Abstract
Choice of direct acting antiviral (DAA) therapy for Hepatitis C Virus (HCV) in the United Kingdom and similar settings usually requires knowledge of the genotype and, in some cases, antiviral resistance (AVR) profile of the infecting virus. To determine these, most laboratories currently use Sanger technology, but next-generation sequencing (NGS) offers potential advantages in throughput and accuracy. However, NGS poses unique technical challenges, which require idiosyncratic development and technical validation approaches. This applies particularly to virology, where sequence diversity is high and the amount of starting genetic material is low, making it difficult to distinguish real data from artifacts. We describe the development and technical validation of a sequence capture-based HCV whole genome sequencing (WGS) assay to determine viral genotype and AVR profile. We use clinical samples of known subtypes and viral loads, and simulated FASTQ datasets to validate the analytical performances of both the wet laboratory and bioinformatic pipeline procedures. We show high concordance of the WGS assay compared to current "gold standard" Sanger assays. Specificity was 92.3 and 96.1% for AVR and genotyping, respectively. Discordances were due to the inability of Sanger assays to assign the correct subtype or accurately call mixed drug-resistant variants. We show high repeatability and reproducibility with >99.8% sequence similarity between sequence runs as well as high precision for variant frequency detection at >98.8% in the 95th percentile. Post-sequencing bioinformatics quality control workflows allow the accurate distinction between mixed infections, cross-contaminants and recombinant viruses at a threshold of >5% for the minority population. The sequence capture-based HCV WGS assay is more accurate than legacy AVR and genotyping assays. The assay has now been implemented in the clinical pathway of England's National Health Service HCV treatment programs, representing the first validated HCV WGS pipeline in clinical service. The data generated will additionally provide granular national-level genomic information for public health policy making and support the WHO HCV elimination strategy.