Although the locations of promoters and enhancers have been identified in several cell types, we still have limited information on their connectivity. We developed HiCap, which combines a 4-cutter restriction enzyme Hi-C with sequence capture of promoter regions. Applying the method to mouse embryonic stem cells, we identified promoter-anchored interactions involving 15,905 promoters and 71,984 distal regions. The distal regions were enriched for enhancer marks and transcription, and had a mean fragment size of only 699 bp — close to single-enhancer resolution. High-resolution maps of promoter-anchored interactions with HiCap will be important for detailed characterizations of chromatin interaction landscapes.

Hundreds of variants associated with atopic dermatitis (AD) and psoriasis, two common inflammatory skin disorders, have previously been discovered through genome-wide association studies (GWAS). The majority of these variants are in non-coding regions and their target genes remain largely unclear. We sought to understand the effects of these non-coding variants on the development of AD and psoriasis by linking them to the genes they regulate. We constructed genomic 3D maps of human keratinocytes during differentiation using capture Hi-C targeting more >20, 000 promoters and 214 GWAS variants and combined this with transcriptome and epigenomic datasets. We validated our results with reporter assays, CRISPR activation and examination of patient gene expression from previous studies. We identified 118 target genes of 82 AD and psoriasis GWAS-variants. Differential expression of 49% (58) of the 118 target genes occurred in either AD or psoriatic lesions, many of which were not previously linked to any skin disease. We highlight AFG1L, CLINT1, ADO, LINC00302, and RP1-140J1.1 genes and provide further evidence for their potential roles in AD and psoriasis. Our work focuses on skin barrier pathology through investigation of the interaction profile of GWAS-variants during keratinocyte differentiation. We provide a catalogue of candidate genes that could modulate the risk of AD and psoriasis. Given that only 35% of the target genes are the nearest gene to the known GWAS variants, we expect that our work will contribute to the discovery of novel pathways involved in AD and psoriasis.

Several Genome Wide Association Studies (GWAS) have reported variants associated to immune diseases. However, the identified variants are rarely the drivers of the associations and the molecular mechanisms behind the genetic contributions remain poorly understood. ChIP-seq data for TFs and histone modifications provide snapshots of protein-DNA interactions allowing the identification of heterozygous SNPs showing significant allele specific signals (AS-SNPs). AS-SNPs can change a TF binding site resulting in altered gene regulation and are primary candidates to explain associations observed in GWAS and expression studies. We identified 17,293 unique AS-SNPs across 7 lymphoblastoid cell lines. In this set of cell lines we interrogated 85% of common genetic variants in the population for potential regulatory effect and we identified 237 AS-SNPs associated to immune GWAS traits and 714 to gene expression in B cells. To elucidate possible regulatory mechanisms we integrated long-range 3D interactions data to identify putative target genes and motif predictions to identify TFs whose binding may be affected by AS-SNPs yielding a collection of 173 AS-SNPs associated to gene expression and 60 to B cell related traits. We present a systems strategy to find functional gene regulatory variants, the TFs that bind differentially between alleles and novel strategies to detect the regulated genes.

Folding of eukaryotic genomes within nuclear space enables physical and functional contacts between regions that are otherwise kilobases away in sequence space. Targeted chromosome conformation capture methods (T2C, chi-C and HiCap) are capable of informing genomic contacts for a subset of regions targeted by probes. We here present HiCapTools, a software package that can design sequence capture probes for targeted chromosome capture applications and analyse sequencing output to detect proximities involving targeted fragments. Two probes are designed for each feature while avoiding repeat elements and non-unique regions. The data analysis suite processes alignment files to report genomic proximities for each feature at restriction fragment level and is isoform-aware for gene features. Statistical significance of contact frequencies is evaluated using an empirically derived background distribution. Targeted chromosome conformation capture applications are invaluable for locating target genes of disease-associated variants found by genome-wide association studies. Hence, we believe our software suite will prove to be useful for a wider user base within clinical and functional applications. https://github.com/sahlenlab/HiCapTools. Supplementary data are available at Bioinformatics online.

Background: Genetic variant landscape of coronary artery disease is dominated by noncoding variants among which many occur within putative enhancers regulating the expression levels of relevant genes. It is crucial to assign the genetic variants to their correct genes both to gain insights into perturbed functions and better assess the risk of disease. Methods: In this study, we generated high-resolution genomic interaction maps (≈750 bases) in aortic endothelial, smooth muscle cells and THP-1 (human leukemia monocytic cell line) macrophages stimulated with lipopolysaccharide using Hi-C coupled with sequence capture targeting 25 429 features, including variants associated with coronary artery disease. We also sequenced their transcriptomes and mapped putative enhancers using chromatin immunoprecipitation with an antibody against H3K27Ac. Results: The regions interacting with promoters showed strong enrichment for enhancer elements and validated several previously known interactions and enhancers. We detected interactions for 727 risk variants obtained by genome-wide association studies and identified novel, as well as established genes and functions associated with cardiovascular diseases. We were able to assign potential target genes for additional 398 genome-wide association studies variants using haplotype information, thereby identifying additional relevant genes and functions. Importantly, we discovered that a subset of risk variants interact with multiple promoters and their expression levels were strongly correlated. Conclusions: In summary, we present a catalog of candidate genes regulated by coronary artery disease–related variants and think that it will be an invaluable resource to further the investigation of cardiovascular pathologies and disease.