Author: Saha, Indrajit; Ghosh, Nimisha; Maity, Debasree; Sharma, Nikhil; Mitra, Kaushik
                    Title: Inferring the genetic variability in Indian SARS-CoV-2 genomes using consensus of multiple sequence alignment techniques  Cord-id: vc7i3zer  Document date: 2020_9_1
                    ID: vc7i3zer
                    
                    Snippet: Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a threat to the human population and has created a worldwide pandemic. Daily thousands of people are getting affected by the SARS-CoV-2 virus; India being no exception. In this situation, there is no doubt that vaccine is the primary prevention strategy to contain the wave of COVID-19 pandemic. In this regard, genome-wide analysis of SARS-CoV-2 is important to understand its genetical variability. This has motivated us to analyse th
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a threat to the human population and has created a worldwide pandemic. Daily thousands of people are getting affected by the SARS-CoV-2 virus; India being no exception. In this situation, there is no doubt that vaccine is the primary prevention strategy to contain the wave of COVID-19 pandemic. In this regard, genome-wide analysis of SARS-CoV-2 is important to understand its genetical variability. This has motivated us to analyse the 566 Indian SARS-CoV-2 sequences using multiple sequence alignment techniques viz. ClustalW, MUSCLE, ClustalO and MAFFT to identify the lists of mutations as substitution, deletion, insertion and SNP. Thereafter, a consensus of these results, called as Consensus Multiple Sequence Alignment (CMSA), is considered to have the final list of mutations so that the advantages of all four alignment techniques can be preserved. The analysis shows 767, 2025 and 54 unique substitutions, deletions and SNPs in Indian SARS-CoV-2 genomes. More precisely, out of 54 SNPs, 4 SNPs are present close to the 60% of the virus population. The results of this experiment can be useful for the virus classification, designing and defining the dose of vaccine for the Indian population.
 
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