The 4D nucleome project

Chromosomics: Bridging the Gap between Genomes and Chromosomes

The recent advances in DNA sequencing technology are enabling a rapid increase in the number of genomes being sequenced. However, many fundamental questions in genome biology remain unanswered, because sequence data alone is unable to provide insight into how the genome is organised into chromosomes, the position and interaction of those chromosomes in the cell, and how chromosomes and their interactions with each other change in response to environmental stimuli or over time. The intimate relationship between DNA sequence and chromosome structure and function highlights the need to integrate genomic and cytogenetic data to more comprehensively understand the role genome architecture plays in genome plasticity. We propose adoption of the term 'chromosomics' as an approach encompassing genome sequencing, cytogenetics and cell biology, and present examples of where chromosomics has already led to novel discoveries, such as the sex-determining gene in eutherian mammals. More importantly, we look to the future and the questions that could be answered as we enter into the chromosomics revolution, such as the role of chromosome rearrangements in speciation and the role more rapidly evolving regions of the genome, like centromeres, play in genome plasticity. However, for chromosomics to reach its full potential, we need to address several challenges, particularly the training of a new generation of cytogeneticists, and the commitment to a closer union among the research areas of genomics, cytogenetics, cell biology and bioinformatics. Overcoming these challenges will lead to ground-breaking discoveries in understanding genome evolution and function.

Chromatin loops associated with active genes and heterochromatin shape rice genome architecture for transcriptional regulation

Insight into high-resolution three-dimensional genome organization and its effect on transcription remains largely elusive in plants. Here, using a long-read ChIA-PET approach, we map H3K4me3- and RNA polymerase II (RNAPII)-associated promoter-promoter interactions and H3K9me2-marked heterochromatin interactions at nucleotide/gene resolution in rice. The chromatin architecture is separated into different independent spatial interacting modules with distinct transcriptional potential and covers approximately 82% of the genome. Compared to inactive modules, active modules possess the majority of active loop genes with higher density and contribute to most of the transcriptional activity in rice. In addition, promoter-promoter interacting genes tend to be transcribed cooperatively. In contrast, the heterochromatin-mediated loops form relative stable structure domains in chromatin configuration. Furthermore, we examine the impact of genetic variation on chromatin interactions and transcription and identify a spatial correlation between the genetic regulation of eQTLs and e-traits. Thus, our results reveal hierarchical and modular 3D genome architecture for transcriptional regulation in rice.

CRISPR/Cas9-mediated knock-in of an optimized TetO repeat for live cell imaging of endogenous loci

Nuclear organization has an important role in determining genome function; however, it is not clear how spatiotemporal organization of the genome relates to functionality. To elucidate this relationship, a method for tracking any locus of interest is desirable. Recently clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) or transcription activator-like effectors were adapted for imaging endogenous loci; however, they are mostly limited to visualization of repetitive regions. Here, we report an efficient and scalable method named SHACKTeR (Short Homology and CRISPR/Cas9-mediated Knock-in of a TetO Repeat) for live cell imaging of specific chromosomal regions without the need for a pre-existing repetitive sequence. SHACKTeR requires only two modifications to the genome: CRISPR/Cas9-mediated knock-in of an optimized TetO repeat and its visualization by TetR-EGFP expression. Our simplified knock-in protocol, utilizing short homology arms integrated by polymerase chain reaction, was successful at labeling 10 different loci in HCT116 cells. We also showed the feasibility of knock-in into lamina-associated, heterochromatin regions, demonstrating that these regions prefer non-homologous end joining for knock-in. Using SHACKTeR, we were able to observe DNA replication at a specific locus by long-term live cell imaging. We anticipate the general applicability and scalability of our method will enhance causative analyses between gene function and compartmentalization in a high-throughput manner.

GWAS4D: multidimensional analysis of context-specific regulatory variant for human complex diseases and traits

Genome-wide association studies have generated over thousands of susceptibility loci for many human complex traits, and yet for most of these associations the true causal variants remain unknown. Tissue/cell type-specific prediction and prioritization of non-coding regulatory variants will facilitate the identification of causal variants and underlying pathogenic mechanisms for particular complex diseases and traits. By leveraging recent large-scale functional genomics/epigenomics data, we develop an intuitive web server, GWAS4D (http://mulinlab.tmu.edu.cn/gwas4d or http://mulinlab.org/gwas4d), that systematically evaluates GWAS signals and identifies context-specific regulatory variants. The updated web server includes six major features: (i) updates the regulatory variant prioritization method with our new algorithm; (ii) incorporates 127 tissue/cell type-specific epigenomes data; (iii) integrates motifs of 1480 transcriptional regulators from 13 public resources; (iv) uniformly processes Hi-C data and generates significant interactions at 5 kb resolution across 60 tissues/cell types; (v) adds comprehensive non-coding variant functional annotations; (vi) equips a highly interactive visualization function for SNP-target interaction. Using a GWAS fine-mapped set for 161 coronary artery disease risk loci, we demonstrate that GWAS4D is able to efficiently prioritize disease-causal regulatory variants.

Galaxy HiCExplorer: a web server for reproducible Hi-C data analysis, quality control and visualization

Galaxy HiCExplorer is a web server that facilitates the study of the 3D conformation of chromatin by allowing Hi-C data processing, analysis and visualization. With the Galaxy HiCExplorer web server, users with little bioinformatic background can perform every step of the analysis in one workflow: mapping of the raw sequence data, creation of Hi-C contact matrices, quality assessment, correction of contact matrices and identification of topological associated domains (TADs) and A/B compartments. Users can create publication ready plots of the contact matrix, A/B compartments, and TADs on a selected genomic locus, along with additional information like gene tracks or ChIP-seq signals. Galaxy HiCExplorer is freely usable at: https://hicexplorer.usegalaxy.eu and is available as a Docker container: https://github.com/deeptools/docker-galaxy-hicexplorer.

