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      Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color

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      1 , 2 , 1 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 9 , 10 , 9 , 10 , 9 , 10 , 11 , 11 , 11 , 11 , 12 , 13 , 14 , 12 , 13 , 15 , 12 , 13 , 12 , 12 , 13 , 15 , 13 , 13 ,   16 , 16 , 17 , 18 , 19 , 20 , 1 , 2 , 21 , 4 , 5 , 6 , 5 , 22 , 23 , 24 , 23 , 25 , 23 , 26 , 23 , 27 , 26 , 19 , 16 , 11 , 21 , 28 , the 23andMe Research Team, the International Visible Trait Genetics Consortium, 7 , 1 , 4 , , 1 , 2 ,
      Science Advances
      American Association for the Advancement of Science

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          Abstract

          A GWAS including 192,986 European and 1636 Asian participants identifies 50 novel discrete associations with eye color.

          Abstract

          Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.

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          The Ensembl Variant Effect Predictor

          The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.
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            Molecular signatures database (MSigDB) 3.0.

            Well-annotated gene sets representing the universe of the biological processes are critical for meaningful and insightful interpretation of large-scale genomic data. The Molecular Signatures Database (MSigDB) is one of the most widely used repositories of such sets. We report the availability of a new version of the database, MSigDB 3.0, with over 6700 gene sets, a complete revision of the collection of canonical pathways and experimental signatures from publications, enhanced annotations and upgrades to the web site. MSigDB is freely available for non-commercial use at http://www.broadinstitute.org/msigdb.
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              GCTA: a tool for genome-wide complex trait analysis.

              For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the "missing heritability" problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.
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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                SciAdv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                March 2021
                10 March 2021
                : 7
                : 11
                : eabd1239
                Affiliations
                [1 ]Department of Twins Research and Genetic Epidemiology, King’s College London, London, UK.
                [2 ]Department of Ophthalmology, King’s College London, London, UK.
                [3 ]Division of Rheumatology, Orthopaedics and Dermatology, School of Medicine, University of Nottingham, Nottingham, UK.
                [4 ]Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.
                [5 ]Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.
                [6 ]University of Chinese Academy of Sciences, Beijing, China.
                [7 ]23andMe Inc., Sunnyvale, CA, USA.
                [8 ]University of Queensland Diamantina Institute, University of Queensland, Brisbane, Queensland, Australia.
                [9 ]MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
                [10 ]Population Health Sciences Bristol Medical School University of Bristol, Bristol, UK.
                [11 ]QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
                [12 ]Department of Medical Sciences, University of Trieste, Trieste, Italy.
                [13 ]Institute for Maternal and Child Health IRCCS “Burlo Garofolo”, Trieste, Italy.
                [14 ]Epidemiology and Biostatistics Department, Faculty of Medicine, School of Public Health, Imperial College London, London, UK.
                [15 ]Division of Genetics of Common Disorders, S. Raffaele Scientific Institute, Milan, Italy.
                [16 ]Centre for Ophthalmology and Visual Science, University of Western Australia, Lions Eye Institute, Perth, Australia.
                [17 ]Centre for Eye Research Australia, University of Melbourne, Department of Ophthalmology, Royal Victorian Eye and Ear Hospital, Melbourne, Australia.
                [18 ]School of Medicine, Menzies Research Institute Tasmania, University of Tasmania, Hobart, Australia.
                [19 ]Department of Epidemiology, Fairbanks School of Public Health, Indiana University, and Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN, USA.
                [20 ]Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
                [21 ]Singapore Eye Research Institute, Singapore National Eye Center, Singapore.
                [22 ]Department of Ophthalmology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.
                [23 ]Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.
                [24 ]Department of Ophthalmology, Radboud University Medical Center, Nijmegen, Netherlands.
                [25 ]Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.
                [26 ]Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.
                [27 ]Nuffield Department of Population Health, University of Oxford, Oxford, UK.
                [28 ]Duke-NUS Medical School, Singapore.
                Author notes
                [*]

                These authors share senior authorship.

                []Corresponding author. Email: pirro.hysi@ 123456kcl.ac.uk
                Author information
                http://orcid.org/0000-0003-2432-0810
                http://orcid.org/0000-0003-1141-4471
                http://orcid.org/0000-0001-9241-8161
                http://orcid.org/0000-0003-0663-4621
                http://orcid.org/0000-0003-0920-1055
                http://orcid.org/0000-0003-3103-9330
                http://orcid.org/0000-0002-1407-8314
                http://orcid.org/0000-0001-7227-632X
                http://orcid.org/0000-0002-5691-1917
                http://orcid.org/0000-0001-7623-328X
                http://orcid.org/0000-0003-1382-380X
                http://orcid.org/0000-0003-2514-2075
                http://orcid.org/0000-0002-4701-9134
                http://orcid.org/0000-0003-3598-2537
                http://orcid.org/0000-0001-9545-6032
                http://orcid.org/0000-0002-1127-7596
                http://orcid.org/0000-0003-2152-2353
                http://orcid.org/0000-0002-5123-5999
                http://orcid.org/0000-0003-0982-771X
                http://orcid.org/0000-0002-4472-8103
                http://orcid.org/0000-0002-3227-2620
                http://orcid.org/0000-0002-0037-1771
                http://orcid.org/0000-0002-2374-9204
                http://orcid.org/0000-0001-9940-2875
                http://orcid.org/0000-0001-7914-4709
                http://orcid.org/0000-0003-4069-8020
                http://orcid.org/0000-0002-4911-803X
                http://orcid.org/0000-0002-9795-0365
                http://orcid.org/0000-0001-5752-2510
                Article
                abd1239
                10.1126/sciadv.abd1239
                7946369
                33692100
                720cab3b-1079-4ef5-8778-0b10d90db9de
                Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                : 04 June 2020
                : 25 January 2021
                Funding
                Funded by: doi http://dx.doi.org/10.13039/100002089, Fight for Sight;
                Funded by: doi http://dx.doi.org/10.13039/100007388, Compagnia di San Paolo;
                Funded by: doi http://dx.doi.org/10.13039/100010269, Wellcome;
                Funded by: doi http://dx.doi.org/10.13039/100011102, Seventh Framework Programme;
                Funded by: doi http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Funded by: doi http://dx.doi.org/10.13039/501100000272, National Institute for Health Research;
                Funded by: doi http://dx.doi.org/10.13039/501100000923, Australian Research Council;
                Funded by: doi http://dx.doi.org/10.13039/501100001108, The Ophthalmic Research Institute of Australia;
                Funded by: doi http://dx.doi.org/10.13039/501100001801, The University of Western Australia;
                Funded by: doi http://dx.doi.org/10.13039/501100002803, Fondazione Cariplo;
                Funded by: doi http://dx.doi.org/10.13039/501100008398, Internationale Stichting Alzheimer Onderzoek;
                Funded by: NIH;
                Funded by: Australian national health and medical research council;
                Funded by: Netherlands Organisation for Scientific Research;
                Funded by: Alzheimer Association;
                Funded by: Center of Medical Systems Biology;
                Funded by: Hersenstichting Nederland;
                Funded by: Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School;
                Categories
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                Research Articles
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                Genetics
                Human Genetics
                Genetics
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                Nielsen Marquez

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