Highly sensitive and full-genome interrogation of SARS-CoV-2 using multiplexed PCR enrichment followed by next-generation sequencing

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Abstract

Many detection methods have been used or reported for the diagnosis and/or surveillance of COVID-19. Among them, reverse transcription polymerase chain reaction (RT-PCR) is the most commonly used because of its high sensitivity, typically claiming detection of about 5 copies of viruses. However, it has been reported that only 47-59% of the positive cases were identified by some RT-PCR methods, probably due to low viral load, timing of sampling, degradation of virus RNA in the sampling process, or possible mutations spanning the primer binding sites. Therefore, alternative and highly sensitive methods are imperative. With the goal of improving sensitivity and accommodating various application settings, we developed a multiplex-PCR-based method comprised of 343 pairs of specific primers, and demonstrated its efficiency to detect SARS-CoV-2 at low copy numbers. The assay produced clean characteristic target peaks of defined sizes, which allowed for direct identification of positives by electrophoresis. We further amplified the entire SARS-CoV-2 genome from 8 to half a million viral copies purified from 13 COVID-19 positive specimens, and detected mutations through next generation sequencing. Finally, we developed a multiplex-PCR-based metagenomic method in parallel, that required modest sequencing depth for uncovering SARS-CoV-2 mutational diversity and potentially novel or emerging isolates.

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  1. SciScore for 10.1101/2020.03.12.988246: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    In Microsoft Excel, the following function was used: P = 1 - POISSON.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    The resulting BAM files were then used to calculate depth and coverage metrics using Samtools version 1.3.1.
    Samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)

    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

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