Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , , |
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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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 instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
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 |
repository.mail.fl_str_mv |
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1799137929899016192 |