The genetic architecture of gene expression in peripheral blood

Lloyd-Jones, Luke R., Holloway, Alexander, McRae, Allan, Yang, Jian, Small, Kerrin, Zeng, Biao, Bakshi, Andrew, Metspalu, Andres, Dermitzakis, Manolis, Gibson, Greg, Spector, Tim, Montgomery, Grant, Esko, Tonu, Visscher, Peter M. and Powell, Joseph E. (2017) The genetic architecture of gene expression in peripheral blood. American Journal of Human Genetics, 100 2: 228-237. doi:10.1016/j.ajhg.2016.12.008

Author Lloyd-Jones, Luke R.
Holloway, Alexander
McRae, Allan
Yang, Jian
Small, Kerrin
Zeng, Biao
Bakshi, Andrew
Metspalu, Andres
Dermitzakis, Manolis
Gibson, Greg
Spector, Tim
Montgomery, Grant
Esko, Tonu
Visscher, Peter M.
Powell, Joseph E.
Title The genetic architecture of gene expression in peripheral blood
Journal name American Journal of Human Genetics   Check publisher's open access policy
ISSN 1537-6605
Publication date 2017-01-05
Year available 2017
Sub-type Article (original research)
DOI 10.1016/j.ajhg.2016.12.008
Open Access Status Not yet assessed
Volume 100
Issue 2
Start page 228
End page 237
Total pages 10
Place of publication Cambridge, MA, United States
Publisher Cell Press
Language eng
Subject 1311 Genetics
2716 Genetics (clinical)
Abstract We analyzed the mRNA levels for 36,778 transcript expression traits (probes) from 2,765 individuals to comprehensively investigate the genetic architecture and degree of missing heritability for gene expression in peripheral blood. We identified 11,204 cis and 3,791 trans independent expression quantitative trait loci (eQTL) by using linear mixed models to perform genome-wide association analyses. Furthermore, using information on both closely and distantly related individuals, heritability was estimated for all expression traits. Of the set of expressed probes (15,966), 10,580 (66%) had an estimated narrow-sense heritability (h2) greater than zero with a mean (median) value of 0.192 (0.142). Across these probes, on average the proportion of genetic variance explained by all eQTL (h2COJO) was 31% (0.060/0.192), meaning that 69% is missing, with the sentinel SNP of the largest eQTL explaining 87% (0.052/0.060) of the variance attributed to all identified cis- and trans-eQTL. For the same set of probes, the genetic variance attributed to genome-wide common (MAF > 0.01) HapMap 3 SNPs (h2g) accounted for on average 48% (0.093/0.192) of h2. Taken together, the evidence suggests that approximately half the genetic variance for gene expression is not tagged by common SNPs, and of the variance that is tagged by common SNPs, a large proportion can be attributed to identifiable eQTL of large effect, typically in cis. Finally, we present evidence that, compared with a meta-analysis, using individual-level data results in an increase of approximately 50% in power to detect eQTL.
Keyword Gene expression
Genetic architecture
Genetic association study
Linear mixed models
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID 1046880
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Queensland Brain Institute Publications
Institute for Molecular Bioscience - Publications
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