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Updated: Jan 15, 2026

Reverse Genetics to Engineer Positive-Sense RNA Virus Variants
Published on: June 9, 2022
Targeted short read NGS of HCV 5'-UTR for genotyping and identification of Sub-variants using Ion Torrent platform
Ritu Sagar1, Pushpendra Singh1,2, Mukesh Kumar Jogi1,3
1Division of Molecular Biology, ICMR-National Institute of Cancer Prevention and Research, Noida, India.
Abstract:
Hepatitis C Virus (HCV) is highly a mutable RNA virus, primarily due to lack of proofreading activity in RNA-dependent RNA polymerase. This intrinsic feature leads to the generation of substantial intra-host variation, resulting in the formation of viral quasispecies. The 5' untranslated region (5'UTR) of the HCV genome is highly conserved across different genotypes and serves as a widely adopted target for genotyping in clinical practice. In this study, the performance of targeted short-read next-generation sequencing of the HCV 5' UTR using Ion Torrent technology was evaluated, with the dual aim of assigning genotypes and detecting low-frequency intra-host variants. The 5'UTR-based nested RT-PCR products were amplified for five clinical plasma samples and sequenced on the Ion Gene Studio S5 platform. The resulting reads were assembled to generate consensus sequences and subjected to comprehensive analysis for iSNVs, SNPs, and indels. Sequencing of the amplicons yielded short-read sequences of 200-300 nucleotides. Phylogenetic analyses using MEGA and Interactive Tree of Life demonstrated that all isolates clustered within genotype 3, with sub-clustering indicative of subtype 3a and other intra-genotypic variants. Fourteen SNPs and several low-frequency iSNVs most notably at positions 72, 78, and 128, with variant frequencies reaching up to ˜25% were detected. These findings underscore the method's ability to discriminate both genotype and sub-variant structure. Overall, this strategy enhances molecular epidemiology, investigations, enables robust transmission tracking, and supports individualized therapeutic decision-making, particularly in resource-limited diagnostic settings.
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