Comprehensive variant and haplotype landscapes of 50,500 global SARS-CoV-2 isolates and accelerating accumulation of country-private variant profiles

  1. Lishuang Shen
  2. Jennifer Dien Bard
  3. Jaclyn A. Biegel
  4. Alexander R. Judkins
  5. Xiaowu Gai

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Abstract

Understanding the genetic etiology of COVID-19 requires a comprehensive understanding of the variant and haplotype landscape of all reported genomes of SARS-COV-2, the causative virus of the disease. Country-, state/region- and possibly even city-private variant profiles may contribute to varied disease exemplifications and fatality rates observed across the globe along with host factors such as age, ethnicity and comorbidity. The Children’s Hospital of Los Angeles (CHLA) COVID-19 Analysis Research Database (CARD) captures up-to-date fulllength SARS-CoV-2 sequences of ~50,500 isolates from GISAID, GenBank, CHLA Center for Personalized Medicine, and other sources (as of June 18, 2020). Among which, 49,637 isolates carry at least one variation from the reference genome NC_045512, a total of 6,070 variants and 2,513 haplotypes were detected in at least three isolates independently. Together, they constituted the most likely SARS-CoV-2 variant and haplotype landscapes world-wide currently.

Evidence supporting positive (orf3a, orf8, S genes) and purifying (M gene) selections were detected, which warrants further investigation. Most interestingly, we identified 1,583 countryprivate variants from 10,238 isolates (20.6% overall) reported in 48 countries. 807 countryprivate haplotypes, defined as a haplotype shared by at least 5 isolates all of which came from the same country, were identified in in 8,656 isolates from 39 countries. United Kingdom, USA, and Australia had 464, 166 and 32 private haplotypes respectively, comprising 22.4%, 16.6% and 16.4% of the isolates from each country. Together with their descendent and private haplotypes with fewer members, 22,171 (45.8%) isolates carried country-private haplotypes globally. The percentage were 28.2-29.6% in January to March, and rapidly increased to 46.4% and 59.6% in April and May, co-occurring with global travel restrictions. The localization of the variant profiles appeared to be similarly accelerating from 14.2% in March and 28.4% in April to over 40% isolates carrying the country-private variants around May.

In summary, a common pattern is seen world-wide in COVID-19 in which at the onset of disease there appeared to be a significant number of SARS-CoV-2 variants that accumulate quickly and then begin to rapidly coalesce into distinct haplotypes. This may be the result of localized outbreaks due to factors such as multiple points viral introduction, geographic separation and the introduction of policies such as travel restriction, social distancing and quarantine, resulting in the emergence of country-private haplotypes.

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    SciScore for 10.1101/2020.07.09.193722: (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
    Variant functional annotation was carried out by snpEff (v4.31t).
    snpEff
    suggested: (SnpEff, RRID:SCR_005191)
    An isolate’s variant profile was compared against the global collection of over 50,500 viral sequences in CARD.
    CARD
    suggested: (CARD, RRID:SCR_016602)
    Multiple sequence alignment (MSA) was done with MAFFT version 7.460 (Katoh et al, 2002; Katoh and Toh, 2008) using speed-oriented method FFT-NS-i (iterative refinement method, two cycles) optimized for large data-sets of thousands of full-length viral genomes.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    The original multiple sequence alignment (MSA) was manually examined in BioEdit to remove obviously low quality or outlier sequences.
    BioEdit
    suggested: (BioEdit, RRID:SCR_007361)
    The phylogenetic tree was visualized in MEGA X and FigTree v1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/).
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)
    FigTree
    suggested: (FigTree, RRID:SCR_008515)

    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.

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  2. Version published to 10.1101/2020.07.09.193722v1 on bioRxiv