The clarifying role of time series data in the population genetics of HIV.

Pleuni S Pennings,Dmitri A Petrov,Alison F Feder,Gregory P Copenhaver

doi:10.1371/journal.pgen.1009050

Pleuni S Pennings, Dmitri A Petrov + Show 2 more

Open Access

https://doi.org/10.1371/journal.pgen.1009050

Copy DOI

Abstract

HIV can evolve remarkably quickly in response to antiretroviral therapies and the immune system. This evolution stymies treatment effectiveness and prevents the development of an HIV vaccine. Consequently, there has been a great interest in using population genetics to disentangle the forces that govern the HIV adaptive landscape (selection, drift, mutation, and recombination). Traditional population genetics approaches look at the current state of genetic variation and infer the processes that can generate it. However, because HIV evolves rapidly, we can also sample populations repeatedly over time and watch evolution in action. In this paper, we demonstrate how time series data can bound evolutionary parameters in a way that complements and informs traditional population genetic approaches. Specifically, we focus on our recent paper (Feder et al., 2016, eLife), in which we show that, as improved HIV drugs have led to fewer patients failing therapy due to resistance evolution, less genetic diversity has been maintained following the fixation of drug resistance mutations. Because soft sweeps of multiple drug resistance mutations spreading simultaneously have been previously documented in response to the less effective HIV therapies used early in the epidemic, we interpret the maintenance of post-sweep diversity in response to poor therapies as further evidence of soft sweeps and therefore a high population mutation rate (θ) in these intra-patient HIV populations. Because improved drugs resulted in rarer resistance evolution accompanied by lower post-sweep diversity, we suggest that both observations can be explained by decreased population mutation rates and a resultant transition to hard selective sweeps. A recent paper (Harris et al., 2018, PLOS Genetics) proposed an alternative interpretation: Diversity maintenance following drug resistance evolution in response to poor therapies may have been driven by recombination during slow, hard selective sweeps of single mutations. Then, if better drugs have led to faster hard selective sweeps of resistance, recombination will have less time to rescue diversity during the sweep, recapitulating the decrease in post-sweep diversity as drugs have improved. In this paper, we use time series data to show that drug resistance evolution during ineffective treatment is very fast, providing new evidence that soft sweeps drove early HIV treatment failure.

Highlights

Diversity signatures from a single time point provide information about evolution In population genetics, we often sample data at a single time point and build models to explain how the observed patterns of genetic diversity might have been generated
As a single adaptive allele rises to high frequency, hitchhiking genetic neighbors fix in the population in an event known as a hard selective sweep
In [11], we examined differences in the diversity signatures of intra-patient HIV populations to understand if this decreasing prevalence of drug resistance evolution was accompanied by a transition from soft sweeps to hard sweeps, as might be expected if these better drugs had effectively increased the waiting time for a beneficial mutation

Summary

Introduction

Diversity signatures from a single time point provide information about evolution In population genetics, we often sample data at a single time point and build models to explain how the observed patterns of genetic diversity might have been generated. In [11], we examined differences in the diversity signatures of intra-patient HIV populations to understand if this decreasing prevalence of drug resistance evolution was accompanied by a transition from soft sweeps to hard sweeps, as might be expected if these better drugs had effectively increased the waiting time for a beneficial mutation. This is illustrated in the left-hand panels of Fig 1. Because HIV populations treated with monotherapies experience both much stronger selection and potentially weaker recombination than what was assumed by Harris and colleagues [12], abundant recombination during slow hard sweeps does not represent a viable alternative to create the patterns observed in Feder and colleagues [11]

Conclusions

Findings

Materials and methods