Discovery of runs-of-homozygosity diplotype clusters and their associations with diseases in UK Biobank
- The University of Texas Health Science Center at Houston, United States
- University of Central Florida, United States
Abstract
Runs of homozygosity (ROH) segments, contiguous homozygous regions in a genome were traditionally linked to families and inbred populations. However, a growing literature suggests that ROHs are ubiquitous in outbred populations. Still, most existing genetic studies of ROH in populations are limited to aggregated ROH content across the genome, which does not offer the resolution for mapping causal loci. This limitation is mainly due to a lack of methods for the efficient identification of shared ROH diplotypes. Here, we present a new method, ROH-DICE, to find large ROH diplotype clusters, sufficiently long ROHs shared by a sufficient number of individuals, in large cohorts. ROH-DICE identified over 1 million ROH diplotypes that span over 100 SNPs and are shared by more than 100 UK Biobank participants. Moreover, we found significant associations of clustered ROH diplotypes across the genome with various self-reported diseases, with the strongest associations found between the extended HLA region and autoimmune disorders. We found an association between a diplotype covering the HFE gene and hemochromatosis, even though the well-known causal SNP was not directly genotyped or imputed. Using a genome-wide scan, we identified a putative association between carriers of an ROH diplotype in chromosome 4 and an increase in mortality among COVID-19 patients (P-value=1.82×10-11). In summary, our ROH-DICE method, by calling out large ROH diplotypes in a large outbred population, enables further population genetics into the demographic history of large populations. More importantly, our method enables a new genome-wide mapping approach for finding disease-causing loci with multi-marker recessive effects at a population scale.
Data availability
This research has been conducted using the UK Biobank Resource under Application Number 24247.The source code is available at https://github.com/ZhiGroup/ROH-DICE.
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The UK Biobank resource with deep phenotyping and genomic datahttps://www.ukbiobank.ac.uk/.
Article and author information
Author details
Funding
National Institutes of Health (R01 HG010086)
- Ardalan Naseri
- Degui Zhi
- Shaojie Zhang
National Institutes of Health (R56 HG011509)
- Ardalan Naseri
- Degui Zhi
- Shaojie Zhang
National Institutes of Health (OT2 OD002751)
- Ardalan Naseri
- Degui Zhi
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Our analysis was approved by The University of Texas Health Science Center at Houston committee for the protection of human subjects under No. HSC-SBMI-23-0583. UK Biobank (UKBB) has secured informed consent from the participants in the use of their data for approved research projects. UKBB data was accessed via approved project 24247.
Copyright
© 2024, Naseri et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Discovery of runs-of-homozygosity diplotype clusters and their associations with diseases in UK Biobank
eLife 13:e81698.
https://doi.org/10.7554/eLife.81698
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