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      Human genomics of the humoral immune response against polyomaviruses

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          Abstract

          Human polyomaviruses are widespread in humans and can cause severe disease in immunocompromised individuals. To identify human genetic determinants of the humoral immune response against polyomaviruses, we performed genome-wide association studies and meta-analyses of qualitative and quantitative immunoglobulin G responses against BK polyomavirus (BKPyV), JC polyomavirus (JCPyV), Merkel cellpolyomavirus (MCPyV), WU polyomavirus (WUPyV), and human polyomavirus 6 (HPyV6) in 15,660 individuals of European ancestry from three independent studies. We observed significant associations for all tested viruses: JCPyV, HPyV6, and MCPyV associated with human leukocyte antigen class II variation, BKPyV and JCPyV with variants in FUT2, responsible for secretor status, MCPyV with variants in STING1, involved in interferon induction, and WUPyV with a functional variant in MUC1, previously associated with risk for gastric cancer. These results provide insights into the genetic control of a family of very prevalent human viruses, highlighting genes and pathways that play a modulating role in human humoral immunity.

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          Second-generation PLINK: rising to the challenge of larger and richer datasets

          PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for even faster and more scalable implementations of key functions. In addition, GWAS and population-genetic data now frequently contain probabilistic calls, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, O(sqrt(n))-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. This will be followed by PLINK 2.0, which will introduce (a) a new data format capable of efficiently representing probabilities, phase, and multiallelic variants, and (b) extensions of many functions to account for the new types of information. The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.
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            UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

            Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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              The UK Biobank resource with deep phenotyping and genomic data

              The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.
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                Author and article information

                Contributors
                Journal
                Virus Evol
                Virus Evol
                vevolu
                Virus Evolution
                Oxford University Press (UK )
                2057-1577
                2021
                11 June 2021
                11 June 2021
                : 7
                : 2
                : veab058
                Affiliations
                Global Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne , CH-1015 Lausanne, Switzerland
                Swiss Institute of Bioinformatics , Quartier UNIL-Sorge, CH-1015 Lausanne, Switzerland
                departmentThe Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive , Oxford OX3 7BN, United Kingdom
                departmentRoche Pharmaceutical Research and Early Development, F. Hoffmann-La Roche Ltd , Headquarters Grenzacherstrasse 124, CH-4070 Basel, Switzerland
                Global Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne , CH-1015 Lausanne, Switzerland
                Swiss Institute of Bioinformatics , Quartier UNIL-Sorge, CH-1015 Lausanne, Switzerland
                Global Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne , CH-1015 Lausanne, Switzerland
                Swiss Institute of Bioinformatics , Quartier UNIL-Sorge, CH-1015 Lausanne, Switzerland
                Global Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne , CH-1015 Lausanne, Switzerland
                departmentPrecision Medicine Unit, Lausanne University Hospital and University of Lausanne , Rue du Bugnon 46, CH-1011 Lausanne, Switzerland
                departmentInstitute for Molecular Medicine Finland, Institute of Life Science HiLIFE, University of Helsinki , Haartmaninkatu 8, 00290 Helsinki, Finland
                departmentDepartment of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne , Rue du Bugnon 46, CH-1011 Lausanne, Switzerland
                departmentDepartment of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne , Rue du Bugnon 46, CH-1011 Lausanne, Switzerland
                departmentClinical Neuroscience, Max Planck Institute of Experimental Medicine, DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain , Hermann-Rein-Straße 3, 37075 Göttingen, Germany
                departmentClinical Neuroscience, Max Planck Institute of Experimental Medicine, DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain , Hermann-Rein-Straße 3, 37075 Göttingen, Germany
                departmentInfections and Cancer Epidemiology, German Cancer Research Center , Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
                departmentInfections and Cancer Epidemiology, German Cancer Research Center , Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
                departmentInfections and Cancer Epidemiology, German Cancer Research Center , Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
                departmentThe Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive , Oxford OX3 7BN, United Kingdom
                departmentBig Data Institute, LiKa Shing Centre for Health Information and Discovery, University of Oxford , Old Road Campus, Oxford OX3 7LF, United Kingdom
                departmentThe Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive , Oxford OX3 7BN, United Kingdom
                departmentThe Jenner Institute, University of Oxford , Old Road Campus Research Build, Roosevelt Dr, Oxford OX1 2JD, United Kingdom
                departmentThe Jenner Institute, University of Oxford , Old Road Campus Research Build, Roosevelt Dr, Oxford OX1 2JD, United Kingdom
                departmentDepartment of Cancer Immunology, Genentech Inc. , 1 DNA Way, South San Francisco, CA 94080, USA
                departmentDepartment of Human Genetics, Genentech Inc. , 1 DNA Way, South San Francisco, CA 94080, USA
                Global Health Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne , CH-1015 Lausanne, Switzerland
                Swiss Institute of Bioinformatics , Quartier UNIL-Sorge, CH-1015 Lausanne, Switzerland
                departmentPrecision Medicine Unit, Lausanne University Hospital and University of Lausanne , Rue du Bugnon 46, CH-1011 Lausanne, Switzerland
                Author notes
                Author information
                https://orcid.org/0000-0001-7331-7357
                https://orcid.org/0000-0002-0765-896X
                https://orcid.org/0000-0002-4502-2209
                https://orcid.org/0000-0003-4548-7548
                Article
                veab058
                10.1093/ve/veab058
                8438875
                34532061
                56ebec33-832a-4c55-a786-6244d3bab822
                © The Author(s) 2021. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 01 February 2021
                : 30 April 2021
                : 09 June 2021
                : 07 June 2021
                : 21 July 2021
                Page count
                Pages: 11
                Funding
                Funded by: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, DOI 10.13039/501100001711;
                Award ID: 175603
                Categories
                Research Article
                AcademicSubjects/MED00860
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI02285

                infection,human,genomics,polyomavirus,gwas,meta-analysis
                infection, human, genomics, polyomavirus, gwas, meta-analysis

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