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Detection of Ancestry Informative HLA Alleles Confirms the Admixed Origins of Japanese Population

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      Abstract

      The polymorphisms in the human leukocyte antigen (HLA) region are powerful tool for studying human evolutionary processes. We investigated genetic structure of Japanese by using five-locus HLA genotypes ( HLA-A, -B, -C, -DRB1, and -DPB1) of 2,005 individuals from 10 regions of Japan. We found a significant level of population substructure in Japanese; particularly the differentiation between Okinawa Island and mainland Japanese. By using a plot of the principal component scores, we identified ancestry informative alleles associated with the underlying population substructure. We examined extent of linkage disequilibrium (LD) between pairs of HLA alleles on the haplotypes that were differentiated among regions. The LDs were strong and weak for pairs of HLA alleles characterized by low and high frequencies in Okinawa Island, respectively. The five-locus haplotypes whose alleles exhibit strong LD were unique to Japanese and South Korean, suggesting that these haplotypes had been recently derived from the Korean Peninsula. The alleles characterized by high frequency in Japanese compared to South Korean formed segmented three-locus haplotype that was commonly found in Aleuts, Eskimos, and North- and Meso-Americans but not observed in Korean and Chinese. The serologically equivalent haplotype was found in Orchid Island in Taiwan, Mongol, Siberia, and Arctic regions. It suggests that early Japanese who existed prior to the migration wave from the Korean Peninsula shared ancestry with northern Asian who moved to the New World via the Bering Strait land bridge. These results may support the admixture model for peopling of Japanese Archipelago.

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      Most cited references 57

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      Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.

      There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined approximately 2,000 individuals for each of 7 major diseases and a shared set of approximately 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 x 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals (including 58 loci with single-point P values between 10(-5) and 5 x 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.
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        Arlequin (version 3.0): An integrated software package for population genetics data analysis

        Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multi-locus genotypes. A Windows version of the software is freely available on http://cmpg.unibe.ch/software/arlequin3.
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          A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals.

          We present methods for imputing data for ungenotyped markers and for inferring haplotype phase in large data sets of unrelated individuals and parent-offspring trios. Our methods make use of known haplotype phase when it is available, and our methods are computationally efficient so that the full information in large reference panels with thousands of individuals is utilized. We demonstrate that substantial gains in imputation accuracy accrue with increasingly large reference panel sizes, particularly when imputing low-frequency variants, and that unphased reference panels can provide highly accurate genotype imputation. We place our methodology in a unified framework that enables the simultaneous use of unphased and phased data from trios and unrelated individuals in a single analysis. For unrelated individuals, our imputation methods produce well-calibrated posterior genotype probabilities and highly accurate allele-frequency estimates. For trios, our haplotype-inference method is four orders of magnitude faster than the gold-standard PHASE program and has excellent accuracy. Our methods enable genotype imputation to be performed with unphased trio or unrelated reference panels, thus accounting for haplotype-phase uncertainty in the reference panel. We present a useful measure of imputation accuracy, allelic R(2), and show that this measure can be estimated accurately from posterior genotype probabilities. Our methods are implemented in version 3.0 of the BEAGLE software package.
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            Author and article information

            Affiliations
            [1 ]Division of Human Genetics, Department of Integrated Genetics, National Institute of Genetics, Mishima, Shizuoka, Japan
            [2 ]Division of Molecular Life Science, School of Medicine, Tokai University, Isehara, Kanagawa, Japan
            [3 ]GenoDive Pharma Inc. Isehara, Kanagawa, Japan
            [4 ]Clinical Pharmacology, Clinical Data Science Department, Takeda Development Center Japan Takeda Pharmaceutical Co, Ltd. Chuo-ku Osaka, Japan
            [5 ]Clinical Pharmacology, Astellas Pharma Global Development Astellas Pharma Inc. Itabashi-ku, Tokyo, Japan
            [6 ]PGx office, Department of Clinical Research and Development, Otsuka Pharmaceutical Co., Ltd. Chuo-ku, Osaka, Japan
            [7 ]Clinical Pharmacology Department, Development Division Mitsubishi Tanabe Pharma Corporation Yodogawa-ku, Osaka, Japan
            [8 ]PGx, Clinical Research Taisho Pharmaceutical Co., Ltd. Toshima-ku, Tokyo, Japan
            [9 ]Translational Medicine and Clinical Pharmacology Department, R&D Division Daiichi-Sankyo Co., Ltd. Shinagawa-ku, Tokyo, Japan
            University of Cagliari, Italy
            Author notes

            Competing Interests: Authors whose affiliations are listed as GenoDive Pharma Inc. are founders of this bio-venture company. Authors whose affiliations are listed as Takeda Pharmaceutical Co, Ltd., Astellas Pharma Inc., Otsuka Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Taisho Pharmaceutical Co., Ltd., and Daiichi-Sankyo Co., Ltd. are employees of these pharmaceutical companies. All of them follow the PLOS ONE policies on sharing data and materials.

            Conceived and designed the experiments: HN SM KH HI II. Performed the experiments: HN. Analyzed the data: HN. Contributed reagents/materials/analysis tools: SM LSY TS TF NT KS AS HI. Wrote the paper: HN II.

            Contributors
            Role: Editor
            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, USA )
            1932-6203
            2013
            5 April 2013
            : 8
            : 4
            23577161
            3618337
            PONE-D-12-28604
            10.1371/journal.pone.0060793
            (Editor)

            This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

            Counts
            Pages: 11
            Funding
            This work was supported by Grant-in-Aid for Scientific Research on Innovative Areas Grant Number 23133507. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Categories
            Research Article
            Biology
            Evolutionary Biology
            Evolutionary Processes
            Genetics
            Human Genetics
            Genetic Association Studies
            Population Genetics
            Gene Flow
            Genetic Polymorphism
            Haplotypes
            Immunology
            Genetics of the Immune System
            Major Histocompatibility Complex
            Medicine
            Clinical Immunology
            Major Histocompatibility Complex

            Uncategorized

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