High-resolution single-cell 3D-models of chromatin ensembles during Drosophila embryogenesis

OpenNucleome for high-resolution nuclear structural and dynamical modeling

The intricate structural organization of the human nucleus is fundamental to cellular function and gene regulation. Recent advancements in experimental techniques, including high-throughput sequencing and microscopy, have provided valuable insights into nuclear organization. Computational modeling has played significant roles in interpreting experimental observations by reconstructing high-resolution structural ensembles and uncovering organization principles. However, the absence of standardized modeling tools poses challenges for furthering nuclear investigations. We present OpenNucleome-an open-source software designed for conducting GPU-accelerated molecular dynamics simulations of the human nucleus. OpenNucleome offers particle-based representations of chromosomes at a resolution of 100 KB, encompassing nuclear lamina, nucleoli, and speckles. This software furnishes highly accurate structural models of nuclear architecture, affording the means for dynamic simulations of condensate formation, fusion, and exploration of non-equilibrium effects. We applied OpenNucleome to uncover the mechanisms driving the emergence of 'fixed points' within the nucleus-signifying genomic loci robustly anchored in proximity to specific nuclear bodies for functional purposes. This anchoring remains resilient even amidst significant fluctuations in chromosome radial positions and nuclear shapes within individual cells. Our findings lend support to a nuclear zoning model that elucidates genome functionality. We anticipate OpenNucleome to serve as a valuable tool for nuclear investigations, streamlining mechanistic explorations and enhancing the interpretation of experimental observations.

From Nucleosomes to Compartments: Physicochemical Interactions Underlying Chromatin Organization

Chromatin organization plays a critical role in cellular function by regulating access to genetic information. However, understanding chromatin folding is challenging due to its complex, multiscale nature. Significant progress has been made in studying in vitro systems, uncovering the structure of individual nucleosomes and their arrays, and elucidating the role of physicochemical forces in stabilizing these structures. Additionally, remarkable advancements have been achieved in characterizing chromatin organization in vivo, particularly at the whole-chromosome level, revealing important features such as chromatin loops, topologically associating domains, and nuclear compartments. However, bridging the gap between in vitro and in vivo studies remains challenging. The resemblance between in vitro and in vivo chromatin conformations and the relevance of internucleosomal interactions for chromatin folding in vivo are subjects of debate. This article reviews experimental and computational studies conducted at various length scales, highlighting the significance of intrinsic interactions between nucleosomes and their roles in chromatin folding in vivo.

Chromosome structure modeling tools and their evaluation in bacteria

The three-dimensional (3D) structure of bacterial chromosomes is crucial for understanding chromosome function. With the growing availability of high-throughput chromosome conformation capture (3C/Hi-C) data, the 3D structure reconstruction algorithms have become powerful tools to study bacterial chromosome structure and function. It is highly desired to have a recommendation on the chromosome structure reconstruction tools to facilitate the prokaryotic 3D genomics. In this work, we review existing chromosome 3D structure reconstruction algorithms and classify them based on their underlying computational models into two categories: constraint-based modeling and thermodynamics-based modeling. We briefly compare these algorithms utilizing 3C/Hi-C datasets and fluorescence microscopy data obtained from Escherichia coli and Caulobacter crescentus, as well as simulated datasets. We discuss current challenges in the 3D reconstruction algorithms for bacterial chromosomes, primarily focusing on software usability. Finally, we briefly prospect future research directions for bacterial chromosome structure reconstruction algorithms.

Efficient Hi-C inversion facilitates chromatin folding mechanism discovery and structure prediction

Genome-wide chromosome conformation capture (Hi-C) experiments have revealed many structural features of chromatin across multiple length scales. Further understanding genome organization requires relating these discoveries to the mechanisms that establish chromatin structures and reconstructing these structures in three dimensions, but both objectives are difficult to achieve with existing algorithms that are often computationally expensive. To alleviate this challenge, we present an algorithm that efficiently converts Hi-C data into contact energies, which measure the interaction strength between genomic loci brought into proximity. Contact energies are local quantities unaffected by the topological constraints that correlate Hi-C contact probabilities. Thus, extracting contact energies from Hi-C contact probabilities distills the biologically unique information contained in the data. We show that contact energies reveal the location of chromatin loop anchors, support a phase separation mechanism for genome compartmentalization, and parameterize polymer simulations that predict three-dimensional chromatin structures. Therefore, we anticipate that contact energy extraction will unleash the full potential of Hi-C data and that our inversion algorithm will facilitate the widespread adoption of contact energy analysis.

