Mating system impacts the genetic architecture of adaptation to heterogeneous environments

Abstract

Self-fertilisation has consequences for variation across the genome as it reduces effective population size, effect recombination rates and pollen flow, with implications for local adaptation.We conducted simulations of divergent stabilising selection on a quantitative trait with drift, pollen flow, mutation, recombination and different outcrossing rates. We quantified trait divergence and the genetic architecture of adaptation. We conducted an F ST outlier analysis to identify candidate loci and quantified the impact of mating system on detectability.Selfing promoted trait divergence mainly through reductions in pollen flow. Moreover, trait architecture became more diffuse with selfing. Average effect size of trait loci was lower, while the number of loci, and their clustering distance increased. The genetic architecture of selfers was also more diffuse than outcrossers for equivalent migration rates. However, when deleterious alleles were included, architectures became more concentrated in selfers, likely to be because of reductions in population size caused by mutational meltdown and impacts of background selection on N e .Our simulations demonstrate that mating system has important impacts on adaptive divergence of traits and the genetic landscape underlying that divergence. Selfing has a significant effect on detectability of regions of the genome important for adaptation because of neutral divergence and diffuse trait architecture.

Establishment of local adaptation in partly self-fertilizing populations

“…A similar conclusion was reached by Olito et al (2018) from a model including male/female antagonism and heterogeneous habitat with full dispersal. Finally, beyond the current work, simulations showed that local adaptation genes tends to aggregate into clusters in outcrossers (Yeaman and Whitlock, 2011) whereas the genetic architecture tends to be more diffuse in selfers (Hodgins andYeaman, 2019, Le Thierry d'Ennequin et al, 1999). Thus, a natural extension of the model would be to consider local adaptation at two loci to dissect the additional effect of selfing on genetic linkage.…”

“…Characterizing the pollination and seed dispersal modes and their quantitative impacts on gene flow appears thus crucial to make proper predictions on the effect of selfing. Finally, if we also consider the effect of linked selection that reduces local effective size beyond the two-fold level in selfing populations (Roze, 2016), selfing reduces the possibility of local adaptation, which requires stronger selection as exemplified by Hodgins and Yeaman (2019) who simulated local adaptation in selfing populations with and without background selection. Overall, the complex and contradictory effects of selfing on local adaptation may explain why no general empirical pattern has emerged so far (Hereford, 2010, Leimu andFischer, 2008).…”

The ecology, evolution, and genetics of plant reproductive systems

“…A number of authors in this Special Issue develop evolutionary models to explore aspects of plant reproductive systems. Hodgins & Yeaman (, in this issue pp. 1201–1214) employed individual‐based simulations of populations to show that self‐fertilization influences evolutionary divergence of quantitative traits through its effect on limiting gene (pollen) flow, and that evolution of quantitative traits in self‐fertilizing populations may involve a larger number of loci, each with smaller average effects compared to that in outcrossing populations.…”

Phenotypic plasticity, not ecotype differentiation, explains the broad ecological niche of a tree species in African dry woodlands

“…However, to date, no study has addressed the mechanisms underlying the broad ecological niche of some tree species of tropical forest. Yet, plants experience generations of selection by local environmental conditions due to their limiting gene dispersal through seeds and pollen (Sork, 2016;Grand et al, 2019;Hodgins and Yeaman, 2019). This selection may result in adaptive genetic differentiation (van Kleunen, 2007;Nicolaus and Edelaar, 2018).…”