DOI: 10.5061/dryad.pvmcvdnkh
title: A population-genomic approach for estimating selection on polygenic traits in heterogeneous environments

description: Strong selection can cause rapid evolutionary change, but temporal
 fluctuations in the form, direction and intensity of selection can limit
 net evolutionary change over longer time periods. Fluctuating selection
 could affect molecular diversity levels and the evolution of plasticity
 and ecological specialization. Nonetheless, this phenomenon remains
 understudied, in part because of analytical limitations and the general
 difficulty of detecting selection that does not occur in a consistent
 manner. Herein, I fill this analytical gap by presenting an approximate
 Bayesian computation (ABC) method to detect and quantify fluctuating
 selection on polygenic traits from population-genomic time-series data. I
 propose a model for environment-dependent phenotypic selection. The
 evolutionary genetic consequences of selection are then modeled based on a
 genotype-phenotype map. Using simulations, I show that the proposed method
 generates accurate and precise estimates of selection when the generative
 model for the data is similar to the model assumed by the method.
 Performance of the method when applied to an evolve-and-resequence study
 of host adaptation in the cowpea seed beetle (Callosobruchus maculatus)
 was more idiosyncratic and depended on specific analytical choices.
 Despite some limitations, these results suggest the proposed method
 provides a powerful approach to connect causes of (variable) selection to
 traits and genome-wide patterns of evolution. Documentation and
 open-source computer software (fsabc) implementing this method are
 available from GitHub (https://github.com/zgompert/fsabc.git).
description: This dataset includes mostly output from simulations of
 evolution, along with associated scripts. An illustrative dataset from an
 experimental evolution study with seed beetles that was analyzed as part
 of this methods study is also included.
description: The following files or sets of files are included here.
 <strong>ABCoutput.tar.gz</strong>. This compressed
 directory contains the output from simulations used to fit the ABC model.
 Subdirectories within the main folder contain the subset of output for
 each set of simulation conditions, along with R scripts used to process
 the simulation output.
 <strong>cmac_L14.tar.gz</strong>. This compressed
 directory contains the input files, ABC simulations, and associated
 processing and analysis scripts for the analysis of the seed beetle
 (<em>Callosobruchus maculatus</em>) data set on which the
 method was tested.
 <strong>methods_comparison.tar.gz</strong>. This
 compressed directory contains the input files, ABC simulations, and
 associated processing and analysis scripts for comparative analysis
 assessing the relative performance of the proposed method and the Berg
 & Coop method for detecting selection that varies in
 time. <strong>simDat.R</strong>. This R
 script simulates the input files that were used as observed data under
 baseline conditions.
 <strong>simDat1k.R</strong>. This is similar to
 simDat.R, but with 1000 loci.
 <strong>simDat5x5.R</strong>. This is similar to
 simDat.R, but with 5 populations sampled for each of 5
 generations. <strong>simGaus.R</strong>.
 This is similar to simDat.R, but for stabilizing selection.