The UK10K project identifies rare variants in health and disease

The UK10K Consortium, Evans, David M., Kemp, John P., Visscher, Peter M. and Yang, Jian (2015) The UK10K project identifies rare variants in health and disease. Nature, 526 7571: 82-89. doi:10.1038/nature14962


Author The UK10K Consortium
Evans, David M.
Kemp, John P.
Visscher, Peter M.
Yang, Jian
Title The UK10K project identifies rare variants in health and disease
Journal name Nature   Check publisher's open access policy
ISSN 1476-4687
0028-0836
Publication date 2015-10-01
Sub-type Article (original research)
DOI 10.1038/nature14962
Open Access Status DOI
Volume 526
Issue 7571
Start page 82
End page 89
Total pages 8
Place of publication London, United Kingdom
Publisher Nature Publishing Group
Collection year 2016
Language eng
Formatted abstract
The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
Official 2016 Collection
UQ Diamantina Institute Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 48 times in Thomson Reuters Web of Science Article | Citations
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