Efficient Hi-C inversion facilitates chromatin folding mechanism discovery and structure prediction

Genome-wide chromosome conformation capture (Hi-C) experiments have revealed many structural features of chromatin across multiple length scales. Further understanding genome organization requires relating these discoveries to the mechanisms that establish chromatin structures and reconstructing these structures in three dimensions, but both objectives are difficult to achieve with existing algorithms that are often computationally expensive. To alleviate this challenge, we present an algorithm that efficiently converts Hi-C data into contact energies, which measure the interaction strength between genomic loci brought into proximity. Contact energies are local quantities unaffected by the topological constraints that correlate Hi-C contact probabilities. Thus, extracting contact energies from Hi-C contact probabilities distills the biologically unique information contained in the data. We show that contact energies reveal the location of chromatin loop anchors, support a phase separation mechanism for genome compartmentalization, and parameterize polymer simulations that predict three-dimensional chromatin structures. Therefore, we anticipate that contact energy extraction will unleash the full potential of Hi-C data and that our inversion algorithm will facilitate the widespread adoption of contact energy analysis.

Homologous chromosome recognition via nonspecific interactions

In many organisms, most notably Drosophila, homologous chromosomes in somatic cells associate with each other, a phenomenon known as somatic homolog pairing. Unlike in meiosis, where homology is read out at the level of DNA sequence complementarity, somatic homolog pairing takes place without double strand breaks or strand invasion, thus requiring some other mechanism for homologs to recognize each other. Several studies have suggested a "specific button" model, in which a series of distinct regions in the genome, known as buttons, can associate with each other, presumably mediated by different proteins that bind to these different regions. Here we consider an alternative model, which we term the "button barcode" model, in which there is only one type of recognition site or adhesion button, present in many copies in the genome, each of which can associate with any of the others with equal affinity. An important component of this model is that the buttons are non-uniformly distributed, such that alignment of a chromosome with its correct homolog, compared with a non-homolog, is energetically favored; since to achieve nonhomologous alignment, chromosomes would be required to mechanically deform in order to bring their buttons into mutual register. We investigated several types of barcodes and examined their effect on pairing fidelity. We found that high fidelity homolog recognition can be achieved by arranging chromosome pairing buttons according to an actual industrial barcode used for warehouse sorting. By simulating randomly generated non-uniform button distributions, many highly effective button barcodes can be easily found, some of which achieve virtually perfect pairing fidelity. This model is consistent with existing literature on the effect of translocations of different sizes on homolog pairing. We conclude that a button barcode model can attain highly specific homolog recognition, comparable to that seen in actual cells undergoing somatic homolog pairing, without the need for specific interactions. This model may have implications for how meiotic pairing is achieved.

An Igh distal enhancer modulates antigen receptor diversity by determining locus conformation

The mouse Igh locus is organized into a developmentally regulated topologically associated domain (TAD) that is divided into subTADs. Here we identify a series of distal V_H enhancers (E_VHs) that collaborate to configure the locus. E_VHs engage in a network of long-range interactions that interconnect the subTADs and the recombination center at the D_HJ_H gene cluster. Deletion of E_VH1 reduces V gene rearrangement in its vicinity and alters discrete chromatin loops and higher order locus conformation. Reduction in the rearrangement of the V_H11 gene used in anti-PtC responses is a likely cause of the observed reduced splenic B1 B cell compartment. E_VH1 appears to block long-range loop extrusion that in turn contributes to locus contraction and determines the proximity of distant V_H genes to the recombination center. E_VH1 is a critical architectural and regulatory element that coordinates chromatin conformational states that favor V(D)J rearrangement.

