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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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          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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            Ancient human genome sequence of an extinct Palaeo-Eskimo.

            We report here the genome sequence of an ancient human. Obtained from approximately 4,000-year-old permafrost-preserved hair, the genome represents a male individual from the first known culture to settle in Greenland. Sequenced to an average depth of 20x, we recover 79% of the diploid genome, an amount close to the practical limit of current sequencing technologies. We identify 353,151 high-confidence single-nucleotide polymorphisms (SNPs), of which 6.8% have not been reported previously. We estimate raw read contamination to be no higher than 0.8%. We use functional SNP assessment to assign possible phenotypic characteristics of the individual that belonged to a culture whose location has yielded only trace human remains. We compare the high-confidence SNPs to those of contemporary populations to find the populations most closely related to the individual. This provides evidence for a migration from Siberia into the New World some 5,500 years ago, independent of that giving rise to the modern Native Americans and Inuit.
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              Population stratification and spurious allelic association.

              Great efforts and expense have been expended in attempts to detect genetic polymorphisms contributing to susceptibility to complex human disease. Concomitantly, technology for detection and scoring of single nucleotide polymorphisms (SNPs) has undergone rapid development, extensive catalogues of SNPs across the genome have been constructed, and SNPs have been increasingly used as a means for investigation of the genetic causes of complex human diseases. For many diseases, population-based studies of unrelated individuals--in which case-control and cohort studies serve as standard designs for genetic association analysis--can be the most practical and powerful approach. However, extensive debate has arisen about optimum study design, and considerable concern has been expressed that these approaches are prone to population stratification, which can lead to biased or spurious results. Over the past decade, a great shift has been noted, away from case-control and cohort studies, towards family-based association designs. These designs have fewer problems with population stratification but have greater genotyping and sampling requirements, and data can be difficult or impossible to gather. We discuss past evidence for population stratification on genotype-phenotype association studies, review methods to detect and account for it, and present suggestions for future study design and analysis.
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                Author and article information

                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
                : e60793
                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.

                Article
                PONE-D-12-28604
                10.1371/journal.pone.0060793
                3618337
                23577161
                99cf453e-c3aa-41cb-b253-1a353761d8af
                Copyright @ 2013

                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.

                History
                : 18 September 2012
                : 3 March 2013
                Page count
                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
                Uncategorized

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