Diagnostics and vaccines against novel SARS-CoV-2 (SCV-2) 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. To demonstrate the advantages of hybrid capture for viral surveillance, we implemented predictive modeling to assess areas in the SCV-2 genome that may be more prone to mutations that could impact primer efficiency in the multiplexing PCR step during amplicon sequencing.

We analyzed 383,656 genome sequences of variant of concern (VOC) and variant of interest (VOI) isolates from GISAID and 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. Our approach identified 4 isolates with excess mutations in ARTIC primers, which we produced synthetic genomes of and compared the performance of ARTIC amplicon sequencing with Twist Bioscience’s SARS-CoV-2 NGS Assay. For each strain, we observed dropouts in sequencing coverage for amplicon libraries only but not for hybrid capture. Incidentally, we observed an additional dropout of ARTIC amplicon 72 in two samples caused by a recurrent 1bp mismatch in the reverse primer. We also compared dropout using invariant reference controls (Twist Synthetic SARS-CoV-2 RNA Control 2) and found hybrid capture sequenced 99.5% of bases at ≥50X coverage compared to 92.1% for amplicon sequencing.

Taken altogether, our results demonstrate that hybrid capture is more robust to genomic variation and leads to fewer dropout events. Although amplicon sequencing provides a low-cost platform for viral surveillance, it comes at the added cost of sequencing dropout which can cause incorrect classification of viral lineages. This is further compounded by the certainty that mutations will accumulate in SCV-2, making it a matter of time until more primers fail. Therefore we suggest that Hybrid Capture is a robust and comprehensive solution for viral surveillance.