ChIA-PET analysis of transcriptional chromatin interactions

Genome structural dynamics: insights from Gaussian network analysis of Hi-C data

Characterization of the spatiotemporal properties of the chromatin is essential to gaining insights into the physical bases of gene co-expression, transcriptional regulation and epigenetic modifications. The Gaussian network model (GNM) has proven in recent work to serve as a useful tool for modeling chromatin structural dynamics, using as input high-throughput chromosome conformation capture data. We focus here on the exploration of the collective dynamics of chromosomal structures at hierarchical levels of resolution, from single gene loci to topologically associating domains or entire chromosomes. The GNM permits us to identify long-range interactions between gene loci, shedding light on the role of cross-correlations between distal regions of the chromosomes in regulating gene expression. Notably, GNM analysis performed across diverse cell lines highlights the conservation of the global/cooperative movements of the chromatin across different types of cells. Variations driven by localized couplings between genomic loci, on the other hand, underlie cell differentiation, underscoring the significance of the four-dimensional properties of the genome in defining cellular identity. Finally, we demonstrate the close relation between the cell type-dependent mobility profiles of gene loci and their gene expression patterns, providing a clear demonstration of the role of chromosomal 4D features in defining cell-specific differential expression of genes.

Epigenetic regulation by TET1 in gene-environmental interactions influencing susceptibility to congenital malformations

The etiology of neural tube defects (NTDs) involves complex gene-environmental interactions. Folic acid (FA) prevents NTDs, but the mechanisms remain poorly understood and at least 30% of human NTDs resist the beneficial effects of FA supplementation. Here, we identify the DNA demethylase TET1 as a nexus of folate-dependent one-carbon metabolism and genetic risk factors post-neural tube closure. We determine that cranial NTDs in Tet1 -/- embryos occur at two to three times higher penetrance in genetically heterogeneous than in homogeneous genetic backgrounds, suggesting a strong impact of genetic modifiers on phenotypic expression. Quantitative trait locus mapping identified a strong NTD risk locus in the 129S6 strain, which harbors missense and modifier variants at genes implicated in intracellular endocytic trafficking and developmental signaling. NTDs across Tet1 -/- strains are resistant to FA supplementation. However, both excess and depleted maternal FA diets modify the impact of Tet1 loss on offspring DNA methylation primarily at neurodevelopmental loci. FA deficiency reveals susceptibility to NTD and other structural brain defects due to haploinsufficiency of Tet1. In contrast, excess FA in Tet1 -/- embryos drives promoter DNA hypermethylation and reduced expression of multiple membrane solute transporters, including a FA transporter, accompanied by loss of phospholipid metabolites. Overall, our study unravels interactions between modified maternal FA status, Tet1 gene dosage and genetic backgrounds that impact neurotransmitter functions, cellular methylation and individual susceptibilities to congenital malformations, further implicating that epigenetic dysregulation may underlie NTDs resistant to FA supplementation.

Epigenome editing in cancer: Advances and challenges for potential therapeutic options

Cancers are diseases caused by genetic and non-genetic environmental factors. Epigenetic alterations, some attributed to non-genetic factors, can lead to cancer development. Epigenetic changes can occur in tumor suppressors or oncogenes, or they may contribute to global cell state changes, making cells abnormal. Recent advances in gene editing technology show potential for cancer treatment. Herein, we will discuss our current knowledge of epigenetic alterations occurring in cancer and epigenetic editing technologies that can be applied to developing therapeutic options.

The dynamic role of cohesin in maintaining human genome architecture

Recent advances in genomic and imaging techniques have revealed the complex manner of organizing billions of base pairs of DNA necessary for maintaining their functionality and ensuring the proper expression of genetic information. The SMC proteins and cohesin complex primarily contribute to forming higher-order chromatin structures, such as chromosomal territories, compartments, topologically associating domains (TADs) and chromatin loops anchored by CCCTC-binding factor (CTCF) protein or other genome organizers. Cohesin plays a fundamental role in chromatin organization, gene expression and regulation. This review aims to describe the current understanding of the dynamic nature of the cohesin-DNA complex and its dependence on cohesin for genome maintenance. We discuss the current 3C technique and numerous bioinformatics pipelines used to comprehend structural genomics and epigenetics focusing on the analysis of Cohesin-centred interactions. We also incorporate our present comprehension of Loop Extrusion (LE) and insights from stochastic modelling.

Enhanced performance of gene expression predictive models with protein-mediated spatial chromatin interactions

There have been multiple attempts to predict the expression of the genes based on the sequence, epigenetics, and various other factors. To improve those predictions, we have decided to investigate adding protein-specific 3D interactions that play a significant role in the condensation of the chromatin structure in the cell nucleus. To achieve this, we have used the architecture of one of the state-of-the-art algorithms, ExPecto, and investigated the changes in the model metrics upon adding the spatially relevant data. We have used ChIA-PET interactions that are mediated by cohesin (24 cell lines), CTCF (4 cell lines), and RNAPOL2 (4 cell lines). As the output of the study, we have developed the Spatial Gene Expression (SpEx) algorithm that shows statistically significant improvements in most cell lines. We have compared ourselves to the baseline ExPecto model, which obtained a 0.82 Spearman's rank correlation coefficient (SCC) score, and 0.85, which is reported by newer Enformer were able to obtain the average correlation score of 0.83. However, in some cases (e.g. RNAPOL2 on GM12878), our improvement reached 0.04, and in some cases (e.g. RNAPOL2 on H1), we reached an SCC of 0.86.

Regulatory architecture of housekeeping genes is driven by promoter assemblies

Genes that are key to cell identity are generally regulated by cell-type-specific enhancer elements bound by transcription factors, some of which facilitate looping to distant gene promoters. In contrast, genes that encode housekeeping functions, whose regulation is essential for normal cell metabolism and growth, generally lack interactions with distal enhancers. We find that Ronin (Thap11) assembles multiple promoters of housekeeping and metabolic genes to regulate gene expression. This behavior is analogous to how enhancers are brought together with promoters to regulate cell identity genes. Thus, Ronin-dependent promoter assemblies provide a mechanism to explain why housekeeping genes can forgo distal enhancer elements and why Ronin is important for cellular metabolism and growth control. We propose that clustering of regulatory elements is a mechanism common to cell identity and housekeeping genes but is accomplished by different factors binding distinct control elements to establish enhancer-promoter or promoter-promoter interactions, respectively.

