Post-GWAS functional characterisation of breast cancer susceptibility loci

Background
More than 70 different breast cancer risk loci have now been discovered via genome wide association studies (GWAS) but until recently it has not been possible to identify the causal variants that are directly responsible for the altered risk. Importantly, the majority of variants lie within non-coding regions of the genome such as introns and intergenic regions, therefore regulatory elements, rather than protein-coding transcripts, are likely responsible for the associated risk at many loci. These regulatory elements may act as long-range enhancers or repressors of genes outside these regions through long-range interactions mediated by the formation of chromatin loops. This project will involve analysing regulatory elements containing candidate causative variants and identifying the target genes and the relevant changes in their regulation that confer an increased risk of breast cancer.

Aims
1. Identify/confirm the target genes of the putative regulatory elements using chromosome conformation-based techniques.
2. Evaluate the likely functional DNA variants at breast cancer susceptibility loci using a combination of in vitro studies.


Approaches
We will initially use an in silico approach to assess whether the top variants from GWAS fine-mapping data fall in putative regulatory elements. The analysis will integrate multiple complementary genome-wide data sets, including ChIP-seq for histone modifications and DNA binding proteins. We will then employ multiple experimental approaches to identify target genes that physically interact with the putative regulatory elements identified in our breast cancer risk loci. These include eQTL analysis, chromosome conformation capture (3C) techniques and reporter assays. To functionally evaluate the cancer-associated DNA variants, we will use a combination of in vitro assays including chromatin immunoprecipitation (ChIP) assays, allele-specific 3C, gene silencing using RNAi or gene overexpression using retroviral expression systems. We will also generate isogenic cell lines for the best candidate DNA variants using new technologies such as TALENs or CRISPR/Cas systems. These specialised lines will be used to measure target gene expression and activity, identify allele-specific chromatin interactions and assess TF binding.

http://www.qimrberghofer.edu.au/page/Lab/Functional_Cancer_Genomics/
http://www.qimrberghofer.edu.au/page/Lab/Functional_Genetics/

Please email Dr Stacey Edwards and Dr Juliet French with your academic CV