Detecting SARS-CoV-2 variants with SNP genotyping

  1. Helen Harper
  2. Amanda Burridge
  3. Mark Winfield
  4. Adam Finn
  5. Andrew Davidson
  6. David Matthews
  7. Stephanie Hutchings
  8. Barry Vipond
  9. Nisha Jain
  10. The COVID-19 Genomics UK (COG-UK) Consortium
  11. Keith Edwards
  12. Gary Barker

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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 61.9% 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 a marker panel at a cost of < £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.

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  1. Version published to 10.1371/journal.pone.0243185
  2. ScreenIT

    SciScore for 10.1101/2020.11.18.388140: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    PHE samples: Viral RNA was extracted using the silica guanidinium isothiocyanate binding method (12) adapted for the ThermoFisher Kingfisher using paramagnetic silica particles (Magnesil, Promega).
    ThermoFisher Kingfisher
    suggested: None
    Genotype calling was performed using the Kraken software package version 11.5 (LGC Genomics).
    Kraken
    suggested: (Kraken, RRID:SCR_005484)
    Samples were grouped into identical genotypes with the script qc_genotype_data.pl, which was added to the GITHUB (https://github.com/pr0kary0te/SARSmarkers) along with the SNP marker discovery pipeline.
    GITHUB
    suggested: (GitHub, RRID:SCR_002630)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Panel update: A limitation of genotyping is the ascertainment bias of the probe design. Novel mutations cannot be detected which relies on an existing sequencing effort such as that performed by the COG-UK Consortium. As new mutations are discovered by traditional sequencing, the tools made available in our software pipeline may be used to design a relevant probe set for the current circulating viral population. Markers in the panel were updated based on variant analysis of the 2020-09-03 release of sequences from the COG-UK consortium to reflect the new variants circulating in the UK. We found 91 SNPs with a frequency > 0.01 in the week 19 – 35 analysis, compared to 41 SNPs in the data to week 18. The majority of the SNPs were rare, however, and we found that limiting the marker set to the most informative 24 markers gave us slightly better discriminatory power on the week 19-35 samples (95% of random pairs differentiated) than our original 19 marker set designed from week 1-18 data (89% differentiated). SNPs will continue to arise and go extinct, but our analysis suggests that a small and cost-effective panel of 20-24 markers will continue to provide useful discriminatory power in many settings. Application: While sequence data may offer a greater depth of information, RT-PACE genotyping can offer a rapid and low-cost solution to rapidly identify sample differences within a population. A set of 20-24 markers may be screened against 192 samples for around £2.30 per sample an...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.11.18.388140v1 on bioRxiv