COVID-19 infection and transmission includes complex sequence diversity

  1. Ernest R. Chan
  2. Lucas D. Jones
  3. Marlin Linger
  4. Jeffrey D. Kovach
  5. Maria M. Torres-Teran
  6. Audric Wertz
  7. Curtis J. Donskey
  8. Peter A. Zimmerman

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Abstract

SARS-CoV-2 whole genome sequencing has played an important role in documenting the emergence of polymorphisms in the viral genome and its continuing evolution during the COVID-19 pandemic. Here we present data from over 360 patients to characterize the complex sequence diversity of individual infections identified during multiple variant surges (e.g., Alpha and Delta). Across our survey, we observed significantly increasing SARS-CoV-2 sequence diversity during the pandemic and frequent occurrence of multiple biallelic sequence polymorphisms in all infections. This sequence polymorphism shows that SARS-CoV-2 infections are heterogeneous mixtures. Convention for reporting microbial pathogens guides investigators to report a majority consensus sequence. In our study, we found that this approach would under-report sequence variation in all samples tested. As we find that this sequence heterogeneity is efficiently transmitted from donors to recipients, our findings illustrate that infection complexity must be monitored and reported more completely to understand SARS-CoV-2 infection and transmission dynamics. Many of the nucleotide changes that would not be reported in a majority consensus sequence have now been observed as lineage defining SNPs in Omicron BA.1 and/or BA.2 variants. This suggests that minority alleles in earlier SARS-CoV-2 infections may play an important role in the continuing evolution of new variants of concern.

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  1. Version published to 10.1371/journal.pgen.1010200
  2. ScreenIT

    SciScore for 10.1101/2022.04.18.488717: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study protocol was approved by the Cleveland VA Medical Center’s Institutional Review Board (IRB protocol number 1584025) with a waiver of consent.
    Sex as a biological variablenot detected.
    RandomizationTo perform this analysis, we randomly selected and analyzed 110 additional COVID-19 infections reported from 18 different laboratories or consortia with raw sequence data available in the sequence read archive (SRA) (Supplemental Table 4).
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Variants were called at positions with a minimum coverage of 100 reads with a base quality score >20 using Samtools mpileup v1.8.
    Samtools
    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.

    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.

  3. Version published to 10.1101/2022.04.18.488717v1 on bioRxiv