Related Experiment Video
Updated: Dec 16, 2025

An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
Published on: March 30, 2014
Multi-Laboratory Comparison of Next-Generation to Sanger-Based Sequencing for HIV-1 Drug Resistance Genotyping
Neil T Parkin1, Santiago Avila-Rios2, David F Bibby3
1Data First Consulting, Inc., Sebastopol, CA 95472, USA.
Abstract:
Next-generation sequencing (NGS) is increasingly used for HIV-1 drug resistance genotyping. NGS methods have the potential for a more sensitive detection of low-abundance variants (LAV) compared to standard Sanger sequencing (SS) methods. A standardized threshold for reporting LAV that generates data comparable to those derived from SS is needed to allow for the comparability of data from laboratories using NGS and SS. Ten HIV-1 specimens were tested in ten laboratories using Illumina MiSeq-based methods. The consensus sequences for each specimen using LAV thresholds of 5%, 10%, 15%, and 20% were compared to each other and to the consensus of the SS sequences (protease 4-99; reverse transcriptase 38-247). The concordance among laboratories' sequences at different thresholds was evaluated by pairwise sequence comparisons. NGS sequences generated using the 20% threshold were the most similar to the SS consensus (average 99.6% identity, range 96.1-100%), compared to 15% (99.4%, 88.5-100%), 10% (99.2%, 87.4-100%), or 5% (98.5%, 86.4-100%). The average sequence identity between laboratories using thresholds of 20%, 15%, 10%, and 5% was 99.1%, 98.7%, 98.3%, and 97.3%, respectively. Using the 20% threshold, we observed an excellent agreement between NGS and SS, but significant differences at lower thresholds. Understanding how variation in NGS methods influences sequence quality is essential for NGS-based HIV-1 drug resistance genotyping.
Related Concept Videos
Next-generation Sequencing
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
Modern Molecular Taxonomy

