Unbiased analysis of potential targets of breast cancer susceptibility loci by Capture Hi-C

Dynamic genome and transcriptional network-based biomarkers and drugs: precision in breast cancer therapy

Despite remarkable progress in medium-term overall survival benefit in the adjuvant, neoadjuvant and metastatic settings, with multiple recent targeted drug approvals, acquired resistance, late relapse, and cancer-related death rates remain challenging. Integrated technological systems have been developed to overcome these unmet needs. The characterization of structural and functional noncoding genome elements through next-generation sequencing (NGS) systems, Hi-C and CRISPR/Cas9, as well as computational models, allows for whole genome and transcriptome analysis. Rapid progress in large-scale single-biopsy genome analysis has identified several novel breast cancer driver genes and oncotargets. The exploration of spatiotemporal tumor evolution has returned exciting while inconclusive data on dynamic intratumor heterogeneity (ITH) through multiregional NGS and single-cell DNA/RNA sequencing and circulating genomic subclones (cGSs) by serial circulating cell-free DNA NGS to predict and overcome intrinsic and acquired therapeutic resistance. This review discusses reliable breast cancer genome analysis data and focuses on two major crucial perspectives. The validation of ITH, cGSs, and intrapatient genetic/genomic heterogeneity as predictive biomarkers, as well as the valid discovery of novel oncotargets within patient-centric genomic trials, encouraging early drug development, could optimize primary and secondary therapeutic decision-making. A longer-term goal is to identify the individualized landscape of both coding and noncoding key mutations. This progress will enable the understanding of molecular mechanisms perturbating regulatory networks, shaping the pharmaceutical controllability of deregulated transcriptional biocircuits.

Modeling three-dimensional genomic organization in evolution and pathogenesis

The regulation of gene expression is mediated via the complex three-dimensional (3D) conformation of the genetic material and its interactions with various intracellular factors. Various experimental and computational approaches have been developed in recent years for understating the relation between the 3D conformation of the genome and the phenotypes of cells in normal condition and diseases. In this review, we will discuss novel approaches for analyzing and modeling the 3D genomic conformation, focusing on deciphering disease-causing mutations that affect gene expression. We conclude that as this is a very challenging mission, an important direction should involve the comparative analysis of various 3D models from various organisms or cells.

The role of 3D genome organization in disease: From compartments to single nucleotides

Since the advent of the chromosome conformation capture technology, our understanding of the human genome 3D organization has grown rapidly and we now know that human interphase chromosomes are folded into multiple layers of hierarchical structures and each layer can play a critical role in transcriptional regulation. Alterations in any one of these finely-tuned layers can lead to unwanted cascade of molecular events and ultimately drive the manifestation of diseases and phenotypes. Here we discuss, starting from chromosome level organization going down to single nucleotide changes, recent studies linking diseases or phenotypes to changes in the 3D genome architecture.

Capture Hi-C Library Generation and Analysis to Detect Chromatin Interactions

Chromosome conformation capture (3C), coupled with next-generation sequencing (Hi-C), provides a means for deciphering not only the principles underlying genome folding and architecture, but more broadly, the role 3D chromatin structure plays in gene regulation and the replication and repair of DNA. The recently implemented modification, in situ Hi-C, maintains nuclear integrity during digestion and ligation steps, reducing random ligation of Hi-C fragments. Although Hi-C allows for genome-wide characterization of chromatin contacts, it requires high-depth sequencing to discover significant contacts. To address this, Capture Hi-C (CHi-C) enriches standard Hi-C libraries for regions of biological interest, for example by specifically targeting gene promoters, aiding identification of biologically significant chromatin interactions compared to conventional Hi-C, for an equivalent number of sequence reads. Illustrating the application of CHi-C applied to genome-wide analysis of chromatin interactions with promoters, we detail the protocols for in situ Hi-C and CHi-C library generation for sequencing, as well as the bioinformatics tools for data analysis. © 2018 by John Wiley & Sons, Inc.

Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways

It remains challenging to boost statistical power of genome-wide association studies (GWASs) to identify more risk variants or loci that can account for "missing heritability." Furthermore, since most identified variants are not in gene-coding regions, a biological interpretation of their function is largely lacking. On the other hand, recent biotechnological advances have made it feasible to experimentally measure the three-dimensional organization of the genome, including enhancer-promoter interactions in high resolutions. Due to the well-known critical roles of enhancer-promoter interactions in regulating gene expression programs, such data have been applied to link GWAS risk variants to their putative target genes, gaining insights into underlying biological mechanisms. However, their direct use in GWAS association testing is yet to be exploited. Here we propose integrating enhancer-promoter interactions into GWAS association analysis to both boost statistical power and enhance interpretability. We demonstrate that through an application to two large-scale schizophrenia (SCZ) GWAS summary data sets, the proposed method could identify some novel SCZ-associated genes and pathways (containing no significant SNPs). For example, after the Bonferroni correction, for the larger SCZ data set with 36,989 cases and 113,075 controls, our method applied to the gene body and enhancer regions identified 27 novel genes and 11 novel KEGG pathways to be significant, all missed by the transcriptome-wide association study (TWAS) approach. We conclude that our proposed method is potentially useful and is complementary to TWAS and other standard gene- and pathway-based methods.

