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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an enormous burden on the healthcare system worldwide as a consequence of its new emerging variants of concern (VOCs) since late 2019. Elucidating viral genome characteristics and its influence on disease severity and clinical outcome has been one of the crucial aspects toward pandemic management. Genomic surveillance holds the key to identify the spectrum of mutations vis-à-vis disease outcome. Here, in our study, we performed a comprehensive analysis of the mutation distribution among the coronavirus disease 2019 (COVID-19) recovered and mortality patients. In addition to the clinical data analysis, the significant mutations within the two groups were analyzed for their global presence in an effort to understand the temporal dynamics of the mutations globally in comparison with our cohort. Interestingly, we found that all the mutations within the recovered patients showed significantly low global presence, indicating the possibility of regional pool of mutations and the absence of preferential selection by the virus during the course of the pandemic. In addition, we found the mutation S194L to have the most significant occurrence in the mortality group, suggesting its role toward a severe disease progression. Also, we discovered three mutations within the mortality patients with a high cohort and global distribution, which later became a part of variants of interest (VOIs)/VOCs, suggesting its significant role in enhancing viral characteristics. To understand the possible mechanism, we performed molecular dynamics (MD) simulations of nucleocapsid mutations, S194L and S194*, from the mortality and recovered patients, respectively, to examine its impacts on protein structure and stability. Importantly, we observed the mutation S194* within the recovered to be comparatively unstable, hence showing a low global frequency, as we observed. Thus, our study provides integrative insights about the clinical features, mutations significantly associated with the two different clinical outcomes, its global presence, and its possible effects at the structural level to understand the role of mutations in driving the COVID-19 pandemic.

SARS-CoV-2 virus pathogenicity and transmissibility are correlated with the mutations acquired over time, giving rise to variants of concern (VOCs). Mutations can significantly influence the genetic make-up of the virus. Herein, we analyzed the SARS-CoV-2 genomes and sub-genomic nucleotide composition in relation to the mutation rate. Nucleotide percentage distributions of 1397 in-house-sequenced SARS-CoV-2 genomes were enumerated, and comparative analyses (i) within the VOCs and of (ii) recovered and mortality patients were performed. Fisher’s test was carried out to highlight the significant mutations, followed by RNA secondary structure prediction and protein modeling for their functional impacts. Subsequently, a uniform dinucleotide composition of AT and GC was found across study cohorts. Notably, the N gene was observed to have a high GC percentage coupled with a relatively higher mutation rate. Functional analysis demonstrated the N gene mutations, C29144T and G29332T, to induce structural changes at the RNA level. Protein secondary structure prediction with N gene missense mutations revealed a differential composition of alpha helices, beta sheets, and coils, whereas the tertiary structure displayed no significant changes. Additionally, the N gene CTD region displayed no mutations. The analysis highlighted the importance of N protein in viral evolution with CTD as a possible target for antiviral drugs.

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