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Infect Genet Evol
. 2021 Jul 13;105003.
doi: 10.1016/j.meegid.2021.105003. Online ahead of print.
Genetic and evolutionary analysis of SARS-CoV-2 circulating in the region surrounding Islamabad, Pakistan
Sana Tamim 1 , Nidia S Trovao 2 , Peter Thielen 3 , Tom Mehoke 3 , Brian Merritt 3 , Aamer Ikram 4 , Muhammad Salman 4 , Muhammad Masroor Alam 5 , Massab Umair 4 , Nazish Badar 4 , Adnan Khurshid 5 , Nayab Mehmood 5
Affiliations
- PMID: 34271187
- PMCID: PMC8277555
- DOI: 10.1016/j.meegid.2021.105003
Abstract
Genomic epidemiology of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has provided global epidemiological insight into the COVID-19 pandemic since it began. Sequencing of the virus has been performed at scale, with many countries depositing data into open access repositories to enable in-depth global phylogenetic analysis. To contribute to these efforts, we established an Oxford Nanopore Technologies (ONT) sequencing capability at the National Institutes of Health (NIH), Pakistan. This study highlights multiple SARS-CoV-2 lineages co-circulating during the peak of a second COVID-19 wave in Pakistan (Nov 2020-Feb 2021), with virus origins traced to the United States of America and Saudi Arabia. Ten SARS-CoV-2 positive samples were used for ONT library preparation. Sequence and phylogenetic analysis determined that the patients were infected with lineage B.1.1.250, originally identified in the United Kingdom and Bangladesh during March and April of 2020, and in circulation until the time of this study in Europe, USA and Australia. Lineage B.1.261 was originally identified in Saudi Arabia with widespread local dissemination in Pakistan. One sample clustered with the parental B.1 lineage and the other with lineage B.6 originally from Singapore. In the future, monitoring the evolutionary dynamics of circulating lineages in Pakistan will enable improved tracing of the viral spread, changing trends of their expansion trajectories, persistence, changes in their demographic dynamics, and provide guidance for better implementation of control measures.
Keywords: Bayesian analysis; COVID-19; Genomics; Pakistan; Phylodynamics; SARS-CoV-2; Viral evolution.