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Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits

Patxot, Marion and Banos, Daniel Trejo and Kousathanas, Athanasios and Orliac, Etienne J. and Ojavee, Sven E. and Moser, Gerhard and Holloway, Alexander and Sidorenko, Julia and Kutalik, Zoltan and Magi, Reedik and Visscher, Peter M. and Rönnegård, Lars and Robinson, Matthew R. (2021). Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits. Nature Communications. 12 , 6972
[Research article]

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Abstract

Improving inference in large-scale genetic data linked to electronic medical record data requires the development of novel computationally efficient regression methods. Here, the authors develop a Bayesian approach for association analyses to improve SNP-heritability estimation, discovery, fine-mapping and genomic prediction.We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only <= 10% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32-44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having >= 95% probability of contributing >= 0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.

Authors/Creators:Patxot, Marion and Banos, Daniel Trejo and Kousathanas, Athanasios and Orliac, Etienne J. and Ojavee, Sven E. and Moser, Gerhard and Holloway, Alexander and Sidorenko, Julia and Kutalik, Zoltan and Magi, Reedik and Visscher, Peter M. and Rönnegård, Lars and Robinson, Matthew R.
Title:Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits
Series Name/Journal:Nature Communications
Year of publishing :2021
Volume:12
Article number:6972
Number of Pages:16
Publisher:NATURE PORTFOLIO
ISSN:2041-1723
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 1 Natural sciences > 102 Computer and Information Science > 10203 Bioinformatics (Computational Biology) (applications to be 10610)
(A) Swedish standard research categories 2011 > 1 Natural sciences > 106 Biological Sciences (Medical to be 3 and Agricultural to be 4) > Genetics (medical genetics to be 30107 and agricultural genetics to be 40402)
URN:NBN:urn:nbn:se:slu:epsilon-p-114699
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-114699
Additional ID:
Type of IDID
DOI10.1038/s41467-021-27258-9
Web of Science (WoS)000724450600023
ID Code:26297
Faculty:VH - Faculty of Veterinary Medicine and Animal Science
Department:(VH) > Dept. of Animal Breeding and Genetics
Deposited By: SLUpub Connector
Deposited On:10 Dec 2021 10:25
Metadata Last Modified:10 Dec 2021 10:31

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