NOVEL RT-qPCR ASSAYS ENABLE RAPID DETECTION AND DIFFERENTIATION BETWEEN SARS-COV-2 OMICRON (BA.1) AND BA.2 VARIANTS

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Abstract

In this report, we describe the development and initial validation of novel SARS-COV-2 Omicron-specific reactions that enable the identification of Omicron (BA.1) and BA.2 variants. Mutations that are either shared by both BA.1 and BA.2, or are exclusive for BA.1 or for BA.2 were identified by bioinformatic analysis, and corresponding probe-based quantitative PCR reactions were developed to identify them. We show that multiplex combinations of these reactions provide a single-reaction identification of the sample as BA.1, BA.2, or as non-Omicron SARS-COV-2. All four reactions described herein have a sensitivity of less than ten copies per reaction, and are amendable for multiplexing. The results of this study suggest that the new assays may be useful for testing both clinical and environmental samples to differentiate between these two variants.

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  1. SciScore for 10.1101/2022.02.22.22271222: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Cell culture: Nasopharyngeal swab samples were used to infect Vero-6 cells as described previously (doi.org/10.1101/ 2021.10.11.21264831).
    Vero-6
    suggested: None

    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.
    • 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.

    Results from scite Reference Check: We found no unreliable references.


    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.