Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing

Detalhes bibliográficos
Autor(a) principal: Vrancken, Bram
Data de Publicação: 2016
Outros Autores: Trovão, Nídia Sequeira, Baele, Guy, Van Wijngaerden, Eric, Vandamme, Anne Mieke, van Laethem, Kristel, Lemey, Philippe
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://doi.org/10.3390/v8010012
Resumo: Genetic analyses play a central role in infectious disease research. Massively parallelized “mechanical cloning” and sequencing technologies were quickly adopted by HIV researchers in order to broaden the understanding of the clinical importance of minor drug-resistant variants. These efforts have, however, remained largely limited to small genomic regions. The growing need to monitor multiple genome regions for drug resistance testing, as well as the obvious benefit for studying evolutionary and epidemic processes makes complete genome sequencing an important goal in viral research. In addition, a major drawback for NGS applications to RNA viruses is the need for large quantities of input DNA. Here, we use a generic overlapping amplicon-based near full-genome amplification protocol to compare low-input enzymatic fragmentation (Nextera™) with conventional mechanical shearing for Roche 454 sequencing. We find that the fragmentation method has only a modest impact on the characterization of the population composition and that for reliable results, the variation introduced at all steps of the procedure—from nucleic acid extraction to sequencing—should be taken into account, a finding that is also relevant for NGS technologies that are now more commonly used. Furthermore, by applying our protocol to deep sequence a number of pre-therapy plasma and PBMC samples, we illustrate the potential benefits of a near complete genome sequencing approach in routine genotyping.
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spelling Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencingFull genome sequencingHIVNGSInfectious DiseasesVirologySDG 3 - Good Health and Well-beingGenetic analyses play a central role in infectious disease research. Massively parallelized “mechanical cloning” and sequencing technologies were quickly adopted by HIV researchers in order to broaden the understanding of the clinical importance of minor drug-resistant variants. These efforts have, however, remained largely limited to small genomic regions. The growing need to monitor multiple genome regions for drug resistance testing, as well as the obvious benefit for studying evolutionary and epidemic processes makes complete genome sequencing an important goal in viral research. In addition, a major drawback for NGS applications to RNA viruses is the need for large quantities of input DNA. Here, we use a generic overlapping amplicon-based near full-genome amplification protocol to compare low-input enzymatic fragmentation (Nextera™) with conventional mechanical shearing for Roche 454 sequencing. We find that the fragmentation method has only a modest impact on the characterization of the population composition and that for reliable results, the variation introduced at all steps of the procedure—from nucleic acid extraction to sequencing—should be taken into account, a finding that is also relevant for NGS technologies that are now more commonly used. Furthermore, by applying our protocol to deep sequence a number of pre-therapy plasma and PBMC samples, we illustrate the potential benefits of a near complete genome sequencing approach in routine genotyping.Instituto de Higiene e Medicina Tropical (IHMT)TB, HIV and opportunistic diseases and pathogens (THOP)Global Health and Tropical Medicine (GHTM)RUNVrancken, BramTrovão, Nídia SequeiraBaele, GuyVan Wijngaerden, EricVandamme, Anne Miekevan Laethem, KristelLemey, Philippe2018-05-11T22:06:36Z2016-01-072016-01-07T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.3390/v8010012eng1999-4915PURE: 2456051http://www.scopus.com/inward/record.url?scp=84954455786&partnerID=8YFLogxKhttps://doi.org/10.3390/v8010012info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:20:11Zoai:run.unl.pt:10362/36646Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:30:36.772008Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing
title Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing
spellingShingle Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing
Vrancken, Bram
Full genome sequencing
HIV
NGS
Infectious Diseases
Virology
SDG 3 - Good Health and Well-being
title_short Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing
title_full Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing
title_fullStr Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing
title_full_unstemmed Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing
title_sort Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing
author Vrancken, Bram
author_facet Vrancken, Bram
Trovão, Nídia Sequeira
Baele, Guy
Van Wijngaerden, Eric
Vandamme, Anne Mieke
van Laethem, Kristel
Lemey, Philippe
author_role author
author2 Trovão, Nídia Sequeira
Baele, Guy
Van Wijngaerden, Eric
Vandamme, Anne Mieke
van Laethem, Kristel
Lemey, Philippe
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Instituto de Higiene e Medicina Tropical (IHMT)
TB, HIV and opportunistic diseases and pathogens (THOP)
Global Health and Tropical Medicine (GHTM)
RUN
dc.contributor.author.fl_str_mv Vrancken, Bram
Trovão, Nídia Sequeira
Baele, Guy
Van Wijngaerden, Eric
Vandamme, Anne Mieke
van Laethem, Kristel
Lemey, Philippe
dc.subject.por.fl_str_mv Full genome sequencing
HIV
NGS
Infectious Diseases
Virology
SDG 3 - Good Health and Well-being
topic Full genome sequencing
HIV
NGS
Infectious Diseases
Virology
SDG 3 - Good Health and Well-being
description Genetic analyses play a central role in infectious disease research. Massively parallelized “mechanical cloning” and sequencing technologies were quickly adopted by HIV researchers in order to broaden the understanding of the clinical importance of minor drug-resistant variants. These efforts have, however, remained largely limited to small genomic regions. The growing need to monitor multiple genome regions for drug resistance testing, as well as the obvious benefit for studying evolutionary and epidemic processes makes complete genome sequencing an important goal in viral research. In addition, a major drawback for NGS applications to RNA viruses is the need for large quantities of input DNA. Here, we use a generic overlapping amplicon-based near full-genome amplification protocol to compare low-input enzymatic fragmentation (Nextera™) with conventional mechanical shearing for Roche 454 sequencing. We find that the fragmentation method has only a modest impact on the characterization of the population composition and that for reliable results, the variation introduced at all steps of the procedure—from nucleic acid extraction to sequencing—should be taken into account, a finding that is also relevant for NGS technologies that are now more commonly used. Furthermore, by applying our protocol to deep sequence a number of pre-therapy plasma and PBMC samples, we illustrate the potential benefits of a near complete genome sequencing approach in routine genotyping.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-07
2016-01-07T00:00:00Z
2018-05-11T22:06:36Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.3390/v8010012
url https://doi.org/10.3390/v8010012
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1999-4915
PURE: 2456051
http://www.scopus.com/inward/record.url?scp=84954455786&partnerID=8YFLogxK
https://doi.org/10.3390/v8010012
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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