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Biased Mutation and Selection in RNA Viruses.

ABSTRACT: RNA viruses are responsible for some of the worst pandemics known to mankind, including outbreaks of Influenza, Ebola, and COVID-19. One major challenge in tackling RNA viruses is the fact they are extremely genetically diverse. Nevertheless, they share common features that include their dependence on host cells for replication, and high mutation rates. We set out to search for shared evolutionary characteristics that may aid in gaining a broader understanding of RNA virus evolution, and constructed a phylogeny-based data set spanning thousands of sequences from diverse single-stranded RNA viruses of animals. Strikingly, we found that the vast majority of these viruses have a skewed nucleotide composition, manifested as adenine rich (A-rich) coding sequences. In order to test whether A-richness is driven by selection or by biased mutation processes, we harnessed the effects of incomplete purifying selection at the tips of virus phylogenies. Our results revealed consistent mutational biases toward U rather than A in genomes of all viruses. In +ssRNA viruses, we found that this bias is compensated by selection against U and selection for A, which leads to A-rich genomes. In -ssRNA viruses, the genomic mutational bias toward U on the negative strand manifests as A-rich coding sequences, on the positive strand. We investigated possible reasons for the advantage of A-rich sequences including weakened RNA secondary structures, codon usage bias, and selection for a particular amino acid composition, and conclude that host immune pressures may have led to similar biases in coding sequence composition across very divergent RNA viruses.

SUBMITTER: Kustin T

PROVIDER: S-EPMC7543401 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundLoss of CpG dinucleotides in genomic DNA through methylation-induced mutation is characteristic of vertebrates and plants. However, these and other eukaryotic phyla show a range of other dinucleotide frequency biases with currently uncharacterized underlying mutational or selection mechanisms. We developed a parameterized Markov process to identify what neighbour context-dependent mutations best accounted for patterns of dinucleotide frequency biases in genomic and cytoplasmically expressed mRNA sequences of different vertebrates, other eukaryotic groups and RNA viruses that infect them.ResultsConsistently, 11- to 14-fold greater frequencies of the methylation-associated mutation of C to T upstream of G (depicted as C?T,G) than other transitions best modelled dinucleotide frequencies in mammalian genomic DNA. However, further mutations such as G?T,T (5-fold greater than the default transversion rate) were required to account for the full spectrum of dinucleotide frequencies in mammalian sequence datasets. Consistent with modeling predictions for these two mutations, instability of both CpG and CpT dinucleotides was identified through SNP frequency analysis of human DNA sequences. Different sets of context-dependent mutations were modelled in other eukaryotes with non-methylated genomic DNA. In contrast to genomic DNA, best-fit models of dinucleotide frequencies in transcribed RNA sequences expressed in the cytoplasm from all organisms were dominated by mutations that eliminated UpA dinucleotides, observations consistent with cytoplasmically driven selection for mRNA stability. Surprisingly, mRNA sequences from organisms with methylated genomes showed evidence for additional selection against CpG through further context-dependent mutations (eg. C?A,G). Similar mutation or selection processes were identified among single-stranded mammalian RNA viruses; these potentially account for their previously described but unexplained under-representations of CpG and UpA dinucleotides.ConclusionsMethods we have developed identify mutational processes and selection pressures in organisms that provide new insights into nucleotide compositional constraints and a wealth of biochemical and evolutionarily testable predictions for the future.

Project description:Picornaviridae are a large virus family causing widespread, often pathogenic infections in humans and other mammals. Picornaviruses are genetically and antigenically highly diverse, with evidence for complex evolutionary histories in which recombination plays a major part. To investigate the nature of recombination and selection processes underlying the evolution of serotypes within different picornavirus genera, large-scale analysis of recombination frequencies and sites, segregation by serotype within each genus, and sequence selection and composition was performed, and results were compared with those for other nonenveloped positive-stranded viruses (astroviruses and human noroviruses) and with flavivirus and alphavirus control groups. Enteroviruses, aphthoviruses, and teschoviruses showed phylogenetic segregation by serotype only in the structural region; lack of segregation elsewhere was attributable to extensive interserotype recombination. Nonsegregating viruses also showed several characteristic sequence divergence and composition differences between genome regions that were absent from segregating virus control groups, such as much greater amino acid sequence divergence in the structural region, markedly elevated ratios of nonsynonymous-to-synonymous substitutions, and differences in codon usage. These properties were shared with other picornavirus genera, such as the parechoviruses and erboviruses. The nonenveloped astroviruses and noroviruses similarly showed high frequencies of recombination, evidence for positive selection, and differential codon use in the capsid region, implying similar underlying evolutionary mechanisms and pressures driving serotype differentiation. This process was distinct from more-recent sequence evolution generating diversity within picornavirus serotypes, in which neutral or purifying selection was prominent. Overall, this study identifies common themes in the diversification process generating picornavirus serotypes that contribute to understanding of their evolution and pathogenicity.

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Biased Mutation and Selection in RNA Viruses.

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