A population-genomic approach for estimating selection on polygenic traits in heterogeneous environments

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).