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the spatio-temporal expression of their target genes through physical contact, often bridging considerable (in some cases hundreds of kilobases) genomic distances and bypassing nearby genes. The human genome harbors an estimated one million enhancers, the vast majority of which have unknown gene targets. Assigning distal regulatory regions to their target genes is thus crucial to understand gene expression control. We developed Promoter Capture Hi-C (PCHi-C) to enable the genome-wide detection of distal promoter-interacting regions (PIRs), for all promoters in a single experiment. In PCHi-C, highly complex Hi-C libraries are specifically enriched for promoter sequences through in-solution hybrid selection with thousands of biotinylated RNA baits complementary to the ends of all promoter-containing restriction fragments. The aim is to then pull-down promoter sequences and their frequent interaction partners such as enhancers and other potential regulatory elements. After high-throughput paired-end sequencing, a statistical test is applied to each promoter-ligated restriction fragment to identify significant PIRs at the restriction fragment level. We have used PCHi-C to generate an atlas of long-range promoter interactions in dozens of human and mouse cell types. These promoter interactome maps have contributed to a greater understanding of mammalian gene expression control by assigning putative regulatory regions to their target genes and revealing preferential spatial promoter-promoter interaction networks. This information also has high relevance to understanding human genetic disease and the identification of potential disease genes, by linking non-coding disease-associated sequence variants in or near control sequences to their target genes.

Chromatin Architectural Changes during Cellular Senescence and Aging

Chromatin 3D structure is highly dynamic and associated with many biological processes, such as cell cycle progression, cellular differentiation, cell fate reprogramming, cancer development, cellular senescence, and aging. Recently, by using chromosome conformation capture technologies, tremendous findings have been reported about the dynamics of genome architecture, their associated proteins, and the underlying mechanisms involved in regulating chromatin spatial organization and gene expression. Cellular senescence and aging, which involve multiple cellular and molecular functional declines, also undergo significant chromatin structural changes, including alternations of heterochromatin and disruption of higher-order chromatin structure. In this review, we summarize recent findings related to genome architecture, factors regulating chromatin spatial organization, and how they change during cellular senescence and aging.

Cell-Specific PEAR1 Methylation Studies Reveal a Locus that Coordinates Expression of Multiple Genes

Chromosomal interactions connect distant enhancers and promoters on the same chromosome, activating or repressing gene expression. PEAR1 encodes the Platelet-Endothelial Aggregation Receptor 1, a contact receptor involved in platelet function and megakaryocyte and endothelial cell proliferation. PEAR1 expression during megakaryocyte differentiation is controlled by DNA methylation at its first CpG island. We identified a PEAR1 cell-specific methylation sensitive region in endothelial cells and megakaryocytes that showed strong chromosomal interactions with ISGL20L2, RRNAD1, MRLP24, HDGF and PRCC, using available promoter capture Hi-C datasets. These genes are involved in ribosome processing, protein synthesis, cell cycle and cell proliferation. We next studied the methylation and expression profile of these five genes in Human Umbilical Vein Endothelial Cells (HUVECs) and megakaryocyte precursors. While cell-specific PEAR1 methylation corresponded to variability in expression for four out of five genes, no methylation change was observed in their promoter regions across cell types. Our data suggest that PEAR1 cell-type specific methylation changes may control long distance interactions with other genes. Further studies are needed to show whether such interaction data might be relevant for the genome-wide association data that showed a role for non-coding PEAR1 variants in the same region and platelet function, platelet count and cardiovascular risk.

Capture Hi-C identifies putative target genes at 33 breast cancer risk loci

Genome-wide association studies (GWAS) have identified approximately 100 breast cancer risk loci. Translating these findings into a greater understanding of the mechanisms that influence disease risk requires identification of the genes or non-coding RNAs that mediate these associations. Here, we use Capture Hi-C (CHi-C) to annotate 63 loci; we identify 110 putative target genes at 33 loci. To assess the support for these target genes in other data sources we test for associations between levels of expression and SNP genotype (eQTLs), disease-specific survival (DSS), and compare them with somatically mutated cancer genes. 22 putative target genes are eQTLs, 32 are associated with DSS and 14 are somatically mutated in breast, or other, cancers. Identifying the target genes at GWAS risk loci will lead to a greater understanding of the mechanisms that influence breast cancer risk and prognosis.

Unravelling the molecular basis for regulatory T-cell plasticity and loss of function in disease

Regulatory T cells (Treg) are critical for preventing autoimmunity and curtailing responses of conventional effector T cells (Tconv). The reprogramming of T‐cell fate and function to generate Treg requires switching on and off of key gene regulatory networks, which may be initiated by a subtle shift in expression levels of specific genes. This can be achieved by intermediary regulatory processes that include microRNA and long noncoding RNA‐based regulation of gene expression. There are well‐documented microRNA profiles in Treg and Tconv, and these can operate to either reinforce or reduce expression of a specific set of target genes, including FOXP3 itself. This type of feedforward/feedback regulatory loop is normally stable in the steady state, but can alter in response to local cues or genetic risk. This may go some way to explaining T‐cell plasticity. In addition, in chronic inflammation or autoimmunity, altered Treg/Tconv function may be influenced by changes in enhancer–promoter interactions, which are highly cell type‐specific. These interactions are impacted by genetic risk based on genome‐wide association studies and may cause subtle alterations to the gene regulatory networks controlled by or controlling FOXP3 and its target genes. Recent insights into the 3D organisation of chromatin and the mapping of noncoding regulatory regions to the genes they control are shedding new light on the direct impact of genetic risk on T‐cell function and susceptibility to inflammatory and autoimmune conditions.

