Cell-Derived Viral Genes Evolve under Stronger Purifying Selection in Rhadinoviruses

Like many other large double-stranded DNA (dsDNA) viruses, herpesviruses are known to capture host genes to evade host defenses. Little is known about the detailed natural history of such genes, nor do we fully understand their evolutionary dynamics. A major obstacle is that they are often highly divergent, maintaining very low sequence similarity to host homologs. Here we use the herpesvirus genus Rhadinovirus as a model system to develop an analytical approach that combines complementary evolutionary and bioinformatic techniques, offering results that are both detailed and robust for a range of genes. Using a systematic phylogenetic strategy, we identify the original host lineage of viral genes with high confidence. We show that although host immunomodulatory genes evolve rapidly compared to other host genes, they undergo a clear increase in purifying selection once captured by a virus. To characterize this shift in detail, we developed a novel technique to identify changes in selection pressure that can be attributable to particular domains. These findings will inform us on how viruses develop strategies to evade the immune system, and our synthesis of techniques can be reapplied to other viruses or biological systems with similar analytical challenges.IMPORTANCE Viruses and hosts have been shown to capture genes from one another as part of the evolutionary arms race. Such genes offer a natural experiment on the effects of evolutionary pressure, since the same gene exists in vastly different selective environments. However, sequences of viral homologs often bear little similarity to the original sequence, complicating the reconstruction of their shared evolutionary history with host counterparts. In this study, we use a genus of herpesviruses as a model system to comprehensively investigate the evolution of host-derived viral genes, using a synthesis of genomics, phylogenetics, selection analysis, and nucleotide and amino acid modeling.