Rapid detection of inter-clade recombination in SARS-CoV-2 with Bolotie

  1. Ales Varabyou
  2. Christopher Pockrandt
  3. Steven L Salzberg
  4. Mihaela Pertea

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Abstract

The ability to detect recombination in pathogen genomes is crucial to the accuracy of phylogenetic analysis and consequently to forecasting the spread of infectious diseases and to developing therapeutics and public health policies. However, in case of the SARS-CoV-2, the low divergence of near-identical genomes sequenced over a short period of time makes conventional analysis infeasible. Using a novel method, we identified 225 anomalous SARS-CoV-2 genomes of likely recombinant origins out of the first 87,695 genomes to be released, several of which have persisted in the population. Bolotie is specifically designed to perform a rapid search for inter-clade recombination events over extremely large datasets, facilitating analysis of novel isolates in seconds. In cases where raw sequencing data were available, we were able to rule out the possibility that these samples represented co-infections by analyzing the underlying sequence reads. The Bolotie software and other data from our study are available at https://github.com/salzberg-lab/bolotie.

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  1. Version published to 10.1093/genetics/iyab074
  2. ScreenIT

    SciScore for 10.1101/2020.09.21.300913: (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
    SARS-CoV-2 reference genome isolate Wuhan-Hu-1 (GenBank, accession no. MN908947) was obtained from NCBI and used to guide the alignment, variant calling and consensus sequence generation in the protocol.
    NCBI
    suggested: (NCBI, RRID:SCR_006472)
    The mappings were further sorted and indexed using samtools (Li et al., 2009).
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    First, we re-built the tree using the set of 4,039 genomes using the general time-reversible model as used by the NextStrain platform and allowing IQ-TREE (Minh et al., 2020) to automatically choose the precise model.
    IQ-TREE
    suggested: (IQ-TREE, RRID:SCR_017254)
    Visualizations: Visualizations of phylogenetic trees were produced using custom scripts implemented in Python and R.
    Python
    suggested: (IPython, RRID:SCR_001658)

    Results from OddPub: Thank you for sharing your code and data.

    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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  3. Version published to 10.1101/2020.09.21.300913v1 on bioRxiv
  4. Version published to 10.1101/2020.09.21.300913v2 on bioRxiv