Abstract
Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology1,2. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations(3-6). Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease(7-17). Here we generated peripheral blood RNA-seq data from 2,116 unrelated individuals and systematically identified context-dependent eQTLs using a hypothesis-free strategy that does not require previous knowledge of the identity of the modifiers. Of the 23,060 significant cis-regulated genes (false discovery rate (FDR)
Original language | English |
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Pages (from-to) | 139-145 |
Number of pages | 7 |
Journal | Nature Genetics |
Volume | 49 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2017 |
Keywords
- GENE-EXPRESSION
- DISEASE ASSOCIATIONS
- HUMAN NEUTROPHILS
- CELL
- GENOME
- VARIANTS
- OBESITY
- ENRICHMENT
- INFECTION
- ALLELES