Regulation of gene expression is a highly heritable, critical component of a variety of biological processes. Studies integrating expression data and genotypic data have successfully identified common-variant expression quantitative trait loci (eQTLs) in a range of cell and tissues samples. As the majority of common genetic variants associated with complex traits map to non-coding regions of the genome, genome-wide studies of the genetic regulation of gene expression are key to interpreting the wealth of data generated in association studies and to understanding the genetic architecture of gene regulation, and by extension, the genetic architecture of complex traits.

We propose to fine-map common variant and identify rare variant eQTLs by integrating UK10K whole genome sequences from the TwinsUK and ALSPAC cohorts with gene expression data generated from the same individuals as part of the MuTHER study (TwinsUK) and ALSPAC expression study. Gene expression data is available from three tissues in the MuTHER individuals - lymphoblastoid cell lines (LCLs), adipose and skin, and LCLs in the ALSPAC individuals. In each case roughly half of the individuals have whole genome sequences generated as part of the cohorts arm of UK10K and the remaining will have imputed genotypes based on the UK10K-reference panel. Both the ALSPAC and TwinsUK expression profiles were generated on the Illumina HT-12 array in the same facility, making them ideally matched for joint analyses. We are applying separately to the UK10K management committee for access to the ALSPAC genome sequences. The proposed research will generate a novel resource of fine-scale regulatory data and inform our understanding of the genetic regulation of gene expression.

We will carry out global single point (MAF greater than 1%) and rare-variants burden scans to identify cis-eQTLs. We will condition on significant peaks to find secondary (and potentially tertiary signals). We will use the discovered cis-eQTLs to answer the following questions: A) How much more of the heritability of expression of a transcript is explained by rare variant or incompletely tagged common variants? B) Where do the cis-eQTLs map and can we use functional annotation to improve the sensitivity of our scans? C) Where we find a secondary eQTL signal under a primary one already linked to a GWAS signal is there evidence that the secondary eQTL also affects the GWAS trait? (We will focus on traits measured in the UK10K analysis of the TwinsUK/ALSPAC full cohort) In addition, we will fine map trans-eQTLs previously discovered with common variant genotypic data in these datasets.