The Encyclopedia of DNA elements (ENCODE): data portal update

The Encyclopedia of DNA Elements (ENCODE) Data Coordinating Center has developed the ENCODE Portal database and website as the source for the data and metadata generated by the ENCODE Consortium. Two principles have motivated the design. First, experimental protocols, analytical procedures and the data themselves should be made publicly accessible through a coherent, web-based search and download interface. Second, the same interface should serve carefully curated metadata that record the provenance of the data and justify its interpretation in biological terms. Since its initial release in 2013 and in response to recommendations from consortium members and the wider community of scientists who use the Portal to access ENCODE data, the Portal has been regularly updated to better reflect these design principles. Here we report on these updates, including results from new experiments, uniformly-processed data from other projects, new visualization tools and more comprehensive metadata to describe experiments and analyses. Additionally, the Portal is now home to meta(data) from related projects including Genomics of Gene Regulation, Roadmap Epigenome Project, Model organism ENCODE (modENCODE) and modERN. The Portal now makes available over 13000 datasets and their accompanying metadata and can be accessed at: https://www.encodeproject.org/.

Improved inference of chromosome conformation from images of labeled loci

We previously published a method that infers chromosome conformation from images of fluorescently-tagged genomic loci, for the case when there are many loci labeled with each distinguishable color.  Here we build on our previous work and improve the reconstruction algorithm to address previous limitations.  We show that these improvements 1) increase the reconstruction accuracy and 2) allow the method to be used on large-scale problems involving several hundred labeled loci.  Simulations indicate that full-chromosome reconstructions at 1/2 Mb resolution are possible using existing labeling and imaging technologies.  The updated reconstruction code and the script files used for this paper are available at:  https://github.com/heltilda/align3d.

Sperm RNA code programmes the metabolic health of offspring

Mammalian sperm RNA is increasingly recognized as an additional source of paternal hereditary information beyond DNA. Environmental inputs, including an unhealthy diet, mental stresses and toxin exposure, can reshape the sperm RNA signature and induce offspring phenotypes that relate to paternal environmental stressors. Our understanding of the categories of sperm RNAs (such as tRNA-derived small RNAs, microRNAs, ribosomal RNA-derived small RNAs and long non-coding RNAs) and associated RNA modifications is expanding and has begun to reveal the functional diversity and information capacity of these molecules. However, the coding mechanism endowed by sperm RNA structures and by RNA interactions with DNA and other epigenetic factors remains unknown. How sperm RNA-encoded information is decoded in early embryos to control offspring phenotypes also remains unclear. Complete deciphering of the 'sperm RNA code' with regard to metabolic control could move the field towards translational applications and precision medicine, and this may lead to prevention of intergenerational transmission of obesity and type 2 diabetes mellitus susceptibility.

Transcription-driven genome organization: a model for chromosome structure and the regulation of gene expression tested through simulations

Current models for the folding of the human genome see a hierarchy stretching down from chromosome territories, through A/B compartments and topologically-associating domains (TADs), to contact domains stabilized by cohesin and CTCF. However, molecular mechanisms underlying this folding, and the way folding affects transcriptional activity, remain obscure. Here we review physical principles driving proteins bound to long polymers into clusters surrounded by loops, and present a parsimonious yet comprehensive model for the way the organization determines function. We argue that clusters of active RNA polymerases and their transcription factors are major architectural features; then, contact domains, TADs and compartments just reflect one or more loops and clusters. We suggest tethering a gene close to a cluster containing appropriate factors—a transcription factory—increases the firing frequency, and offer solutions to many current puzzles concerning the actions of enhancers, super-enhancers, boundaries and eQTLs (expression quantitative trait loci). As a result, the activity of any gene is directly influenced by the activity of other transcription units around it in 3D space, and this is supported by Brownian-dynamics simulations of transcription factors binding to cognate sites on long polymers.

Impact of genome architecture on the functional activation and repression of Hox regulatory landscapes

BACKGROUND

The spatial organization of the mammalian genome relies upon the formation of chromatin domains of various scales. At the level of gene regulation in cis, collections of enhancer sequences define large regulatory landscapes that usually match with the presence of topologically associating domains (TADs). These domains often contain ranges of enhancers displaying similar or related tissue specificity, suggesting that in some cases, such domains may act as coherent regulatory units, with a global on or off state. By using the HoxD gene cluster, which specifies the topology of the developing limbs via highly orchestrated regulation of gene expression, as a paradigm, we investigated how the arrangement of regulatory domains determines their activity and function.

RESULTS

Proximal and distal cells in the developing limb express different levels of Hoxd genes, regulated by flanking 3' and 5' TADs, respectively. We characterized the effect of large genomic rearrangements affecting these two TADs, including their fusion into a single chromatin domain. We show that, within a single hybrid TAD, the activation of both proximal and distal limb enhancers globally occurred as when both TADs are intact. However, the activity of the 3' TAD in distal cells is generally increased in the fused TAD, when compared to wild type where it is silenced. Also, target gene activity in distal cells depends on whether or not these genes had previously responded to proximal enhancers, which determines the presence or absence of H3K27me3 marks. We also show that the polycomb repressive complex 2 is mainly recruited at the Hox gene cluster and can extend its coverage to far-cis regulatory sequences as long as confined to the neighboring TAD structure.

CONCLUSIONS

We conclude that antagonistic limb proximal and distal enhancers can exert their specific effects when positioned into the same TAD and in the absence of their genuine target genes. We also conclude that removing these target genes reduced the coverage of a regulatory landscape by chromatin marks associated with silencing, which correlates with its prolonged activity in time.

