Quantifying the regulatory effect size of cis-acting genetic variation using allelic fold change

Pejman Mohammadi (Lead / Corresponding author), Stephane E Castel, Andrew A Brown, Tuuli Lappalainen

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)
92 Downloads (Pure)

Abstract

Mapping cis-acting expression quantitative trait loci (cis-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 cis-eQTLs and a mathematically convenient approach for systematic modeling of cis-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 cis-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.

Original languageEnglish
Pages (from-to)1872-1884
Number of pages13
JournalGenome Research
Volume27
Issue number11
Early online date11 Oct 2017
DOIs
Publication statusPublished - Nov 2017

Keywords

  • Alleles
  • Databases, Genetic
  • Gene Expression
  • Gene Expression Profiling/methods
  • Gene Regulatory Networks
  • Genetic Variation
  • Humans
  • Models, Theoretical
  • Quantitative Trait Loci

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