Development and Validation of a Template-Independent Next-Generation Sequencing Assay for Detecting Low-Level Resistance-Associated Variants of Hepatitis C Virus.
J Mol Diagn
; 18(5): 643-656, 2016 09.
Article
em En
| MEDLINE
| ID: mdl-27393904
ABSTRACT
To develop hepatitis C virus (HCV) direct-acting antiviral (DAA) drugs that can treat most HCV genotypes and offer higher barriers for treatment-resistant mutations, it is important to study resistance-associated variants (RAVs). Current commercially available RAV detection assays rely on genotype- or subtype-specific template-dependent PCR amplification. These assays are limited to genotypes and subtypes that are often prevalent in developed countries because of availability of public sequence databases. To support global clinical trials of DAAs, we developed and validated a template-independent (TI) next-generation sequencing (NGS) assay for HCV whole genome sequencing that can perform HCV subtyping, detect HCV mixed genotype or subtype infection, and identify low-level RAVs at a 5% fraction of the viral population with sensitivity and positive predictive value ≥ 0.9. We compared TI-NGS with commercial genotype- or subtype-specific Sanger sequencing assays, and found that TI-NGS both confirmed most of variants called by Sanger sequencing and avoided biases likely caused by PCR primers used in Sanger sequencing. To confirm TI-NGS assay's variant calls at the discrepant positions with Sanger sequencing, we custom designed template-dependent NGS assays and obtained 100% concordance with the TI-NGS assay. The ability to reliably detect low-level RAVs in HCV samples of any subtype without PCR primer-related bias makes this TI-NGS assay an important tool in studying HCV DAA drug resistance.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Antivirais
/
Variação Genética
/
Hepatite C
/
Hepacivirus
/
Farmacorresistência Viral
/
Sequenciamento de Nucleotídeos em Larga Escala
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article