SARS-CoV-2 Genomes From Oklahoma, United States

  1. Sai Narayanan
  2. John C. Ritchey
  3. Girish Patil
  4. Teluguakula Narasaraju
  5. Sunil More
  6. Jerry Malayer
  7. Jeremiah Saliki
  8. Anil Kaul
  9. Pratul K. Agarwal
  10. Akhilesh Ramachandran

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Abstract

Genomic sequencing has played a major role in understanding the pathogenicity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With the current pandemic, it is essential that SARS-CoV-2 viruses are sequenced regularly to determine mutations and genomic modifications in different geographical locations. In this study, we sequenced SARS-CoV-2 from five clinical samples obtained in Oklahoma, United States during different time points of pandemic presence in the state. One sample from the initial days of the pandemic in the state and four during the peak in Oklahoma were sequenced. Previously reported mutations including D614G in S gene, P4715L in ORF1ab, S194L, R203K, and G204R in N gene were identified in the genomes sequenced in this study. Possible novel mutations were also detected in the S gene (G1167V), ORF1ab (A6269S and P3371S), ORF7b (T28I), and ORF8 (G96R). Phylogenetic analysis of the genomes showed similarity to other SARS-CoV-2 viruses reported from across the globe. Structural characterization indicates that the mutations in S gene possibly influences conformational flexibility and motion of the spike protein, and the mutations in N gene are associated with disordered linker region within the nucleocapsid protein.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.15.20195420: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the Institutional Review Board (Application number: IRB-20-357) at Oklahoma State
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Libraries were then pooled and sequenced using MinION (Oxford Nanopore Technologies, UK) platform following manufacturer recommendations.
    MinION
    suggested: (MinION, RRID:SCR_017985)
    Genome Assembly, Alignment and Phylogenetic analysis: Sequences obtained were assembled de novo using Canu (28).
    Canu
    suggested: (Canu, RRID:SCR_015880)
    To assess uniqueness of the genomes sequenced in this study, MAFFT (31, 32) was used to align whole sequences of the 5 genomes to SARS-CoV-2 reference genome (NC_045512.2).
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Individual genes were aligned to SARS-CoV-2 Wuhan Hu-1 genome from NCBI (GenBank ID: MN908947.3) using MUSCLE aligner in MEGA-X (35) to identify SNPs and changes in the amino acid produced by the gene.
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)
    A General Time Reversible (GTR) substitution model based Unweighted Pair Group Method with Arithmetic Mean (UPGMA) alignment was constructed using MAFFT and FastTree (36).
    FastTree
    suggested: (FastTree, RRID:SCR_015501)

    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.
    • 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 10.3389/fgene.2020.612571
  3. Version published to 10.1101/2020.09.15.20195420 on medRxiv