Detection and whole-genome sequencing of SARS-CoV-2 B.1.617.2 and B.1.351 variants of concern from Pakistan during the COVID-19 third wave

  1. Massab Umair
  2. Aamer Ikram
  3. Muhammad Salman
  4. Nazish Badar
  5. Syed Adnan Haider
  6. Zaira Rehman
  7. Muhammad Ammar
  8. Muhammad Suleman Rana
  9. Qasim Ali

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The viral lineages reflecting variants of concern have emerged worldwide and among them B.1.1.7 (Alpha), B.1351 (Beta) and B.1.617.2 (Delta) variants are the most significant ones and merit close monitoring. In Pakistan, very limited information is available on the circulation of these variants and only the alpha variant has been reported as the main circulating lineage. The objective of this study was to detect and explore the genomic diversity of B.1.351 and B.1.617.2 during the third wave in the indigenous population. During the current study, a total of 2274 samples were tested on real-time PCR for the presence of SARS-CoV-2 from May 14 to May 31, 2021, and among these, 17% were spike positive, whereas 83% of samples had the spike gene target failure (SGTF). From these spike positive samples, 22 samples were processed for whole-genome sequencing. Among VOCs, 45.5% (n=10) belonged to B.1.351 followed by B.1.617.2, 36% (n=8). The delta variant cases were reported mostly from Islamabad (n = 5; 63%) followed by Peshawar and Azad Kashmir (n = 1; 13% each). Beta variant cases originated from Islamabad (n=5; 56%), Peshawar (n=2; 22%), Azad Kashmir and Rawalpindi (n=1; 11% each). The mutation profile of delta variant isolates reported significant mutations, L452R, T478K, P681R, and D950N. The beta variant isolates reported characteristic mutations, D215G, K417N, E484K, N501Y, and A701V. Notably, a characteristic mutation, E484Q was also found in delta variant, B.1.617.2. Our current findings suggest detection of these VOCs from the local population and warrants large-scale genomic surveillance in the country. In addition, it provides timely information to the health authorities to take appropriate actions.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.07.14.21259909: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The prepared libraries were pooled and subjected to sequencing on Illumina platform, iSeq using sequencing reagent, iSeq 100 i1 Reagent v2 (300-cycle) (Illumina, Inc, USA) at Department of Virology, National Institute of Health, Islamabad, Pakistan. Data Analysis: The FastQC tool (v0.11.9) was used to assess the read quality of sequenced files [16].
    FastQC
    suggested: (FastQC, RRID:SCR_014583)
    Trimmomatic (v0.39) [15] was employed to remove Illumina adapter sequences and low-quality base calls with scores less than 30 to eliminate technical biases and artifacts.
    Trimmomatic
    suggested: (Trimmomatic, RRID:SCR_011848)
    The filtered reads were assembled by aligning with the available reference genome of SARS-CoV-2 (Accession number: NC_045512.2) using the Burrows-Wheeler Aligner’s (BWA, v0.7.17) default settings [16].
    BWA
    suggested: (BWA, RRID:SCR_010910)
    To begin, BLAST searches were conducted on the GISAID database against all SARS-CoV-2 genome sequences for each of the current study’s beta and delta isolates.
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    The sequences were clustered using Augur,
    Augur
    suggested: None
    Alignment of the sequences to the Wuhan reference genome was performed using MAFFT v7.470 [21].
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    The initial phylogenetic tree was constructed using IQTREE v1.6.12 [22], which implements the Augur tree using the generalized time reversible (GTR) model and performs bootstrapping to ensure a high degree of confidence in the tree topology.
    IQTREE
    suggested: None

    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.

    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 10.1101/2021.07.14.21259909v1 on medRxiv