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The UK10K project identifies rare variants in health and disease

Authors :
UK10K Consortium
Walter, Klaudia
Min, Josine L
Huang, Jie
Crooks, Lucy
Memari, Yasin
McCarthy, Shane
Perry, John RB
Xu, ChangJiang
Futema, Marta
Lawson, Daniel
Iotchkova, Valentina
Schiffels, Stephan
Hendricks, Audrey E
Danecek, Petr
Li, Rui
Floyd, James
Wain, Louise V
Barroso, Inês
Humphries, Steve E
Hurles, Matthew E
Zeggini, Eleftheria
Barrett, Jeffrey C
Plagnol, Vincent
Richards, J Brent
Greenwood, Celia MT
Timpson, Nicholas J
Durbin, Richard
Soranzo, Nicole
McCarthy, Shane [0000-0002-2715-4187]
Durbin, Richard [0000-0002-9130-1006]
Apollo - University of Cambridge Repository
Publication Year :
2018
Publisher :
Springer Science and Business Media LLC, 2018.

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.

Details

ISSN :
14764687 and 00280836
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....8d70ab68d80f8f56d00034a89f9ec09c
Full Text :
https://doi.org/10.17863/cam.24790