Genomic epidemiology of SARS-CoV-2 in Russia reveals recurring cross-border transmission throughout 2020

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Abstract

SARS-CoV-2 has spread rapidly across the globe, with most nations failing to prevent or substantially delay its introduction. While many countries have imposed some limitations on trans-border passenger traffic, the effect of these measures on the spread of COVID-19 strains remains unclear. Here, we report an analysis of whole-genome sequencing of 3206 SARS-CoV-2 samples from 78 regions of Russia covering the period between March and November 2020. We describe recurring imports of multiple COVID-19 strains throughout this period, giving rise to 457 uniquely Russian transmission lineages, as well as repeated cross-border transmissions of local circulating variants out of Russia.

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  1. SciScore for 10.1101/2021.03.31.21254115: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Library concentration was measured with the Qubit 4 Fluorometer (Thermo Fisher Scientific; Waltham, MA, USA) using the Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific).
    Thermo Fisher Scientific
    suggested: (Thermo Fisher Scientific, RRID:SCR_008452)
    Supplementary Data ACKN) and aligned with MAFFT v7.45324 against the reference genome Wuhan-Hu-1/2019 (NCBI ID: MN908947.3) with --addfragments - -keeplength options.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Phylogenetic analysis: For each of the five subsets, we constructed a phylogenetic tree using IQ-Tree v2.1.126 under the GTR substitution model and ‘-fast -altr 1000’ as options and reconstructed ancestral sequences at the internal tree nodes with TreeTime v0.8.012.
    IQ-Tree
    suggested: (IQ-TREE, RRID:SCR_017254)

    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.