Tracing Back the Temporal Change of SARS-CoV-2 with Genomic Signatures

  1. Sourav Biswas
  2. Suparna Saha
  3. Sanghamitra Bandyopadhyay
  4. Malay Bhattacharyya

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Abstract

The coronavirus disease (COVID-19) outbreak starting from China at the end of 2019 and its subsequent spread in many countries have given rise to thousands of coronavirus samples being collected and sequenced till date. To trace back the initial temporal change of SARS-CoV-2, the coronavirus implicated in COVID-19, we study the limited genomic sequences that were available within the first couple of months of its spread. These samples were collected under varying circumstances and highlight wide variations in their genomic compositions. In this paper, we explore whether these variations characterize the initial temporal change of SARS-CoV-2 sequences. We observe that n -mer distributions in the SARS-CoV-2 samples, which were collected at an earlier period of time, predict its collection timeline with approximately 78% accuracy. However, such a distinctive pattern disappears with the inclusion of samples collected at a later time. We further observe that isolation sources (e.g., oronasopharynx, saliva, feces, etc.) could not be predicted by the n -mer patterns in these sequences. Finally, the phylogenetic and protein-alignment analyses highlight interesting associations between SARS-CoV-2 and other coronaviruses.

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    SciScore for 10.1101/2020.04.24.057380: (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 phylogenmetic tree was built using the tool embedded in NCBI Virus and further processed in the form of a consensus network using SplitsTree (version 5.0.0_alpha).
    SplitsTree
    suggested: (SplitsTree, RRID:SCR_014734)

    Results from OddPub: Thank you for sharing your 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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.04.24.057380 on bioRxiv