Ongoing Positive Selection Drives the Evolution of SARS-CoV-2 Genomes

Analysis of SARS-CoV-2 genome evolutionary patterns

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 (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 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 dN/dS 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 dN/dS change was observed in E, NSP1, and NSP13. The Ti/Tv 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 dN/dS ratio. Protein-wise dN/dS ratio was also seen to vary across the different variants.IMPORTANCETo 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.

Sequence analysis of the Spike, RNA-dependent RNA polymerase, and protease genes reveals a distinct evolutionary pattern of SARS-CoV-2 variants circulating in Yogyakarta and Central Java provinces, Indonesia

During the Covid-19 pandemic, the resurgence of SARS-CoV-2 was due to the development of novel variants of concern (VOC). Thus, genomic surveillance is essential to monitor continuing evolution of SARS-CoV-2 and to track the emergence of novel variants. In this study, we performed phylogenetic, mutation, and selection pressure analyses of the Spike, nsp12, nsp3, and nsp5 genes of SARS-CoV-2 isolates circulating in Yogyakarta and Central Java provinces, Indonesia from May 2021 to February 2022. Various bioinformatics tools were employed to investigate the evolutionary dynamics of distinct SARS-CoV-2 isolates. During the study period, 213 and 139 isolates of Omicron and Delta variants were identified, respectively. Particularly in the Spike gene, mutations were significantly more abundant in Omicron than in Delta variants. Consistently, in all of four genes studied, the substitution rates of Omicron were higher than that of Delta variants, especially in the Spike and nsp12 genes. In addition, selective pressure analysis revealed several sites that were positively selected in particular genes, implying that these sites were functionally essential for virus evolution. In conclusion, our study demonstrated a distinct evolutionary pattern of SARS-CoV-2 variants circulating in Yogyakarta and Central Java provinces, Indonesia.

Introduction and effect of natural selection analysis at common mutations of SARS-CoV-2 spike gene in Iran

The epidemic of coronavirus disease 2019 (COVID-19) was caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spike (S) protein of SARS-Cov-2 is composed of two subunits, S1 and S2. This study aimed to describe SARS-CoV-2 haplotypes in Iranians based on the S gene, which plays a key role in the receptor recognition and cell membrane fusion proses. 95 positive saliva samples for SARS-CoV-2 were amplified and sequenced for the S gene. The sequences were classified into 35 haplotypes, which 11 haplotypes were new (H1, H2, H3, H4, H6, H7, H11, H13, H15, H16, H25) and have not been reported so far. Amino acid substitutions were found at 40 positions that 23 were located at S1 subunit and 16 were at S2 subunit and one was at cleavage loop (P681H/R), thus polymorphisms at S1 subunit were found to be higher than S2. The neutrality index (NI) analyses showed a negative departure from the neutral substitution patterns (NI > 1) for S1 and S2 subunit in the studied sequences. The co-occurrence of B-cell epitopes and mutation sites were found in seven positions with more probably to be exposed the immune system pressure. In conclusion, the results provide the significant data to design an effective vaccine based on this protein.

Molecular Evolutionary Analyses of the Spike Protein Gene and Spike Protein in the SARS-CoV-2 Omicron Subvariants

To better understand the evolution of the SARS-CoV-2 Omicron subvariants, we performed molecular evolutionary analyses of the spike (S) protein gene/S protein using advanced bioinformatics technologies. First, time-scaled phylogenetic analysis estimated that a common ancestor of the Wuhan, Alpha, Beta, Delta variants, and Omicron variants/subvariants diverged in May 2020. After that, a common ancestor of the Omicron variant generated various Omicron subvariants over one year. Furthermore, a chimeric virus between the BM.1.1.1 and BJ.1 subvariants, known as XBB, diverged in July 2021, leading to the emergence of the prevalent subvariants XBB.1.5 and XBB.1.16. Next, similarity plot (SimPlot) data estimated that the recombination point (breakpoint) corresponded to nucleotide position 1373. As a result, XBB.1.5 subvariants had the 5' nucleotide side from the breakpoint as a strain with a BJ.1 sequence and the 3' nucleotide side as a strain with a BM.1.1.1 sequence. Genome network data showed that Omicron subvariants were genetically linked with the common ancestors of the Wuhan and Delta variants, resulting in many amino acid mutations. Selective pressure analysis estimated that the prevalent subvariants, XBB.1.5 and XBB.1.16, had specific amino acid mutations, such as V445P, G446S, N460K, and F486P, located in the RBD when compared with the BA.4 and BA.5 subvariants. Moreover, some representative immunogenicity-associated amino acid mutations, including L452R, F486V, R493Q, and V490S, were also found in these subvariants. These substitutions were involved in the conformational epitopes, implying that these mutations affect immunogenicity and vaccine evasion. Furthermore, these mutations were identified as positive selection sites. These results suggest that the S gene/S protein Omicron subvariants rapidly evolved, and mutations observed in the conformational epitopes may reduce the effectiveness of the current vaccine, including bivalent vaccines such as mRNA vaccines containing the BA.4/BA.5 subvariants.

On the Evolutionary Trajectory of SARS-CoV-2: Host Immunity as a Driver of Adaptation in RNA Viruses

Host immunity can exert a complex array of selective pressures on a pathogen, which can drive highly mutable RNA viruses towards viral escape. The plasticity of a virus depends on its rate of mutation, as well as the balance of fitness cost and benefit of mutations, including viral adaptations to the host's immune response. Since its emergence, SARS-CoV-2 has diversified into genetically distinct variants, which are characterised often by clusters of mutations that bolster its capacity to escape human innate and adaptive immunity. Such viral escape is well documented in the context of other pandemic RNA viruses such as the human immunodeficiency virus (HIV) and influenza virus. This review describes the selection pressures the host's antiviral immunity exerts on SARS-CoV-2 and other RNA viruses, resulting in divergence of viral strains into more adapted forms. As RNA viruses obscure themselves from host immunity, they uncover weak points in their own armoury that can inform more comprehensive, long-lasting, and potentially cross-protective vaccine coverage.