Biological characterization of expression quantitative trait loci (eQTLs) showing tissue-specific opposite directional effects

Interpreting the susceptible loci documented by genome-wide association studies (GWASs) is of utmost importance in the post-GWAS era. Since most complex traits are contributed by multiple tissues, analyzing tissue-specific effects of expression quantitative trait loci (eQTLs) is a promising approach. Here we describe “opposite eQTL effects”, i.e., gene expression effects of eQTLs that are in the opposite direction between different tissues, as the biologically meaningful annotations of genes and genetic variants for understanding the GWAS loci. The genes and single-nucleotide polymorphisms (SNPs) associated with the opposite eQTL effects (opp-multi-eQTL-Genes and opp-multi-eQTL-SNPs) were extracted from the largest eQTL database provided by the Genotype-Tissue Expression (GTEx) project (release version 7). The opposite eQTL effects were detected even between closely related tissues such as cerebellum and brain cortex, and a significant proportion of the genes having eQTLs were annotated as the opp-multi-eQTL-Genes (2,323 out of 31,212; 7.4%). The opp-multi-eQTL-SNPs showed locational enrichment at the transcription start site and also possible involvement of epigenetic regulation. The biological importance of the opposite eQTL effects was also assessed using the SNPs reported in GWASs (GWAS-SNPs), which demonstrated that a high proportion of the opp-multi-eQTL-SNPs are in linkage disequilibrium with the GWAS-SNPs (2,498 out of 9,290; 26.9%). Based on the results, the opposite eQTL effects can be a common phenomenon in the tissue-specific gene regulation with a possible contribution to the development of complex traits.

Atlas of Subcellular RNA Localization Revealed by APEX-Seq

We introduce APEX-seq, a method for RNA sequencing based on direct proximity labeling of RNA using the peroxidase enzyme APEX2. APEX-seq in nine distinct subcellular locales produced a nanometer-resolution spatial map of the human transcriptome as a resource, revealing extensive patterns of localization for diverse RNA classes and transcript isoforms. We uncover a radial organization of the nuclear transcriptome, which is gated at the inner surface of the nuclear pore for cytoplasmic export of processed transcripts. We identify two distinct pathways of messenger RNA localization to mitochondria, each associated with specific sets of transcripts for building complementary macromolecular machines within the organelle. APEX-seq should be widely applicable to many systems, enabling comprehensive investigations of the spatial transcriptome.

Three-dimensional chromosome architecture and drug addiction

Aberrant gene expression underlies drug addiction. Therefore, studying the regulation of gene expression in drug addiction may provide mechanistic insights into this disease, for which there are still only limited treatments. Recently, the three-dimensional (3D) organization of linear DNA in the nucleus has been recognized as having a major influence on gene transcription. Here, we review its roles in both basic brain function and neuropsychiatric disorders, while also highlighting its emerging implications in drug addiction. Unraveling the 3D architecture of chromosomes in drug addiction is adding to our understanding of this disease and has the potential to trigger novel approaches for better diagnosis and therapy.

Super-Resolution Microscopy of Chromatin

Since the advent of super-resolution microscopy, countless approaches and studies have been published contributing significantly to our understanding of cellular processes. With the aid of chromatin-specific fluorescence labeling techniques, we are gaining increasing insight into gene regulation and chromatin organization. Combined with super-resolution imaging and data analysis, these labeling techniques enable direct assessment not only of chromatin interactions but also of the function of specific chromatin conformational states.

Mapping chromatin modifications at the single cell level

Understanding chromatin regulation holds enormous promise for controlling gene regulation, predicting cellular identity, and developing diagnostics and cellular therapies. However, the dynamic nature of chromatin, together with cell-to-cell heterogeneity in its structure, limits our ability to extract its governing principles. Single cell mapping of chromatin modifications, in conjunction with expression measurements, could help overcome these limitations. Here, we review recent advances in single cell-based measurements of chromatin modifications, including optimization to reduce DNA loss, improved DNA sequencing, barcoding, and antibody engineering. We also highlight several applications of these techniques that have provided insights into cell-type classification, mapping modification co-occurrence and heterogeneity, and monitoring chromatin dynamics.

The multi-faceted regulation of nuclear tRNA gene transcription

Transfer RNAs are among the most ancient molecules of life on earth. Beyond their crucial role in protein synthesis as carriers of amino acids, they are also important players in a plethora of other biological processes. Many debates in term of biogenesis, regulation and function persist around these fascinating non-coding RNAs. Our review focuses on the first step of their biogenesis in eukaryotes, i.e. their transcription from nuclear genes. Numerous and complementary ways have emerged during evolution to regulate transfer RNA gene transcription. Here, we will summarize the different actors implicated in this process: cis-elements, trans-factors, genomic contexts, epigenetic environments and finally three-dimensional organization of nuclear genomes. © 2019 IUBMB Life, 2019 © 2019 IUBMB Life, 71(8):1099-1108, 2019.

Functional Assays to Screen and Dissect Genomic Hits: Doubling Down on the National Investment in Genomic Research

The National Institutes of Health have made substantial investments in genomic studies and technologies to identify DNA sequence variants associated with human disease phenotypes. The National Heart, Lung, and Blood Institute has been at the forefront of these commitments to ascertain genetic variation associated with heart, lung, blood, and sleep diseases and related clinical traits. Genome-wide association studies, exome- and genome-sequencing studies, and exome-genotyping studies of the National Heart, Lung, and Blood Institute-funded epidemiological and clinical case-control studies are identifying large numbers of genetic variants associated with heart, lung, blood, and sleep phenotypes. However, investigators face challenges in identification of genomic variants that are functionally disruptive among the myriad of computationally implicated variants. Studies to define mechanisms of genetic disruption encoded by computationally identified genomic variants require reproducible, adaptable, and inexpensive methods to screen candidate variant and gene function. High-throughput strategies will permit a tiered variant discovery and genetic mechanism approach that begins with rapid functional screening of a large number of computationally implicated variants and genes for discovery of those that merit mechanistic investigation. As such, improved variant-to-gene and gene-to-function screens-and adequate support for such studies-are critical to accelerating the translation of genomic findings. In this White Paper, we outline the variety of novel technologies, assays, and model systems that are making such screens faster, cheaper, and more accurate, referencing published work and ongoing work supported by the National Heart, Lung, and Blood Institute's R21/R33 Functional Assays to Screen Genomic Hits program. We discuss priorities that can accelerate the impressive but incomplete progress represented by big data genomic research.

