Comparative Analysis of Emerging B.1.1.7+E484K SARS-CoV-2 Isolates

  1. Ahmed M Moustafa
  2. Colleen Bianco
  3. Lidiya Denu
  4. Azad Ahmed
  5. Susan E Coffin
  6. Brandy Neide
  7. John Everett
  8. Shantan Reddy
  9. Emilie Rabut
  10. Jasmine Deseignora
  11. Michael D Feldman
  12. Kyle G Rodino
  13. Frederic Bushman
  14. Rebecca M Harris
  15. Josh Chang Mell
  16. Paul J Planet

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Abstract

We report the genome of a B.1.1.7+E484K severe acute respiratory syndrome coronavirus 2 from Southeastern Pennsylvania and compare it with all high-coverage B.1.1.7+E484K genomes (n = 235) available. Analyses showed the existence of at least 4 distinct clades of this variant circulating in the United States and the possibility of at least 59 independent acquisitions of the E484K mutation.

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  1. Version published to 10.1093/ofid/ofab300
  2. ScreenIT

    SciScore for 10.1101/2021.04.21.440801: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: The sample was obtained by as part of routine clinical care, solely for non-research purposes, carrying minimal risk, and were therefore granted a waiver of informed consent as reviewed under protocol number under IRB 21-018478.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Briefly, WGS of extracted viral RNA was performed as previously described using Paragon Genomics CleanPlex SARS-CoV-2 Research and Surveillance NGS Panel17,18.
    WGS
    suggested: None
    All the high coverage SARS-CoV-2 genomes (n=236) were assigned a clonal complex using the GNUVID v2.2 database (version January 6th 2021)15.
    GNUVID
    suggested: None
    Temporal plots were plotted in GraphPad Prism v7.0a.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.04.21.440801v1 on bioRxiv