title: Rare variation facilitates inferences of fine-scale population structure in humans.
abstract: Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European-American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies.
authors.affiliation: Institute for Genome Sciences, University of Maryland School of Medicine Program in Personalized and Genomic Medicine, University of Maryland School of Medicine timothydoconnor@gmail.com.
authors.forename: Timothy D
authors.initials: TD
authors.lastname: O'Connor
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle.
authors.forename: Wenqing
authors.initials: W
authors.lastname: Fu
authors.affiliation: Department of Public Health Sciences, University of Virginia School of Medicine.
authors.forename: Josyf C
authors.initials: JC
authors.lastname: Mychaleckyj
authors.affiliation: Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Logsdon
authors.affiliation: Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA Biostatistics: University of Wisconsin-Milwaukee, School of Public Health.
authors.forename: Paul
authors.initials: P
authors.lastname: Auer
authors.affiliation: Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
authors.forename: Christopher S
authors.initials: CS
authors.lastname: Carlson
authors.affiliation: Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX.
authors.forename: Suzanne M
authors.initials: SM
authors.lastname: Leal
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle.
authors.forename: Joshua D
authors.initials: JD
authors.lastname: Smith
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle.
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Rieder
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle Department of Pediatrics, University of Washington, Seattle.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Bamshad
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle.
authors.forename: Deborah A
authors.initials: DA
authors.lastname: Nickerson
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle.
authors.forename: Joshua M
authors.initials: JM
authors.lastname: Akey
mesh_terms: D005006:Ethnicity / Q000235:genetics; D059472:Exome / Q000235:genetics*; D005828:Genetics, Population / Q000379:methods*; D006801:Humans; D007257:Information Theory; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D025341:Principal Component Analysis
keywords: exome sequencing; information theory; recent demography