Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multi-trait GWA studies.

Data for "Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multi-trait GWA studies". Results from simulations with four different genetic architectures to compare how pleiotropy and linkage differentially affect the genetic correlation between traits. Three different sets of genetic architecture had varying distances between 120 pairs of additive loci affecting two quantitative traits. Each pair of loci was located on its own chromosome (i.e., unlinked to other pairs) and the recombination distance between each pair on a chromosome was either 0cM, 0.1cM, or 1cM apart for a particular genetic architecture representing no recombination between linked loci, as well as an average and an extreme value of recombination at ``hotspots'' in the human genome, respectively. A fourth genetic architecture consisted of 120 unlinked, additive, pleiotropic loci that affected both quantitative traits. Each simulation was run with 5,000 initially monomorphic (variation is gradually introduced through mutations), diploid individuals for 10,000 generations achieving mutation-selection(-migration) balance in order to observe general patterns of genetic correlation in the near-absence of drift. Individuals were hermaphrodites mating at random within a population, with non-overlapping generations. Phenotypes were calculated for each of the two traits modeled by summing the allelic values of all loci affecting one trait. Gaussian stabilizing selection was applied and determined the survival probability of juveniles. To examine the effects of the strength of stabilizing selection on each trait and strength of correlational selection between traits, different sets of simulations were run with selection strength of 50 or 100 and correlational selection of 0.5 and 0.9. To examine the effects of mutational input on genetic correlation between traits, different sets of simulations were run with mutation rates of 0.001, 0.0001, or 0.00001, and mutational effect sizes of 0.1, 0.01, or 0.001. 

To examine the effects of migration from a source population on genetic correlation between traits, additional sets of simulations were run with uni-directional migration from a second population (as in an island-mainland model with each population consisting of 5000 individuals) with backward migration rates of 0.1, 0.01, and 0.001. The backward migration rate represents the average proportion of new individuals in the focal population whose parent is from the source population. The local optimum values for the two traits in the source population were set at 10 units distance from the focal population's local optimum. Both focal and source populations had weak stabilizing selection with a strength of 100, the focal population had no correlational selection between the two traits and the source population had a correlational selection of 0 or 0.9. Fifty replicate simulations were run for each set of parameter values and statistics were averaged over replicates.