Genomic Epidemiology of SARS-CoV-2 in Pakistan

  1. Shuhui Song
  2. Cuiping Li
  3. Lu Kang
  4. Dongmei Tian
  5. Nazish Badar
  6. Wentai Ma
  7. Shilei Zhao
  8. Xuan Jiang
  9. Chun Wang
  10. Yongqiao Sun
  11. Wenjie Li
  12. Meng Lei
  13. Shuangli Li
  14. Qiuhui Qi
  15. Aamer Ikram
  16. Muhammad Salman
  17. Massab Umair
  18. Huma Shireen
  19. Fatima Batool
  20. Bing Zhang
  21. Hua Chen
  22. Yun-Gui Yang
  23. Amir Ali Abbasi
  24. Mingkun Li
  25. Yongbiao Xue
  26. Yiming Bao

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Abstract

COVID-19 has swept globally and Pakistan is no exception. To investigate the initial introductions and transmissions of the SARS-CoV-2 in Pakistan, we performed the largest genomic epidemiology study of COVID-19 in Pakistan and generated 150 complete SARS-CoV-2 genome sequences from samples collected from March 16 to June 1, 2020. We identified a total of 347 mutated positions, 31 of which were over-represented in Pakistan. Meanwhile, we found over 1000 intra-host single-nucleotide variants (iSNVs). Several of them occurred concurrently, indicating possible interactions among them or coevolution. Some of the high-frequency iSNVs in Pakistan were not observed in the global population, suggesting strong purifying selections. The genomic epidemiology revealed five distinctive spreading clusters. The largest cluster consisted of 74 viruses which were derived from different geographic locations of Pakistan and formed a deep hierarchical structure, indicating an extensive and persistent nation-wide transmission of the virus that was probably attributed to a signature mutation (G8371T in ORF1ab) of this cluster. Furthermore, 28 putative international introductions were identified, several of which are consistent with the epidemiological investigations. In all, this study has inferred the possible pathways of introductions and transmissions of SARS-CoV-2 in Pakistan, which could aid ongoing and future viral surveillance and COVID-19 control.

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  1. Version published to 10.1016/j.gpb.2021.08.007
  2. ScreenIT

    SciScore for 10.1101/2021.06.24.21255875: (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
    Reads with high mapping quality (MQ > 25) were retained by SAMtools(14), and duplicated reads were marked with MarkDuplicates package in Genome Analysis Toolkit (GATK)(15).
    Genome Analysis Toolkit
    suggested: None
    Genomic variants were identified using uniquely mapped reads by HaplotypeCaller package in GATK.
    HaplotypeCaller
    suggested: None
    GATK
    suggested: (GATK, RRID:SCR_001876)
    Detection of intra-host variations: To identify the intra-host variant, mpileup files were generated by samtools v1.8 and then parsed by VarScan v2.3.9 along with an in-house script to identify intra-host variants.
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    VarScan
    suggested: (VARSCAN, RRID:SCR_006849)
    All intra-host variants identified had to satisfy the following criteria: (1) sequencing depth ≥ 100, (2) minor allele frequency ≥ 5%, (3) minor allele frequency ≥ 2% on each strand, (4) minor allele counts ≥ 10 on each strand, (5) strand bias of the minor allele < 10, (6) minor allele was supported by the inner part of the read (excluding 10 base pairs on each end), and (7) minor allele was supported by ≥ 10 reads that mapped exclusively to the genome of Betacoronavirus by Kraken v2.0.8-beta on each strand.
    Kraken
    suggested: (Kraken, RRID:SCR_005484)
    Multiple sequence alignment was performed with MUSCLE v 3.8.31(20), and the UTR sequences of all sequences were truncated based on nucleotide coordinates of the reference genome (GenBank: MN908947.3)(12).
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)

    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.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.06.24.21255875 on medRxiv