A functional variant rs4442975 modulating FOXA1-binding affinity does not influence the risk or progression of breast cancer in Chinese Han population

The DNA-binding protein FOXA1 has been shown to regulate nearly all estrogen receptor-chromatin interactions, thereby influencing target gene expression levels in breast cancer (BC) cells. Recently, the rs4442975 T-allele, which disrupts the recruitment of FOXA1 and interacts with the IGFBP5 promoter, was associated to BC susceptibility in a European population. We conducted a hospital-based case-control study that included 1227 cases and 1285 controls to explore the potential association between rs4442975 and BC risk in Chinese Han population, and the effect of this SNP on BC progression was also observed in cases. No significant associations between rs4442975 and BC risk were observed under any genetic models, with an odds ratio of 0.96 (95% confidence interval = 0.81-1.15) under the additive model. When stratified based on estrogen or progesterone receptor expression, smoking or drinking habits, or menopausal status, similar negative associations were observed for all subgroups. No significant associations were observed between rs4442975 and traditional progression factors such as tumor size, nodal status, distant metastasis, or TNM staging. These results reveal that rs4442975 may not confer a risk of BC occurrence or progression in the Chinese Han population, which indicates a distinct association related to genetic heterogeneity across ethnic populations.

HiCapTools: a software suite for probe design and proximity detection for targeted chromosome conformation capture applications

Summary

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.

Availability

https://github.com/sahlenlab/HiCapTools.

Contact

pelinak@kth.se.

Supplementary information

Supplementary data are available at Bioinformatics online.

Sequence-based multiscale modeling for high-throughput chromosome conformation capture (Hi-C) data analysis

In this paper, we introduce sequence-based multiscale modeling for biomolecular data analysis. We employ spectral clustering method in our modeling and reveal the difference between sequence-based global scale clustering and local scale clustering. Essentially, two types of distances, i.e., Euclidean (or spatial) distance and genomic (or sequential) distance, can be used in data clustering. Clusters from sequence-based global scale models optimize spatial distances, meaning spatially adjacent loci are more likely to be assigned into the same cluster. Sequence-based local scale models, on the other hand, result in clusters that optimize genomic distances. That is to say, in these models, sequentially adjoining loci tend to be cluster together. We propose two sequence-based multiscale models (SeqMMs) for the study of chromosome hierarchical structures, including genomic compartments and topological associated domains (TADs). We find that genomic compartments are determined only by global scale information in the Hi-C data. The removal of all the local interactions within a band region as large as 10 Mb in genomic distance has almost no significant influence on the final compartment results. Further, in TAD analysis, we find that when the sequential scale is small, a tiny variation of diagonal band region in a contact map will result in a great change in the predicted TAD boundaries. When the scale value is larger than a threshold value, the TAD boundaries become very consistent. This threshold value is highly related to TAD sizes. By the comparison of our results with those previously obtained using a spectral clustering model, we find that our method is more robust and reliable. Finally, we demonstrate that almost all TAD boundaries from both clustering methods are local minimum of a TAD summation function.

Genome-Wide Association Studies in Glioma

Since the first reports in 2009, genome-wide association studies (GWAS) have been successful in identifying germline variants associated with glioma susceptibility. In this review, we describe a chronological history of glioma GWAS, culminating in the most recent study comprising 12,496 cases and 18,190 controls. We additionally summarize associations at the 27 glioma-risk SNPs that have been reported so far. Future efforts are likely to be principally focused on assessing association of germline-risk SNPs with particular molecular subgroups of glioma, as well as investigating the functional basis of the risk loci in tumor formation. These ongoing studies will be important to maximize the impact of research into glioma susceptibility, both in terms of insight into tumor etiology as well as opportunities for clinical translation. Cancer Epidemiol Biomarkers Prev; 27(4); 418-28. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

The 4D nucleome project

The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic insights into how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental technologies will be combined with biophysical approaches to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells.

Characteristic arrangement of nucleosomes is predictive of chromatin interactions at kilobase resolution

High-throughput chromosome conformation capture (3C) technologies, such as Hi-C, have made it possible to survey 3D genome structure. However, obtaining 3D profiles at kilobase resolution at low cost remains a major challenge. Therefore, we herein present an algorithm for precise identification of chromatin interaction sites at kilobase resolution from MNase-seq data, termed chromatin interaction site detector (CISD), and a CISD-based chromatin loop predictor (CISD_loop) that predicts chromatin–chromatin interactions (CCIs) from low-resolution Hi-C data. We show that the predictions of CISD and CISD_loop overlap closely with chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) anchors and loops, respectively. The validity of CISD/CISD_loop was further supported by a 3C assay at about 5 kb resolution. Finally, we demonstrate that only modest amounts of MNase-seq and Hi-C data are sufficient to achieve ultrahigh resolution CCI maps. Our results suggest that CCIs may result in characteristic nucleosomes arrangement patterns flanking the interaction sites, and our algorithms may facilitate precise and systematic investigations of CCIs on a larger scale than hitherto have been possible.

Technical Review: A Hitchhiker's Guide to Chromosome Conformation Capture

The introduction of chromosome conformation capture (3C) technologies boosted the field of 3D-genome research and significantly enhanced the available toolset to study chromosomal architecture. 3C technologies not only offer increased resolution compared to the previously dominant cytological approaches but also allow the simultaneous study of genome-wide 3D chromatin contacts, thereby enabling a candidate-free perspective on 3D-genome architecture. Since its introduction in 2002, 3C technologies evolved rapidly and now constitute a collection of tools, each with their strengths and pitfalls with respect to specific research questions. This chapter aims at guiding 3C novices through the labyrinth of potential applications of the various family members, hopefully providing a valuable basis for choosing the appropriate strategy for different research questions.

