PLoS ONEGenomicsPeer-reviewed journal article
Detecting SARS-CoV-2 variants with SNP genotyping
Helen HarperiD, Amanda J. BurridgeiD, Mark WinfieldiD, Adam H.R. FinniD, Andrew D. DavidsoniD, David A. MatthewsiD, Stephanie HutchingsiD, Barry B. Vipond, Nisha Jain, Keith J. EdwardsiD, Gary BarkeriD
Abstract
Tracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020- and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 76% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with our marker panel at a cost of < {pound}1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation.
- organism: virus
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 60
- FWCI
- 4.11
- Field percentile
- top 5%
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