On the Analysis of Intrahost and Interhost Viral Populations: Human Cytomegalovirus as a Case Study of Pitfalls and Expectations.

Intrahost and interhost assessments of viral diversity are often treated as measures of separate and distinct evolutionary processes, with numerous investigations reporting seemingly incompatible results between the two. For example, in human cytomegalovirus, the nucleotide diversity estimates are 10-fold higher for interhost data, while the number of segregating (i.e., polymorphic) sites is 6-fold lower. These results have been interpreted as demonstrating that sampled intrahost variants are strongly deleterious. In reality, however, these observations are fully consistent with standard population genetic expectations. Here, we analyze published intra- and interhost data sets within this framework, utilizing statistical inference tools to quantify the fitness effects of segregating mutations. Further, we utilize population level simulations to clarify expectations under common evolutionary models. Contrary to common claims in the literature, these results suggest that most observed polymorphisms are likely nearly neutral with regard to fitness and that standard population genetic models in fact well predict observed levels of both intra- and interhost variability. With the increasing number of evolutionary virology studies examining both intrahost and interhost patterns of genomic variation, a number of seemingly incompatible results have emerged, revolving around the far greater level of observed intrahost than interhost variation. This has led many authors to suggest that the great majority of sampled within-host polymorphisms are strongly deleterious. Here, we demonstrate that there is in fact no incompatibility of these results and, indeed, that the vast majority of sampled within-host variation is likely neutral. These results thus represent a major shift in the current view of observed viral variation.