The Driving Force: Nuclear Mechanotransduction in Cellular Function, Fate, and Disease

Cellular behavior is continuously affected by microenvironmental forces through the process of mechanotransduction, in which mechanical stimuli are rapidly converted to biochemical responses. Mounting evidence suggests that the nucleus itself is a mechanoresponsive element, reacting to cytoskeletal forces and mediating downstream biochemical responses. The nucleus responds through a host of mechanisms, including partial unfolding, conformational changes, and phosphorylation of nuclear envelope proteins; modulation of nuclear import/export; and altered chromatin organization, resulting in transcriptional changes. It is unclear which of these events present direct mechanotransduction processes and which are downstream of other mechanotransduction pathways. We critically review and discuss the current evidence for nuclear mechanotransduction, particularly in the context of stem cell fate, a largely unexplored topic, and in disease, where an improved understanding of nuclear mechanotransduction is beginning to open new treatment avenues. Finally, we discuss innovative technological developments that will allow outstanding questions in the rapidly growing field of nuclear mechanotransduction to be answered.

Understanding the 3D genome: Emerging impacts on human disease

Recent burst of new technologies that allow for quantitatively delineating chromatin structure has greatly expanded our understanding of how the genome is organized in the three-dimensional (3D) space of the nucleus. It is now clear that the hierarchical organization of the eukaryotic genome critically impacts nuclear activities such as transcription, replication, as well as cellular and developmental events such as cell cycle, cell fate decision and embryonic development. In this review, we discuss new insights into how the structural features of the 3D genome hierarchy are established and maintained, how this hierarchy undergoes dynamic rearrangement during normal development and how its perturbation will lead to human disease, highlighting the accumulating evidence that links the diverse 3D genome architecture components to a multitude of human diseases and the emerging mechanisms by which 3D genome derangement causes disease phenotypes.

Tasks, Techniques, and Tools for Genomic Data Visualization

Genomic data visualization is essential for interpretation and hypothesis generation as well as a valuable aid in communicating discoveries. Visual tools bridge the gap between algorithmic approaches and the cognitive skills of investigators. Addressing this need has become crucial in genomics, as biomedical research is increasingly data-driven and many studies lack well-defined hypotheses. A key challenge in data-driven research is to discover unexpected patterns and to formulate hypotheses in an unbiased manner in vast amounts of genomic and other associated data. Over the past two decades, this has driven the development of numerous data visualization techniques and tools for visualizing genomic data. Based on a comprehensive literature survey, we propose taxonomies for data, visualization, and tasks involved in genomic data visualization. Furthermore, we provide a comprehensive review of published genomic visualization tools in the context of the proposed taxonomies.

Identification of Cancer Drivers at CTCF Insulators in 1,962 Whole Genomes

Recent studies have shown that mutations at non-coding elements, such as promoters and enhancers, can act as cancer drivers. However, an important class of non-coding elements, namely CTCF insulators, has been overlooked in the previous driver analyses. We used insulator annotations from CTCF and cohesin ChIA-PET and analyzed somatic mutations in 1,962 whole genomes from 21 cancer types. Using the heterogeneous patterns of transcription-factor-motif disruption, functional impact, and recurrence of mutations, we developed a computational method that revealed 21 insulators showing signals of positive selection. In particular, mutations in an insulator in multiple cancer types, including 16% of melanoma samples, are associated with TGFB1 up-regulation. Using CRISPR-Cas9, we find that alterations at two of the most frequently mutated regions in this insulator increase cell growth by 40%-50%, supporting the role of this boundary element as a cancer driver. Thus, our study reveals several CTCF insulators as putative cancer drivers.

Determination of local chromatin interactions using a combined CRISPR and peroxidase APEX2 system

The architecture and function of chromatin are largely regulated by local interacting molecules, such as transcription factors and noncoding RNAs. However, our understanding of these regulatory molecules at a given locus is limited because of technical difficulties. Here, we describe the use of Clustered Regularly Interspaced Short Palindromic Repeats and an engineered ascorbate peroxidase 2 (APEX2) system to investigate local chromatin interactions (CAPLOCUS). We showed that with specific small-guide RNA targets, CAPLOCUS could efficiently identify both repetitive genomic regions and single-copy genomic locus with high resolution. Genome-wide sequencing revealed known and potential long-range chromatin interactions for a specific single-copy locus. CAPLOCUS also identified telomere-associated RNAs. CAPLOCUS, followed by mass spectrometry, identified both known and novel telomere-associated proteins in their native states. Thus, CAPLOCUS may be a useful approach for studying local interacting molecules at any given chromosomal location.

Nucleosome dynamics of human iPSC during neural differentiation

Nucleosome positioning is important for neurodevelopment, and genes mediating chromatin remodelling are strongly associated with human neurodevelopmental disorders. To investigate changes in nucleosome positioning during neural differentiation, we generate genome‐wide nucleosome maps from an undifferentiated human‐induced pluripotent stem cell (hiPSC) line and after its differentiation to the neural progenitor cell (NPC) stage. We find that nearly 3% of nucleosomes are highly positioned in NPC, but significantly, there are eightfold fewer positioned nucleosomes in pluripotent cells, indicating increased positioning during cell differentiation. Positioned nucleosomes do not strongly correlate with active chromatin marks or gene transcription. Unexpectedly, we find a small population of nucleosomes that occupy similar positions in pluripotent and neural progenitor cells and are found at binding sites of the key gene regulators NRSF/REST and CTCF. Remarkably, the presence of these nucleosomes appears to be independent of the associated regulatory complexes. Together, these results present a scenario in human cells, where positioned nucleosomes are sparse and dynamic, but may act to alter gene expression at a distance via the structural conformation at sites of chromatin regulation.

