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Viral population analysis and minority-variant detection using short read next-generation sequencing

Watson, SJ; Welkers, MR; Depledge, DP; Coulter, E; Breuer, JM; de Jong, MD; Kellam, P; (2013) Viral population analysis and minority-variant detection using short read next-generation sequencing. Philosophical transactions of the Royal Society of London. Series B, Biological sciences , 368 (1614) , Article 20120205. 10.1098/rstb.2012.0205. Green open access

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Abstract

RNA viruses within infected individuals exist as a population of evolutionary-related variants. Owing to evolutionary change affecting the constitution of this population, the frequency and/or occurrence of individual viral variants can show marked or subtle fluctuations. Since the development of massively parallel sequencing platforms, such viral populations can now be investigated to unprecedented resolution. A critical problem with such analyses is the presence of sequencing-related errors that obscure the identification of true biological variants present at low frequency. Here, we report the development and assessment of the Quality Assessment of Short Read (QUASR) Pipeline (http://sourceforge.net/projects/quasr) specific for virus genome short read analysis that minimizes sequencing errors from multiple deep-sequencing platforms, and enables post-mapping analysis of the minority variants within the viral population. QUASR significantly reduces the error-related noise in deep-sequencing datasets, resulting in increased mapping accuracy and reduction of erroneous mutations. Using QUASR, we have determined influenza virus genome dynamics in sequential samples from an in vitro evolution of 2009 pandemic H1N1 (A/H1N1/09) influenza from samples sequenced on both the Roche 454 GSFLX and Illumina GAIIx platforms. Importantly, concordance between the 454 and Illumina sequencing allowed unambiguous minority-variant detection and accurate determination of virus population turnover in vitro.

Type: Article
Title: Viral population analysis and minority-variant detection using short read next-generation sequencing
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1098/rstb.2012.0205
Publisher version: http://dx.doi.org/10.1098/rstb.2012.0205
Language: English
Additional information: © 2013 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, provided the original author and source are credited. PMCID: PMC3678329
Keywords: Cells, Cultured, DNA Primers, Evolution, Molecular, Genetic Variation, Genome, Viral, Genomics, High-Throughput Nucleotide Sequencing, Humans, Influenza A Virus, H1N1 Subtype, Population Dynamics, Reverse Transcriptase Polymerase Chain Reaction, Software
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Infection, Immunity and Inflammation Dept
URI: https://discovery.ucl.ac.uk/id/eprint/1385502
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