Inferring the genetic variability in Indian SARS-CoV-2 genomes using consensus of multiple sequence alignment...

Area of Science:

• Genomics
• Virology
• Bioinformatics

Background:

• Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) causes a global pandemic, necessitating effective prevention strategies like vaccination.
• Understanding the genetic variability of SARS-CoV-2 is crucial for developing targeted interventions, especially within specific populations like India.

Purpose of the Study:

• To perform a genome-wide analysis of 566 Indian SARS-CoV-2 sequences to identify genetic mutations.
• To establish a consensus multiple sequence alignment (CMSA) to consolidate findings from various alignment tools.
• To identify specific mutations, including substitutions, deletions, and single nucleotide polymorphisms (SNPs), prevalent in the Indian SARS-CoV-2 strains.

Main Methods:

• Utilized multiple sequence alignment techniques including ClustalW, MUSCLE, ClustalO, and MAFFT to analyze 566 Indian SARS-CoV-2 genomes.
• Generated a Consensus Multiple Sequence Alignment (CMSA) to integrate results from the four alignment methods, preserving the advantages of each.
• Identified and cataloged unique substitutions, deletions, and SNPs within the analyzed viral genomes.

Main Results:

• The analysis revealed 767 unique substitutions, 2025 unique deletions, and 54 unique SNPs in the Indian SARS-CoV-2 genomes.
• Identified four specific SNPs that are present in approximately 60% of the analyzed Indian SARS-CoV-2 population.
• The identified mutations provide insights into the genetic landscape of SARS-CoV-2 in India.

Conclusions:

• The comprehensive mutation profile of Indian SARS-CoV-2 strains can aid in virus classification.
• The identified prevalent SNPs are valuable for informing the design and dosage of vaccines tailored for the Indian population.
• This genomic analysis contributes to a better understanding of SARS-CoV-2 evolution and pandemic response strategies.