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Validation of a Genotype-Independent Hepatitis C Virus Near-Whole Genome Sequencing Assay Lapointe, Hope R.; Dong, Weiyan; Dong, Winnie W. Y.; Kirkby, Don; Woods, Conan; Poon, Art F. Y.; Howe, Anita; Harrigan, Richard; Brumme, Chanson J.
Abstract
Despite the effectiveness of direct-acting antiviral agents in treating hepatitis C virus (HCV), cases of treatment failure have been associated with the emergence of resistance-associated substitutions. To better guide clinical decision-making, we developed and validated a near-whole-genome HCV genotype-independent next-generation sequencing strategy. HCV genotype 1–6 samples from direct-acting antiviral agent treatment-naïve and -treated HCV-infected individuals were included. Viral RNA was extracted using a NucliSens easyMAG and amplified using nested reverse transcription-polymerase chain reaction. Libraries were prepared using Nextera XT and sequenced on the Illumina MiSeq sequencing platform. Data were processed by an in-house pipeline (MiCall). Nucleotide consensus sequences were aligned to reference strain sequences for resistance-associated substitution identification and compared to NS3, NS5a, and NS5b sequence data obtained from a validated in-house assay optimized for HCV genotype 1. Sequencing success rates (defined as achieving >100-fold read coverage) approaching 90% were observed for most genotypes in samples with a viral load >5 log10 IU/mL. This genotype-independent sequencing method resulted in >99.8% nucleotide concordance with the genotype 1-optimized method, and 100% agreement in genotype assignment with paired line probe assay-based genotypes. The assay demonstrated high intra-run repeatability and inter-run reproducibility at detecting substitutions above 2% prevalence. This study highlights the performance of a freely available laboratory and bioinformatic approach for reliable HCV genotyping and resistance-associated substitution detection regardless of genotype.
Item Metadata
Title |
Validation of a Genotype-Independent Hepatitis C Virus Near-Whole Genome Sequencing Assay
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Creator | |
Contributor | |
Publisher |
Multidisciplinary Digital Publishing Institute
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Date Issued |
2021-08-30
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Description |
Despite the effectiveness of direct-acting antiviral agents in treating hepatitis C virus (HCV), cases of treatment failure have been associated with the emergence of resistance-associated substitutions. To better guide clinical decision-making, we developed and validated a near-whole-genome HCV genotype-independent next-generation sequencing strategy. HCV genotype 1–6 samples from direct-acting antiviral agent treatment-naïve and -treated HCV-infected individuals were included. Viral RNA was extracted using a NucliSens easyMAG and amplified using nested reverse transcription-polymerase chain reaction. Libraries were prepared using Nextera XT and sequenced on the Illumina MiSeq sequencing platform. Data were processed by an in-house pipeline (MiCall). Nucleotide consensus sequences were aligned to reference strain sequences for resistance-associated substitution identification and compared to NS3, NS5a, and NS5b sequence data obtained from a validated in-house assay optimized for HCV genotype 1. Sequencing success rates (defined as achieving >100-fold read coverage) approaching 90% were observed for most genotypes in samples with a viral load >5 log10 IU/mL. This genotype-independent sequencing method resulted in >99.8% nucleotide concordance with the genotype 1-optimized method, and 100% agreement in genotype assignment with paired line probe assay-based genotypes. The assay demonstrated high intra-run repeatability and inter-run reproducibility at detecting substitutions above 2% prevalence. This study highlights the performance of a freely available laboratory and bioinformatic approach for reliable HCV genotyping and resistance-associated substitution detection regardless of genotype.
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Subject | |
Genre | |
Type | |
Language |
eng
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Date Available |
2021-10-14
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Provider |
Vancouver : University of British Columbia Library
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Rights |
CC BY 4.0
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DOI |
10.14288/1.0402529
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URI | |
Affiliation | |
Citation |
Viruses 13 (9): 1721 (2021)
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Publisher DOI |
10.3390/v13091721
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Peer Review Status |
Reviewed
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Scholarly Level |
Faculty
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DSpace
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Item Media
Item Citations and Data
Rights
CC BY 4.0