Evidence map›Paper›PMID 39464729›Full record

ArticleVirusdisease2024

Molecular characterization, phylogenetic and variation analyses of SARS-CoV-2 strains in India.

Meghna Banerjee, Dipjyoti Chakraborty, Arindom Chakraborty

Abstract read
In one paragraph

Article in Virusdisease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Meghna BanerjeeDepartment of Bioscience and Biotechnology, Banasthali Vidyapith, Vanasthali, Rajasthan 304022 India.
Dipjyoti ChakrabortyDepartment of Bioscience and Biotechnology, Banasthali Vidyapith, Vanasthali, Rajasthan 304022 India.
Arindom ChakrabortyDepartment of Statistics, Visva-Bharati University, Santiniketan, West Bengal 731235 India.ORCID 0000-0003-0741-8955

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the wake of the havoc caused by the COVID-19 pandemic, it is imperative to use the available genomic sequence data to gain insight into the mutational and genomic diversity of SARS-CoV-2. Here we have performed comparative phylogenetic, mutational and genetic diversity analysis on 1962 SARS-CoV-2 genome sequences from seven worst hit Indian states during the third Covid-19 wave, to determine the SARS-CoV-2 strains and mutations in circulation during the third wave and the transmission pattern and disease epidemiology across the states and gain valuable insight into the viral evolution. 6083 Single nucleotide polymorphisms (SNPs) were discovered in the analysis with 93 SNPs common to all states. The genetic relatedness among the statewise multilocus genotypes was visualized by plotting a minimum spanning tree based on Bruvo's distance framework. The phylogenetic tree based on Nei's genetic distance showed distinct clades. The AMOVA results indicated that large proportion of the total genetic variation is distributed within the samples, rather than between the samples within each population and between the populations. Our findings provide insight into the SARS-CoV-2 variants and mutations which dominated the third COVID-19 wave in India and thus provide a basis to monitor and further assess these variants and their sub lineages and mutations for their clinical impact and reaction to existing and newly designed drugs and vaccines. The genetic diversity analysis helps in comprehending the viral transmission scenarios across the Indian states so as to enable the State government and researchers in developing state specific prevention measures for future. Supplementary Information: The online version contains supplementary material available at 10.1007/s13337-024-00878-7.

Indexed as

Genetic diversity analysisMutational analysisPhylogenySARS-CoV-2Single nucleotide polymorphism (SNP)

Identifiers

PMID39464729
PMCPMC11502728

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