sequencing has revolutionized infectious disease surveillance for tracking and monitoring the spread and evolution of pathogens. However, using a linear reference genome for genomic analyses may introduce biases, especially when studies are conducted on highly variable bacterial genomes of the same species. Pangenome graphs provide an efficient model for representing and analyzing multiple genomes and their variants as a graph structure that includes all types of variations. In this study, we present a practical bioinformatics pipeline that employs the PanGenome Graph Builder and the Variation Graph toolkit to build pangenomes from assembled genomes, align whole genome sequencing data and call variants against a graph reference. The pangenome graph enables the identification of structural variants, rearrangements, and small variants (e.g., single nucleotide polymorphisms and insertions/deletions) simultaneously. We demonstrate that using a pangenome graph, instead of a single linear reference genome, improves mapping rates and variant calling for both simulated and real datasets of the pathogen Neisseria meningitidis. Overall, pangenome graphs offer a promising approach for comparative genomics and comprehensive genetic variation analysis in infectious disease. Moreover, this innovative pipeline, leveraging pangenome graphs, can bridge variant analysis, genome assembly, population genetics, and evolutionary biology, expanding the reach of genomic understanding and applications. Frontiers Media S.A. 2023-08-10 /pmc/articles/PMC10448961/ /pubmed/37636268 http://dx.doi.org/10.3389/fgene.2023.1225248 Text en Copyright © 2023 Yang, Guarracino, Biggs, Black, Ismail, Wold, Merriman, Prins, Garrison and de Ligt. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Yang, Zuyu Guarracino, Andrea Biggs, Patrick J. Black, Michael A. Ismail, Nuzla Wold, Jana Renee Merriman, Tony R. Prins, Pjotr Garrison, Erik de Ligt, Joep Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads |
title | Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads |
title_full | Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads |
title_fullStr | Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads |
title_full_unstemmed | Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads |
title_short | Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads |
title_sort | pangenome graphs in infectious disease: a comprehensive genetic variation analysis of neisseria meningitidis leveraging oxford nanopore long reads |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448961/ https://www.ncbi.nlm.nih.gov/pubmed/37636268 http://dx.doi.org/10.3389/fgene.2023.1225248 |
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