tetano
Editor, Senior Moderator
J Med Virol
. 2020 Dec 23.
doi: 10.1002/jmv.26756. Online ahead of print.
Dynamic tracking of variant frequencies depicts the evolution of mutation sites amongst SARS-CoV-2 genomes from India
Shenu Hudson B[SUP] 1 [/SUP], Vaishnavi Kolte[SUP] 1 [/SUP], Azra Khan[SUP] 1 [/SUP], Gaurav Sharma[SUP] 1 [/SUP]
Affiliations
Abstract
With the exponential spread of the coronavirus disease 2019 (COVID-19) pandemic across the world within the 12 months, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains are continuously trying to adapt themselves to the host environment by random mutations. When doing so, some variants with evolutionary advantages such as better human to human transmissibility potential might get naturally selected. This short communication demonstrates how the mutation frequency patterns are evolving in 2457 SAR-CoV-2 strains isolated from COVID-19 patients across diverse Indian states. We have identified 19 such variants showing contrasting mutational probabilities in the span of 7 months. Out of these, 14 variants are showing increasing mutational probabilities suggesting their propagation with time due to their unexplored evolutionary advantages. However, the mutational probabilities of five variants have significantly decreased in June onward as compared to March/April, suggesting their termination with time. Further in-depth investigation of these identified variants will provide valuable knowledge about the evolution, infection strategies, transmission rates, and epidemiology of SARS-CoV-2.
Keywords: COVID-19; SARS; bioinformatics; coronavirus; epidemiology; genomics.
. 2020 Dec 23.
doi: 10.1002/jmv.26756. Online ahead of print.
Dynamic tracking of variant frequencies depicts the evolution of mutation sites amongst SARS-CoV-2 genomes from India
Shenu Hudson B[SUP] 1 [/SUP], Vaishnavi Kolte[SUP] 1 [/SUP], Azra Khan[SUP] 1 [/SUP], Gaurav Sharma[SUP] 1 [/SUP]
Affiliations
- PMID: 33368386
- DOI: 10.1002/jmv.26756
Abstract
With the exponential spread of the coronavirus disease 2019 (COVID-19) pandemic across the world within the 12 months, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains are continuously trying to adapt themselves to the host environment by random mutations. When doing so, some variants with evolutionary advantages such as better human to human transmissibility potential might get naturally selected. This short communication demonstrates how the mutation frequency patterns are evolving in 2457 SAR-CoV-2 strains isolated from COVID-19 patients across diverse Indian states. We have identified 19 such variants showing contrasting mutational probabilities in the span of 7 months. Out of these, 14 variants are showing increasing mutational probabilities suggesting their propagation with time due to their unexplored evolutionary advantages. However, the mutational probabilities of five variants have significantly decreased in June onward as compared to March/April, suggesting their termination with time. Further in-depth investigation of these identified variants will provide valuable knowledge about the evolution, infection strategies, transmission rates, and epidemiology of SARS-CoV-2.
Keywords: COVID-19; SARS; bioinformatics; coronavirus; epidemiology; genomics.