As the SARS-CoV-2 (SCV-2) virus evolves, diagnostics and vaccines against novel strains rely on viral genome sequencing. Researchers have gravitated towards the cost-effective and highly sensitive amplicon-based (e.g. ARTIC) and hybrid capture sequencing (e.g. SARS-CoV-2 NGS Assay) to selectively target the SCV-2 genome. We provide an in silico predictive model to compare these 2 technologies and present additional data on the high scalability of the SARS-CoV-2 NGS Assay.

In silico work implemented alignments of 383,656 genome sequences of variant of concern (VOC) and variant of interest (VOI) isolates (GISAID). We compared the clinical performance of ARTIC V3 amplicon sequencing and SARS-CoV-2 NGS Assay (Twist Bioscience) using viral isolates with mutations within amplicon primers and hybrid capture probes. The miniaturized hybrid capture workflow was optimized and clinically evaluated to support high-throughput (384-plex), and sequencing data was processed by COVID-DX software.

We found 101,432 viruses (27%) had ≥1 mismatch in the last 6 base pairs from the 3’ end of ARTIC primers. In contrast, only 38 viruses (0.01%) had enough mutations (≥10) predicted to have a similar effect on hybrid capture sequencing. We then created synthetic genomes of 4 isolates with excess mutations in ARTIC primers and observed dropouts in sequencing coverage for amplicon libraries but not hybrid capture. In fact, we observed an incidental dropout of amplicon 72 in 2 samples caused by a recurrent 1bp mismatch. Both assays detected a wide range of variants (~99.9% coverage at 5X depth) in clinical samples (CT value < 30) collected in NY (Spring 2020-Spring 2021). The distribution of the number of reads and on target rates were more uniform among specimens within amplicon-based sequencing. However, uneven genome coverage and primer dropouts, some in the spike protein, were observed on VOC/VOI and other isolates highlighting some limitations of an amplicon-based approach.

The SARS-CoV-2 NGS Assay is a comprehensive and scalable sequencing tool for variant profiling, yields more consistent coverage and smaller dropout rate compared to ARTIC (0.05% vs. 7.7%).