Defining the Genetic, Genomic, Cellular, and Diagnostic Architectures of Psychiatric Disorders

Studies of the genetics of psychiatric disorders have become one of the most exciting and fast-moving areas in human genetics. A decade ago, there were few reproducible findings, and now there are hundreds. In this review, we focus on the findings that have illuminated the genetic architecture of psychiatric disorders and the challenges of using these findings to inform our understanding of pathophysiology. The evidence is now overwhelming that psychiatric disorders are "polygenic"-that many genetic loci contribute to risk. With the exception of a subset of those with ASD, few individuals with a psychiatric disorder have a single, deterministic genetic cause; rather, developing a psychiatric disorder is influenced by hundreds of different genetic variants, consistent with a polygenic model. As progressively larger studies have uncovered more about their genetic architecture, the need to elucidate additional architectures has become clear. Even if we were to have complete knowledge of the genetic architecture of a psychiatric disorder, full understanding requires deep knowledge of the functional genomic architecture-the implicated loci impact regulatory processes that influence gene expression and the functional coordination of genes that control biological processes. Following from this is cellular architecture: of all brain regions, cell types, and developmental stages, where and when are the functional architectures operative? Given that the genetic architectures of different psychiatric disorders often strongly overlap, we are challenged to re-evaluate and refine the diagnostic architectures of psychiatric disorders using fundamental genetic and neurobiological data.

Systematic Evaluation of Statistical Methods for Identifying Looping Interactions in 5C Data

Chromosome-Conformation-Capture-Carbon-Copy (5C) is a molecular technology based on proximity ligation that enables high-resolution and high-coverage inquiry of long-range looping interactions. Computational pipelines for analyzing 5C data involve a series of interdependent normalization procedures and statistical methods that markedly influence downstream biological results. A detailed analysis of the trade-offs inherent to all stages of 5C data analysis has not been reported. Here, we provide a comparative assessment of method performance at each step in the 5C analysis pipeline, including sequencing depth and library complexity correction, bias mitigation, spatial noise reduction, distance-dependent expected and variance estimation, statistical modeling, and loop detection. We discuss methodological advantages and disadvantages at each step and provide a full suite of algorithms, lib5C, to allow investigators to test the range of approaches on their own 5C data. Principles learned from our comparative analyses can be applied to protein-independent proximity ligation-based data, including Hi-C, 4C, and Capture-C.

DNA Replication Timing Enters the Single-Cell Era

In mammalian cells, DNA replication timing is controlled at the level of megabase (Mb)-sized chromosomal domains and correlates well with transcription, chromatin structure, and three-dimensional (3D) genome organization. Because of these properties, DNA replication timing is an excellent entry point to explore genome regulation at various levels and a variety of studies have been carried out over the years. However, DNA replication timing studies traditionally required at least tens of thousands of cells, and it was unclear whether the replication domains detected by cell population analyses were preserved at the single-cell level. Recently, single-cell DNA replication profiling methods became available, which revealed that the Mb-sized replication domains detected by cell population analyses were actually well preserved in individual cells. In this article, we provide a brief overview of our current knowledge on DNA replication timing regulation in mammals based on cell population studies, outline the findings from single-cell DNA replication profiling, and discuss future directions and challenges.

Cohesin-Mediated Genome Architecture Does Not Define DNA Replication Timing Domains

3D genome organization is strongly predictive of DNA replication timing in mammalian cells. This work tested the extent to which loop-based genome architecture acts as a regulatory unit of replication timing by using an auxin-inducible system for acute cohesin ablation. Cohesin ablation in a population of cells in asynchronous culture was shown not to disrupt patterns of replication timing as assayed by replication sequencing (RepliSeq) or BrdU-focus microscopy. Furthermore, cohesin ablation prior to S phase entry in synchronized cells was similarly shown to not impact replication timing patterns. These results suggest that cohesin-mediated genome architecture is not required for the execution of replication timing patterns in S phase, nor for the establishment of replication timing domains in G1.

Rhodamine-Hoechst positional isomers for highly efficient staining of heterochromatin

Hoechst conjugates to fluorescent dyes are popular DNA stains for live-cell imaging, but the relationship between their structure and performance remains elusive. This study of carboxyrhodamine-Hoechst 33258 conjugates reveals that a minimal change in the attachment point of the dye has dramatic effects on the properties of the final probe. All tested 6'-carboxyl dye-containing probes exhibited dual-mode binding to DNA and formed a dimmer complex at high DNA concentrations. The 5'-carboxyl dye-containing probes exhibited single-mode binding to DNA which translated into increased brightness and lower cytotoxicity. Up to 10-fold brighter nuclear staining by the newly developed probes allowed acquisition of stimulated emission depletion (STED) nanoscopy images of outstanding quality in living and fixed cells. Therefore we were able to estimate a diameter of ∼155 nm of the heterochromatin exclusion zones in the nuclear pore region in living cells and intact chicken erythrocytes and to localize telomeres relative to heterochromatin in living U-2 OS cells. Employing the highly efficient probes for two-color STED allowed visualization of DNA and tubulin structures in intact nucleated erythrocytes - a system where imaging is greatly hampered by high haemoglobin absorbance.

Extensive Heterogeneity and Intrinsic Variation in Spatial Genome Organization

Several general principles of global 3D genome organization have recently been established, including non-random positioning of chromosomes and genes in the cell nucleus, distinct chromatin compartments, and topologically associating domains (TADs). However, the extent and nature of cell-to-cell and cell-intrinsic variability in genome architecture are still poorly characterized. Here, we systematically probe heterogeneity in genome organization. High-throughput optical mapping of several hundred intra-chromosomal interactions in individual human fibroblasts demonstrates low association frequencies, which are determined by genomic distance, higher-order chromatin architecture, and chromatin environment. The structure of TADs is variable between individual cells, and inter-TAD associations are common. Furthermore, single-cell analysis reveals independent behavior of individual alleles in single nuclei. Our observations reveal extensive variability and heterogeneity in genome organization at the level of individual alleles and demonstrate the coexistence of a broad spectrum of genome configurations in a cell population.

