The error rate displayed during template copying to produce viral RNA progeny is a biologically relevant parameter of the replication complexes of viruses. It has consequences for virus–host interactions, and it represents the first step in the diversification of viruses in nature. Measurements during infections and with purified viral polymerases indicate that mutation rates for RNA viruses are in the range of 10⁻³ to 10⁻⁶ copying errors per nucleotide incorporated into the nascent RNA product. Although viruses are thought to exploit high error rates for adaptation to changing environments, some of them possess misincorporation correcting activities. One of them is a proofreading-repair 3′ to 5′ exonuclease present in coronaviruses that may decrease the error rate during replication. Here we review experimental evidence and models of information maintenance that explain why elevated mutation rates have been preserved during the evolution of RNA (and some DNA) viruses. The models also offer an interpretation of why error correction mechanisms have evolved to maintain the stability of genetic information carried out by large viral RNA genomes such as the coronaviruses.

Populations of RNA viruses are composed of complex and dynamic mixtures of variant genomes that are termed mutant spectra or mutant clouds. This applies also to SARS-CoV-2, and mutations that are detected at low frequency in an infected individual can be dominant (represented in the consensus sequence) in subsequent variants of interest or variants of concern. Here we briefly review the main conclusions of our work on mutant spectrum characterization of hepatitis C virus (HCV) and SARS-CoV-2 at the nucleotide and amino acid levels and address the following two new questions derived from previous results: (i) how is the SARS-CoV-2 mutant and deletion spectrum composition in diagnostic samples, when examined at progressively lower cut-off mutant frequency values in ultra-deep sequencing; (ii) how the frequency distribution of minority amino acid substitutions in SARS-CoV-2 compares with that of HCV sampled also from infected patients. The main conclusions are the following: (i) the number of different mutations found at low frequency in SARS-CoV-2 mutant spectra increases dramatically (50- to 100-fold) as the cut-off frequency for mutation detection is lowered from 0.5% to 0.1%, and (ii) that, contrary to HCV, SARS-CoV-2 mutant spectra exhibit a deficit of intermediate frequency amino acid substitutions. The possible origin and implications of mutant spectrum differences among RNA viruses are discussed.

The study shows that extensive replication of an RNA virus in a constant biological environment does not limit exploration of sequence space and adaptive options. There was no convergence toward a restricted set of adapted genomes. Mutational waves and mutant spectrum broadening affected infectious genomes. Therefore, profound modifications of mutant spectrum composition and consensus sequence diversification are not exclusively dependent on environmental alterations or the intervention of population bottlenecks.

Replication of SARS-CoV-2 in the human population is defined by distributions of mutants that are present at different frequencies within the infected host and can be detected by ultra-deep sequencing techniques. In this study, we examined the SARS-CoV-2 mutant spectra of amplicons from the spike-coding (S-coding) region of 5 nasopharyngeal isolates derived from patients with vaccine breakthrough. Interestingly, all patients became infected with the Alpha variant, but amino acid substitutions that correspond to the Delta Plus, Iota, and Omicron variants were present in the mutant spectra of the resident virus. Deep sequencing analysis of SARS-CoV-2 from patients with vaccine breakthrough revealed a rich reservoir of mutant types and may also identify tolerated substitutions that can be represented in epidemiologically dominant variants.