Practical Analysis of Hi-C Data: Generating A/B Compartment Profiles

Recent advances in next-generation sequencing (NGS) and chromosome conformation capture (3C) analysis have led to the development of Hi-C, a genome-wide version of the 3C method. Hi-C has identified new levels of chromosome organization such as A/B compartments, topologically associating domains (TADs) as well as large megadomains on the inactive X chromosome, while allowing the identification of chromatin loops at the genome scale. Despite its powerfulness, Hi-C data analysis is much more involved compared to conventional NGS applications such as RNA-seq or ChIP-seq and requires many more steps. This presents a significant hurdle for those who wish to implement Hi-C technology into their laboratory. On the other hand, genomics data repository sites sometimes contain processed Hi-C data sets, allowing researchers to perform further analysis without the need for high-spec workstations and servers. In this chapter, we provide a detailed description on how to calculate A/B compartment profiles from processed Hi-C data on the autosomes and the active/inactive X chromosomes.

Intergenic disease-associated regions are abundant in novel transcripts

BACKGROUND

Genotyping of large populations through genome-wide association studies (GWAS) has successfully identified many genomic variants associated with traits or disease risk. Unexpectedly, a large proportion of GWAS single nucleotide polymorphisms (SNPs) and associated haplotype blocks are in intronic and intergenic regions, hindering their functional evaluation. While some of these risk-susceptibility regions encompass cis-regulatory sites, their transcriptional potential has never been systematically explored.

RESULTS

To detect rare tissue-specific expression, we employed the transcript-enrichment method CaptureSeq on 21 human tissues to identify 1775 multi-exonic transcripts from 561 intronic and intergenic haploblocks associated with 392 traits and diseases, covering 73.9 Mb (2.2%) of the human genome. We show that a large proportion (85%) of disease-associated haploblocks express novel multi-exonic non-coding transcripts that are tissue-specific and enriched for GWAS SNPs as well as epigenetic markers of active transcription and enhancer activity. Similarly, we captured transcriptomes from 13 melanomas, targeting nine melanoma-associated haploblocks, and characterized 31 novel melanoma-specific transcripts that include fusion proteins, novel exons and non-coding RNAs, one-third of which showed allelically imbalanced expression.

CONCLUSIONS

This resource of previously unreported transcripts in disease-associated regions ( http://gwas-captureseq.dingerlab.org ) should provide an important starting point for the translational community in search of novel biomarkers, disease mechanisms, and drug targets.

MYBL2 Is Targeted by miR-143-3p and Regulates Breast Cancer Cell Proliferation and Apoptosis

Breast cancer remains a public health issue on a global scale. The present study aimed to explore the functional role of MYB proto-oncogene like 2 (MYBL2) in breast cancer, as well as underlying mechanisms. The regulatory relationship between miR-143-3p and MYBL2 was analyzed, and the effects of dysregulation of miR-143-3p and MYBL2 on cell proliferation and apoptosis were investigated. The results showed that MYBL2 and miR-143-3p were inversely expressed in breast cancer tissues and cells: MYBL2 was highly expressed, whereas miR-143-3p was lowly expressed. MYBL2 was confirmed as a target gene of miR-143-3p. Suppression of MYBL2 inhibited proliferation and induced apoptosis of breast cancer cells, which was similar to the effects of overexpression of miR-143-3p. Our findings reveal that MYBL2 is targeted by miR-143-3p and regulates breast cancer cell proliferation and apoptosis.

HiTAD: detecting the structural and functional hierarchies of topologically associating domains from chromatin interactions

A current question in the high-order organization of chromatin is whether topologically associating domains (TADs) are distinct from other hierarchical chromatin domains. However, due to the unclear TAD definition in tradition, the structural and functional uniqueness of TAD is not well studied. In this work, we refined TAD definition by further constraining TADs to the optimal separation on global intra-chromosomal interactions. Inspired by this constraint, we developed a novel method, called HiTAD, to detect hierarchical TADs from Hi-C chromatin interactions. HiTAD performs well in domain sensitivity, replicate reproducibility and inter cell-type conservation. With a novel domain-based alignment proposed by us, we defined several types of hierarchical TAD changes which were not systematically studied previously, and subsequently used them to reveal that TADs and sub-TADs differed statistically in correlating chromosomal compartment, replication timing and gene transcription. Finally, our work also has the implication that the refinement of TAD definition could be achieved by only utilizing chromatin interactions, at least in part. HiTAD is freely available online.

Novel insights into chromosomal conformations in cancer

Exploring gene function is critical for understanding the complexity of life. DNA sequences and the three-dimensional organization of chromatin (chromosomal interactions) are considered enigmatic factors underlying gene function, and interactions between two distant fragments can regulate transactivation activity via mediator proteins. Thus, a series of chromosome conformation capture techniques have been developed, including chromosome conformation capture (3C), circular chromosome conformation capture (4C), chromosome conformation capture carbon copy (5C), and high-resolution chromosome conformation capture (Hi-C). The application of these techniques has expanded to various fields, but cancer remains one of the major topics. Interactions mediated by proteins or long noncoding RNAs (lncRNAs) are typically found using 4C-sequencing and chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). Currently, Hi-C is used to identify chromatin loops between cancer risk-associated single-nucleotide polymorphisms (SNPs) found by genome-wide association studies (GWAS) and their target genes. Chromosomal conformations are responsible for altered gene regulation through several typical mechanisms and contribute to the biological behavior and malignancy of different tumors, particularly prostate cancer, breast cancer and hematologic neoplasms. Moreover, different subtypes may exhibit different 3D-chromosomal conformations. Thus, C-tech can be used to help diagnose cancer subtypes and alleviate cancer progression by destroying specific chromosomal conformations. Here, we review the fundamentals and improvements in chromosome conformation capture techniques and their clinical applications in cancer to provide insight for future research.

