SARS-CoV-2 gene content and COVID-19 mutation impact by comparing 44 Sarbecovirus genomes

  1. Irwin Jungreis
  2. Rachel Sealfon
  3. Manolis Kellis

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Despite its clinical importance, the SARS-CoV-2 gene set remains unresolved, hindering dissection of COVID-19 biology. We use comparative genomics to provide a high-confidence protein-coding gene set, characterize evolutionary constraint, and prioritize functional mutations. We select 44 Sarbecovirus genomes at ideally-suited evolutionary distances, and quantify protein-coding evolutionary signatures and overlapping constraint. We find strong protein-coding signatures for ORFs 3a, 6, 7a, 7b, 8, 9b, and a novel alternate-frame gene, ORF3c, whereas ORFs 2b, 3d/3d-2, 3b, 9c, and 10 lack protein-coding signatures or convincing experimental evidence of protein-coding function. Furthermore, we show no other conserved protein-coding genes remain to be discovered. Mutation analysis suggests ORF8 contributes to within-individual fitness but not person-to-person transmission. Cross-strain and within-strain evolutionary pressures agree, except for fewer-than-expected within-strain mutations in nsp3 and S1, and more-than-expected in nucleocapsid, which shows a cluster of mutations in a predicted B-cell epitope, suggesting immune-avoidance selection. Evolutionary histories of residues disrupted by spike-protein substitutions D614G, N501Y, E484K, and K417N/T provide clues about their biology, and we catalog likely-functional co-inherited mutations. Previously reported RNA-modification sites show no enrichment for conservation. Here we report a high-confidence gene set and evolutionary-history annotations providing valuable resources and insights on SARS-CoV-2 biology, mutations, and evolution.

Article activity feed

  1. Version published to 10.1038/s41467-021-22905-7
  2. Version published to 10.21203/rs.3.rs-80345/v1 on Research Square
  3. Version published to 10.1101/2020.06.02.130955v2 on bioRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.06.02.130955: (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
    The UniProt annotations for SARS-CoV-2 were obtained from the UCSC Genome Browser 48 on April 5, 2020.
    UCSC Genome Browser
    suggested: (UCSC Genome Browser, RRID:SCR_005780)
    The Phylogenetic tree was calculated using RAxML 51 using the GTRCATX model.
    RAxML
    suggested: (RAxML, RRID:SCR_006086)
    FRESCo 29 was run using HYPHY version 2.220180618beta(MP) for Linux on x86_64 on 9-codon windows in each of the NCBI annotated ORFs.
    HYPHY
    suggested: (HyPhy, RRID:SCR_016162)
    However, in Supplementary Table S3, we also classified variants according to our proposed reference gene annotations (fields beginning with New_); when classifying variants in overlapping ORFs 3a/3c and N/9b we classify SNVs relative to the ORF in which the variant is non-synonymous if that is true for only one of the frames, or the ORF for which the amino acid change is more radical (as defined by the blosum62 matrix obtained from biopython version 1.58 53) if it is non-synonymous in both frames, or the larger ORF if the variant is synonymous in both frames.
    biopython
    suggested: (Biopython, RRID:SCR_007173)
    To further test significance of the SNV depletion in S1, we downloaded a larger set of SNVs from the UCSC Table Browser as above on 2020-05-09.
    UCSC Table Browser
    suggested: None

    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.

  5. Version published to 10.1101/2020.06.02.130955v1 on bioRxiv