The rise and fall of SARS-CoV-2 variants and the mutational profile of Omicron

  1. Tanner Wiegand
  2. Aidan McVey
  3. Anna Nemudraia
  4. Artem Nemudryi
  5. Blake Wiedenheft

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

In late December of 2019, high throughput sequencing technologies enabled rapid identification of SARS-CoV-2 as the etiological agent of COVID-19, and global sequencing efforts are now a critical tool for monitoring the ongoing spread and evolution of this virus. Here, we analyze a subset (n=87,032) of all publicly available SARS-CoV-2 genomes (n=∼5.6 million) that were randomly selected, but equally distributed over the course of the pandemic. We plot the appearance of new variants of concern (VOCs) over time and show that the mutation rates in Omicron viruses are significantly greater than those in previously identified SARS-CoV-2 variants. Mutations in Omicron are primarily restricted to the spike protein, while 25 other viral proteins— including those involved in SARS-CoV-2 replication—are highly conserved. Collectively, this suggests that the genetic distinction of Omicron primarily arose from selective pressures on the spike, and that the fidelity of replication of this variant has not been altered.

Importance

Omicron is the fifth SARS-CoV-2 variant to be designated a Variant of Concern (VOC) by the World Health Organization (WHO). Here we provide a retrospective analysis of SARS-CoV-2 variants and explain how the Omicron variant is distinct. Our work shows that the spike protein is a ‘hotspot’ for viral evolution in all variants, suggesting that existing vaccines and diagnostics that target this protein may become less effective against Omicron and that our therapeutic and public health strategies will have to evolve along with the virus.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.12.16.473096: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot 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 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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.12.16.473096v1 on bioRxiv