Enhanced performance of gene expression predictive models with protein-mediated spatial chromatin interactions

There have been multiple attempts to predict the expression of the genes based on the sequence, epigenetics, and various other factors. To improve those predictions, we have decided to investigate adding protein-specific 3D interactions that play a major role in the compensation of the chromatin structure in the cell nucleus. To achieve this, we have used the architecture of one of the state-of-the-art algorithms, ExPecto (J. Zhou et al., 2018), and investigated the changes in the model metrics upon adding the spatially relevant data. We have used ChIA-PET interactions that are mediated by cohesin (24 cell lines), CTCF (4 cell lines), and RNAPOL2 (4 cell lines). As the output of the study, we have developed the Spatial Gene Expression (SpEx) algorithm that shows statistically significant improvements in most cell lines.

Human 5-lipoxygenase regulates transcription by association to euchromatin

Human 5-lipoxygenase (5-LO) is the key enzyme of leukotriene biosynthesis, mostly expressed in leukocytes and thus a crucial component of the innate immune system. In this study, we show that 5-LO, besides its canonical function as an arachidonic acid metabolizing enzyme, is a regulator of gene expression associated with euchromatin. By Crispr-Cas9-mediated 5-LO knockout (KO) in MonoMac6 (MM6) cells and subsequent RNA-Seq analysis, we identified 5-LO regulated genes which could be clustered to immune/defense response, cell adhesion, transcription and growth/developmental processes. Analysis of differentially expressed genes (DEG) identified cyclooxygenase-2 (COX2, PTGS2) and kynureninase (KYNU) as strongly regulated 5-LO target genes. 5-LO knockout affected MM6 cell adhesion and tryptophan metabolism via inhibition of the degradation of the immunoregulator kynurenine. By subsequent FAIRE-Seq and 5-LO ChIP-Seq analyses, we found an association of 5-LO with euchromatin, with prominent 5-LO binding to promoter regions in actively transcribed genes. By enrichment analysis of the ChIP-Seq results, we identified potential 5-LO interaction partners. Furthermore, 5-LO ChIP-Seq peaks resemble patterns of H3K27ac histone marks, suggesting that 5-LO recruitment mainly takes place at acetylated histones. In summary, we demonstrate a noncanonical function of 5-LO as transcriptional regulator in monocytic cells.

Whole-genome methods to define DNA and histone accessibility and long-range interactions in chromatin

Defining the genome-wide chromatin landscape has been a goal of experimentalists for decades. Here we review highlights of these efforts, from seminal experiments showing discontinuities in chromatin structure related to gene activation to extensions of these methods elucidating general features of chromatin related to gene states by exploiting deep sequencing methods. We also review chromatin conformational capture methods to identify patterns in long-range interactions between genomic loci.

Key transcription factors mediating cocaine-induced plasticity in the nucleus accumbens

Repeated cocaine use induces coordinated changes in gene expression that drive plasticity in the nucleus accumbens (NAc), an important component of the brain's reward circuitry, and promote the development of maladaptive, addiction-like behaviors. Studies on the molecular basis of cocaine action identify transcription factors, a class of proteins that bind to specific DNA sequences and regulate transcription, as critical mediators of this cocaine-induced plasticity. Early methods to identify and study transcription factors involved in addiction pathophysiology primarily relied on quantifying the expression of candidate genes in bulk brain tissue after chronic cocaine treatment, as well as conventional overexpression and knockdown techniques. More recently, advances in next generation sequencing, bioinformatics, cell-type-specific targeting, and locus-specific neuroepigenomic editing offer a more powerful, unbiased toolbox to identify the most important transcription factors that drive drug-induced plasticity and to causally define their downstream molecular mechanisms. Here, we synthesize the literature on transcription factors mediating cocaine action in the NAc, discuss the advancements and remaining limitations of current experimental approaches, and emphasize recent work leveraging bioinformatic tools and neuroepigenomic editing to study transcription factors involved in cocaine addiction.

Assessing Specific Networks of Chromatin Interactions with HiChIP

The introduction of chromosome conformation capture (3C)-based technologies coupled with next-generation sequencing have significantly advanced our understanding of how the genetic material is organized within the eukaryotic nucleus. Three-dimensional (3D) genomic organization occurs at hierarchical levels, ranging from chromosome territories and subnuclear compartments to smaller self-associated domains and fine-scale chromatin interactions. The latter can be further categorized into different subtypes, such as structural or regulatory, based either on their presumed functionality and/or the factors that mediate their formation. Various enrichment strategies coupled with 3C-based technologies have been developed to prospectively isolate and quantify chromatin interactions around regions occupied by specific proteins or marks of interest. These approaches not only enable high-resolution characterization of the selected chromatin contacts at a cost-effective manner, but also offer important biological insights into their organizational principles and regulatory function. In this chapter, we will focus on the recently developed HiChIP technology with an emphasis on the discovery of putative active enhancers and promoter interactions in cell types of interest. We will describe the specific steps for designing, performing and analyzing successful HiChIP experiments as well as important limitations and considerations.

SPRITE: a genome-wide method for mapping higher-order 3D interactions in the nucleus using combinatorial split-and-pool barcoding

A fundamental question in gene regulation is how cell-type-specific gene expression is influenced by the packaging of DNA within the nucleus of each cell. We recently developed Split-Pool Recognition of Interactions by Tag Extension (SPRITE), which enables mapping of higher-order interactions within the nucleus. SPRITE works by cross-linking interacting DNA, RNA and protein molecules and then mapping DNA-DNA spatial arrangements through an iterative split-and-pool barcoding method. All DNA molecules within a cross-linked complex are barcoded by repeatedly splitting complexes across a 96-well plate, ligating molecules with a unique tag sequence, and pooling all complexes into a single well before repeating the tagging. Because all molecules in a cross-linked complex are covalently attached, they will sort together throughout each round of split-and-pool and will obtain the same series of SPRITE tags, which we refer to as a barcode. The DNA fragments and their associated barcodes are sequenced, and all reads sharing identical barcodes are matched to reconstruct interactions. SPRITE accurately maps pairwise DNA interactions within the nucleus and measures higher-order spatial contacts occurring among up to thousands of simultaneously interacting molecules. Here, we provide a detailed protocol for the experimental steps of SPRITE, including a video ( https://youtu.be/6SdWkBxQGlg ). Furthermore, we provide an automated computational pipeline available on GitHub that allows experimenters to seamlessly generate SPRITE interaction matrices starting with raw fastq files. The protocol takes ~5 d from cell cross-linking to high-throughput sequencing for the experimental steps and 1 d for data processing.

