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

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. FastSM...

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Autores principales: Nait Saada, Juba, Kalantzis, Georgios, Shyr, Derek, Cooper, Fergus, Robinson, Martin, Gusev, Alexander, Palamara, Pier Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704644/
https://www.ncbi.nlm.nih.gov/pubmed/33257650
http://dx.doi.org/10.1038/s41467-020-19588-x
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author Nait Saada, Juba
Kalantzis, Georgios
Shyr, Derek
Cooper, Fergus
Robinson, Martin
Gusev, Alexander
Palamara, Pier Francesco
author_facet Nait Saada, Juba
Kalantzis, Georgios
Shyr, Derek
Cooper, Fergus
Robinson, Martin
Gusev, Alexander
Palamara, Pier Francesco
author_sort Nait Saada, Juba
collection PubMed
description 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.
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spelling pubmed-77046442020-12-03 Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations Nait Saada, Juba Kalantzis, Georgios Shyr, Derek Cooper, Fergus Robinson, Martin Gusev, Alexander Palamara, Pier Francesco Nat Commun Article 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. Nature Publishing Group UK 2020-11-30 /pmc/articles/PMC7704644/ /pubmed/33257650 http://dx.doi.org/10.1038/s41467-020-19588-x Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Nait Saada, Juba
Kalantzis, Georgios
Shyr, Derek
Cooper, Fergus
Robinson, Martin
Gusev, Alexander
Palamara, Pier Francesco
Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations
title Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations
title_full Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations
title_fullStr Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations
title_full_unstemmed Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations
title_short Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations
title_sort identity-by-descent detection across 487,409 british samples reveals fine scale population structure and ultra-rare variant associations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704644/
https://www.ncbi.nlm.nih.gov/pubmed/33257650
http://dx.doi.org/10.1038/s41467-020-19588-x
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