Rampant C->U hypermutation in the genomes of SARS-CoV-2 and other coronaviruses – causes and consequences for their short and long evolutionary trajectories

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Abstract

The pandemic of SARS coronavirus 2 (SARS-CoV-2) has motivated an intensive analysis of its molecular epidemiology following its worldwide spread. To understand the early evolutionary events following its emergence, a dataset of 985 complete SARS-CoV-2 sequences was assembled. Variants showed a mean 5.5-9.5 nucleotide differences from each other, commensurate with a mid-range coronavirus substitution rate of 3×10 −4 substitutions/site/year. Almost half of sequence changes were C->U transitions with an 8-fold base frequency normalised directional asymmetry between C->U and U->C substitutions. Elevated ratios were observed in other recently emerged coronaviruses (SARS-CoV and MERS-CoV) and to a decreasing degree in other human coronaviruses (HCoV-NL63, -OC43, -229E and -HKU1) proportionate to their increasing divergence. C->U transitions underpinned almost half of the amino acid differences between SARS-CoV-2 variants, and occurred preferentially in both 5’U/A and 3’U/A flanking sequence contexts comparable to favoured motifs of human APOBEC3 proteins. Marked base asymmetries observed in non-pandemic human coronaviruses (U>>A>G>>C) and low G+C contents may represent long term effects of prolonged C->U hypermutation in their hosts.

Importance

The evidence that much of sequence change in SARS-CoV-2 and other coronaviruses may be driven by a host APOBEC-like editing process has profound implications for understanding their short and long term evolution. Repeated cycles of mutation and reversion in favoured mutational hotspots and the widespread occurrence of amino acid changes with no adaptive value for the virus represents a quite different paradigm of virus sequence change from neutral and Darwinian evolutionary frameworks that are typically used in molecular epidemiology investigations.

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  1. SciScore for 10.1101/2020.05.01.072330: (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

    No key resources detected.


    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.

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