Data on the association of SNPs with diseases was obtained from a catalog of genome wide association studies available at http://www.genome.gov/gwastudies, (accessed 12/13/10). All statistical analyses were performed with R ver. 2.10 (R Foundation for Statistical Computing, Vienna, Austria; http:// www.r-project.org/) considering 0.05 as significance threshold. Simulations We simulated three populations of diploid organisms of fixed sample size evolving independently each other. Individuals are represented by 20 markers, where half of them are assumed to be neutral, and the remaining ones contribute additively and uniformly to the phenotype in a codominant way. Basically, markers evolve under a Wright-Fisher model with recombination. Polygenic selection is then simulated through viability selection. Denoting with m the number of beneficial alleles carried by an individual, each contributing with x to the phenotype, the fitness is parameterized as exp(-(m-m)2 x2/(2s) ). In the previous expression the quantity s measures the selection strength and m is the number of beneficial alleles that maximizes the fitness. In figure S1 it is shown a particular case where the sample size is N = 10,000, s = 10, m = 10 and x = 5. Furthermore, the initial allele frequency is set to 0.5 for all markers. Lower values of N increase the effect of genetic drift, while different values of m change the number of alleles rising in frequency in each population. By tuning the value of x2/s one can change the strength of selection hence affecting the References 1. Nielsen R, Hellmann I, Hubisz M, Bustamante C, Clark AG (2007) Recent and ongoing selection in the human genome. Nature reviews. Genetics 8: 857–68. 2. Sabeti PC (2006) Positive Natural Selection in the Human Lineage. Science 312: 1614–1620. 3. Stearns SC, Byars SG, Govindaraju DR, Ewbank D (2010) Measuring selection in contemporary human populations. Nature reviews. Genetics 11: 611–22. 4. 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