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Genome-wide comparison of African-ancestry populations from CARe and other cohorts reveals signals of natural selection
Authors:Bhatia Gaurav  Patterson Nick  Pasaniuc Bogdan  Zaitlen Noah  Genovese Giulio  Pollack Samuela  Mallick Swapan  Myers Simon  Tandon Arti  Spencer Chris  Palmer Cameron D  Adeyemo Adebowale A  Akylbekova Ermeg L  Cupples L Adrienne  Divers Jasmin  Fornage Myriam  Kao W H Linda  Lange Leslie  Li Mingyao  Musani Solomon  Mychaleckyj Josyf C  Ogunniyi Adesola  Papanicolaou George  Rotimi Charles N  Rotter Jerome I  Ruczinski Ingo  Salako Babatunde  Siscovick David S  Tayo Bamidele O  Yang Qiong  McCarroll Steve  Sabeti Pardis  Lettre Guillaume  De Jager Phil  Hirschhorn Joel  Zhu Xiaofeng  Cooper Richard  Reich David  Wilson James G
Affiliation:1Harvard- Massachusetts Institute of Technology (MIT) Division of Health, Science and Technology, Cambridge, MA 02139, USA;2Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA;3Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA;4Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA;5Division of Nephrology, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA;6Department of Genetics, Harvard Medical School, Boston, MA 02115, USA;7Department of Statistics, University of Oxford, Oxford OX1 3TG, UK;8Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK;9Divisions of Genetics and Endocrinology and Program in Genomics, Children's Hospital Boston, Boston, MA 02115, USA;10National Institutes of Health (NIH) Intramural Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA;11Jackson Heart Study, Jackson State University, Jackson, MS 39213, USA;12Department of Biostatistics and Epidemiology, Boston University School of Public Health, Boston, MA 02218, USA;13Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest University, Winston Salem, NC 27157, USA;14Institute of Molecular Medicine and Division of Epidemiology School of Public Health, University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA;15Department of Epidemiology, Johns Hopkins University, Baltimore, MD 21205, USA;16Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD 21205, USA;17Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA;18Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA 19104, USA;19University of Mississippi Medical Center, Jackson, MS 39216, USA;20Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22902, USA;21Department of Medicine, University of Ibadan, Ibadan, Nigeria 5017;22National Heart, Lung, and Blood Institute (NHLBI), Division of Cardiovascular Sciences, NIH, Bethesda, MD 20892, USA;23Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA;24Cedars-Sinai Medical Center, Medical Genetics Institute, Los Angeles, CA 90048, USA;25Departments of Medicine and Epidemiology, University of Washington, Seattle, WA 98195, USA;26Cardiovascular Health Research Unit, University of Washington, Seattle, WA 98101, USA;27Department of Preventive Medicine and Epidemiology, Loyola University Chicago Stritch School of Medicine, Maywood, IL 60153, USA;28Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA;29Montreal Heart Institute, 5000 Bélanger Street, Montréal, Québec H1T 1C8, Canada;30Département de Médecine, Université de Montréal, C.P. 6128, succursale Centreville, Montréal, Québec H3T 3J7, Canada;31Division of Molecular Immunology, Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA;32Partners Center for Personalized Genetic Medicine, Boston, MA 02115, USA;33Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
Abstract:The study of recent natural selection in human populations has important applications to human history and medicine. Positive natural selection drives the increase in beneficial alleles and plays a role in explaining diversity across human populations. By discovering traits subject to positive selection, we can better understand the population level response to environmental pressures including infectious disease. Our study examines unusual population differentiation between three large data sets to detect natural selection. The populations examined, African Americans, Nigerians, and Gambians, are genetically close to one another (FST < 0.01 for all pairs), allowing us to detect selection even with moderate changes in allele frequency. We also develop a tree-based method to pinpoint the population in which selection occurred, incorporating information across populations. Our genome-wide significant results corroborate loci previously reported to be under selection in Africans including HBB and CD36. At the HLA locus on chromosome 6, results suggest the existence of multiple, independent targets of population-specific selective pressure. In addition, we report a genome-wide significant (p = 1.36 × 10−11) signal of selection in the prostate stem cell antigen (PSCA) gene. The most significantly differentiated marker in our analysis, rs2920283, is highly differentiated in both Africa and East Asia and has prior genome-wide significant associations to bladder and gastric cancers.
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