Signs of Selection on Human Height Figure 2. Variants associated to height with high iHS score. Red squares indicate mark the population in which the iHS score for the variant falls in the top 5th percentile of the respective distribution. doi:10.1371/journal.pone.0027588.g002 one population) with alleles associated to other traits in genome- wide studies. We found 11 SNPs, 9 of which belonging to the ‘‘core set’’ (Table S1). As far as we know, there are no clearly identified signals of selective pressure on the phenotypes in linkage disequilibrium with the height associated SNPs. Moreover, also removing these SNPs from the analysis, the ‘‘core set’’ still show a significant higher FST (median = 0.099 vs. 0.086; p = 0.03452, one- tailed Mann-Whitney test). We are aware that the increase in the mean FST value could be, at least in part, due to an eventual difference across the mean heights of the three populations considered. In other words, the increase in the mean FST value can be divided in two distinct components, where the first one accounts for the differences in the mean height while the second one accounts for the pure genetic differences. Unfortunately, at the best of our knowledge, data regarding the mean height of each population are not present in literature so far. For this reason, we were unable to estimate the relative weight of the two components or exclude the effect of the first one. Moreover, it is worth stressing that the 180 associated SNPs found by Lango Allen and colleagues only explain about 10% of the variance in adult height [8]. For this reason, wherever present, phenotypic differences among populations should have a marginal effect. In conclusion, with the increasing availability of genomic data, the study of adaption of polygenic traits is becoming possible at experimental level. The lack of methods and models specifically tailored to this kind of study still leave it a great challenge. In this work we found that in the particular case of the height signals of population differentiation are present but, conversely from ‘‘hard sweeps’’, they are small and distributed as recently hypothesized. Moreover, we suggest that, for this specific trait, mechanisms of spontaneous symmetry breaking seem to be a reasonably model to explain, at least in part, its evolutionary dynamic. Materials and Methods Data and statistical analysis Analysis is based on the HapMap Public Release #27 (merged II+III) datafiles. We analyzed data from the CEPH (Utah residents with ancestry from northern and western Europe), Yoruba in Ibadan, Nigeria (YRI), Han Chinese in Beijing, China (CHB) and Japanese in Tokyo, Japan (JPT) samples. We pooled the CHB and JPT samples to form a single sample. Additional SNP information about physical positions and SNP-gene association were obtained from dbSNP build 129. We excluded by this analysis SNPs that were either non sampled or non polymorphic in all the three samples. We also excluded SNPs with a minor allele frequency ,5% in all of the 3 samples. Per-population linkage disequilibrium data (r2) were obtained from HapMap Public Release #27 (merged II+III) as well. FST was calculated using the unbiased estimator proposed by Weir and Cockerham as in Amato et al [15]. All data was merged in a local MySQL database. As ‘‘genomic background’’ we refer to all the SNPs in this database, for a total of 3,294,557 SNPs. Variants associated with height were collected from [8]. Of the 180 provided SNPs, 176 were present in our database and hence considered in our analysis. The normalized iHS scores were obtained from UCSC Genome Browser ‘‘HGDP iHS’’ track. They were calculated using SNPs genotyped in 1,043 individual coming from 53 populations worldwide by the Human Genome Diversity Project in collabo- ration with the Centre d’Etude du Polymorphisme Humain (HGDP-CEPH). The 53 populations were divided into seven continental groups: Africa (Bantu populations only), Middle East, Europe, South Asia, East Asia, Oceania and the Americas. Per- SNP iHS scores were smoothed in windows of 31 SNPs, centered on each SNP. PLoS ONE | www.plosone.org 3 November 2011 | Volume 6 | Issue 11 | e27588