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.

The UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Here we describe the genome-wide genotype data (~805,000 markers) collected on all individuals in the cohort and its quality control procedures. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestries of the individuals in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data -such as population structure and relatedness -that can be important for downstream analyses. In addition, we phased and imputed genotypes into the dataset, using computationally efficient methods combined with the Haplotype Reference Consortium (HRC) and UK10K haplotype resource. This increases the number of testable variants by over 100-fold to ~96 million variants. We also imputed classical allelic variation at 11 human leukocyte antigen (HLA) genes, and as a quality control check of this imputation, we replicate signals of known associations between HLA alleles and many common diseases. We describe tools that allow efficient genome-wide association studies (GWAS) of multiple traits and fast phenome-wide association studies (PheWAS), which work together with a new compressed file format that has been used to distribute the dataset. As a further check of the genotyped and imputed datasets, we performed a test-case genome-wide association scan on a well-studied human trait, standing height.

Summary Meiotic recombination proceeds via binding of RPA, RAD51, and DMC1 to single-stranded DNA (ssDNA) substrates created after formation of programmed DNA double-strand breaks. Here we report high-resolution in vivo maps of RPA and RAD51 in meiosis, mapping their binding locations and lifespans to individual homologous chromosomes using a genetically engineered hybrid mouse. Together with high-resolution microscopy and DMC1 binding maps, we show that DMC1 and RAD51 have distinct spatial localization on ssDNA: DMC1 binds near the break site, and RAD51 binds away from it. We characterize inter-homolog recombination intermediates bound by RPA in vivo , with properties expected for the critical displacement loop (D-loop) intermediates. These data support the hypothesis that DMC1, not RAD51, performs strand exchange in mammalian meiosis. RPA-bound D-loops can be resolved as crossovers or non-crossovers, but crossover-destined D-loops may have longer lifespans. D-loops resemble crossover gene conversions in size, but their extent is similar in both repair pathways.