A Comprehensive Toolbox to Analyze Enhancer-Promoter Functions

Knowledge in gene transcription and chromatin regulation has been intensely studied for decades, but thanks to next-generation sequencing (NGS) techniques there has been a major leap forward in the last few years. Historically, identification of specific enhancer elements has led to the identification of master transcription factors (TFs) in the 1990s. Genetic and biochemical experiments have identified the key regulators controlling RNA polymerase II (RNAPII) transcription and structurally analyses have elucidated detailed mechanisms. NGS and the development of chromatin immunoprecipitation (ChIP) have accelerated the gain of knowledge in the recent years. By now, we have a dazzling wealth of techniques that are currently used to put gene expression into a genome-wide context. This book is an attempt to assemble useful protocols for many researchers within and nearby research areas. In general, these innovative techniques focus on enhancer and promoter studies. The techniques should also be of interest for related fields such as DNA repair and replication.

Hi-CO: 3D genome structure analysis with nucleosome resolution

The nucleosome is the basic organizational unit of the genome. The folding structure of nucleosomes is closely related to genome functions, and has been reported to be in dynamic interplay with binding of various nuclear proteins to genomic loci. Here, we describe our high-throughput chromosome conformation capture with nucleosome orientation (Hi-CO) technology to derive 3D nucleosome positions with their orientations at every genomic locus in the nucleus. This technology consists of an experimental procedure for nucleosome proximity analysis and a computational procedure for 3D modeling. The experimental procedure is based on an improved method of high-throughput chromosome conformation capture (Hi-C) analysis. Whereas conventional Hi-C allows spatial proximity analysis among genomic loci with 1-10 kbp resolution, our Hi-CO allows proximity analysis among DNA entry or exit points at every nucleosome locus. This analysis is realized by carrying out ligations among the entry/exit points in every nucleosome in a micrococcal-nuclease-fragmented genome, and by quantifying frequencies of ligation products with next-generation sequencing. Our protocol has enabled this analysis by cleanly excluding unwanted non-ligation products that are abundant owing to the frequent genome fragmentation by micrococcal nuclease. The computational procedure is based on simulated annealing-molecular dynamics, which allows determination of optimized 3D positions and orientations of every nucleosome that satisfies the proximity ligation data sufficiently well. Typically, examination of the Saccharomyces cerevisiae genome with 130 million sequencing reads facilitates analysis of a total of 66,360 nucleosome loci with 6.8 nm resolution. The technique requires 2-3 weeks for sequencing library preparation and 2 weeks for simulation.

A hierarchical regulatory network analysis of the vitamin D induced transcriptome reveals novel regulators and complete VDR dependency in monocytes

The transcription factor vitamin D receptor (VDR) is the high affinity nuclear target of the biologically active form of vitamin D₃ (1,25(OH)₂D₃). In order to identify pure genomic transcriptional effects of 1,25(OH)₂D₃, we used VDR cistrome, transcriptome and open chromatin data, obtained from the human monocytic cell line THP-1, for a novel hierarchical analysis applying three bioinformatics approaches. We predicted 75.6% of all early 1,25(OH)₂D₃-responding (2.5 or 4 h) and 57.4% of the late differentially expressed genes (24 h) to be primary VDR target genes. VDR knockout led to a complete loss of 1,25(OH)₂D₃–induced genome-wide gene regulation. Thus, there was no indication of any VDR-independent non-genomic actions of 1,25(OH)₂D₃ modulating its transcriptional response. Among the predicted primary VDR target genes, 47 were coding for transcription factors and thus may mediate secondary 1,25(OH)₂D₃ responses. CEBPA and ETS1 ChIP-seq data and RNA-seq following CEBPA knockdown were used to validate the predicted regulation of secondary vitamin D target genes by both transcription factors. In conclusion, a directional network containing 47 partly novel primary VDR target transcription factors describes secondary responses in a highly complex vitamin D signaling cascade. The central transcription factor VDR is indispensable for all transcriptome-wide effects of the nuclear hormone.

Epigenomics and the kidney

PURPOSE OF REVIEW

Epigenetic modifications are reversible changes to a cell's DNA or histones that alter gene expression but not DNA sequence. The present review will explore epigenomic profiling and bioinformatics techniques for the study of kidney development and disease.

RECENT FINDINGS

Reversible DNA and histone modifications influence chromatin accessibility and can be measured by a variety of recent techniques including DNase-seq, ATAC-seq, and single cell ATAC-seq. These approaches have been used to demonstrate that DNA methylation is critical for nephron progenitor maturation, for example. New bioinformatics techniques allow the prediction of chromatin loops that connect regulatory elements to target genes. Recent studies have demonstrated that DNA elements regulate transcription in the kidney via long-range physical interactions and create a new framework for understanding how genome wide association studies risk loci contribute to kidney disease. Increasingly, epigenomic approaches are being combined with transcriptomic analyses to generate multimodal datasets.

SUMMARY

Epigenomics has expanded our knowledge of gene architecture and regulation. Novel tools and techniques have led to the emergence of 'multiomics' in which epigenomic profiling, transcriptomics, and additional methods complement each other to improve our understanding of kidney disease and development.

Total Functional Score of Enhancer Elements Identifies Lineage-Specific Enhancers That Drive Differentiation of Pancreatic Cells

The differentiation of embryonic stem cells into various lineages is highly dependent on the chromatin state of the genome and patterns of gene expression. To identify lineage-specific enhancers driving the differentiation of progenitors into pancreatic cells, we used a previously described computational framework called Total Functional Score of Enhancer Elements (TFSEE), which integrates multiple genomic assays that probe both transcriptional and epigenomic states. First, we evaluated and compared TFSEE as an enhancer-calling algorithm with enhancers called using GRO-seq-defined enhancer transcripts (method 1) versus enhancers called using histone modification ChIP-seq data (method 2). Second, we used TFSEE to define the enhancer landscape and identify transcription factors (TFs) that maintain the multipotency of a subpopulation of endodermal stem cells during differentiation into pancreatic lineages. Collectively, our results demonstrate that TFSEE is a robust enhancer-calling algorithm that can be used to perform multilayer genomic data integration to uncover cell type-specific TFs that control lineage-specific enhancers.

Tet3 regulates cellular identity and DNA methylation in neural progenitor cells

TET enzymes oxidize 5-methylcytosine (5mC) into 5-hydroxymethylcytosine (5hmC), a process thought to be intermediary in an active DNA demethylation mechanism. Notably, 5hmC is highly abundant in the brain and in neuronal cells. Here, we interrogated the function of Tet3 in neural precursor cells (NPCs), using a stable and inducible knockdown system and an in vitro neural differentiation protocol. We show that Tet3 is upregulated during neural differentiation, whereas Tet1 is downregulated. Surprisingly, Tet3 knockdown led to a de-repression of pluripotency-associated genes such as Oct4, Nanog or Tcl1, with concomitant hypomethylation. Moreover, in Tet3 knockdown NPCs, we observed the appearance of OCT4-positive cells forming cellular aggregates, suggesting de-differentiation of the cells. Notably, Tet3 KD led to a genome-scale loss of DNA methylation and hypermethylation of a smaller number of CpGs that are located at neurogenesis-related genes and at imprinting control regions (ICRs) of Peg10, Zrsr1 and Mcts2 imprinted genes. Overall, our results suggest that TET3 is necessary to maintain silencing of pluripotency genes and consequently neural stem cell identity, possibly through regulation of DNA methylation levels in neural precursor cells.

