Error baseline rates of five sample preparation methods used to characterize RNA virus populations

Individual RNA viruses typically occur as populations of genomes that differ slightly from each other due to mutations introduced by the error-prone viral polymerase. Understanding the variability of RNA virus genome populations is critical for understanding virus evolution because individual mutant...

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Vydáno v:	PloS one Ročník 12; číslo 2; s. e0171333
Hlavní autoři:	Kugelman, Jeffrey R., Wiley, Michael R., Nagle, Elyse R., Reyes, Daniel, Pfeffer, Brad P., Kuhn, Jens H., Sanchez-Lockhart, Mariano, Palacios, Gustavo F.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 09.02.2017 Public Library of Science (PLoS)
Témata:	Algorithms Amplification Analysis Biological evolution Biology and life sciences Deoxyribonucleic acid Diagnostic Errors DNA DNA Mutational Analysis - methods DNA Mutational Analysis - standards DNA polymerase DNA sequencing Ebola virus Ebolavirus Error analysis Error detection Gene mutation Gene sequencing Genome, Viral Genomes Genomics High-Throughput Nucleotide Sequencing - methods High-Throughput Nucleotide Sequencing - standards Humans In vitro methods and tests Infections Infectious diseases Medical research Mutation Nucleotide sequence Plasmid DNA Plasmids Polymorphism, Single Nucleotide Population Populations Research and analysis methods Research Design Reverse transcription Ribonucleic acid RNA RNA polymerase RNA viruses RNA Viruses - genetics RNA, Viral - analysis RNA, Viral - genetics Sample preparation Sampling methods Sequence Analysis, RNA - methods Sequence Analysis, RNA - standards Specimen Handling - methods Specimen Handling - standards Subpopulations Viral diseases Viruses
ISSN:	1932-6203, 1932-6203
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Shrnutí:	Individual RNA viruses typically occur as populations of genomes that differ slightly from each other due to mutations introduced by the error-prone viral polymerase. Understanding the variability of RNA virus genome populations is critical for understanding virus evolution because individual mutant genomes may gain evolutionary selective advantages and give rise to dominant subpopulations, possibly even leading to the emergence of viruses resistant to medical countermeasures. Reverse transcription of virus genome populations followed by next-generation sequencing is the only available method to characterize variation for RNA viruses. However, both steps may lead to the introduction of artificial mutations, thereby skewing the data. To better understand how such errors are introduced during sample preparation, we determined and compared error baseline rates of five different sample preparation methods by analyzing in vitro transcribed Ebola virus RNA from an artificial plasmid-based system. These methods included: shotgun sequencing from plasmid DNA or in vitro transcribed RNA as a basic "no amplification" method, amplicon sequencing from the plasmid DNA or in vitro transcribed RNA as a "targeted" amplification method, sequence-independent single-primer amplification (SISPA) as a "random" amplification method, rolling circle reverse transcription sequencing (CirSeq) as an advanced "no amplification" method, and Illumina TruSeq RNA Access as a "targeted" enrichment method. The measured error frequencies indicate that RNA Access offers the best tradeoff between sensitivity and sample preparation error (1.4-5) of all compared methods.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Conceptualization: GP.Formal analysis: JRK MRW MS JHK GP.Funding acquisition: GP.Investigation: ERN DR BPP.Methodology: ERN DR BPP.Project administration: GP.Resources: GP.Supervision: GP.Visualization: JRK.Writing – original draft: JRK MRW MS JHK GP.Writing – review & editing: JRK MRW MS JHK GP. Competing Interests: We have the following interests: Jens H. Kuhn is employed by Tunnell Government Services, Inc. Tunnell Government Services provided support in the form of salaries, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. All work under contract HHSN272200700016I is performed under the agreement/understanding that it will belong to the client and will be affiliated directly to the NIH/NIAID Integrated Research Facility at Fort Detrick. There are no patents, products in development or marketed products to declare. This employment does not alter our adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0171333