Disentangling effects of genetic linkage on estimates of selection in intrahost HIV evolution

The evolutionary history of a population contains information about the underlying forces driving population diversity and adaptation. However, it is difficult for current methods to disentangle the effects of individual mutations from complex evolutionary dynamics. Here we describe a method to infer selection from genetic time-series data while also accounting for the confounding effects of genetic linkage, using a path integral approach based in statistical physics. We apply this method to investigate within-host HIV-1 evolution at the half-genome scale. Our approach reveals selective pressures for escape from human immune responses. Due to clonal interference between escape mutants, we find that accounting for genetic linkage is crucial to infer realistic estimates of selection. Our ability to account for genetic linkage is also critical for insight into complex evolutionary scenarios, highlighted by a struggle for dominance between co-infecting strains of the virus in an individual who ultimately develops broadly neutralizing antibodies.