Enhancer occlusion transcripts regulate the activity of human enhancer domains via transcriptional interference: a computational perspective

Analysis of ENCODE long RNA-Seq and ChIP-seq (Chromatin Immunoprecipitation Sequencing) datasets for HepG2 and HeLa cell lines uncovered 1647 and 1958 transcripts that interfere with transcription factor binding to human enhancer domains. TFBSs (Transcription Factor Binding Sites) intersected by these 'Enhancer Occlusion Transcripts' (EOTrs) displayed significantly lower relative transcription factor (TF) binding affinities compared to TFBSs for the same TF devoid of EOTrs. Expression of most EOTrs was regulated in a cell line specific manner; analysis for the same TFBSs across cell lines, i.e. in the absence or presence of EOTrs, yielded consistently higher relative TF/DNA-binding affinities for TFBSs devoid of EOTrs. Lower activities of EOTr-associated enhancer domains coincided with reduced occupancy levels for histone tail modifications H3K27ac and H3K9ac. Similarly, the analysis of EOTrs with allele-specific expression identified lower activities for alleles associated with EOTrs. ChIA-PET (Chromatin Interaction Analysis by Paired-End Tag Sequencing) and 5C (Carbon Copy Chromosome Conformation Capture) uncovered that enhancer domains associated with EOTrs preferentially interacted with poised gene promoters. Analysis of EOTr regions with GRO-seq (Global run-on) data established the correlation of RNA polymerase pausing and occlusion of TF-binding. Our results implied that EOTr expression regulates human enhancer domains via transcriptional interference.

Integrative analysis of reference epigenomes in 20 rice varieties

Epigenomic modifications are instrumental for transcriptional regulation, but comprehensive reference epigenomes remain unexplored in rice. Here, we develop an enhanced chromatin immunoprecipitation (eChIP) approach for plants, and generate genome-wide profiling of five histone modifications and RNA polymerase II occupancy with it. By integrating chromatin accessibility, DNA methylation, and transcriptome datasets, we construct comprehensive epigenome landscapes across various tissues in 20 representative rice varieties. Approximately 81.8% of rice genomes are annotated with different epigenomic properties. Refinement of promoter regions using open chromatin and H3K4me3-marked regions provides insight into transcriptional regulation. We identify extensive enhancer-like promoters with potential enhancer function on transcriptional regulation through chromatin interactions. Active and repressive histone modifications and the predicted enhancers vary largely across tissues, whereas inactive chromatin states are relatively stable. Together, these datasets constitute a valuable resource for functional element annotation in rice and indicate the central role of epigenomic information in understanding transcriptional regulation.

Transcriptional network dynamics during the progression of pluripotency revealed by integrative statistical learning

The developmental potential of cells, termed pluripotency, is highly dynamic and progresses through a continuum of naive, formative and primed states. Pluripotency progression of mouse embryonic stem cells (ESCs) from naive to formative and primed state is governed by transcription factors (TFs) and their target genes. Genomic techniques have uncovered a multitude of TF binding sites in ESCs, yet a major challenge lies in identifying target genes from functional binding sites and reconstructing dynamic transcriptional networks underlying pluripotency progression. Here, we integrated time-resolved ‘trans-omic’ datasets together with TF binding profiles and chromatin conformation data to identify target genes of a panel of TFs. Our analyses revealed that naive TF target genes are more likely to be TFs themselves than those of formative TFs, suggesting denser hierarchies among naive TFs. We also discovered that formative TF target genes are marked by permissive epigenomic signatures in the naive state, indicating that they are poised for expression prior to the initiation of pluripotency transition to the formative state. Finally, our reconstructed transcriptional networks pinpointed the precise timing from naive to formative pluripotency progression and enabled the spatiotemporal mapping of differentiating ESCs to their in vivo counterparts in developing embryos.

BAT Hi-C maps global chromatin interactions in an efficient and economical way

Chromosome Conformation Capture (3C)-based technologies, such as Hi-C, have represented a significant breakthrough in investigating the structure and function of higher-order genome architecture. However, the mapping of global chromatin interactions remains challenging across many biological conditions due to high background noise and financial constraints, especially for small laboratories. Here, we describe the Bridge linker-Alul-Tn5 Hi-C (BAT Hi-C) method, which is a simple and efficient method for delineating chromatin conformational features of mouse embryonic stem (mES) cells and uncover DNA loops. This protocol combines Alul fragmentation and biotinylated linker-mediated proximity ligation to obtain kilobase (kb) resolution with a marked increase in the amount of unique read pairs. The protocol also includes chromatin isolation to reduce background noise and Tn5 tagmentation to cut down on preparation time. Importantly, with only one-third sequencing depth, our method revealed the same spectrum of chromatin contacts as in situ Hi-C. BAT Hi-C is an economical (i.e., approximately $40 for library preparation) and straightforward (total hands-on time of 3 days) tool that is ideal for the in-depth analysis of long-range chromatin looping events in a genome-wide fashion.

AdaSampling for Positive-Unlabeled and Label Noise Learning With Bioinformatics Applications

Class labels are required for supervised learning but may be corrupted or missing in various applications. In binary classification, for example, when only a subset of positive instances is labeled whereas the remaining are unlabeled, positive-unlabeled (PU) learning is required to model from both positive and unlabeled data. Similarly, when class labels are corrupted by mislabeled instances, methods are needed for learning in the presence of class label noise (LN). Here we propose adaptive sampling (AdaSampling), a framework for both PU learning and learning with class LN. By iteratively estimating the class mislabeling probability with an adaptive sampling procedure, the proposed method progressively reduces the risk of selecting mislabeled instances for model training and subsequently constructs highly generalizable models even when a large proportion of mislabeled instances is present in the data. We demonstrate the utilities of proposed methods using simulation and benchmark data, and compare them to alternative approaches that are commonly used for PU learning and/or learning with LN. We then introduce two novel bioinformatics applications where AdaSampling is used to: 1) identify kinase-substrates from mass spectrometry-based phosphoproteomics data and 2) predict transcription factor target genes by integrating various next-generation sequencing data.