A cautionary note on the use of chromosome conformation capture in plants

BACKGROUND

The chromosome conformation capture (3C) technique is a method to study chromatin interactions at specific genomic loci. Initially established for yeast the 3C technique has been adapted to plants in recent years in order to study chromatin interactions and their role in transcriptional gene regulation. As the plant scientific community continues to implement this technology, a discussion on critical controls, validations steps and interpretation of 3C data is essential to fully benefit from 3C in plants.

RESULTS

Here we assess the reliability and robustness of the 3C technique for the detection of chromatin interactions in Arabidopsis. As a case study, we applied this methodology to the genomic locus of a floral integrator gene SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1), and demonstrate the need of several controls and standard validation steps to allow a meaningful interpretation of 3C data. The intricacies of this promising but challenging technique are discussed in depth.

CONCLUSIONS

The 3C technique offers an interesting opportunity to study chromatin interactions at a resolution infeasible by microscopy. However, for interpretation of 3C interaction data and identification of true interactions, 3C technology demands a stringent experimental setup and extreme caution.

Genome-wide association studies of cancer: current insights and future perspectives

Genome-wide association studies (GWAS) provide an agnostic approach for investigating the genetic basis of complex diseases. In oncology, GWAS of nearly all common malignancies have been performed, and over 450 genetic variants associated with increased risks have been identified. As well as revealing novel pathways important in carcinogenesis, these studies have shown that common genetic variation contributes substantially to the heritable risk of many common cancers. The clinical application of GWAS is starting to provide opportunities for drug discovery and repositioning as well as for cancer prevention. However, deciphering the functional and biological basis of associations is challenging and is in part a barrier to fully unlocking the potential of GWAS.

The Three-Dimensional Organization of Mammalian Genomes

Animal development depends on not only the linear genome sequence that embeds millions of cis-regulatory elements, but also the three-dimensional (3D) chromatin architecture that orchestrates the interplay between cis-regulatory elements and their target genes. Compared to our knowledge of the cis-regulatory sequences, the understanding of the 3D genome organization in human and other eukaryotes is still limited. Recent advances in technologies to map the 3D genome architecture have greatly accelerated the pace of discovery. Here, we review emerging concepts of chromatin organization in mammalian cells, discuss the dynamics of chromatin conformation during development, and highlight important roles for chromatin organization in cancer and other human diseases.

Three-dimensional genome architecture and emerging technologies: looping in disease

Genome compaction is a universal feature of cells and has emerged as a global regulator of gene expression. Compaction is maintained by a multitude of architectural proteins, long non-coding RNAs (lncRNAs), and regulatory DNA. Each component comprises interlinked regulatory circuits that organize the genome in three-dimensional (3D) space to manage gene expression. In this review, we update the current state of 3D genome catalogues and focus on how recent technological advances in 3D genomics are leading to an enhanced understanding of disease mechanisms. We highlight the use of genome-wide chromatin conformation capture (Hi-C) coupled with oligonucleotide capture technology (capture Hi-C) to map interactions between gene promoters and distal regulatory elements such as enhancers that are enriched for disease variants from genome-wide association studies (GWASs). We discuss how aberrations in architectural units are associated with various pathological outcomes, and explore how recent advances in genome and epigenome editing show great promise for a systematic understanding of complex genetic disorders. Our growing understanding of 3D genome architecture—coupled with the ability to engineer changes in it—may create novel therapeutic opportunities.

Chromosome contacts in activated T cells identify autoimmune disease candidate genes

Background

Autoimmune disease-associated variants are preferentially found in regulatory regions in immune cells, particularly CD4⁺ T cells. Linking such regulatory regions to gene promoters in disease-relevant cell contexts facilitates identification of candidate disease genes.

Results

Within 4 h, activation of CD4⁺ T cells invokes changes in histone modifications and enhancer RNA transcription that correspond to altered expression of the interacting genes identified by promoter capture Hi-C. By integrating promoter capture Hi-C data with genetic associations for five autoimmune diseases, we prioritised 245 candidate genes with a median distance from peak signal to prioritised gene of 153 kb. Just under half (108/245) prioritised genes related to activation-sensitive interactions. This included IL2RA, where allele-specific expression analyses were consistent with its interaction-mediated regulation, illustrating the utility of the approach.

Conclusions

Our systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1285-0) contains supplementary material, which is available to authorized users.

Genome organization: connecting the developmental origins of disease and genetic variation

An adverse early life environment can increase the risk of metabolic and other disorders later in life. Genetic variation can modify an individual's susceptibility to these environmental challenges. These gene by environment interactions are important, but difficult, to dissect. The nucleus is the primary organelle where environmental responses impact directly on the genetic variants within the genome, resulting in changes to the biology of the genome and ultimately the phenotype. Understanding genome biology requires the integration of the linear DNA sequence, epigenetic modifications and nuclear proteins that are present within the nucleus. The interactions between these layers of information may be captured in the emergent spatial genome organization. As such genome organization represents a key research area for decoding the role of genetic variation in the Developmental Origins of Health and Disease.

