Submitted by ja607 on
Title | Quantifying the regulatory effect size of -acting genetic variation using allelic fold change. |
Publication Type | Journal Article |
Year of Publication | 2017 |
Authors | Mohammadi, P, Castel, SE, Brown, AA, Lappalainen, T |
Journal | Genome Res |
Volume | 27 |
Issue | 11 |
Pagination | 1872-1884 |
Date Published | 2017 11 |
ISSN | 1549-5469 |
Keywords | Alleles, Databases, Genetic, Gene Expression, Gene Expression Profiling, Gene Regulatory Networks, Genetic Variation, Humans, Models, Theoretical, Quantitative Trait Loci |
Abstract | Mapping -acting expression quantitative trait loci (-eQTL) has become a popular approach for characterizing proximal genetic regulatory variants. In this paper, we describe and characterize log allelic fold change (aFC), the magnitude of expression change associated with a given genetic variant, as a biologically interpretable unit for quantifying the effect size of -eQTLs and a mathematically convenient approach for systematic modeling of -regulation. This measure is mathematically independent from expression level and allele frequency, additive, applicable to multiallelic variants, and generalizable to multiple independent variants. We provide efficient tools and guidelines for estimating aFC from both eQTL and allelic expression data sets and apply it to Genotype Tissue Expression (GTEx) data. We show that aFC estimates independently derived from eQTL and allelic expression data are highly consistent, and identify technical and biological correlates of eQTL effect size. We generalize aFC to analyze genes with two eQTLs in GTEx and show that in nearly all cases the two eQTLs act independently in regulating gene expression. In summary, aFC is a solid measure of -regulatory effect size that allows quantitative interpretation of cellular regulatory events from population data, and it is a valuable approach for investigating novel aspects of eQTL data sets. |
DOI | 10.1101/gr.216747.116 |
Alternate Journal | Genome Res |
PubMed ID | 29021289 |
PubMed Central ID | PMC5668944 |
Grant List | R01 DA006227 / DA / NIDA NIH HHS / United States R01 MH101782 / MH / NIMH NIH HHS / United States R01 MH101810 / MH / NIMH NIH HHS / United States R01 MH101819 / MH / NIMH NIH HHS / United States R01 DA033684 / DA / NIDA NIH HHS / United States R01 MH106842 / MH / NIMH NIH HHS / United States UM1 HG008901 / HG / NHGRI NIH HHS / United States R01 MH090936 / MH / NIMH NIH HHS / United States R01 MH090951 / MH / NIMH NIH HHS / United States R01 MH101820 / MH / NIMH NIH HHS / United States R01 MH101825 / MH / NIMH NIH HHS / United States R01 MH090948 / MH / NIMH NIH HHS / United States R01 MH090941 / MH / NIMH NIH HHS / United States R01 MH101822 / MH / NIMH NIH HHS / United States HHSN261200800001C / RC / CCR NIH HHS / United States R01 MH090937 / MH / NIMH NIH HHS / United States HHSN268201000029C / HL / NHLBI NIH HHS / United States HHSN261200800001E / CA / NCI NIH HHS / United States R01 MH101814 / MH / NIMH NIH HHS / United States |