Lineage-specific reorganization of nuclear peripheral heterochromatin and H3K9me2 domains

Dynamic organization of chromatin within the three-dimensional nuclear space has been postulated to regulate gene expression and cell fate. Here, we define the genome-wide distribution of nuclear peripheral heterochromatin as a multipotent P19 cell adopts either a neural or a cardiac fate. We demonstrate that H3K9me2-marked nuclear peripheral heterochromatin undergoes lineage-specific reorganization during cell-fate determination. This is associated with spatial repositioning of genomic loci away from the nuclear periphery as shown by 3D immuno-FISH. Locus repositioning is not always associated with transcriptional changes, but a subset of genes is upregulated. Mef2c is specifically repositioned away from the nuclear periphery during early neurogenic differentiation, but not during early cardiogenic differentiation, with associated transcript upregulation. Myocd is specifically repositioned during early cardiogenic differentiation, but not during early neurogenic differentiation, and is transcriptionally upregulated at later stages of cardiac differentiation. We provide experimental evidence for lineage-specific regulation of nuclear architecture during cell-fate determination in a mouse cell line.

Chromosomes in the DNA era: Perspectives in diagnostics and research

Chromosomes were discovered more than 130 years ago. The implementation of chromosomal investigations in clinical diagnostics was fueled by determining the correct number of human chromosomes to be 46 and the development of specific banding techniques. Subsequent technical improvements in the field of genetic diagnostics, such as fluorescence in situ hybridization (FISH), chromosomal microarrays (CMA, array CGH) or next-generation sequencing (NGS) techniques, partially succeeded in overcoming limitations of banding cytogenetics. Consequently, nowadays, higher diagnostic yields can be achieved if new approaches such as NGS, CMA or FISH are applied in combination with cytogenetics. Nonetheless, high-resolution DNA-focused techniques have dominated clinical diagnostics more recently, rather than a “chromosomic view,” including banding cytogenetics as a precondition for the application of higher resolution methods. Currently, there is a renaissance of this “chromosomic view” in research, understanding chromosomes to be an essential feature of genomic architecture, owing to the discovery of (i) higher order chromosomal sub-compartments, (ii) chromosomal features that influence genomic architecture, gene expression, and evolution, and (iii) 3D and 4D chromatin organization within the nucleus, including the complex way in which chromosomes interact with each other. Interestingly, in many instances research was triggered by specific clinical diagnostic cases or diseases that contributed to new and fascinating insights, not only into disease mechanisms but also into basic principles of chromosome biology. Here we review the role, the intrinsic value, and the perspectives of chromosomes in a molecular genetics-dominated human genetics diagnostic era and make comparison with basic research, where these benefits are well-recognized.

The multidimensional brain

Brain activity takes place in three spatial-plus time dimensions. This rather obvious claim has been recently questioned by papers that, taking into account the big data outburst and novel available computational tools, are starting to unveil a more intricate state of affairs. Indeed, various brain activities and their correlated mental functions can be assessed in terms of trajectories embedded in phase spaces of dimensions higher than the canonical ones. In this review, I show how further dimensions may not just represent a convenient methodological tool that allows a better mathematical treatment of otherwise elusive cortical activities, but may also reflect genuine functional or anatomical relationships among real nervous functions. I then describe how to extract hidden multidimensional information from real or artificial neurodata series, and make clear how our mind dilutes, rather than concentrates as currently believed, inputs coming from the environment. Finally, I argue that the principle "the higher the dimension, the greater the information" may explain the occurrence of mental activities and elucidate the mechanisms of human diseases associated with dimensionality reduction.

Deciphering Hi-C: from 3D genome to function

Hi-C is a commonly used technology in 3D genomics which can depict global chromatin interactions across eukaryotic genome. Integrating with different datasets, it can also be applied to studying various biological questions, such as nuclear organization, gene transcription regulation, spatiotemporal development, genome assembly, and cancer genomics. During the last decade, the development and application of Hi-C have dramatically changed the view of genome architecture, chromatin conformation, and gene interaction. So far, Hi-C-related studies remain vivacious and controversial; thus, a unified standard of library construction and bioinformatics analysis are urgently needed. In this review, we have summarized its history, development, methodologies, advances, applications, shortages, and future perspectives. We discuss a few limitations of the current Hi-C technologies and future directions for improvement and highlight how Hi-C can bridge 3D structure to gene function. This review will be helpful for scientists who want to engage in the 3D genomics field; it also shows some future tracks.

Epigenetic Regulation of Chromatin in Prostate Cancer

Epigenetics refers to mitotically/meiotically heritable mechanisms that regulate gene transcription without a need for changes in the DNA code. Covalent modifications of DNA, in the form of methylation, and histone post-translational modifications, in the form of acetylation and methylation, constitute the epigenetic code of a cell. Both DNA and histone modifications are highly dynamic and often work in unison to define the epigenetic state of a cell. Most epigenetic mechanisms regulate gene transcription by affecting localized/genome-wide transitions between heterochromatin and euchromatin states, thereby altering the accessibility of the transcriptional machinery and in turn, reduce/increase transcriptional output. Altered chromatin structure is associated with cancer progression, and epigenetic plasticity primarily governs the resistance of cancer cells to therapeutic agents. In this chapter, we specifically focus on regulators of histone methylation and acetylation, the two well-studied chromatin post-translational modifications, in the context of prostate cancer.

