Integrating genealogical and dynamical modelling to infer escape and reversion rates in HIV epitopes
Duncan Palmer, Angela McLean, Gil McVean
(Submitted on 5 Feb 2013)

The rates of escape and reversion in response to selection pressure arising from the host immune system, notably the cytotoxic T-lymphocyte (CTL) response, are key factors determining the evolution of HIV. Existing methods for estimating these parameters from cross-sectional population data using ordinary differential equations (ODE) ignore information about the genealogy of sampled HIV sequences, which has the potential to cause systematic bias and over-estimate certainty. Here, we describe an integrated approach, validated through extensive simulations, which combines genealogical inference and epidemiological modelling, to estimate rates of CTL escape and reversion in HIV epitopes. We show that there is substantial uncertainty about rates of viral escape and reversion from cross-sectional data, which arises from the inherent stochasticity in the evolutionary process. By application to empirical data, we find that point estimates of rates from a previously published ODE model and the integrated approach presented here are often similar, but can also differ several-fold depending on the structure of the genealogy. The model-based approach we apply provides a framework for the statistical analysis of escape and reversion in population data and highlights the need for longitudinal and denser cross-sectional sampling to enable accurate estimate of these key parameters.

Genetic draft, selective interference, and population genetics of rapid adaptation
Richard A. Neher
(Submitted on 5 Feb 2013)

To learn about the past from a sample of genomic sequences, one needs to understand how evolutionary processes shape genetic diversity. Most population genetic inference is based on frameworks assuming adaptive evolution is rare. But if positive selection operates on many loci simultaneously, as has recently been suggested for many species including animals such as flies, a different approach is necessary. In this review, I discuss recent progress in characterizing and understanding evolution in rapidly adapting populations where random associations of mutations with genetic backgrounds of different fitness, i.e., genetic draft, dominate over genetic drift. As a result, neutral genetic diversity depends weakly on population size, but strongly on the rate of adaptation or more generally the variance in fitness. Coalescent processes with multiple mergers, rather than Kingman’s coalescent, are appropriate genealogical models for rapidly adapting populations with important implications for population genetic inference.

Identifying Signatures of Selection in Genetic Time Series
Alison Feder, Sergey Kryazhimskiy, Joshua B. Plotkin
(Submitted on 3 Feb 2013)

We develop a rigorous test for natural selection based on allele frequencies sampled from a population over multiple time points. We demonstrate that the standard method of estimating selection coefficients in this setting, and the associated chi-squared likelihood-ratio test of neutrality, is biased and it therefore does not provide a reliable test of selection. We introduce two methods to correct this bias, and we demonstrate that the new methods have power to detect selection in practical parameter regimes, such as those encountered in fitness assays of microbial populations. Our analysis is limited to a single diallelic locus, assumed independent of all other loci in a genome, which is again relevant to simple competition assays of laboratory and natural isolates; other techniques will be required to detect selection in time series of co-segregating, linked loci.