The Role of RNA Polymerase II Contiguity and Long-Range Interactions in the Regulation of Gene Expression in Human Pluripotent Stem Cells

The eukaryotic nucleus is a highly complex structure that carries out multiple functions primarily needed for gene expression, and among them, transcription seems to be the most fundamental. Diverse approaches have demonstrated that transcription takes place at discrete sites known as transcription factories, wherein RNA polymerase II (RNAP II) is attached to the factory and immobilized while transcribing DNA. It has been proposed that transcription factories promote chromatin loop formation, creating long-range interactions in which relatively distant genes can be transcribed simultaneously. In this study, we examined long-range interactions between the POU5F1 gene and genes previously identified as being POU5F1 enhancer-interacting, namely, CDYL, TLE2, RARG, and MSX1 (all involved in transcriptional regulation), in human pluripotent stem cells (hPSCs) and their early differentiated counterparts. As a control gene, RUNX1 was used, which is expressed during hematopoietic differentiation and not associated with pluripotency. To reveal how these long-range interactions between POU5F1 and the selected genes change with the onset of differentiation and upon RNAP II inhibition, we performed three-dimensional fluorescence in situ hybridization (3D-FISH) followed by computational simulation analysis. Our analysis showed that the numbers of long-range interactions between specific genes decrease during differentiation, suggesting that the transcription of monitored genes is associated with pluripotency. In addition, we showed that upon inhibition of RNAP II, long-range associations do not disintegrate and remain constant. We also analyzed the distance distributions of these genes in the context of their positions in the nucleus and revealed that they tend to have similar patterns resembling normal distribution. Furthermore, we compared data created in vitro and in silico to assess the biological relevance of our results.

Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells

Transcriptional regulatory networks (TRNs) provide insight into cellular behavior by describing interactions between transcription factors (TFs) and their gene targets. The assay for transposase-accessible chromatin (ATAC)–seq, coupled with TF motif analysis, provides indirect evidence of chromatin binding for hundreds of TFs genome-wide. Here, we propose methods for TRN inference in a mammalian setting, using ATAC-seq data to improve gene expression modeling. We test our methods in the context of T Helper Cell Type 17 (Th17) differentiation, generating new ATAC-seq data to complement existing Th17 genomic resources. In this resource-rich mammalian setting, our extensive benchmarking provides quantitative, genome-scale evaluation of TRN inference, combining ATAC-seq and RNA-seq data. We refine and extend our previous Th17 TRN, using our new TRN inference methods to integrate all Th17 data (gene expression, ATAC-seq, TF knockouts, and ChIP-seq). We highlight newly discovered roles for individual TFs and groups of TFs (“TF–TF modules”) in Th17 gene regulation. Given the popularity of ATAC-seq, which provides high-resolution with low sample input requirements, we anticipate that our methods will improve TRN inference in new mammalian systems, especially in vivo, for cells directly from humans and animal models.

GITAR: An Open Source Tool for Analysis and Visualization of Hi-C Data

Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources (GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains (TADs). GITAR is composed of two main modules: (1) HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and (2) processed data library, a large collection of human and mouse datasets processed using HiCtool. HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://genomegitar.org as an open-source software.

Modulation of vitamin D signaling by the pioneer factor CEBPA

The myeloid master regulator CCAAT enhancer-binding protein alpha (CEBPA) is known as a pioneer factor. In this study, we report the CEBPA cistrome of THP-1 human monocytes after stimulation with the vitamin D receptor (VDR) ligand 1α,25-dihydroxyvitamin D₃ (1,25(OH)₂D₃) for 2, 8 and 24 h. About a third of the genomic VDR binding sites co-located with those of CEBPA. In parallel, the binding strength of 5% of the CEBPA cistrome, i.e. some 1500 sites, is significantly (p < 0.001) affected by 1,25(OH)₂D₃. Transcriptome-wide analysis after CEBPA silencing indicated that the pioneer factor enhances both the basal expression and ligand inducibility of 70 vitamin D target genes largely involved in lipid signaling and metabolism. In contrast, CEBPA suppresses 82 vitamin D target genes many of which are related to the modulation of T cell activity by monocytes. The inducibility of the promoter-specific histone marker H3K4me3 distinguishes the former class of genes from the latter. Moreover, prominent occupancy of the myeloid pioneer factor PU.1 on 1,25(OH)₂D₃-sensitive CEBPA enhancers mechanistically explains the dichotomy of vitamin D target genes. In conclusion, CEBPA supports vitamin D signaling concerning actions of the innate immune system, but uses the antagonism with PU.1 for suppressing possible overreactions of adaptive immunity.

Chromatin Interaction Analysis Using Paired-End-Tag (ChIA-PET) Sequencing in Tadpole Tissues

Proper gene expression involves communication between the regulatory elements and promoters of genes. Today, chromosome conformation capture (3C)-based methods efficiently probe chromosome folding in the nucleus and thus provide a molecular description of physical proximity through DNA looping between enhancer(s) and their target promoter(s). One such method, chromatin interaction analysis using paired-end-tag (ChIA-PET) sequencing is a powerful high-throughput method for detection of genome-wide chromatin interactions. Following enrichment of the chromatin complexes with a dedicated antibody, through a process of immunoprecipitation (IP), DNA fragments are end-joined with specifically designed DNA-linkers through proximity ligation. The DNA-linkers contain the binding site for the type II restriction enzyme MmeI, which cleaves 20 bp from each end of the ligated fragments, thus releasing a "paired end tag" (PET): [20 bp tag]-[linker]-[20 bp tag]. The PETs are then deep-sequenced and reads are mapped to the reference genome, revealing both binding sites, as well as remote chromatin interactions mediated by the protein factors of interest. The method detailed here focuses on ChIA-PET library construction and can be completed in 2 wk.

