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Viral long-term evolutionary strategies favor stability 1 over proliferation
Abstract
Viruses are known to have some of the highest and most diverse mutation rates found 12 in any biological replicator, with single-stranded (ss) RNA viruses evolving the fastest, 13 and double-stranded (ds) DNA viruses having rates approaching those of bacteria. As 14 mutation rates are tightly and negatively correlated with genome size, selection is a clear 15 driver of viral evolution. However, the role of intragenomic interactions as drivers of 16 viral evolution is still unclear. To understand how these two processes affect the long-17 term evolution of viruses infecting humans, we comprehensively analyzed ssRNA, ssDNA, 18 dsRNA, and dsDNA viruses, to find which virus types and which functions show evidence 19 for episodic diversifying selection and correlated evolution. We show that selection mostly 20 affects single stranded viruses, that correlated evolution is more prevalent in DNA viruses, 21 and that both processes, taken independently, mostly affect viral replication. However, 22 the genes that are jointly affected by both processes are involved in key aspects of their life 23 cycle, favoring viral stability over proliferation. We further show that both evolutionary 24 processes are intimately linked at the amino acid level, which suggests that it is the 25 joint action of selection and correlated evolution, and not just selection, that shapes the 26 evolutionary trajectories of viruses -and possibly of their epidemiological potential.
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Humanity is regularly reminded of the epidemiological toll of viruses, in part due to recent To date, one of the most salient evolutionary feature shared by all viruses is the ex-38 istence of a negative correlation between mutation rate and genome size Holmes (2009) . 39 This is a critical result as it suggests that selection is driving the evolution of mutation The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/539239 doi: bioRxiv preprint 4 the stem region necessitates a second mutation to restore the correct, functional, struc-53 ture Meer et al. (2010) . This process is of particular interest as correlated evolution can 54 be underlain by epistasis, which occurs when the fitness effects of these two mutations Gblocks 0.91b at the codon level using the stringent default settings Castresana (2000) .
Both trees and alignments are available from https://github.com/sarisbro.
To obtain gene annotations, Gene Ontology (GO) terms were retrieved from gene ver. 2.2.6 was used, still with the 2.3.3 HyPhy engine, to infer nonsynonymous to synony-147 mous rate ratios ω assuming that these rates can vary across lineages and among sites.
In this implementation, two categories of sites were assumed, those for which ω neg ≤ 1, in 149 . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/539239 doi: bioRxiv preprint 8 proportion p, and those for which ω pos > 1, that are under positive selection, in propor-150 tion 1 − p. Evidence for selection was derived by means of a likelihood ratio test between 151 this model, and a null model where ω pos was constrained to take its value between 0 152 and 1. Linear models were fitted through robust regressions Yohai et al. (1991) . All R 153 scripts and HyPhy source files are available from https://github.com/sarisbro (file 154 "API scripts.zip," in "data"). The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/539239 doi: bioRxiv preprint our original hypothesis, there were no differences between dsDNA and dsRNA viruses 176 (X 2 = 0.26, df = 1, P = 0.6110), or between ssDNA and ssRNA viruses in terms of 177 prevalence of diversifying selection (X 2 = 2.07, df = 1, P = 0.1503). Note that these 178 differences cannot be attributed to genetic diversity, as dsDNA and dsRNA, which have 179 similar levels of selection, have however different levels of diversity ( Figure S3 ). However, 180 it is unlikely that "strandedness" (single vs. double stranded genetic material) alone drives The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/539239 doi: bioRxiv preprint dsDNA, while it is mostly peptidase activity and methylation on the viral envelope in 226 ssRNA viruses (Table S1 ; P < 0.01). In spite of these differences, we note that episodic 227 diversifying selection mostly affects genes involved in viral replication (Table S1 ). Genes (Table S2) . Again, most of these 231 functions and processes are involved in viral replication (Table S2 ). At the intersect of 232 these evolutionary processes however, the genes that are jointly affected by selection and Table S3 ). This suggests that despite key differences in life history strategies adopted Altogether, we showed that episodic diversifying selection is mostly found in single stranded 281 viruses, while correlated evolution is more prevalent in DNA viruses. More critically, we 282 also showed that the genes affected by each process, when acting independently, are in-283 volved in viral replication. However, the genes that are jointly affected by both processes 284 are mostly involved in viral stability (cell entry, integrity, assembly, immune escape), and 285 that the same amino acid sites tend to be affected by both processes. In retrospect, this 286 . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/539239 doi: bioRxiv preprint tight relationship between selection and correlated evolution may not be surprising, as 296 We note however that we neglected some aspects of viral structure: indeed, viruses can 297 be segmented or not, with a circular or linear genome, with positive or negative strands, 298 overlapping reading frames, complications that we could not consider here due to the 299 resulting small sample sizes, even if these factors can impact the mode of evolution of 300 viruses Holmes (2009). Future work should however strive to address these limitations. 301 We also neglected the population genetics context in which different viruses evolve, con-302 text that can often be correlated to structural constraints Lynch (2007); Holmes (2009) . 303 Furthermore, as we solely focused on intragenic interactions, and not intergenic or higher 304 order correlations, it is not impossible that we missed higher-level constraints affecting The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/539239 doi: bioRxiv preprint
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