Nature CommunicationsGeneticsPeer-reviewed journal article
Identity-by-descent detection across 487,409 British samples reveals fine-scale population structure, evolutionary history, and trait associations
Juba Nait SaadaiD, Georgios KalantzisiD, Derek ShyriD, Fergus CooperiD, Martin J. RobinsoniD, Alexander GuseviD, Pier Francesco PalamaraiD
Abstract
Detection of Identical-By-Descent (IBD) segments provides a fundamental measure of genetic relatedness and plays a key role in a wide range of genomic analyses. We developed a new method, called FastSMC, that enables accurate biobank-scale detection of IBD segments transmitted by common ancestors living up to several hundreds of generations in the past. FastSMC combines a fast heuristic search for IBD segments with accurate coalescent-based likelihood calculations and enables estimating the age of common ancestors transmitting IBD regions. We applied FastSMC to 487,409 phased samples from the UK Biobank and detected the presence of [~]214 billion IBD segments transmitted by shared ancestors within the past 1,500 years. We quantified time-dependent shared ancestry within and across 120 postcodes, obtaining a fine-grained picture of genetic relatedness within the past two millennia in the UK. Sharing of common ancestors strongly correlates with geographic distance, enabling the localization of a samples birth coordinates from genomic data. We sought evidence of recent positive selection by identifying loci with unusually strong shared ancestry within recent millennia and we detected 12 genome-wide significant signals, including 7 novel loci. We found IBD sharing to be highly predictive of the sharing of ultra-rare variants in exome sequencing samples from the UK Biobank. Focusing on loss-of-function variation discovered using exome sequencing, we devised an IBD-based association test and detected 29 associations with 7 blood-related traits, 20 of which were not detected in the exome sequencing study. These results underscore the importance of modelling distant relatedness to reveal subtle population structure, recent evolutionary history, and rare pathogenic variation.
- organism: human
- assay: whole-exome sequencing
- assay: GWAS summary statistics
- research focus: fine-mapping
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 125
- FWCI
- 7.32
- Field percentile
- top 2%
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