학술논문

Unbiased analysis of potential targets of breast cancer susceptibility loci by Capture Hi-C
Document Type
article
Source
Genome Research. 24(11)
Subject
Biological Sciences
Genetics
Human Genome
Breast Cancer
Cancer
Biotechnology
Aetiology
2.1 Biological and endogenous factors
Breast Neoplasms
Cell Line
Tumor
Chromatin Immunoprecipitation
Chromosome Mapping
Chromosomes
Human
Pair 2
Chromosomes
Human
Pair 8
Chromosomes
Human
Pair 9
Genetic Predisposition to Disease
Genome
Human
Genome-Wide Association Study
Hepatocyte Nuclear Factor 3-alpha
Homeodomain Proteins
Humans
Kruppel-Like Factor 4
MCF-7 Cells
Oligonucleotide Array Sequence Analysis
Polymorphism
Single Nucleotide
Protein Binding
Protein Interaction Mapping
RNA
Long Noncoding
Real-Time Polymerase Chain Reaction
Regulatory Sequences
Nucleic Acid
Reproducibility of Results
Sequence Analysis
DNA
Medical and Health Sciences
Bioinformatics
Language
Abstract
Genome-wide association studies have identified more than 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 kilobases lacking protein-coding genes. We hypothesized that gene deserts harbor 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 noncoding (lnc) RNAs over distances of 6.6 kb to 2.6 Mb. 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.