The dynamics of three-dimensional chromatin organization and phase separation in cell fate transitions and diseases

Cell fate transition is a fascinating process involving complex dynamics of three-dimensional (3D) chromatin organization and phase separation, which play an essential role in cell fate decision by regulating gene expression. Phase separation is increasingly being considered a driving force of chromatin folding. In this review, we have summarized the dynamic features of 3D chromatin and phase separation during physiological and pathological cell fate transitions and systematically analyzed recent evidence of phase separation facilitating the chromatin structure. In addition, we discuss current advances in understanding how phase separation contributes to physical and functional enhancer-promoter contacts. We highlight the functional roles of 3D chromatin organization and phase separation in cell fate transitions, and more explorations are required to study the regulatory relationship between 3D chromatin organization and phase separation. 3D chromatin organization (shown by Hi-C contact map) and phase separation are highly dynamic and play functional roles during early embryonic development, cell differentiation, somatic reprogramming, cell transdifferentiation and pathogenetic process. Phase separation can regulate 3D chromatin organization directly, but whether 3D chromatin organization regulates phase separation remains unclear.

Application of the 3C Method to Study the Developmental Genes in Drosophila Larvae

A transition from one developmental stage to another is accompanied by activation of developmental programs and corresponding gene ensembles. Changes in the spatial conformation of the corresponding loci are associated with this activation and can be investigated with the help of the Chromosome Conformation Capture (3C) methodology. Application of 3C to specific developmental stages is a sophisticated task. Here, we describe the use of the 3C method to study the spatial organization of developmental loci in Drosophila larvae. We critically analyzed the existing protocols and offered our own solutions and the optimized protocol to overcome limitations. To demonstrate the efficiency of our procedure, we studied the spatial organization of the developmental locus Dad in 3rd instar Drosophila larvae. Differences in locus conformation were found between embryonic cells and living wild-type larvae. We also observed the establishment of novel regulatory interactions in the presence of an adjacent transgene upon activation of its expression in larvae. Our work fills the gap in the application of the 3C method to Drosophila larvae and provides a useful guide for establishing 3C on an animal model.

Uncovering the statistical physics of 3D chromosomal organization using data-driven modeling

In recent years, much effort has been devoted to understanding the three-dimensional (3D) organization of the genome and how genomic structure mediates nuclear function. The development of experimental techniques that combine DNA proximity ligation with high-throughput sequencing, such as Hi-C, have substantially improved our knowledge about chromatin organization. Numerous experimental advancements, not only utilizing DNA proximity ligation but also high-resolution genome imaging (DNA tracing), have required theoretical modeling to determine the structural ensembles consistent with such data. These 3D polymer models of the genome provide an understanding of the physical mechanisms governing genome architecture. Here, we present an overview of the recent advances in modeling the ensemble of 3D chromosomal structures by employing the maximum entropy approach combined with polymer physics. Particularly, we discuss the minimal chromatin model (MiChroM) along with the "maximum entropy genomic annotations from biomarkers associated with structural ensembles" (MEGABASE) model, which have been remarkably successful in the accurate modeling of chromosomes consistent with both Hi-C and DNA-tracing data.

Modeling and simulation of cell nuclear architecture reorganization process

We develop a special phase field/diffusive interface method to model the nuclear architecture reorganization process. In particular, we use a Lagrange multiplier approach in the phase field model to preserve the specific physical and geometrical constraints for the biological events. We develop several efficient and robust linear and weakly nonlinear schemes for this new model. To validate the model and numerical methods, we present ample numerical simulations which in particular reproduce several processes of nuclear architecture reorganization from the experiment literature.

Understanding 3D Genome Organization and Its Effect on Transcriptional Gene Regulation Under Environmental Stress in Plant: A Chromatin Perspective