The impact of the vitamin D-modulated epigenome on VDR target gene regulation

The micronutrient vitamin D significantly modulates the human epigenome via enhancing genome-wide the rate of accessible chromatin and vitamin D receptor (VDR) binding. This study focuses on histone marks of active chromatin at promoter and enhancer regions and investigates, whether these genomic loci are sensitive to vitamin D. The epigenome of THP-1 human monocytes contains nearly 23,000 sites with H3K4me3 histone modifications, 550 of which sites are significantly (p < 0.05) modulated by stimulation with the VDR ligand 1α,25-dihydroxyvitamin D₃ (1,25(OH)₂D₃). H3K27ac histone modifications mark active chromatin and 2473 of 45,500 sites are vitamin D sensitive. The two types of ligand-dependent histone marks allow to distinguish promoter and enhancer regulation by vitamin D, respectively. Transcription start site overlap is the prime attribute of ligand-dependent H3K4me3 marks, while VDR co-location is the top ranking parameter describing 1,25(OH)₂D₃-sensitive H3K27ac marks at enhancers. A categorization of 1,25(OH)₂D₃-sensitive histone marks by machine learning algorithms - using the attributes overall peak strength and ligand inducibility - highlights 260 and 287 regions with H3K4me3 and H3K27ac modifications, respectively. These loci are found at the promoter regions of 59 vitamin D target genes and their associated enhancers. In this way, ligand-dependent histone marks provide a link of the effects of 1,25(OH)₂D₃ on the epigenome with previously reported mRNA expression changes of vitamin D target genes. In conclusion, the human epigenome responds also on the level of histone modifications to 1,25(OH)₂D₃ stimulation. This allows a more detailed understanding of vitamin D target gene regulation.

The pleiotropic transcriptional regulator COUP-TFI plays multiple roles in neural development and disease

Transcription factors are expressed in a dynamic fashion both in time and space during brain development, and exert their roles by activating a cascade of multiple target genes. This implies that understanding the precise function of a transcription factor becomes a challenging task. In this review, we will focus on COUP-TFI (or NR2F1), a nuclear receptor belonging to the superfamily of the steroid/thyroid hormone receptors, and considered to be one of the major transcriptional regulators orchestrating cortical arealization, cell-type specification and maturation. Recent data have unraveled the multi-faceted functions of COUP-TFI in the development of several mouse brain structures, including the neocortex, hippocampus and ganglionic eminences. Despite NR2F1 mutations and deletions in humans have been linked to a complex neurodevelopmental disease mainly associated to optic atrophy and intellectual disability, its role during the formation of the retina and optic nerve remains unclear. In light of its major influence in cortical development, we predict that its haploinsufficiency might be the cause of other cognitive diseases, not identified so far. Mouse models offer a unique opportunity of dissecting COUP-TFI function in different regions during brain assembly; hence, the importance of comparing and discussing common points linking mouse models to human patients' symptoms.

ETS transcription factor family member GABPA contributes to vitamin D receptor target gene regulation

Binding motifs of the ETS-domain transcription factor GABPA are found with high significance below the summits of the vitamin D receptor (VDR) cistrome. VDR is the nuclear receptor for the biologically most active vitamin D metabolite 1α,25-dihydroxyvitamin D₃ (1,25(OH)₂D₃). In this study, we determined the GABPA cistrome in THP-1 human monocytes and found that it is comprised of 3822 genomic loci, some 20% of which were modulated by 1,25(OH)₂D₃. The GABPA cistrome showed a high overlap rate with accessible chromatin and the pioneer transcription factor PU.1. Interestingly, 23 and 12% of persistent and transient VDR binding sites, respectively, co-localized with GABPA, which is clearly higher than the rate of secondary VDR loci (4%). Some 40% of GABPA binding sites were found at transcription start sites, nearly 100 of which are of 1,25(OH)₂D₃ target genes. On 593 genomic loci VDR and GABPA co-localized with PU.1, while only 175 VDR sites bound GABPA in the absence of PU.1. In total, VDR sites with GABPA co-localization may control some 450 vitamin D target genes. Those genes that are co-controlled by PU.1 preferentially participate in cellular and immune signaling processes, while the remaining genes are involved in cellular metabolism pathways. In conclusion, GABPA may contribute to differential VDR target gene regulation.

Analysis of high-resolution 3D intrachromosomal interactions aided by Bayesian network modeling

Long-range intrachromosomal interactions play an important role in 3D chromosome structure and function, but our understanding of how various factors contribute to the strength of these interactions remains poor. In this study we used a recently developed analysis framework for Bayesian network (BN) modeling to analyze publicly available datasets for intrachromosomal interactions. We investigated how 106 variables affect the pairwise interactions of over 10 million 5-kb DNA segments in the B-lymphocyte cell line GB12878. Strictly data-driven BN modeling indicates that the strength of intrachromosomal interactions (hic_strength) is directly influenced by only four types of factors: distance between segments, Rad21 or SMC3 (cohesin components),transcription at transcription start sites (TSS), and the number of CCCTC-binding factor (CTCF)-cohesin complexes between the interacting DNA segments. Subsequent studies confirmed that most high-intensity interactions have a CTCF-cohesin complex in at least one of the interacting segments. However, 46% have CTCF on only one side, and 32% are without CTCF. As expected, high-intensity interactions are strongly dependent on the orientation of the ctcf motif, and, moreover, we find that the interaction between enhancers and promoters is similarly dependent on ctcf motif orientation. Dependency relationships between transcription factors were also revealed, including known lineage-determining B-cell transcription factors (e.g., Ebf1) as well as potential novel relationships. Thus, BN analysis of large intrachromosomal interaction datasets is a useful tool for gaining insight into DNA-DNA, protein-DNA, and protein-protein interactions.

Selective regulation of biological processes by vitamin D based on the spatio-temporal cistrome of its receptor

The transcription factor vitamin D receptor (VDR) is the exclusive nuclear target of the biologically active form of vitamin D (1,25(OH)₂D₃). In THP-1 human monocytes we obtained a highly accurate VDR cistrome after 2 and 24h ligand stimulation comprising >11,600 genomic loci, 78% of which were detected exclusively after 24h. In contrast, a group of 510 persistent VDR sites occurred at all conditions and some 2100 VDR loci were only transiently occupied. Machine learning and statistical analysis as well as a comparison with the re-analyzed B cell VDR cistrome indicated a subgroup of 339 highly conserved persistent VDR sites that were suited best for describing vitamin D-triggered gene regulatory scenarios. The 1,25(OH)₂D₃-dependent transcriptome of THP-1 cells comprised 587 genes, 311 of which were primary targets with main functions in the immune system. More than 97% of the latter genes were located within 1,25(OH)₂D₃-modulated topologically associated domains (TADs). The number of persistent and transient VDR sites was found to be the main discriminator for sorting these TADs into five classes carrying vitamin D target genes involved in distinct biological processes. In conclusion, specific regulation of biological processes by vitamin D depends on differences in time-dependent VDR binding.

