The analysis of deletions may reveal evolutionary trends and provide new insight into the surprising variability and rapidly spreading capability that SARS-CoV-2 has shown since its emergence. To understand the factors governing genomic stability, it is important to define the molecular mechanisms of deletions in the viral genome. In this work, we performed a statistical analysis of deletions. Specifically, we analyzed correlations between deletions in the SARS-CoV-2 genome and repetitive elements and documented a significant association of deletions with runs of identical (poly-) nucleotides and direct repeats. Our analyses of deletions in the accessory genes of SARS-CoV-2 suggested that there may be a hypervariability in ORF7A and ORF8 that is not associated with repetitive elements. Such recurrent search in a “sequence space” of accessory genes (that might be driven by natural selection) did not yet cause increased viability of the SARS-CoV-2 variants. However, deletions in the accessory genes may ultimately produce new variants that are more successful compared to the viral strains with the conventional architecture of the SARS-CoV-2 accessory genes.

SARS-CoV-2 has accumulated many mutations since its emergence in late 2019. Nucleotide substitutions leading to amino acid replacements constitute the primary material for natural selection. Insertions, deletions, and substitutions appear to be critical for coronavirus’s macro- and microevolution. Understanding the molecular mechanisms of mutations in the mutational hotspots (positions, loci with recurrent mutations, and nucleotide context) is important for disentangling roles of mutagenesis and selection. In the SARS-CoV-2 genome, deletions and insertions are frequently associated with repetitive sequences, whereas C>U substitutions are often surrounded by nucleotides resembling the APOBEC mutable motifs. We describe various approaches to mutation spectra analyses, including the context features of RNAs that are likely to be involved in the generation of recurrent mutations. We also discuss the interplay between mutations and natural selection as a complex evolutionary trend. The substantial variability and complexity of pipelines for the reconstruction of mutations and the huge number of genomic sequences are major problems for the analyses of mutations in the SARS-CoV-2 genome. As a solution, we advocate for the development of a centralized database of predicted mutations, which needs to be updated on a regular basis.