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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
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.
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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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