Spatial and Temporal Analysis of SARS-CoV-2 Genome Evolutionary Patterns

Abstract

ABSTRACTThe spread of SARS-CoV-2 virus accompanied by availability of abundant sequence data publicly, provides a window for determining the spatio-temporal patterns of viral evolution in response to vaccination. In this study, SARS-CoV-2 genome sequences were collected from seven countries in the period January 2020-December 2022. The sequences were classified into three phases, namely: pre-vaccination, post-vaccination, and recent period. Comparison was performed between these phases based on parameters like mutation rates, selection pressure (dN/dS ratio), and transition to transversion ratios (Ti/Tv). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t-test. The comparative analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across different countries from the pre-vaccination phase. The dN/dS ratios showed positive selection that increased after vaccination, and the Ti/Tv ratios decreased after vaccination. C→U and G→U were the most frequent transitions and transversions in all the countries. However, U→G was the most frequent transversion in recent period. The Omicron variant had the highest genomic mutation rates, while Delta showed the highest dN/dS ratio. Mutation rates were highest in NSP3, S, N and NSP12b before and increased further after vaccination. NSP4 showed the largest change in mutation rates after vaccination. N, ORF8, ORF3a and ORF10 were under highest positive selection before vaccination. They were overtaken by E, S and NSP1 in the after vaccination as well as recent sequences, with the largest change observed in NSP1. Protein-wise dN/dS ratio was also seen to vary across the different variants.ImportanceIrrespective of the different vaccine technologies used, geographical regions and host genetics, variations in the SARS-CoV-2 genome have maintained similar patterns worldwide. To the best of our knowledge, there exists no other large-scale study of the genomic and protein-wise mutation patterns during the time course of evolution in different countries. Analysing the SARS-CoV-2 evolution patterns in response to spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.