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

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

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, previous methods for detecting recombination and reassortment events cannot handle the computational requirements of analyzing tens of thousands of genomes, a scenario that has now emerged in the effort to track the spread of the SARS-CoV-2 virus. Furthermore, the low divergence of near-identical genomes sequenced in short periods of time presents a statistical challenge not addressed by available methods. In this work we present Bolotie, an efficient method designed to detect recombination and reassortment events between clades of viral genomes. We applied our method to a large collection of SARS-CoV-2 genomes and discovered hundreds of isolates that are likely of a recombinant origin. In cases where raw sequencing data was available, we were able to rule out the possibility that these samples represented co-infections by analyzing the underlying sequence reads. Our findings further show that several recombinants appear to have persisted in the population.

Article activity feed

  1. 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.

    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 10.1101/2020.09.21.300913 on bioRxiv