Elucidation of Genome Polymorphisms in Emerging SARS-CoV-2

  1. Manisha Ray
  2. Saurav Sarkar
  3. Surya Narayan Rath
  4. Mukund Namdev Sable

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Abstract

The COVID-19 pandemic is having a devastating effect on the healthcare system and the economy of the world. The unavailability of a specific treatment regime and a candidate vaccine yet opens up scope for new approaches and discoveries of drugs for mitigation of the sufferings of humankind due to the disease. The present isolated whole-genome sequences of SARS-CoV-2 from 11 different nations subjected to evolutionary study and genome-wide association study through in silico approaches including multiple sequence alignment, phylogenetic study through MEGA7 and have been analyzed through DNAsp respectively. These investigations recognized the nucleotide varieties and single nucleotide mutations/polymorphisms on the genomic regions as well as protein-coding regions. The resulted mutations have diversified the genomic contents of SARS-CoV-2 according to the altered nucleotides found in 11 genome sequences. India and Nepal have found to have progressively more distinct species of SARS-CoV-2 with variations in Spike protein and Nucleocapsid protein-coding sites. These genomic variations might be the explanation behind the less case fatality rate of India and Nepal dependent on the populaces. The anticipated idea of this investigation upgrades the information about genomic medication and might be useful in the planning of antibodies against SARS-CoV-2.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.22.215731: (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.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Sequence Mining: There were total 92 whole-genome sequences of SARS-CoV-2 virus from different preceding countries throughout the world, have been deposited in the genome database (https://www.ncbi.nlm.nih.gov/genome/) of National Centre for Biotechnology Information (NCBI) (https://www.ncbi.nlm.nih.gov/) web portal.
    https://www.ncbi.nlm.nih.gov/
    suggested: (GENSAT at NCBI - Gene Expression Nervous System Atlas, RRID:SCR_003923)
    Multiple Sequence Alignment and Phylogenetic Analysis: All the collected genome sequences of SARS-CoV-2 were subjected to multiple sequence alignment through the Molecular Evolutionary Genetics Analysis 7 (MEGA 7)12 (https://www.megasoftware.net/) package by using the MUSCLE algorithm.
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)
    Study of Nucleotide Diversity and Haplotype: The study of genomics diversity has been implemented on the aligned sequences to analyze the difference between the genome sequences of SARS-CoV-2 by examining the variable sites, Nucleotide, and haplotype diversity in retrieved genome sequences through DNA sequence polymorphism software DNAsp 6 (http://www.ub.edu/dnasp/) 13.
    http://www.ub.edu/dnasp/
    suggested: (DnaSP, RRID:SCR_003067)

    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.
    • No funding statement was detected.
    • 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 10.1101/2020.07.22.215731v1 on bioRxiv