Analysis of SARS-CoV-2 genome evolutionary patterns

Abstract

The spread of SARS-CoV-2 virus accompanied by public availability of abundant sequence data provides a window for the determination of viral evolutionary patterns. 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 (d N /d S ratio), and transition to transversion ratios (T i /T v ). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t -test. The analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across all countries from the pre-vaccination sequences. 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. The d N /d S ratios showed purifying selection that shifted toward neutral selection after vaccination. N, ORF8, ORF3a, and ORF10 were under highest positive selection before vaccination. Shift toward neutral selection was driven by E, NSP3, and ORF7a in the after vaccination set. In recent sequences, the largest d N /d S change was observed in E, NSP1, and NSP13. The T i /T v ratios decreased with time. C→U and G→U were the most frequent transitions and transversions. 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 d N /d S ratio. Protein-wise d N /d S ratio was also seen to vary across the different variants. IMPORTANCE 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. Analyzing the SARS-CoV-2 evolutionary patterns in view of the varying spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.

On the SARS-CoV-2 Variants

“…The host immune response represents a significant force driving viral evolution [33]. As the virus interacts with the host immune system, mutations that confer a selective advantage, such as enhanced immune evasion or increased replication efficiency, may arise and become prevalent within the viral population [34]. Moreover, the landscape of susceptible hosts within a population undergoes dynamic changes due to natural infection, vaccination campaigns, and other factors.…”

Unique RNA replication characteristics and nucleocapsid protein expression may explain differences in the replication capacity of SARS-COV-2 lineages

“…The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was identified in December 2019 and responsible for the coronavirus disease 2019 (COVID-19) pandemic. Despite its lower mutation rates compared to other RNA viruses, some factors contribute to the accumulation/selection of mutations within the viral genome such as: the widespread virus circulation, independent introduction events, host adaptive immune pressure, persistent infections, and the high immunization level 1,2,3 . The first major mutation that altered viral dynamics was the Spike (S) glycoprotein substitution D614G, which arose in March 2020 and was rapidly overcoming the original Wuhan virus 4 .…”