Evolutionary dynamics of indels in SARS-CoV-2 spike glycoprotein

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Abstract

SARS-CoV-2, responsible for the current COVID-19 pandemic that claimed over 4.2 million lives, belongs to a class of enveloped viruses that undergo quick evolutionary adjustments under selection pressure. Numerous variants have emerged in SARS-CoV-2 that are currently posing a serious challenge to the global vaccination effort and COVID-19 management. The evolutionary dynamics of this virus are only beginning to be explored. In this work, we have analysed 1.79 million spike glycoprotein sequences of SARS-CoV-2 and found that the virus is fine-tuning the spike with numerous amino acid insertions and deletions (indels). Indels seem to have a selective advantage as the proportions of sequences with indels were steadily increasing over time, currently at over 89%, with similar trends across countries/variants. There were as many as 420 unique indel positions and 447 unique combinations of indels. Despite their high frequency, indels resulted in only minimal alteration, including both gain and loss, of N-glycosylation sites. As indels and point mutations are positively correlated and sequences with indels have significantly more point mutations, they have implications in the context of evolutionary dynamics of the SARS-CoV-2 spike glycoprotein.

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  1. SciScore for 10.1101/2021.07.30.454557: (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
    For each sequence, a pair-wise alignment with the reference (EPI_ISL_402124) was done using Biopython (Cock et al., 2009).
    Biopython
    suggested: (Biopython, RRID:SCR_007173)
    Multiple sequence alignments, where required, were done using Clustal Omega (https://www.ebi.ac.uk/Tools/msa/clustalo/).
    Clustal Omega
    suggested: (Clustal Omega, RRID:SCR_001591)
    All sequence analysis and data handling, where specifically not mentioned, were performed in Python; and visualization/graphs were created in Microsoft Excel.
    Python
    suggested: (IPython, RRID:SCR_001658)
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    Structural analyses: The positions of indels and N-glycosylation sites were visualized on the 3D-structure of SARS-CoV-2 spike glycoprotein (PDB ID: 6VXX or 6XR8) using the Visual Molecular Dynamics (VMD) program (https://www.ks.uiuc.edu/Research/vmd/).
    https://www.ks.uiuc.edu/Research/vmd/
    suggested: (Visual Molecular Dynamics, RRID:SCR_001820)
    Finally, information on different functional domains of SARS-CoV-2 spike glycoprotein was obtained from the literature/UniProt (https://www.uniprot.org/) and residue overlap coefficient was enumerated (Table S2) (Vijaymeena and Kavitha, 2016).
    https://www.uniprot.org/
    suggested: (Universal Protein Resource, RRID:SCR_002380)

    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

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