Jan 31, 2018

Leveraging allele-specific expression to refine fine-mapping for eQTL studies

BioRxiv : the Preprint Server for Biology
Jennifer ZouEleazar Eskin

Abstract

Many disease risk loci identified in genome-wide association studies are present in non-coding regions of the genome. It is hypothesized that these variants affect complex traits by acting as expression quantitative trait loci (eQTLs) that influence expression of nearby genes. This indicates that many causal variants for complex traits are likely to be causal variants for gene expression. Hence, identifying causal variants for gene expression is important for elucidating the genetic basis of not only gene expression but also complex traits. However, detecting causal variants is challenging due to complex genetic correlation among variants known as linkage disequilibrium (LD) and the presence of multiple causal variants within a locus. Although several fine-mapping approaches have been developed to overcome these challenges, they may produce large sets of putative causal variants when true causal variants are in high LD with many non-causal variants. In eQTL studies, there is an additional source of information that can be used to improve fine-mapping called allele-specific expression (ASE) that measures imbalance in gene expression due to different alleles. In this work, we develop a novel statistical method that leverages both...Continue Reading

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Mentioned in this Paper

Genome-Wide Association Study
Study
Quantitative Trait Loci
Imbalance
Genome
Genes
Dysequilibrium Syndrome
Gene Expression
Mapping, Vessel
Simulation

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