Orphan CpG islands define a novel class of highly active enhancers

CpG islands (CGI) are critical genomic regulatory elements that support transcriptional initiation and are associated with the promoters of most human genes. CGI are distinguished from the bulk genome by their high CpG density, lack of DNA methylation, and euchromatic features. While CGI are canonically known as strong promoters, thousands of 'orphan' CGI lie far from any known transcript, leaving their function an open question. We undertook a comprehensive analysis of the epigenetic state of orphan CGI across over 100 cell types. Here we show that most orphan CGI display the chromatin features of active enhancers (H3K4me1, H3K27Ac) in at least one cell type. Relative to classical enhancers, these enhancer CGI (ECGI) are stronger, as gauged by chromatin state and in functional assays, are more broadly expressed, and are more highly conserved. Likewise, ECGI engage in more genomic contacts and are enriched for transcription factor binding relative to classical enhancers. In human cancers, these epigenetic differences between ECGI vs. classical enhancers manifest in distinct alterations in DNA methylation. Thus, ECGI define a class of highly active enhancers, strengthened by the broad transcriptional activity, CpG density, hypomethylation, and chromatin features they share with promoter CGI. In addition to indicating a role for thousands of orphan CGI, these findings suggests that enhancer activity may be an intrinsic function of CGI in general and provides new insights into the evolution of enhancers and their epigenetic regulation during development and tumorigenesis.

Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings

Understanding the three-dimensional (3D) architecture of chromatin and its relation to gene expression and regulation is fundamental to understanding how the genome functions. Advances in Hi-C technology now permit us to study 3D genome organization, but we still lack an understanding of the structural dynamics of chromosomes. The dynamic couplings between regions separated by large genomic distances (>50 Mb) have yet to be characterized. We adapted a well-established protein-modeling framework, the Gaussian Network Model (GNM), to model chromatin dynamics using Hi-C data. We show that the GNM can identify spatial couplings at multiple scales: it can quantify the correlated fluctuations in the positions of gene loci, find large genomic compartments and smaller topologically-associating domains (TADs) that undergo en bloc movements, and identify dynamically coupled distal regions along the chromosomes. We show that the predictions of the GNM correlate well with genome-wide experimental measurements. We use the GNM to identify novel cross-correlated distal domains (CCDDs) representing pairs of regions distinguished by their long-range dynamic coupling and show that CCDDs are associated with increased gene co-expression. Together, these results show that GNM provides a mathematically well-founded unified framework for modeling chromatin dynamics and assessing the structural basis of genome-wide observations.

Long-read ChIA-PET for base-pair-resolution mapping of haplotype-specific chromatin interactions

Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) is a robust method for capturing genome-wide chromatin interactions. Unlike other 3C-based methods, it includes a chromatin immunoprecipitation (ChIP) step that enriches for interactions mediated by specific target proteins. This unique feature allows ChIA-PET to provide the functional specificity and higher resolution needed to detect chromatin interactions, which chromosome conformation capture (3C)/Hi-C approaches have not achieved. The original ChIA-PET protocol generates short paired-end tags (2 × 20 base pairs (bp)) to detect two genomic loci that are far apart on linear chromosomes but are in spatial proximity in the folded genome. We have improved the original approach by developing long-read ChIA-PET, in which the length of the paired-end tags is increased (up to 2 × 250 bp). The longer PET reads not only improve the tag-mapping efficiency but also increase the probability of covering phased single-nucleotide polymorphisms (SNPs), which allows haplotype-specific chromatin interactions to be identified. Here, we provide the detailed protocol for long-read ChIA-PET that includes cell fixation and lysis, chromatin fragmentation by sonication, ChIP, proximity ligation with a bridge linker, Tn5 tagmentation, PCR amplification and high-throughput sequencing. For a well-trained molecular biologist, it typically takes 6 d from cell harvesting to the completion of library construction, up to a further 36 h for DNA sequencing and <20 h for processing of raw sequencing reads.

Epigenomic PU.1-VDR crosstalk modulates vitamin D signaling

The ETS-domain transcription factor PU.1 acts as a pioneer factor for other transcription factors including nuclear receptors. In this study, we report that in THP-1 human monocytes the PU.1 cistrome comprises 122,319 genomic sites. Interestingly, at 6498 (5.3%) of these loci PU.1 binding was significantly modulated by the vitamin D receptor (VDR) ligand 1α,25-dihydroxyvitamin D₃ (1,25(OH)₂D₃). In most cases 1,25(OH)₂D₃ increased PU.1 association, which correlated strongly with VDR co-location and overlap ratios for canonical DR3-type VDR binding sites. Genome-wide 6488 sites associating both with PU.1 and VDR as well as 5649 non-VDR overlapping, 1,25(OH)₂D₃-sensitive PU.1 loci represent the PU.1-VDR crosstalk and can be described by four gene regulatory scenarios, each. Chromatin accessibility was the major discriminator between these models. The location of the PU.1 binding loci in open chromatin coincided with a significantly smaller mean distance to the closest 1,25(OH)₂D₃ target gene. PU.1 knockdown indicated that the pioneer factor is relevant for the transcriptional activation of 1,25(OH)₂D₃ target genes but its impact differed in magnitude and orientation. In conclusion, PU.1 is an important modulator of VDR signaling in monocytes, including but also exceeding its role as a pioneer factor, but we found no evidence for a direct interaction of both proteins.

Computational Prediction of the Global Functional Genomic Landscape: Applications, Methods, and Challenges

Technological advances have led to an explosive growth of high-throughput functional genomic data. Exploiting the correlation among different data types, it is possible to predict one functional genomic data type from other data types. Prediction tools are valuable in understanding the relationship among different functional genomic signals. They also provide a cost-efficient solution to inferring the unknown functional genomic profiles when experimental data are unavailable due to resource or technological constraints. The predicted data may be used for generating hypotheses, prioritizing targets, interpreting disease variants, facilitating data integration, quality control, and many other purposes. This article reviews various applications of prediction methods in functional genomics, discusses analytical challenges, and highlights some common and effective strategies used to develop prediction methods for functional genomic data.

Deciphering Noncoding RNA and Chromatin Interactions: Multiplex Chromatin Interaction Analysis by Paired-End Tag Sequencing (mChIA-PET)

Genomic DNA is dynamically associated with protein factors and folded to form chromatin fibers. The 3-dimensional (3D) configuration of the chromatin will enable the distal genetic elements to come into close proximity, allowing transcriptional regulation. Noncoding RNA can mediate the 3D structure of chromatin. Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET) is a valuable and powerful technique in molecular biology which allows the study of unbiased, genome-wide de novo chromatin interactions with paired-end tags. Here, we describe the standard version of ChIA-PET and a Multiplex ChIA-PET version.