Activation of the alpha-globin gene expression correlates with dramatic upregulation of nearby non-globin genes and changes in local and large-scale chromatin spatial structure

BACKGROUND

In homeotherms, the alpha-globin gene clusters are located within permanently open genome regions enriched in housekeeping genes. Terminal erythroid differentiation results in dramatic upregulation of alpha-globin genes making their expression comparable to the rRNA transcriptional output. Little is known about the influence of the erythroid-specific alpha-globin gene transcription outburst on adjacent, widely expressed genes and large-scale chromatin organization. Here, we have analyzed the total transcription output, the overall chromatin contact profile, and CTCF binding within the 2.7 Mb segment of chicken chromosome 14 harboring the alpha-globin gene cluster in cultured lymphoid cells and cultured erythroid cells before and after induction of terminal erythroid differentiation.

RESULTS

We found that, similarly to mammalian genome, the chicken genomes is organized in TADs and compartments. Full activation of the alpha-globin gene transcription in differentiated erythroid cells is correlated with upregulation of several adjacent housekeeping genes and the emergence of abundant intergenic transcription. An extended chromosome region encompassing the alpha-globin cluster becomes significantly decompacted in differentiated erythroid cells, and depleted in CTCF binding and CTCF-anchored chromatin loops, while the sub-TAD harboring alpha-globin gene cluster and the upstream major regulatory element (MRE) becomes highly enriched with chromatin interactions as compared to lymphoid and proliferating erythroid cells. The alpha-globin gene domain and the neighboring loci reside within the A-like chromatin compartment in both lymphoid and erythroid cells and become further segregated from the upstream gene desert upon terminal erythroid differentiation.

CONCLUSIONS

Our findings demonstrate that the effects of tissue-specific transcription activation are not restricted to the host genomic locus but affect the overall chromatin structure and transcriptional output of the encompassing topologically associating domain.

Challenges and progress in interpretation of non-coding genetic variants associated with human disease

Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.

Inhibition of bromodomain-containing protein 9 for the prevention of epigenetically-defined drug resistance

Bromodomain-containing protein 9 (BRD9), an epigenetic "reader" of acetylated lysines on post-translationally modified histone proteins, is upregulated in multiple cancer cell lines. To assess the functional role of BRD9 in cancer cell lines, we identified a small-molecule inhibitor of the BRD9 bromodomain. Starting from a pyrrolopyridone lead, we used structure-based drug design to identify a potent and highly selective in vitro tool compound 11, (GNE-375). While this compound showed minimal effects in cell viability or gene expression assays, it showed remarkable potency in preventing the emergence of a drug tolerant population in EGFR mutant PC9 cells treated with EGFR inhibitors. Such tolerance has been linked to an altered epigenetic state, and 11 decreased BRD9 binding to chromatin, and this was associated with decreased expression of ALDH1A1, a gene previously shown to be important in drug tolerance. BRD9 inhibitors may therefore show utility in preventing epigenetically-defined drug resistance.

RNA-Seq based genome-wide analysis reveals loss of inter-chromosomal regulation in breast cancer

Breast cancer is a complex heterogeneous disease. Common hallmark features of cancer can be found. Their origin may be traced back to their intricate relationships governing regulatory programs during the development of this disease. To unveil distinctive features of the transcriptional regulation program in breast cancer, a pipeline for RNA-seq analysis in 780 breast cancer and 101 healthy breast samples, at gene expression and network level, was implemented. Inter-chromosomal relationships between genes resulted strikingly scarce in a cancer network, in comparison to its healthy counterpart. We suggest that inter-chromosomal regulation loss may be a novel feature in breast cancer. Additional evidence was obtained by independent validation in microarray and Hi-C data as well as supplementary computational analyses. Functional analysis showed upregulation in processes related to cell cycle and division; while migration, adhesion and cell-to-cell communication, were downregulated. Both the BRCA1 DNA repairing signalling and the Estrogen-mediated G1/S phase entry pathways were found upregulated. In addition, a synergistic underexpression of the γ-protocadherin complex, located at Chr5q31 is also shown. This region has previously been reported to be hypermethylated in breast cancer. These findings altogether provide further evidence for the central role of transcriptional regulatory programs in shaping malignant phenotypes.

Capturing genomic relationships that matter

There is a strong interrelationship within the cell nucleus between form and function of the genome. This connection is exhibited across multiple hierarchies, ranging from grand-scale positioning of chromosomes and their intersection with specific nuclear functional activities, the segregation of chromosome structure into distinct domains and long-range regulatory contacts that drive spatial and temporal expression patterns of genes. Fifteen years ago, the development of the chromosome conformation capture method placed the nature of specific, long-range regulatory interactions under scrutiny. However, its development and integration with next-generation sequencing technologies has greatly expanded the breadth and scope of what is detected. The sheer scale of data offered by these important advances has come with new and challenging bottlenecks that are both experimental and bioinformatical. Here, we discuss the recent and prospective development and implementation of new methodologies and analytical tools that are allowing an in-depth, yet focussed characterisation of genomic contacts that are associated with functional activities in the nucleus.

Disruption of the 3D cancer genome blueprint

Recent advances in chromosome conformation capture technologies are improving the current appreciation of how 3D genome architecture affects its function in different cell types and disease. Long-range chromatin interactions are organized into topologically associated domains, which are known to play a role in constraining gene expression patterns. However, in cancer cells there are alterations in the 3D genome structure, which impacts on gene regulation. Disruption of topologically associated domains architecture can result in alterations in chromatin interactions that bring new regulatory elements and genes together, leading to altered expression of oncogenes and tumor suppressor genes. Here, we discuss the impact of genetic and epigenetic changes in cancer and how this affects the spatial organization of chromatin. Understanding how disruptions to the 3D architecture contribute to the cancer genome will provide novel insights into the principles of epigenetic gene regulation in cancer and mechanisms responsible for cancer associated mutations and rearrangements.

