polygenic adaptation - senecio7の日記

Stetter MG, Thornton K & Ross-Ibarra J 2018 Genetic architecture and selective sweeps after polygenic adaptation to distant trait optima. PLoS Genet 14:e1007794.

during the stationary phase before the shift and after reaching the new optimum we followed a Gaussian fitness function appropriate for a trait under stabilizing selection
during the optimum shift, however, such a model would be problematic, as only a few individuals in the upper tail of the fitness distribution would have extremely high relative fitness, inducing a strong population bottleneck
instead, we applied a model of truncation selection, first calculating fitness under the Gaussian fitness function but then assigning a fitness of 1 to the top half of the population and 0 to the bottom half
such a model is reasonable for sudden shifts in trait optima that do not lead to the extinction of a population, but where higher trait values are unambiguously advantageous and the maximum population size is limited
in natural populations these factors can be observed when sudden changes in the environment favor a specific phenotype for invasive species

we modeled 20 QTL resembling 50kb regions, each with a 4 kb "genic" region centered in a 46 kb "intergenic" region
fitness
w = exp[− (z − z_opt)² / (2V_S)] ... (1)
this standard model for traits under stabilizing selection is well suited for populations at equilibrium
under strong directional selection, however, this model greatly amplifies fitness differences among individuals in the tails of the phenotypic distribution
during the adaptive phase of the simulation, we calculated individual fitness following Eq 1, but then apply truncation selection by assigning a fitness of 1 to the top 50% of the distribution of w and 0 for the remaining 50%
this model allowed for truncation selection on z, while the population was distant from the new optimum, but allows for selection against phenotypes that surpass the new optimum during the final stages of adaptation
we stopped truncation selection once the population mean reached the new optimum
initial genetic variance
the genetic variance at equilibrium can be approximated by the house of cards (HoC) model
E[V_G] = 4μV_S ... (2)
and the stochastic HoC approximation
E[V_G]_SHC = 4μV_S / (1 + V_S / (Nσ_m²)) ... (3)
background
computational limitations do not allow simulation of an entire eukaryotic genomes
we added a heritable background (G_B) to our simulations to account for the adaptive potential of the rest of the genome
sweeps
we defined as a sweep any mutation that fixed faster than 99% of neutral alleles