ChIP-seq Analysis of Condensin Complex in Cultured Mammalian Cells

ChIP-seq, or chromatin immunoprecipitation combined with massively parallel DNA sequencing, is a powerful technique to investigate in vivo protein-DNA interactions on a genome-wide scale at high resolution. Here we describe a ChIP-seq protocol optimized for analysis of condensin I complex on human mitotic chromosomes. The protocol includes procedures of intensive cell fixation by two cross-linking reagents and thorough chromatin shearing by nuclease and sonication treatments, both of which contribute to improving the signal-to-noise ratio of condensin I ChIP-seq profiles. The optimized protocol may also be helpful to explore chromosomal binding sites of other "hard-to-see" proteins by ChIP-seq.

Mapping RNA-RNA interactome and RNA structure in vivo by MARIO

The pervasive transcription of our genome presents a possibility of revealing new genomic functions by investigating RNA interactions. Current methods for mapping RNA–RNA interactions have to rely on an ‘anchor' protein or RNA and often require molecular perturbations. Here we present the MARIO (Mapping RNA interactome in vivo) technology to massively reveal RNA–RNA interactions from unperturbed cells. We mapped tens of thousands of endogenous RNA–RNA interactions from mouse embryonic stem cells and brain. We validated seven interactions by RNA antisense purification and one interaction using single-molecule RNA–FISH. The experimentally derived RNA interactome is a scale-free network, which is not expected from currently perceived promiscuity in RNA–RNA interactions. Base pairing is observed at the interacting regions between long RNAs, including transposon transcripts, suggesting a class of regulatory sequences acting in trans. In addition, MARIO data reveal thousands of intra-molecule interactions, providing in vivo data on high-order RNA structures.

Current methods for mapping RNA-RNA interactions have to rely on an ‘anchor' protein or RNA. Here, the authors report the MARIO (Mapping RNA interactome in vivo) technology that can massively reveal RNA-RNA interactions and RNA structure from unperturbed cells.

Epigenome-wide effects of vitamin D and their impact on the transcriptome of human monocytes involve CTCF

The physiological functions of vitamin D are mediated by its metabolite 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3) activating the transcription factor vitamin D receptor (VDR). In THP-1 human monocytes we demonstrated epigenome-wide effects of 1,25(OH)2D3 at 8979 loci with significantly modulated chromatin accessibility. Maximal chromatin opening was observed after 24 h, while after 48 h most sites closed again. The chromatin-organizing protein CTCF bound to 14% of the 1,25(OH)2D3-sensitive chromatin regions. Interestingly, 1,25(OH)2D3 affected the chromatin association of CTCF providing an additional mechanism for the epigenome-wide effects of the VDR ligand. The 1,25(OH)2D3-modulated transcriptome of THP-1 cells comprised 1284 genes, 77.5% of which responded only 24 h after stimulation. During the 1,25(OH)2D3 stimulation time course the proportion of down-regulated genes increased from 0% to 44.9% and the top-ranking physiological function of the respective genes shifted from anti-microbial response to connective tissue disorders. The integration of epigenomic and transcriptomic data identified 165 physiologically important 1,25(OH)2D3 target genes, including HTT and NOD2, whose expression can be predicted primarily from epigenomic data of their genomic loci. Taken together, a large number of 1,25(OH)2D3-triggered epigenome-wide events precede and accompany the transcriptional activation of target genes of the nuclear hormone.

3D-GNOME: an integrated web service for structural modeling of the 3D genome

Recent advances in high-throughput chromosome conformation capture (3C) technology, such as Hi-C and ChIA-PET, have demonstrated the importance of 3D genome organization in development, cell differentiation and transcriptional regulation. There is now a widespread need for computational tools to generate and analyze 3D structural models from 3C data. Here we introduce our 3D GeNOme Modeling Engine (3D-GNOME), a web service which generates 3D structures from 3C data and provides tools to visually inspect and annotate the resulting structures, in addition to a variety of statistical plots and heatmaps which characterize the selected genomic region. Users submit a bedpe (paired-end BED format) file containing the locations and strengths of long range contact points, and 3D-GNOME simulates the structure and provides a convenient user interface for further analysis. Alternatively, a user may generate structures using published ChIA-PET data for the GM12878 cell line by simply specifying a genomic region of interest. 3D-GNOME is freely available at http://3dgnome.cent.uw.edu.pl/.

Genetics of Common Endocrine Disease: The Present and the Future

CONTEXT

In honor of the 75th issue of the Journal of Clinical Endocrinology and Metabolism, the author was invited to present his perspectives on genetics in human endocrinology. This paper reviews what the field has achieved in the genetics of common endocrine disease, and offers predictions on where the field will move in the future and its impact on endocrine clinical practice.

EVIDENCE ACQUISITION

The October 2015 data release of the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) Catalog of Published Genome-wide Association Studies was queried regarding endocrinologic diseases and traits. PubMed searches were focused on genetic prediction of disease, genetic findings and drug targets, functional interrogation of genetic loci, use of genetics to subtype disease, missing heritability, systems genomics, and higher order chromatin structures as regulators of gene function.

EVIDENCE SYNTHESIS

Nearly a quarter of genome wide association study findings concern endocrinologic diseases and traits. While these findings have not yet dramatically altered clinical care, genetics will have a major impact by providing the drug targets of tomorrow, facilitated by experimental and bioinformatic advances that will shorten the time from gene discovery to drug development. Use of genetic findings to subtype common endocrine disease will allow more precise prevention and treatment efforts. Future advances will allow us to move away from the common view of DNA as a string of letters, allowing exploration of higher order structure that likely explains much "missing heritability."

CONCLUSIONS

The future will see a greater role of genetics at the bedside, with genetic epidemiologic discoveries leading not only to new treatments of endocrine disease, but also helping us prescribe the right drug to the right patients by allowing subclassification of common heterogeneous endocrine conditions. Future technological breakthroughs will reveal the heritable mysteries hidden in chromatin structure, leading to a more complete characterization of heritability that will propel our ability to translate genetic findings into new preventions and treatments.

Mechanisms and Consequences of Cancer Genome Instability: Lessons from Genome Sequencing Studies

During tumor evolution, cancer cells can accumulate numerous genetic alterations, ranging from single nucleotide mutations to whole-chromosomal changes. Although a great deal of progress has been made in the past decades in characterizing genomic alterations, recent cancer genome sequencing studies have provided a wealth of information on the detailed molecular profiles of such alterations in various types of cancers. Here, we review our current understanding of the mechanisms and consequences of cancer genome instability, focusing on the findings uncovered through analysis of exome and whole-genome sequencing data. These analyses have shown that most cancers have evidence of genome instability, and the degree of instability is variable within and between cancer types. Importantly, we describe some recent evidence supporting the idea that chromosomal instability could be a major driving force in tumorigenesis and cancer evolution, actively shaping the genomes of cancer cells to maximize their survival advantage.