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J Clin Microbiol. 2016 Oct;54(10):2470-84. doi: 10.1128/JCM.00330-16. Epub 2016 Jul 6.

Comparison of Next-Generation Sequencing Technologies for Comprehensive Assessment of Full-Length Hepatitis C Viral Genomes.

Author information

1
MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom.
2
Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
3
Virus Reference Department, Public Health England, London, United Kingdom.
4
University College London (UCL), Division of Infection and Immunity, London, United Kingdom.
5
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
6
Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.
7
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom ellie.barnes@ndm.ox.ac.uk.
8
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.

Abstract

Affordable next-generation sequencing (NGS) technologies for hepatitis C virus (HCV) may potentially identify both viral genotype and resistance genetic motifs in the era of directly acting antiviral (DAA) therapies. This study compared the ability of high-throughput NGS methods to generate full-length, deep, HCV sequence data sets and evaluated their utility for diagnostics and clinical assessment. NGS methods using (i) unselected HCV RNA (metagenomics), (ii) preenrichment of HCV RNA by probe capture, and (iii) HCV preamplification by PCR implemented in four United Kingdom centers were compared. Metrics of sequence coverage and depth, quasispecies diversity, and detection of DAA resistance-associated variants (RAVs), mixed HCV genotypes, and other coinfections were compared using a panel of samples with different viral loads, genotypes, and mixed HCV genotypes/subtypes [geno(sub)types]. Each NGS method generated near-complete genome sequences from more than 90% of samples. Enrichment methods and PCR preamplification generated greater sequence depth and were more effective for samples with low viral loads. All NGS methodologies accurately identified mixed HCV genotype infections. Consensus sequences generated by different NGS methods were generally concordant, and majority RAVs were consistently detected. However, methods differed in their ability to detect minor populations of RAVs. Metagenomic methods identified human pegivirus coinfections. NGS provided a rapid, inexpensive method for generating whole HCV genomes to define infecting genotypes, RAVs, comprehensive viral strain analysis, and quasispecies diversity. Enrichment methods are particularly suited for high-throughput analysis while providing the genotype and information on potential DAA resistance.

PMID:
27385709
PMCID:
PMC5035407
DOI:
10.1128/JCM.00330-16
[Indexed for MEDLINE]
Free PMC Article

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