Computational methods for analyzing and modeling genome structure and organization

Recent advances in chromosome conformation capture technologies have led to the discovery of previously unappreciated structural features of chromatin. Computational analysis has been critical in detecting these features and thereby helping to uncover the building blocks of genome architecture. Algorithms are being developed to integrate these architectural features to construct better three-dimensional (3D) models of the genome. These computational methods have revealed the importance of 3D genome organization to essential biological processes. In this article, we review the state of the art in analytic and modeling techniques with a focus on their application to answering various biological questions related to chromatin structure. We summarize the limitations of these computational techniques and suggest future directions, including the importance of incorporating multiple sources of experimental data in building a more comprehensive model of the genome. This article is categorized under: Analytical and Computational Methods > Computational Methods Laboratory Methods and Technologies > Genetic/Genomic Methods Models of Systems Properties and Processes > Mechanistic Models.

A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome

Central questions to epigenome evolution include whether interspecies changes of histone modifications are independent of evolutionary changes of DNA, and if there is dependence whether they depend on any specific types of DNA sequence changes. Here, we present a likelihood approach for testing hypotheses on the co-evolution of genome and histone modifications. The gist of this approach is to convert evolutionary biology hypotheses into probabilistic forms, by explicitly expressing the joint probability of multispecies DNA sequences and histone modifications, which we refer to as a class of Joint Evolutionary Model for the Genome and the Epigenome (JEMGE). JEMGE can be summarized as a mixture model of four components representing four evolutionary hypotheses, namely dependence and independence of interspecies epigenomic variations to underlying sequence substitutions and to underlying sequence insertions and deletions (indels). We implemented a maximum likelihood method to fit the models to the data. Based on comparison of likelihoods, we inferred whether interspecies epigenomic variations depended on substitution or indels in local genomic sequences based on DNase hypersensitivity and spermatid H3K4me3 ChIP-seq data from human and rhesus macaque. Approximately 5.5% of homologous regions in the genomes exhibited H3K4me3 modification in either species, among which approximately 67% homologous regions exhibited local-sequence-dependent interspecies H3K4me3 variations. Substitutions accounted for less local-sequence-dependent H3K4me3 variations than indels. Among transposon-mediated indels, ERV1 insertions and L1 insertions were most strongly associated with H3K4me3 gains and losses, respectively. By initiating probabilistic formulation on the co-evolution of genomes and epigenomes, JEMGE helps to bring evolutionary biology principles to comparative epigenomic studies.

Epigenetic modifications play a significant role in gene regulations and thus heavily influence phenotypic outcomes. Whereas cross-species epigenomic comparisons have been fruitful in revealing the function of epigenetic modifications, it still remains unclear how the epigenome changes across species. A central question in epigenome evolution studies is whether interspecies epigenomic variations rely on genomic changes in cis and, if partially yes, whether different genomic changes have distinct impacts. To tackle this question, we initiated a likelihood-based approach, in which different hypotheses related to the co-evolution of the genome and the epigenome could be converted into probabilistic models. By fitting the models to actual data, each model yielded a likelihood, and the hypothesis corresponded to the largest likelihood was selected as most supported by observed data. In this work, we focused on the influence of two types of underlying sequence changes: substitutions, and insertions and deletions (indels). We quantitatively assessed the dependence of H3K4me3 variations on substitutions and indels between human and rhesus, and separated their relative impacts within each genomic region with H3K4me3. The methodology presented here provides a framework for modeling the epigenome together with the genome and a quantitative approach to test different evolutionary hypotheses.

Hi-C analysis: from data generation to integration

In the epigenetics field, large-scale functional genomics datasets of ever-increasing size and complexity have been produced using experimental techniques based on high-throughput sequencing. In particular, the study of the 3D organization of chromatin has raised increasing interest, thanks to the development of advanced experimental techniques. In this context, Hi-C has been widely adopted as a high-throughput method to measure pairwise contacts between virtually any pair of genomic loci, thus yielding unprecedented challenges for analyzing and handling the resulting complex datasets. In this review, we focus on the increasing complexity of available Hi-C datasets, which parallels the adoption of novel protocol variants. We also review the complexity of the multiple data analysis steps required to preprocess Hi-C sequencing reads and extract biologically meaningful information. Finally, we discuss solutions for handling and visualizing such large genomics datasets.

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.

Nucleosome structure and dynamics are coming of age

Since the first high-resolution structure of the nucleosome was reported in 1997, the available information on chromatin structure has increased very rapidly. Here, we review insights derived from cutting-edge biophysical and structural approaches applied to the study of nucleosome dynamics and nucleosome-binding factors, with a focus on the experimental advances driving the research. In addition, we highlight emerging challenges in nucleosome structural biology.

Chain organization of human interphase chromosome determines the spatiotemporal dynamics of chromatin loci

We investigate spatiotemporal dynamics of human interphase chromosomes by employing a heteropolymer model that incorporates the information of human chromosomes inferred from Hi-C data. Despite considerable heterogeneities in the chromosome structures generated from our model, chromatins are organized into crumpled globules with space-filling (SF) statistics characterized by a single universal scaling exponent (ν = 1/3), and this exponent alone can offer a quantitative account of experimentally observed, many different features of chromosome dynamics. The local chromosome structures, whose scale corresponds to that of topologically associated domains (∼ 0.1 − 1 Mb), display dynamics with a fast relaxation time (≲ 1 − 10 sec); in contrast, the long-range spatial reorganization of the entire chromatin (≳O(102) Mb) occurs on a much slower time scale (≳ hour), providing the dynamic basis of cell-to-cell variability and glass-like behavior of chromosomes. Biological activities, modeled using stronger isotropic white noises added to active loci, accelerate the relaxation dynamics of chromatin domains associated with the low frequency modes and induce phase segregation between the active and inactive loci. Surprisingly, however, they do not significantly change the dynamics at local scales from those obtained under passive conditions. Our study underscores the role of chain organization of chromosome in determining the spatiotemporal dynamics of chromatin loci.

