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    A next generation sequencing (NGS) analysis to reveal genomic and proteomic mutation landscapes of SARS-CoV-2 in South Asia

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    2021
    Author
    Saha, Ayan
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    Abstract
    Counts for SARS-CoV-2 associated infections and fatalities are on the rise globally even in regions which con- tained the spread momentarily. The pattern of infections has been found to be controlled by the distinctive selection pressures exerted by fluctuating environmental nature and hosts. A total of 410 whole-genome se- quences submitted by the South Asian countries were retrieved from the GISAID database and analyzed to assess the impact and pattern of mutations in this region. Most common and frequent mutations in the South Asian countries are 241C > T, 3037C > T, 14408C > T, and 23403A > G and about 85% SNPs are localized in ORF1ab, spike protein, and nucleocapsid. Among the identified mutations, the proportion of missense type (54.17%) was highest, followed by the synonymous (41.66%) and the non-coding types (4.17%). While analyzing transmission source in terms of geolocation, the largest clustered group from the South Asian countries was based on the G- clade (D614G) (81.7%; 335/410 samples), tracing the inception and transmission of SARS-CoV-2 infections in the South Asian countries from European regions. Phylogenetic analysis also revealed that the South Asian strains are highly related to the South American and European strains. We found that G-clade mutations are more prevalent (96.19%) in the samples of Bangladesh which were also prevalent in the European isolates. Surpris- ingly, one missense mutation (1163A > T) in ORF1ab gene became dominant only in Bangladesh (78.8%), which led to debates regarding effects on the pathogenicity and transmissibility of the virus. Overall, the findings of this study highlight the frequently mutated SARS-CoV-2 variants among the COVID-19 patients in the South Asian countries which might ease containment of the disease in this region through investigating the virulence reducing factors as the identified mutations are strongly correlated with low infection and mortality rate.
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    https://repository.auw.edu.bd/handle/123456789/853
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