To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3, 9q31.1) and one for endometrioid EOC (5q12.3). We then meta-analysed the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified an additional three loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a novel susceptibility gene for low grade/borderline serous EOC.

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10−8) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.

Genome-wide association studies of colorectal cancer (CRC) have identified a number of common variants associated with modest risk, including rs3802842 at chromosome 11q23.1. Several genes map to this region but rs3802842 does not map to any known transcribed or regulatory sequences. We reasoned, therefore, that rs3802842 is not the functional single-nucleotide polymorphism (SNP), but is in linkage disequilibrium (LD) with a functional SNP(s). We performed ChIP-seq for histone modifications in SW480 and HCT-116 CRC cells, and incorporated ChIP-seq and DNase I hypersensitivity data available through ENCODE within a 137-kb genomic region containing rs3802842 on 11q23.1. We identified SNP rs10891246 in LD with rs3802842 that mapped within a bidirectional promoter region of genes C11orf92 and C11orf93. Following mutagenesis to the risk allele, the promoter demonstrated lower levels of reporter gene expression. A second SNP rs7130173 was identified in LD with rs3802842 that mapped to a candidate enhancer region, which showed strong unidirectional activity in both HCT-116 and SW480 CRC cells. The risk allele of rs7130173 demonstrated reduced enhancer activity compared with the common allele, and reduced nuclear protein binding affinity in electromobility shift assays compared with the common allele suggesting differential transcription factor (TF) binding. SNPs rs10891246 and rs7130173 are on the same haplotype, and expression quantitative trait loci (eQTL) analyses of neighboring genes implicate C11orf53, C11orf92 and C11orf93 as candidate target genes. These data imply that rs10891246 and rs7130173 are functional SNPs mapping to 11q23.1 and that C11orf53, C11orf92 and C11orf93 represent novel candidate target genes involved in CRC etiology.

To identify genes heretofore undiscovered as critical players in the biogenesis of teeth, we have used microarray gene expression analysis of the developing mouse molar tooth (DMT) between postnatal day (P) 1 and P10 to identify genes differentially expressed when compared with 16 control tissues. Of the top 100 genes exhibiting increased expression in the DMT, 29 were found to have been previously associated with tooth development. Differential expression of the remaining 71 genes not previously associated with tooth development was confirmed by quantitative reverse transcription-polymerase chain reaction analysis. Further analysis of seven of the latter genes by mRNA in situ hybridization found that five were specific to the developing tooth in the craniofacial region (Rspo4, Papln, Amtn, Gja1, Maf). Of the remaining two, one was found to be more widely expressed (Sp7) and the other was found to be specific to the nasal serous gland, which is close to, but distinct from, the developing tooth (Vrm). Developmental Dynamics 236: 2245-2257, 2007.

Glioma is the most common malignant primary brain tumor and is associated with poor prognosis. Genetic factors contributing to glioma risk have recently been investigated through genome-wide association studies (GWAS), implicating seven independent glioma risk loci in six chromosomal regions. Here, we performed an in-depth functional analysis of the risk locus proximal to the PHLDB1 gene on 11q23.3. We retrieved all SNPs in linkage disequilibrium (r2 ≥ 0.2) with the glioma-associated SNP (rs498872) and performed a comprehensive bioinformatics and experimental functional analysis for the region. After testing candidate SNPs for allele-specific activity in a luciferase-based enhancer scanning assay, we established a subset of 10 functional SNPs in the promoters of PHLDB1 and DDX6, and in a putative enhancer element. Chromatin conformation capture (3C) identified a physical interaction between the enhancer element containing a functional SNP (rs73001406) and the promoter of the DDX6 gene. Knockdown experiments in cell culture and 3D assays to evaluate the role of PHLDB1 and DDX6 suggest that both genes may contribute to the phenotype. These studies reveal the functional landscape of the 11q23.3 glioma susceptibility locus and identify a network of functional SNPs in regulatory elements and two target genes as a possible mechanism driving glioma risk association.

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer.Significance: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene. 12 16,915,387-16,915,739 NOTE: LD (r 2 ! 0.3) to rs3814113 based on 1000GP data v3. rs2153271 is reported in dbSNP as the reverse orientation to the genome. SNPs in bold represent the final five SNPs remaining at the end of the functional analysis. SNP in bold and underline indicates the only SNP that is common to the two analytic approaches. Abbreviations: MAF, minor allele frequency; NA, not available.Buckley et al.

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P < 5.0 × 10 ). One of the most significant signals (P=1.01 × 10 ;P=3.54 × 10 ) occurred at 3q25.31 for rs62273959, a missense variant mapping to the LEKR1 gene that is in LD (r=0.90) with a previously identified 'best hit' (rs7651446) mapping to an intron of TIPARP. Suggestive associations (5.0 × 10 >P≥5.0 ×10 ) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (P=3.23 × 10 ; P=9.23 × 10 ) and KRT13 (P=1.67 × 10 ; P=1.07 × 10 ), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease.

The present protocol provides a rapid, streamlined and scalable strategy to systematically scan genomic regions for the presence of transcriptional regulatory regions active in a specific cell type. It creates genomic tiles spanning a region of interest that are subsequently cloned by recombination into a luciferase reporter vector containing the Simian Virus 40 promoter. Tiling clones are transfected into specific cell types to test for the presence of transcriptional regulatory regions. The protocol includes testing of different SNP (single nucleotide polymorphism) alleles to determine their effect on regulatory activity. This procedure provides a systematic framework to identify candidate functional SNPs within a locus during functional analysis of genome-wide association studies. This protocol adapts and combines previous well-established molecular biology methods to provide a streamlined strategy, based on automated primer design and Author Contributions: MB, AG, RSC, NTW and ANAM conceived the project and designed the experiments. MB, GMF, AG, RB, and RSC performed the experiments. MB, GMF, AG, RB, RSC, MAC, NTW, and ANAM performed the analysis and contributed to the discussion and overall data interpretation. MB, GMF, AG, and ANAM wrote the paper. All authors provided intellectual input and approved the final manuscript.Editorial Summary: This protocol for enhancer scanning to locate regulatory regions in genomic loci, enables the identification of candidate functional SNPs within a locus during functional analysis of genome-wide association studies Tweet: Enhancer scanning to identify candidate functional SNPs from GWAS data CFI: The authors declare that they have no competing financial interests. HHS Public Access Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript recombinational cloning to rapidly go from a genomic locus to a set of candidate functional SNPs in eight weeks.