%0 Journal Article %1 berg2014population %A Berg, Jeremy J. %A Coop, Graham %D 2014 %I Public Library of Science %J PLoS Genet %K F_ST GWAS Q_ST methods polygenic_adaptation population_genetics quantitative_genetics %N 8 %P e1004412 %R 10.1371/journal.pgen.1004412 %T A Population Genetic Signal of Polygenic Adaptation %U http://dx.doi.org/10.1371%2Fjournal.pgen.1004412 %V 10 %X The process of adaptation is of fundamental importance in evolutionary biology. Within the last few decades, genotyping technologies and new statistical methods have given evolutionary biologists the ability to identify individual regions of the genome that are likely to have been important in this process. When adaptation occurs in traits that are underwritten by many genes, however, the genetic signals left behind are more diffuse, and no individual region of the genome is likely to show strong signatures of selection. Identifying this signature therefore requires a detailed annotation of sites associated with a particular phenotype. Here we develop and implement a suite of statistical methods to integrate this sort of annotation from genome wide association studies with allele frequency data from many populations, providing a powerful way to identify the signal of adaptation in polygenic traits. We apply our methods to test for the impact of selection on human height, skin pigmentation, body mass index, type 2 diabetes risk, and inflammatory bowel disease risk. We find relatively strong signals for height and skin pigmentation, moderate signals for inflammatory bowel disease, and comparatively little evidence for body mass index and type 2 diabetes risk.

@article{berg2014population, abstract = {The process of adaptation is of fundamental importance in evolutionary biology. Within the last few decades, genotyping technologies and new statistical methods have given evolutionary biologists the ability to identify individual regions of the genome that are likely to have been important in this process. When adaptation occurs in traits that are underwritten by many genes, however, the genetic signals left behind are more diffuse, and no individual region of the genome is likely to show strong signatures of selection. Identifying this signature therefore requires a detailed annotation of sites associated with a particular phenotype. Here we develop and implement a suite of statistical methods to integrate this sort of annotation from genome wide association studies with allele frequency data from many populations, providing a powerful way to identify the signal of adaptation in polygenic traits. We apply our methods to test for the impact of selection on human height, skin pigmentation, body mass index, type 2 diabetes risk, and inflammatory bowel disease risk. We find relatively strong signals for height and skin pigmentation, moderate signals for inflammatory bowel disease, and comparatively little evidence for body mass index and type 2 diabetes risk.}, added-at = {2015-04-22T07:41:57.000+0200}, author = {Berg, Jeremy J. and Coop, Graham}, biburl = {https://www.bibsonomy.org/bibtex/258d34dd08ab8701ba5f65b630adf4899/peter.ralph}, doi = {10.1371/journal.pgen.1004412}, interhash = {72e761cbf17a5a97343e2ec7e9069e43}, intrahash = {58d34dd08ab8701ba5f65b630adf4899}, journal = {PLoS Genet}, keywords = {F_ST GWAS Q_ST methods polygenic_adaptation population_genetics quantitative_genetics}, month = {08}, number = 8, pages = {e1004412}, publisher = {Public Library of Science}, timestamp = {2015-04-22T07:41:57.000+0200}, title = {A Population Genetic Signal of Polygenic Adaptation}, url = {http://dx.doi.org/10.1371%2Fjournal.pgen.1004412}, volume = 10, year = 2014 }