Abstract
Genome-wide association studies (GWAS) have identified more than 2,000 trait-SNP associations, and the number continues to increase. GWAS have focused on traits with potential consequences for human fitness, including many immunological, metabolic, cardiovascular, and behavioral phenotypes. Given the polygenic nature of complex traits, selection may exert its influence on them by altering allele frequencies at many associated loci, a possibility which has yet to be explored empirically. Here we use 38 different measures of allele frequency variation and 8 iHS scores to characterize over 1,300 GWAS SNPs in 53 globally distributed human populations. We apply these same techniques to evaluate SNPs grouped by trait association. We find that groups of SNPs associated with pigmentation, blood pressure, infectious disease, and autoimmune disease traits exhibit unusual allele frequency patterns and elevated iHS scores in certain geographical locations. We also find that GWAS SNPs have generally elevated scores for measures of allele frequency variation and for iHS in Eurasia and East Asia. Overall, we believe that our results provide evidence for selection on several complex traits that has caused changes in allele frequencies and/or elevated iHS scores at a number of associated loci. Since GWAS SNPs collectively exhibit elevated allele frequency measures and iHS scores, selection on complex traits may be quite widespread. Our findings are most consistent with this selection being either positive or negative, although the relative contributions of the two are difficult to discern. Our results also suggest that trait-SNP associations identified in Eurasian samples may not be present in Africa, Oceania, and the Americas, possibly due to differences in linkage disequilibrium patterns. This observation suggests that non-Eurasian and non-East Asian sample populations should be included in future GWAS.
Highlights
Genome-wide association studies (GWAS) have become a popular method for identifying genomic loci that contribute to complex traits [1]
While pigmentation SNPs do seem to exhibit the most extreme variations in allele frequency, we found that groups of SNPs associated with blood pressure, infectious disease, and autoimmune disease differ from random groups of SNPs in their allele frequency distributions
Our analyses indicate that SNPs associated with pigmentation, blood pressure, and autoimmune disease have unusual allele frequency distributions relative to random SNPs; to a lesser degree, this is true for SNPs associated with infectious disease, metabolic, and hematological traits
Summary
Genome-wide association studies (GWAS) have become a popular method for identifying genomic loci that contribute to complex traits [1]. In GWAS, large sample sets of individuals ( on the order of several thousand), whose phenotype for some trait has been assessed, are genotyped for common SNPs. Algorithms are used to identify SNPs that demonstrate allele frequency differences between cases and controls or between persons representing opposite ends of the phenotypic range (for continuous traits such as height) [1]. Algorithms are used to identify SNPs that demonstrate allele frequency differences between cases and controls or between persons representing opposite ends of the phenotypic range (for continuous traits such as height) [1] It remains controversial how often the alleles at these SNPs themselves have direct effects on the phenotype under study; it is likely that in many cases these SNPs instead act as markers linked to the causal genomic variants [2,3]. As it is increasingly common for complex traits to have been the focus of multiple independent GWAS, it is possible to discern which SNPs are most likely to have true trait associations and which are likely false positives [5]
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