Introduction: Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had a disastrous effect worldwide during the previous three years due to widespread infections with SARS-CoV-2 and its emerging variations. More than 674 million confirmed cases and over 6.7 million deaths have been attributed to successive waves of SARS-CoV-2 infections as of 29th January 2023. Similar to other RNA viruses, SARS-CoV-2 is more susceptible to genetic evolution and spontaneous mutations over time, resulting in the continual emergence of variants with distinct characteristics. Spontaneous mutations of SARS-CoV-2 variants increase its transmissibility, virulence, and disease severity and diminish the efficacy of therapeutics and vaccines, resulting in vaccine-breakthrough infections and re-infection, leading to high mortality and morbidity rates.Materials and methods: In this study, we evaluated 10,531 whole genome sequences of all reported variants globally through a computational approach to assess the spread and emergence of the mutations in the SARS-CoV-2 genome. The available data sources of NextCladeCLI 2.3.0 (https://clades.nextstrain.org/) and NextStrain (https://nextstrain.org/) were searched for tracking SARS-CoV-2 mutations, analysed using the PROVEAN, Polyphen-2, and Predict SNP mutational analysis tools and validated by Machine Learning models.Result: Compared to the Wuhan-Hu-1 reference strain NC 045512.2, genome-wide annotations showed 16,954 mutations in the SARS-CoV-2 genome. We determined that the Omicron variant had 6,307 mutations (retrieved sequence:1947), including 67.8% unique mutations, more than any other variant evaluated in this study. The spike protein of the Omicron variant harboured 876 mutations, including 443 deleterious mutations. Among these deleterious mutations, 187 were common and 256 were unique non-synonymous mutations. In contrast, after analysing 1,884 sequences of the Delta variant, we discovered 4,468 mutations, of which 66% were unique, and not previously reported in other variants. Mutations affecting spike proteins are mostly found in RBD regions for Omicron, whereas most of the Delta variant mutations drawn to focus on amino acid regions ranging from 911 to 924 in the context of epitope prediction (B cell & T cell) and mutational stability impact analysis protruding that Omicron is more transmissible.Discussion: The pathogenesis of the Omicron variant could be prevented if the deleterious and persistent unique immunosuppressive mutations can be targeted for vaccination or small-molecule inhibitor designing. Thus, our findings will help researchers monitor and track the continuously evolving nature of SARS-CoV-2 strains, the associated genetic variants, and their implications for developing effective control and prophylaxis strategies.

The identification of deleterious mutations in different variants of SARS-CoV-2, and their roles in the morbidity of COVID-19 patients are yet to be explored. Analyzing 5,724 complete genomes of SARS-CoV-2, sequenced from deceased COVID-19 patients globally during January 2020 to February 2023, we found that SARS-CoV-2 genomes of the deceased belonged to 21 Nextstrain clades, of which clade 20I (Alpha variant) was the most predominating clade followed by clade 20H (Beta variant) and clade 20J (Gamma variant). The highest percentage (33.4%) of SARS-CoV-2 genomes from deceased patients were sequenced from North America, while the lowest (0.98%) was from Africa. The “G” clade was found to be predominated in the SARS-CoV-2 genomes Asian, African, and North American regions whereas “GRY” clade outweighed in Europe. We identified 35,799 nucleotide mutations throughout the genome keeping the highest (n = 11,402) frequency in the spike protein. More importantly, 4,150 point-specific amino acids (aa) mutations in SARS-CoV-2 genomes, and of them, D614G (20%) and N501Y (14%) deleterious mutations in the spike protein were found as the top two mutations worldwide. We also detected five frequent deleterious aa mutations such as G18V, W45S, I33T, P30L, and Q418H, responsible for defining each clade of the SARS-CoV-2. Our novel findings could therefore be useful for genomic surveillance and monitoring the integrated pattern of SARS-CoV-2 infection, its emerging variants, and their impacts on developing effective vaccination and control methodology.