Together with several collaborators at Stanford, I published a paper on the BioRxiv on selective sweeps in HIV. We find that when treatments didn’t work well (think AZT in the 1980s), sweeps were very soft, but with better treatments sweeps are getting “harder.” The first author on the paper, Alison Feder, has done most of the work on this paper including making all the figures (and they are cool!).
Alison F Feder, Soo-Yon Rhee, Robert W Shafer, Dmitri A Petrov, Pleuni S Pennings. 2015. More efficacious drugs lead to harder selective sweeps in the evolution of drug resistance in HIV-1. BioRxiv, doi:http://dx.doi.org/10.1101/024109
In the early days of HIV treatment, drug resistance occurred rapidly and predictably in all patients, but under modern treatments, resistance arises slowly, if at all. The probability of resistance should be controlled by the rate of generation of resistant mutations. If many adaptive mutations arise simultaneously, then adaptation proceeds by soft selective sweeps in which multiple adaptive mutations spread concomitantly, but if adaptive mutations occur rarely in the population, then a single adaptive mutation should spread alone in a hard selective sweep. Here we use 6,717 HIV-1 consensus sequences from patients treated with first-line therapies between 1989 and 2013 to confirm that the transition from fast to slow evolution of drug resistance was indeed accompanied with the expected transition from soft to hard selective sweeps. This suggests more generally that evolution proceeds via hard sweeps if resistance is unlikely and via soft sweeps if it is likely.
Figure 3: Drug resistance mutations are correlated with diversity reduction differently in different types of treatments. Treatment efficacy from literature review (% of patients with virologic suppression after 48 weeks) showed positive correspondence with clinical recommendation among RTI regimens (A) and PI+RTI regimens (B). DRM SE lower among the more efficacious and clinically recommended treatments among RTI treatments (C) and RTI+PI treatments (D). Mixed effect model shows significantly different slopes for NNRTI treatments versus NRTI treatments (E) and PI/r treatments versus PI treatments (F). Each line in (EF) represents the fitted decay in diversity with each DRM for a different treatment from the full mixed effects model and p-value labeling indicates the difference between the plotted full model and the null not fitting slopes separately for treatment groups.