Estimation of the Distribution of Fitness Effects, ωa, and α

The DFE was estimated using the DFE-alpha software v2.16 (with default parameters) (Keightley and Eyre-Walker 2007; Eyre-Walker and Keightley 2009), which is based on a maximum likelihood framework to model the DFE of nonsynonymous mutations assuming a gamma distribution of fitness effects on the negative real line. The program estimates the DFE by comparing the folded SFS of mutations that are neutrally evolving to mutations that are under selection. The SFS of neutrally evolving mutations is used to estimate the population mutation rate (N_eμ) allowing for simple demographic scenarios that may equally influence the neutral and the selected SFS. The null model assumes a constant N_e (constant model) through time, while the alternative model allows for a one-step change in N_e (one-step change model). We compared the two models using a LRT with a 0.01 significance level and show the results for the best-fit model for every mutation category and bin. The parameters of the demographic model for each mutation category and recombination rate bin were estimated using only synonymous sites of that respective category and bin. Hence, the “selected” SFS was normalized by the “neutral” SFS of the same genomic region and mutation category, a normalization procedure that corrects for variation in mutation rate along the genome. Importantly, it also accounts for variation in the degree of linkage between sites and hence the strength of background selection and genetic draft in different genomic regions (Messer and Petrov 2013; Huber et al. 2017). To assess the goodness of fit statistically, we estimated r² between the observed and expected SFS for each mutation category (Keightley and Eyre-Walker 2007); the fit is shown in supplementary figure S6 and table S5, Supplementary Material online.

The estimation of ω_a and α was performed with the DFE-alpha software v2.16 (Keightley and Eyre-Walker 2007; Eyre-Walker and Keightley 2009), and based on the total number of nonsynonymous and synonymous substitutions retrieved for the different mutation categories using the L95 model in the bio++ suite (as described earlier) and the respective DFE. As the L95 model corrects for multiple substitutions, the Jukes–Cantor correction made by DFE-alpha was not applied, neither a correction for ancestral polymorphisms.