Unbiased analysis of potential targets of breast cancer susceptibility loci by Capture Hi-C
- Nicola H Dryden1,
- Laura R Broome1,
- Frank Dudbridge2,
- Nichola Johnson1,
- Nick Orr1,
- Stefan Schoenfelder3,
- Takashi Nagano3,
- Simon Andrews3,
- Steven Wingett3,
- Iwanka Kozarewa1,
- Ioannis Assiotis1,
- Kerry Fenwick1,
- Sarah L Maguire1,
- James Campbell1,
- Rachael Natrajan1,
- Maryou Lambros1,
- Eleni Perrakis1,
- Alan Ashworth1,
- Peter Fraser3 and
- Olivia Fletcher1,4
- 1 Institute of Cancer Research;
- 2 London School of Hygiene and Tropical Medicine;
- 3 The Babraham Institute
- ↵* Corresponding author; email: olivia.fletcher{at}icr.ac.uk
Abstract
Genome-wide association studies have identified over 70 common variants that are associated with breast cancer risk. Most of these variants map to non-protein-coding regions and several map to gene deserts, regions of several hundred kb lacking protein-coding genes. We hypothesised that gene deserts harbour long range regulatory elements that can physically interact with target genes to influence their expression. To test this, we developed Capture Hi-C (CHi-C) which, by incorporating a sequence capture step into a Hi-C protocol, allows high resolution analysis of targeted regions of the genome. We used CHi-C to investigate long range interactions at three breast cancer gene deserts mapping to 2q35, 8q24.21 and 9q31.2. We identified interaction peaks between putative regulatory elements ('bait fragments') within the captured regions and 'targets' that included both protein coding genes and long non-coding (lnc)RNAs, over distances of 6.6kb to 2.6Mb. Target protein-coding genes were IGFBP5, KLF4, NSMCE2 and MYC and target lncRNAs included DIRC3, PVT1 and CCDC26. For one gene desert we were able to define two SNPs (rs12613955 and rs4442975) that were highly correlated with the published risk variant and that mapped within the bait end of an interaction peak. In vivo ChIP-qPCR data show that one of these, rs4442975, affects the binding of FOXA1 and implicate this SNP as a putative functional variant.
- Received March 7, 2014.
- Accepted August 6, 2014.
- Published by Cold Spring Harbor Laboratory Press
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