A pathway-centric view of spatial proximity in the 3D nucleome across cell lines

In various contexts, spatially proximal genes have been shown to be functionally related. However, the extent to which spatial proximity of genes in a pathway contributes to the pathway's context-specific activity is not known. Leveraging Hi-C data in six human cell-lines, we show that spatial proximity of genes in a pathway is highly correlated with the pathway's context-specific expression and function. Furthermore, spatial proximity of pathway genes correlates with interactions of their protein products, and the specific pathway genes that are proximal to one another tend to occupy higher levels in the regulatory hierarchy. In addition to intra-pathway proximity, related pathways are spatially proximal to one another and housekeeping-genes tend to be proximal to several other pathways suggesting their coordinating role. Substantially extending previous works, our study reveals a pathway-centric organization of 3D-nucleome, whereby, functionally related interacting driver genes tend to be in spatial-proximity in a context-specific manner.

Genome-wide mapping and analysis of chromosome architecture

Chromosomes of eukaryotes adopt highly dynamic and complex hierarchical structures in the nucleus. The three-dimensional (3D) organization of chromosomes profoundly affects DNA replication, transcription and the repair of DNA damage. Thus, a thorough understanding of nuclear architecture is fundamental to the study of nuclear processes in eukaryotic cells. Recent years have seen rapid proliferation of technologies to investigate genome organization and function. Here, we review experimental and computational methodologies for 3D genome analysis, with special focus on recent advances in high-throughput chromatin conformation capture (3C) techniques and data analysis.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

A Compendium of Chromatin Contact Maps Reveals Spatially Active Regions in the Human Genome

The three-dimensional configuration of DNA is integral to all nuclear processes in eukaryotes, yet our knowledge of the chromosome architecture is still limited. Genome-wide chromosome conformation capture studies have uncovered features of chromatin organization in cultured cells, but genome architecture in human tissues has yet to be explored. Here, we report the most comprehensive survey to date of chromatin organization in human tissues. Through integrative analysis of chromatin contact maps in 21 primary human tissues and cell types, we find topologically associating domains highly conserved in different tissues. We also discover genomic regions that exhibit unusually high levels of local chromatin interactions. These frequently interacting regions (FIREs) are enriched for super-enhancers and are near tissue-specifically expressed genes. They display strong tissue-specificity in local chromatin interactions. Additionally, FIRE formation is partially dependent on CTCF and the Cohesin complex. We further show that FIREs can help annotate the function of non-coding sequence variants.

Capture Hi-C identifies a novel causal gene, IL20RA, in the pan-autoimmune genetic susceptibility region 6q23

BACKGROUND

The identification of causal genes from genome-wide association studies (GWAS) is the next important step for the translation of genetic findings into biologically meaningful mechanisms of disease and potential therapeutic targets. Using novel chromatin interaction detection techniques and allele specific assays in T and B cell lines, we provide compelling evidence that redefines causal genes at the 6q23 locus, one of the most important loci that confers autoimmunity risk.

RESULTS

Although the function of disease-associated non-coding single nucleotide polymorphisms (SNPs) at 6q23 is unknown, the association is generally assigned to TNFAIP3, the closest gene. However, the DNA fragment containing the associated SNPs interacts through chromatin looping not only with TNFAIP3, but also with IL20RA, located 680 kb upstream. The risk allele of the most likely causal SNP, rs6927172, is correlated with both a higher frequency of interactions and increased expression of IL20RA, along with a stronger binding of both the NFκB transcription factor and chromatin marks characteristic of active enhancers in T-cells.

CONCLUSIONS

Our results highlight the importance of gene assignment for translating GWAS findings into biologically meaningful mechanisms of disease and potential therapeutic targets; indeed, monoclonal antibody therapy targeting IL-20 is effective in the treatment of rheumatoid arthritis and psoriasis, both with strong GWAS associations to this region.

Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21

Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88x10 -15), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22x10 -9) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70x10 -8). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 ( NR5A2), chr8q24.21 ( MYC) and chr5p15.33 ( CLPTM1L- TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal ( n = 10) and tumor ( n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7x10 -8). This finding was validated in a second set of paired ( n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5x10 -4-2.0x10 -3). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology.

An intergenic risk locus containing an enhancer deletion in 2q35 modulates breast cancer risk by deregulating IGFBP5 expression

Breast cancer is the most diagnosed malignancy and the second leading cause of cancer mortality in females. Previous association studies have identified variants on 2q35 associated with the risk of breast cancer. To identify functional susceptibility loci for breast cancer, we interrogated the 2q35 gene desert for chromatin architecture and functional variation correlated with gene expression. We report a novel intergenic breast cancer risk locus containing an enhancer copy number variation (enCNV; deletion) located approximately 400Kb upstream to IGFBP5, which overlaps an intergenic ERα-bound enhancer that loops to the IGFBP5 promoter. The enCNV is correlated with modified ERα binding and monoallelic-repression of IGFBP5 following oestrogen treatment. We investigated the association of enCNV genotype with breast cancer in 1,182 cases and 1,362 controls, and replicate our findings in an independent set of 62,533 cases and 60,966 controls from 41 case control studies and 11 GWAS. We report a dose-dependent inverse association of 2q35 enCNV genotype (percopy OR = 0.68 95%CI 0.55-0.83, P = 0.0002; replication OR = 0.77 95% CI 0.73-0.82, P = 2.1 × 10-19) and identify 13 additional linked variants (r2 > 0.8) in the 20Kb linkage block containing the enCNV (P = 3.2 × 10-15 - 5.6 × 10-17). These associations were independent of previously reported 2q35 variants, rs13387042/rs4442975 and rs16857609, and were stronger for ER-positive than ER-negative disease. Together, these results suggest that 2q35 breast cancer risk loci may be mediating their effect through IGFBP5.

Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity

BACKGROUND

Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity, to integrate the epigenomic landscape of a specific cell type with its chromatin interaction network and thus investigate which proteins or chromatin marks mediate genomic contacts.

RESULTS

We use high-resolution promoter capture Hi-C and Hi-Cap data as well as ChIA-PET data from mouse embryonic stem cells to investigate promoter-centered chromatin interaction networks and calculate the presence of specific epigenomic features in the chromatin fragments constituting the nodes of the network. We estimate the association of these features with the topology of four chromatin interaction networks and identify features localized in connected areas of the network. Polycomb group proteins and associated histone marks are the features with the highest chromatin assortativity in promoter-centered networks. We then ask which features distinguish contacts amongst promoters from contacts between promoters and other genomic elements. We observe higher chromatin assortativity of the actively elongating form of RNA polymerase 2 (RNAPII) compared with inactive forms only in interactions between promoters and other elements.

CONCLUSIONS

Contacts among promoters and between promoters and other elements have different characteristic epigenomic features. We identify a possible role for the elongating form of RNAPII in mediating interactions among promoters, enhancers, and transcribed gene bodies. Our approach facilitates the study of multiple genome-wide epigenomic profiles, considering network topology and allowing the comparison of chromatin interaction networks.

CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data

Capture Hi-C (CHi-C) is a method for profiling chromosomal interactions involving targeted regions of interest, such as gene promoters, globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments. We implement these procedures in CHiCAGO ( http://regulatorygenomicsgroup.org/chicago ), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs.

IDH-mutant glioma specific association of rs55705857 located at 8q24.21 involves MYC deregulation

The single nucleotide polymorphism rs55705857, located in a non-coding but evolutionarily conserved region at 8q24.21, is strongly associated with IDH-mutant glioma development and was suggested to be a causal variant. However, the molecular mechanism underlying this association has remained unknown. With a case control study in 285 gliomas, 316 healthy controls, 380 systemic cancers, 31 other CNS-tumors, and 120 IDH-mutant cartilaginous tumors, we identified that the association was specific to IDH-mutant gliomas. Odds-ratios were 9.25 (5.17–16.52; 95% CI) for IDH-mutated gliomas and 12.85 (5.94–27.83; 95% CI) for IDH-mutated, 1p/19q co-deleted gliomas. Decreasing strength with increasing anaplasia implied a modulatory effect. No somatic mutations were noted at this locus in 114 blood-tumor pairs, nor was there a copy number difference between risk-allele and only-ancestral allele carriers. CCDC26 RNA-expression was rare and not different between the two groups. There were only minor subtype-specific differences in common glioma driver genes. RNA sequencing and LC-MS/MS comparisons pointed to significantly altered MYC-signaling. Baseline enhancer activity of the conserved region specifically on the MYC promoter and its further positive modulation by the SNP risk-allele was shown in vitro. Our findings implicate MYC deregulation as the underlying cause of the observed association.

Active and Inactive Enhancers Cooperate to Exert Localized and Long-Range Control of Gene Regulation

V(D)J recombination relies on the presence of proximal enhancers that activate the antigen receptor (AgR) loci in a lineage- and stage-specific manner. Unexpectedly, we find that both active and inactive AgR enhancers cooperate to disseminate their effects in a localized and long-range manner. Here, we demonstrate the importance of short-range contacts between active enhancers that constitute an Igk super-enhancer in B cells. Deletion of one element reduces the interaction frequency between other enhancers in the hub, which compromises the transcriptional output of each component. Furthermore, we establish that, in T cells, long-range contact and cooperation between the inactive Igk enhancer MiEκ and the active Tcrb enhancer Eβ alters enrichment of CBFβ binding in a manner that impacts Tcrb recombination. These findings underline the complexities of enhancer regulation and point to a role for localized and long-range enhancer-sharing between active and inactive elements in lineage- and stage-specific control.

Genetic susceptibility to rheumatoid arthritis and its implications for novel drug discovery

INTRODUCTION

Over 100 susceptibility loci have now been identified for rheumatoid arthritis (RA), several of which are already the targets of approved RA therapies providing proof of concept for the use of genetics in novel drug development for RA. Determining how these loci contribute to disease will be key to elucidating the mechanisms driving disease development, which has the potential for major impact on therapeutic development.

AREAS COVERED

Here the authors review the use of genetics in drug discovery, including the use of 'omics' data to prioritise potential drug targets at susceptibility loci using RA as an exemplar. They discuss the current state of RA genetics its impact on stratified medicine, and how the findings from RA genetics studies can be used to inform drug discovery.

EXPERT OPINION

It is anticipated that functional characterisation of disease variants will provide biological validation of a gene as a drug target, providing safer targets, with an increased likelihood of efficacy. In the future, techniques such as genome editing may represent a plausible option for RA therapy. Technologies such as genome-wide chromatin conformation capture Hi-C and CRISPR will be crucial to inform our understanding of how diseases develop and in developing new treatments.

4D nucleomes in single cells: what can computational modeling reveal about spatial chromatin conformation?

Genome-wide sequencing technologies enable investigations of the structural properties of the genome in various spatial dimensions. Here, we review computational techniques developed to model the three-dimensional genome in single cells versus ensembles of cells and assess their underlying assumptions. We further address approaches to study the spatio-temporal aspects of genome organization from single-cell data.