The sequences of 150,119 genomes in the UK biobank

Abstract

We describe the analysis of whole genome sequencing (WGS) of 150,119 individuals from the UK biobank (UKB). This yielded a set of high quality variants, including 585,040,410 SNPs, representing 7.0% of all possible human SNPs, and 58,707,036 indels. The large set of variants allows us to characterize selection based on sequence variation within a population through a Depletion Rank (DR) score for windows along the genome. DR analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UKB, a large British Irish cohort (XBI) and smaller African (XAF) and South Asian (XSA) cohorts. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large scale WGS studies. Using this formidable new resource, we provide several noteworthy examples of trait associations with rare variants with large effects not found previously through studies based on exome sequencing and/or imputation.

Large-scale comparison of immunoassay- and aptamer-based plasma proteomics through genetics and disease

“…We used the Olink Explore 1536 platform with 1,459 assays targeting 1,450 unique proteins (Supplementary Table 1) to measure plasma protein levels of 54,303 UKB participants with 57.7 million imputed sequence variants discovered through whole-genome sequencing of 150,119 individuals from UKB 10 . Of the UKB participants with protein level measurements, 47,151 individuals were of British or Irish ancestry.…”

“…The 47K participants in the UK Biobank with Olink Explore measure plasma protein levels in this study had 57.7 million imputed sequence variants discovered through whole-genome sequencing of 150,119 individuals from UKB 10 .…”

Whole genome sequencing identifies common and rare structural variants contributing to hematologic traits in the NHLBI TOPMed program

“…For replication analyses, we defined an SV in replication datasets to represent a TOPMed SV, if located within 5 kb of the TOPMed SV and if the two SV sizes overlapped by at least 25%. We tested for association for all representative SVs and their corresponding phenotypes based on the linear mixed model implemented in BOLT-LMM 69 and described in 17,20 . We considered an association to be replicated if at least one of the p-values from the deCODE, UKBB British, UKBB African, or UKBB South Asian cohorts was < 0.05/(number of its representative SVs in given dataset).…”

“…We attempted replication for each of the 33 trait-associated SVs using a combination of short-read and long-read WGS data and genotype imputation. We utilized independent datasets composed of Icelandic (deCODE genetics) [17][18][19] and multi-ancestry (UK Biobank, UKBB) 20 participants. Note that the SV calling and genotyping algorithms used in replication datasets (described under Methods) are different from the Parliament2 pipeline used for SV discovery in TOPMed.…”

“…SVs were called from 150,119 short-read sequenced individuals in UKBB. Three cohorts were used in UKBB with 132,169, 2,963, and 3,047 sequenced and 431,805, 9,633, and 9,252 imputed individuals, in British/Irish (XBI), African (XAF) and South Asian (XSA) populations, respectively 20 . For replication analyses, we defined an SV in replication datasets to represent a TOPMed SV, if located within 5 kb of the TOPMed SV and if the two SV sizes overlapped by at least 25%.…”