ERASE: Extended Randomization for assessment of annotation enrichment in ASE datasets

Abstract

Genome-wide association studies (GWAS) have identified thousands of genetic variants 24 associated with various human phenotypes and many of these loci are thought to act at a molecular 25 level by regulating gene expression. Detection of allele specific expression (ASE), namely 26 preferential usage of an allele at a transcribed locus, is an increasingly important means of studying 27 the genetic regulation of gene expression. However, there are currently a paucity of tools available 28 to link ASE sites with GWAS risk loci. Existing integration methods first use ASE sites to infer 29 cis-acting expression quantitative trait loci (eQTL) and then apply eQTL-based approaches. 30ERASE is a method that assesses the enrichment of risk loci amongst ASE sites directly. 31 Furthermore, ERASE enables additional biological insights to be made through the addition of 32 other SNP level annotations. ERASE is based on a randomization approach and controls for read 33 depth, a significant confounder in ASE analyses. In this paper, we demonstrate that ERASE can 34 efficiently detect the enrichment of eQTLs and risk loci within ASE data and that it remains 35 sensitive even when used with underpowered GWAS datasets. Finally, using ERASE in 36 combination with GWAS data for Parkinson's disease and data on the splicing potential of 37 individual SNPs, we provide evidence to suggest that risk loci for Parkinson's disease are enriched 38 amongst ASEs likely to affect splicing. Thus, we show that ERASE is an important new tool for 39 the integration of ASE and GWAS data, capable of providing novel insights into the 40 pathophysiology of complex diseases. 41 42 43 44 Over the last decade our understanding of complex genetic disorders has been transformed by the 45 use of genome-wide association studies (GWAS) with 71,673 SNP-trait associations reported in 46 the latest release of the NHGRI-EBI GWAS catalogue 1 . Complex neurological and 47 neuropsychiatric disorders are no exception. The most recent GWAS for Parkinson's disease (PD) 48 reported 78 risk loci 2 , while that for schizophrenia 3 reported 145. While there is a lag in terms of 49 understanding the underlying biological processes involved in contributing to disease risk, it is 50 thought that risk loci largely act by regulating gene expression as opposed to changing protein 51 function 4 . This observation has led to an increasing interest in the genetic regulation of gene 52 expression and the identification of expression quantitative trait loci (eQTLs, genetic variants that 53are associated with variation in gene expression) across the genome. eQTL studies have helped in 54 the interpretation of GWAS findings across a range of disorders 5; 6 . However, one limitation of 55 eQTL analyses is the requirement for large sample sizes. Since this can be difficult to achieve for 56 some human tissues, such as specific brain regions, alternative approaches more robust to small 57 sample sets are required. 58Allele specific expression (ASE) analysis is another means of studying ...