Chromosomes are giant chain molecules made of hundreds of megabase-long DNA intercalated with proteins. Structure and dynamics of interphase chromatin in space and time hold the key to understanding the cell type-dependent gene regulation. In this study, we establish that the crumpled and space-filling (SF) organization of chromatin fiber in the chromosome territory, characterized by a single scaling exponent, is sufficient to explain the complex spatiotemporal hierarchy in chromatin dynamics as well as the subdiffusive motion of the chromatin loci. While seemingly a daunting problem at a first glance, our study shows that relatively simple principles, rooted in polymer physics, can be used to grasp the essence of dynamical properties of the interphase chromatin.

Communicating Genome Architecture: Biovisualization of the Genome, from Data Analysis and Hypothesis Generation to Communication and Learning

Genome discoveries at the core of biology are made by visual description and exploration of the cell, from microscopic sketches and biochemical mapping to computational analysis and spatial modeling. We outline the experimental and visualization techniques that have been developed recently which capture the three-dimensional interactions regulating how genes are expressed. We detail the challenges faced in integration of the data to portray the components and organization and their dynamic landscape. The goal is more than a single data-driven representation as interactive visualization for de novo research is paramount to decipher insights on genome organization in space.

The senescent cell epigenome

A critical hallmark of aging is cellular senescence, a state of growth arrest and inflammatory cytokine release in cells, caused by a variety of stresses. Recent work has convincingly linked the accumulation of senescent cells in aged tissues to a decline in health and a limit of lifespan, primarily through "inflammaging". Importantly, interventions that clear senescent cells have achieved marked improvements in healthspan and lifespan in mice. A growing list of studies show that environmental stimuli can affect aging and longevity through conserved pathways which, in turn, modulate chromatin states. This review consolidates key findings of chromatin state changes in senescence including histone modifications, histone variants, DNA methylation and changes in three-dimensional genome organization. This information will facilitate the identification of mechanisms and discovery of potential epigenetic targets for therapeutic interventions in aging and age-related disease.

CRISPR-Sirius: RNA scaffolds for signal amplification in genome imaging

Clustered regularly interspaced short palindromic repeats (CRISPR) guide RNA scaffolds have been adapted to carry multiple binding sites for fluorescent proteins to enhance brightness for live cell imaging of genomic loci. However, many of these modifications result in guide RNA instability and thus produce lower genome-labeling efficiency than anticipated. Here we introduce CRISPR-Sirius, based on octet arrays of aptamers conferring both enhanced guide RNA stability and brightness, and provide initial biological applications of this platform.

Visual Pattern-Driven Exploration of Big Data

Pattern extraction algorithms are enabling insights into the ever-growing amount of today's datasets by translating reoccurring data properties into compact representations. Yet, a practical problem arises: With increasing data volumes and complexity also the number of patterns increases, leaving the analyst with a vast result space. Current algorithmic and especially visualization approaches often fail to answer central overview questions essential for a comprehensive understanding of pattern distributions and support, their quality, and relevance to the analysis task. To address these challenges, we contribute a visual analytics pipeline targeted on the pattern-driven exploration of result spaces in a semi-automatic fashion. Specifically, we combine image feature analysis and unsupervised learning to partition the pattern space into interpretable, coherent chunks, which should be given priority in a subsequent in-depth analysis. In our analysis scenarios, no ground-truth is given. Thus, we employ and evaluate novel quality metrics derived from the distance distributions of our image feature vectors and the derived cluster model to guide the feature selection process. We visualize our results interactively, allowing the user to drill down from overview to detail into the pattern space and demonstrate our techniques in two case studies on Earth observation and biomedical genomic data.

The seekers: how epigenetic modifying enzymes find their hidden genomic targets in Arabidopsis

Epigenetic regulation plays fundamental roles in modulating chromatin-based processes and shaping the epigenome in multicellular eukaryotes, including plants. How epigenetic factors recognize their target loci hiding in the vast genomic DNA sequence remains a long-standing mystery. During the past several years, a growing body of work has revealed the complex, dynamic, and diverse chromatin-targeting mechanisms of these epigenetic factors. In this review, we focus on recent advances in understanding the recruitment of epigenetic factors to specific genomic regions, based on data from Arabidopsis thaliana.

From association to mechanism in complex disease genetics: the role of the 3D genome

Genome-wide association studies (GWAS) and fine mapping studies in autoimmune diseases have identified thousands of genetic variants, the majority of which are located in non-protein-coding enhancer regions. Enhancers function within the context of the three-dimensional (3D) genome to form long-range DNA looping events with target gene promoters that spatially and temporally regulate gene expression. Investigating the functional significance of GWAS variants in the context of the 3D genome is essential for mechanistic understanding of these variants and how they influence disease pathology by altering DNA looping between enhancers and the target gene promoters they regulate. In this review, we discuss the functional complexity of the 3D genome and the technological approaches used to characterize DNA looping events. We then highlight examples from the literature that illustrate how functional mapping of the 3D genome can assist in defining mechanisms that influence pathogenic gene expression. We conclude by highlighting future advances necessary to fully integrate 3D genome analyses into the functional workup of GWAS variants in the continuing effort to improve the health of patients with autoimmune diseases.

Challenges and guidelines toward 4D nucleome data and model standards

Due to recent advances in experimental and theoretical approaches, the dynamic three-dimensional organization (3D) of the nucleus has become a very active area of research in life sciences. We now understand that the linear genome is folded in ways that may modulate how genes are expressed during the basic functioning of cells. Importantly, it is now possible to build 3D models of how the genome folds within the nucleus and changes over time (4D). Because genome folding influences its function, this opens exciting new possibilities to broaden our understanding of the mechanisms that determine cell fate. However, the rapid evolution of methods and the increasing complexity of data can result in ambiguity and reproducibility challenges, which may hamper the progress of this field. Here, we describe such challenges ahead and provide guidelines to think about strategies for shared standardized validation of experimental 4D nucleome data sets and models.