Prediction of the Effects of Synonymous Variants on SARS-CoV-2 Genome

Background: The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had led to a global pandemic since December 2019. SARS-CoV-2 is single-stranded RNA virus, which mutates at higher rate. Multiple studies been done identify and study nonsynonymous mutations, change amino acid residues proteins. On the other hand, there little on effects synonymous mutations. Although these mutations do not alter acids, some suggest that they may affect viral fitness. This aims predict effect genome. Methods: A total 30,229 genomic sequences were retrieved from Global Initiative Sharing all Influenza Data (GISAID) database aligned using MAFFT. Then, their respective frequency identified. A prediction secondary structures base pair probabilities was performed structure stability. Relative codon usage (RSCU) analysis also measure bias (CUB) SARS-CoV-2. Results: 150 The mutation identified with highest C3037U in nsp3 ORF1a, followed by C313U C9286U nsp1 nsp4 respectively. Conclusion: Among identified, C913U ORF1a C26735U membrane (M) protein structure, reducing stability folding possibly resulting translation However, lab experiments are required validate results obtained analysis.