Temporal patterns in the evolutionary genetic distance of SARS-CoV-2 during the COVID-19 pandemic

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Abstract

Background

During the pandemic of coronavirus disease 2019 (COVID-19), the genetic mutations occurred in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cumulatively or sporadically. In this study, we employed a computational approach to identify and trace the emerging patterns of the SARS-CoV-2 mutations, and quantify accumulative genetic distance across different periods and proteins.

Methods

Full-length human SARS-CoV-2 strains in United Kingdom were collected. We investigated the temporal variation in the evolutionary genetic distance defined by the Hamming distance since the start of COVID-19 pandemic.

Findings

Our results showed that the SARS-CoV-2 was in the process of continuous evolution, mainly involved in spike protein (S protein), the RNA-dependent RNA polymerase (RdRp) region of open reading frame 1 (ORF1) and nucleocapsid protein (N protein). By contrast, mutations in other proteins were sporadic and genetic distance to the initial sequenced strain did not show an increasing trend.

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  1. SciScore for 10.1101/2020.11.01.363739: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationWe used a stratified sampling scheme to randomly selected sequences in biweekly time interval.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Multiple sequences alignment was performed using MEGA-X (version 10.1.8).
    MEGA-X
    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.

    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.