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Walter, K.; Min, J. L.; Huang, J.; Crooks, L.; Memari, Y.; McCarthy, S.; Perry, J. R. B.; Xu, C.; Futema, M.; Lawson, D.; Iotchkova, V.; Schiffels, S.; Hendricks, A. E.; Danecek, P.; Li, R.; Floyd, J.; Wain, L. V.; Barroso, I.; Humphries, S. E.; Hurles, M. E.; Zeggini, E.; Barrett, J. C.; Plagnol, V.; Richards, J. B.; Greenwood, C. M. T.; Timpson, N. J.; Durbin, R.; Soranzo, N.; Bala, S.; Clapham, P. ... view all 339 authors View less authors (2015)
Journal: Nature
Languages: English
Types: Article
Subjects: 3141 Health care science, Adiponectin, Receptors, LDL, Lipid Metabolism, UK10K Consortium, SEQUENCE VARIATION, Multidisciplinary Sciences, Research Support, Non-U.S. Gov't, HERITABILITY, Molecular Sequence Annotation, COMMON, Sequence Analysis, DNA, Science & Technology, Multidisciplinary Sciences, Science & Technology, Genome-Wide Association, Of-Function Mutations, Low-Frequency, Incidental Findings, Sequence Variation, Complex Traits, Population, Common, Heritability, APOC3, Genomics, INCIDENTAL FINDINGS, APOC3, Science & Technology - Other Topics, Female, Alleles, Genome, Human, MD Multidisciplinary, OF-FUNCTION MUTATIONS, Disease, COMPLEX TRAITS, Genetic Variation, Health, Great Britain, Triglycerides, /dk/atira/pure/publication/pubmedpublicationtype/D013485, Reference Standards, Article, POPULATION, Genetics, Medical, genetics,UK10K,Whole-genome sequencing, Exome, Science & Technology, Genome-Wide Association Study, Cohort Studies, Genetics, Population, General Science & Technology, /dk/atira/pure/publication/pubmedpublicationtype/D016428, Journal Article, GENOME-WIDE ASSOCIATION, LOW-FREQUENCY, Genetic Predisposition to Disease, Humans, Male

The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.