The genome of a eukaryotic organism is comprised of a supra-molecular complex of chromatin fibers and intricately folded three-dimensional (3D) structures. Chromosomal interactions and topological changes in response to the developmental and/or environmental stimuli affect gene expression. Chromatin architecture plays important roles in DNA replication, gene expression, and genome integrity. Higher-order chromatin organizations like chromosome territories (CTs), A/B compartments, topologically associating domains (TADs), and chromatin loops vary among cells, tissues, and species depending on the developmental stage and/or environmental conditions (4D genomics). Every chromosome occupies a separate territory in the interphase nucleus and forms the top layer of hierarchical structure (CTs) in most of the eukaryotes. While the A and B compartments are associated with active (euchromatic) and inactive (heterochromatic) chromatin, respectively, having well-defined genomic/epigenomic features, TADs are the structural units of chromatin. Chromatin architecture like TADs as well as the local interactions between promoter and regulatory elements correlates with the chromatin activity, which alters during environmental stresses due to relocalization of the architectural proteins. Moreover, chromatin looping brings the gene and regulatory elements in close proximity for interactions. The intricate relationship between nucleotide sequence and chromatin architecture requires a more comprehensive understanding to unravel the genome organization and genetic plasticity. During the last decade, advances in chromatin conformation capture techniques for unravelling 3D genome organizations have improved our understanding of genome biology. However, the recent advances, such as Hi-C and ChIA-PET, have substantially increased the resolution, throughput as well our interest in analysing genome organizations. The present review provides an overview of the historical and contemporary perspectives of chromosome conformation capture technologies, their applications in functional genomics, and the constraints in predicting 3D genome organization. We also discuss the future perspectives of understanding high-order chromatin organizations in deciphering transcriptional regulation of gene expression under environmental stress (4D genomics). These might help design the climate-smart crop to meet the ever-growing demands of food, feed, and fodder.

Chromatin as self-returning walks: From population to single cell and back

With a growing understanding of the chromatin structure, many efforts remain focused on bridging the gap between what is suggested by population-averaged data and what is visualized for single cells. A popular approach to traversing these scales is to fit a polymer model to Hi-C contact data. However, Hi-C is an average of millions to billions of cells, and each cell may not contain all population-averaged contacts. Therefore, we employ a novel approach of summing individual chromosome trajectories-determined by our Self-Returning Random Walk model-to create populations of cells. We allow single cells to consist of disparate structures and reproduce a variety of experimentally relevant contact maps. We show that the amount of shared topology between cells, and their mechanism of formation, changes the population-averaged structure. Therefore, we present a modeling technique that, with few constraints and little oversight, can be used to understand which single-cell chromatin structures underlie population-averaged behavior.

Single-cell Hi-C data analysis: safety in numbers

Over the past decade, genome-wide assays for chromatin interactions in single cells have enabled the study of individual nuclei at unprecedented resolution and throughput. Current chromosome conformation capture techniques survey contacts for up to tens of thousands of individual cells, improving our understanding of genome function in 3D. However, these methods recover a small fraction of all contacts in single cells, requiring specialised processing of sparse interactome data. In this review, we highlight recent advances in methods for the interpretation of single-cell genomic contacts. After discussing the strengths and limitations of these methods, we outline frontiers for future development in this rapidly moving field.

Multiscale modeling of genome organization with maximum entropy optimization

Three-dimensional (3D) organization of the human genome plays an essential role in all DNA-templated processes, including gene transcription, gene regulation, and DNA replication. Computational modeling can be an effective way of building high-resolution genome structures and improving our understanding of these molecular processes. However, it faces significant challenges as the human genome consists of over 6 × 109 base pairs, a system size that exceeds the capacity of traditional modeling approaches. In this perspective, we review the progress that has been made in modeling the human genome. Coarse-grained models parameterized to reproduce experimental data via the maximum entropy optimization algorithm serve as effective means to study genome organization at various length scales. They have provided insight into the principles of whole-genome organization and enabled de novo predictions of chromosome structures from epigenetic modifications. Applications of these models at a near-atomistic resolution further revealed physicochemical interactions that drive the phase separation of disordered proteins and dictate chromatin stability in situ. We conclude with an outlook on the opportunities and challenges in studying chromosome dynamics.

Multi-Scale Organization of the Drosophila melanogaster Genome

Interphase chromatin, despite its appearance, is a highly organized framework of loops and bends. Chromosomes are folded into topologically associating domains, or TADs, and each chromosome and its homolog occupy a distinct territory within the nucleus. In Drosophila, genome organization is exceptional because homologous chromosome pairing is in both germline and somatic tissues, which promote interhomolog interactions such as transvection that can affect gene expression in trans. In this review, we focus on what is known about genome organization in Drosophila and discuss it from TADs to territory. We start by examining intrachromosomal organization at the sub-chromosome level into TADs, followed by a comprehensive analysis of the known proteins that play a key role in TAD formation and boundary establishment. We then zoom out to examine interhomolog interactions such as pairing and transvection that are abundant in Drosophila but rare in other model systems. Finally, we discuss chromosome territories that form within the nucleus, resulting in a complete picture of the multi-scale organization of the Drosophila genome.