Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits

ARG-Needle is a method to infer genome-wide genealogies from large-scale genotyping data that can be used in association analyses. Applied to UK Biobank data, genealogy-based testing finds more trait associations than using imputed genotypes. Genome-wide genealogies compactly represent the evolutionary history of a set of genomes and inferring them from genetic data has the potential to facilitate a wide range of analyses. We introduce a method, ARG-Needle, for accurately inferring biobank-scale genealogies from sequencing or genotyping array data, as well as strategies to utilize genealogies to perform association and other complex trait analyses. We use these methods to build genome-wide genealogies using genotyping data for 337,464 UK Biobank individuals and test for association across seven complex traits. Genealogy-based association detects more rare and ultra-rare signals ( N  = 134, frequency range 0.0007−0.1%) than genotype imputation using ~65,000 sequenced haplotypes ( N  = 64). In a subset of 138,039 exome sequencing samples, these associations strongly tag (average r  = 0.72) underlying sequencing variants enriched (4.8×) for loss-of-function variation. These results demonstrate that inferred genome-wide genealogies may be leveraged in the analysis of complex traits, complementing approaches that require the availability of large, population-specific sequencing panels.