Investigating the Extent of Primer Dropout in SARS-CoV-2 Genome Sequences During the Early Circulation of Delta Variants

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Abstract

The SARS-CoV-2 Delta variant, corresponding to the Pangolin lineage B.1.617.2, was first detected in India in July 2020 and rapidly became dominant worldwide. The ARTIC v3 protocol for SARS-CoV-2 whole-genome sequencing, which relies on a large number of PCR primers, was among the first available early in the pandemic, but may be prone to coverage dropouts that result in incomplete genome sequences. A new set of primers (v4) was designed to circumvent this issue in June 2021. In this study, we investigated whether the sequencing community adopted the new sets of primers, especially in the context of the spread of the Delta lineage, in July 2021. Because information about protocols from individual laboratories is generally difficult to obtain, the aims of the study were to identify whether large under-sequenced regions were present in deposited Delta variant genome sequences (from April to August 2021), to investigate the extent of the coverage dropout among all the currently available Delta sequences in six countries, and to propose simple PCR primer modifications to sequence the missing region, especially for the first circulating Delta variants observed in 2021 in Switzerland. Candidate primers were tested on few clinical samples, highlighting the need to further pursue primer optimization and validation on a larger and diverse set of samples.

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  1. SciScore for 10.1101/2021.09.09.21262951: (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.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The proportion of Ns in the ROI sequences was calculated with the alphabetfrequency function of the Biostrings package [12].
    Biostrings
    suggested: (Biostrings, RRID:SCR_016949)

    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.