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1.
Transbound Emerg Dis ; 69(5): e2418-e2430, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1819932

ABSTRACT

Surveillance of genetic diversity of the SARS-CoV-2 is extremely important to detect the emergence of more infectious and deadly strains of the virus. In this study, we evaluated mutational events in the SARS-CoV-2 genomes through whole genome sequencing. The samples were collected from COVID-19 patients in different major cities of Pakistan during the four waves of the pandemic (May 2020 to July 2021) and subjected to whole genome sequencing. Using in silico and machine learning tools, the viral mutational events were analyzed, and variants of concern and of interest were identified during each of the four waves. The overall mutation frequency (mutations per genome) increased during the course of the pandemic from 12.19 to 23.63, 31.03, and 41.22 in the first, second, third, and fourth waves, respectively. We determined that the viral strains rose to higher frequencies in local transmission. The first wave had three most common strains B.1.36, B.1.160, and B.1.255, the second wave comprised B.1.36 and B.1.247 strains, the third wave had B.1.1.7 (Alpha variant) and B.1.36 strains, and the fourth waves comprised B.1.617.2 (Delta). Intriguingly, the B.1.36 variants were found in all the waves of the infection indicating their survival fitness. Through phylogenetic analysis, the probable routes of transmission of various strains in the country were determined. Collectively, our study provided an insight into the evolution of SARS-CoV-2 lineages in the spatiotemporal local transmission during different waves of the pandemic, which aided the state institutions in implementing adequate preventive measures.


Subject(s)
COVID-19 , SARS-CoV-2 , Animals , COVID-19/epidemiology , COVID-19/veterinary , Genome, Viral/genetics , Genomics , Mutation , Pakistan/epidemiology , Phylogeny , SARS-CoV-2/genetics
2.
J Med Virol ; 93(7): 4382-4391, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1263102

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic has spread around the globe very rapidly. Previously, the evolution pattern and similarity among the COVID-19 causative organism severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and causative organisms of other similar infections have been determined using a single type of genetic marker in different studies. Herein, the SARS-CoV-2 and related ß coronaviruses Middle East respiratory syndrome coronavirus (MERS-CoV), SARS-CoV,  bat coronavirus (BAT-CoV) were comprehensively analyzed using a custom-built pipeline that employed phylogenetic approaches based on multiple types of genetic markers including the whole genome sequences, mutations in nucleotide sequences, mutations in protein sequences, and microsatellites. The whole-genome sequence-based phylogeny revealed that the strains of SARS-CoV-2 are more similar to the BAT-CoV strains. The mutational analysis showed that on average MERS-CoV and BAT-CoV genomes differed at 134.21 and 136.72 sites, respectively, whereas the SARS-CoV genome differed at 26.64 sites from the reference genome of SARS-CoV-2. Furthermore, the microsatellite analysis highlighted a relatively higher number of average microsatellites for MERS-CoV and SARS-CoV-2 (106.8 and 107, respectively), and a lower number for SARS-CoV and BAT-CoV (95.8 and 98.5, respectively). Collectively, the analysis of multiple genetic markers of selected ß viral genomes revealed that the newly born SARS-COV-2 is closely related to BAT-CoV, whereas, MERS-CoV is more distinct from the SARS-CoV-2 than BAT-CoV and SARS-CoV.


Subject(s)
Alphacoronavirus/genetics , Genome, Viral/genetics , Microsatellite Repeats/genetics , Middle East Respiratory Syndrome Coronavirus/genetics , SARS-CoV-2/genetics , Severe acute respiratory syndrome-related coronavirus/genetics , Animals , Base Sequence/genetics , Chiroptera/virology , DNA Mutational Analysis , Genetic Markers/genetics , Genetic Variation/genetics , Humans , Phylogeny , Sequence Alignment , Sequence Homology, Nucleic Acid , Whole Genome Sequencing
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