Genomics of Indian SARS-CoV-2: Implications in Genetic Diversity, Possible Origin and Spread of Virus

  1. Mainak Mondal
  2. Ankita Lawarde
  3. Kumaravel Somasundaram

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Abstract

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  1. Version published to 10.18520/cs/v118/i11/1786-1791
  2. ScreenIT

    SciScore for 10.1101/2020.04.25.20079475: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Among Indian viral isolates, seven viral genome sequences that belong to passaged virus through cell lines (Vero CCL81 isolate P1) were excluded in this study.
    Vero CCL81
    suggested: None
    Software and Algorithms
    SentencesResources
    Phylogenetic tree analysis: A total of 449 complete genomes were taken for alignment using MAFFT version 7.402 at CIPRES Science Gateway (Miller et al., 2010).
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    The tree file obtained was visualized using Figtree version 1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/).
    Figtree
    suggested: (FigTree, RRID:SCR_008515)
    Obtained genes were aligned using CLUSTAL Omega algorithm (Madeira et al., 2019) and translated to amino acid sequences.
    CLUSTAL
    suggested: (Clustal X , RRID:SCR_017055)
    The aligned protein coding genes was visualized in BioEdit version 7.2.5 (Hall et al., 1999).
    BioEdit
    suggested: (BioEdit, RRID:SCR_007361)

    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: We detected the following sentences addressing limitations in the study:
    Although the sequence information is available from 11,919 SARS-CoV-2 isolates from all continents, the phylogenetic data from 3123 samples, which included 4 Indian isolates, is only available at GISAID website because of limitation with respect to single view performance and legibility reasons (Figure 1; Supplementary figure 1). It is of our interest to note that there are two major clusters-Asian cluster represented by purple and related colours and European cluster represented by greenish yellow. The Indian samples, represented by arrows (black and white) cluster with both Asian cluster and European clusters. It is interesting to note that while the Indian samples with black arrows were isolated during January 2020, the other two samples with white arrows were isolated during March 2020 (see more details later). Further to precisely map the origin of Indian SARS-CoV-2 isolates, we carried out an independent phylogenetic analysis using a selected set of samples representing most regions and countries where COVID-19 infection rate is high. Our selection criteria also considered the fact that more genomes are sequenced in USA, Europe, East Asia and Oceania compared to other parts of the world. Hence, we chose a set of 449 samples derived from USA (75), Europe (80), China (75), East Asia (64), South Asia (41), Oceania (75), Middle East (11) and India (28). The analysis shows interesting features about the possible source of Indian SARS-CoV-2 samples (Figure 2; Supplementary fi...

    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.

  3. Version published to 10.1101/2020.04.25.20079475v1 on medRxiv