Emergence of SARS-CoV-2 stains harbouring the signature mutations of both A2a and A3 clade

  1. Rakesh Sarkar
  2. Anindita Banerjee
  3. Shanta Dutta
  4. Mamta Chawla-Sarkar

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Abstract

SARS-CoV-2 strains with both high transmissibility and potential to cause asymptomatic infection is expected to gain selective advantage over other circulating strains having either high transmissibility or ability to trigger asymptomatic infection. The D614G mutation in spike glycoprotein, the characteristic mutation A2a clade, has been associated with high transmissibility, whereas the A3 clade specific mutation L37F in NSP6 protein has been linked with asymptomatic infection. In this study, we performed a comprehensive mutational analysis of 3,77,129 SARS-CoV-2 genomes collected during January, 2020 to December, 2020 from all across the world for the presence of D614G and L37F mutations. Out of 3,77,129 SARS-CoV-2 strains analysed, 14, 598 (3.87%) were found to harbour both the D614G and L37F mutations. Majority of these double mutant SARS-CoV-2 strains were identified in Europe (11097) followed by North America (1915), Asia (980), Oceania (242), Africa (219), and South America (145). Geographical root surveillance revealed their first emergence during February-March in all the six continents. Temporal prevalence analysis from February, 2020 to December, 2020 showed a gradual upsurge in their frequencies worldwide, which strongly demonstrated the adaptive selection of these double mutants. Evolutionary analysis depicted that these double mutants emerged as a new clade in the dendrogram (named as A2a/3), and were sub-divided into four distinct clusters (Cluster I, II, III and IV) according to different sets of coexisting mutations. The frequency distribution pattern showed the global predominance of cluster III (41.42%), followed by cluster IV (23.31%), cluster II (21.02%) and cluster I (14.25%). Overall, our study highlighted the emergence of a unique phylogenetic clade encompassing the double-mutant SARS-CoV-2 strains which may provide a fitness advantage during course of virus evolution.

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    SciScore for 10.1101/2021.02.04.21251117: (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
    For phylogenetic analysis multiple genome sequence alignment was done with online alignment program MAFT version 7 (https://mafft.cbrc.jp/alignment/server/).
    https://mafft.cbrc.jp/alignment/server/
    suggested: (MAFFT, RRID:SCR_011811)
    The whole genome phylogenetic dendrogram was constructed using the MAFT alignment file by MEGA, version X (Molecular Evolutionary Genetics Analysis), employing the maximum-likelihood statistical method (at 1000 bootstrap replicates) and using the best fit nucleotide substitution model.
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)

    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.

  2. Version published to 10.1101/2021.02.04.21251117v1 on medRxiv