Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations

Juba Nait Saada (), Georgios Kalantzis, Derek Shyr, Fergus Cooper, Martin Robinson, Alexander Gusev and Pier Francesco Palamara ()
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Juba Nait Saada: University of Oxford
Georgios Kalantzis: University of Oxford
Derek Shyr: Harvard T.H. Chan School of Public Health
Fergus Cooper: University of Oxford
Martin Robinson: University of Oxford
Alexander Gusev: Division of Genetics
Pier Francesco Palamara: University of Oxford

Nature Communications, 2020, vol. 11, issue 1, 1-15

Abstract: 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 analyses. We develop FastSMC, an IBD detection algorithm that combines a fast heuristic search with accurate coalescent-based likelihood calculations. FastSMC enables biobank-scale detection and dating of IBD segments within several thousands of years in the past. We apply FastSMC to 487,409 UK Biobank samples and detect ~214 billion IBD segments transmitted by shared ancestors within the past 1500 years, obtaining a fine-grained picture of genetic relatedness in the UK. Sharing of common ancestors strongly correlates with geographic distance, enabling the use of genomic data to localize a sample’s birth coordinates with a median error of 45 km. We seek evidence of recent positive selection by identifying loci with unusually strong shared ancestry and detect 12 genome-wide significant signals. We devise an IBD-based test for association between phenotype and ultra-rare loss-of-function variation, identifying 29 association signals in 7 blood-related traits.

Date: 2020
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DOI: 10.1038/s41467-020-19588-x

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