Four-dimensional chromosome reconstruction elucidates the spatiotemporal reorganization of the mammalian X chromosome

PRC2-RNA interactions: Viewpoint from YongWoo Lee and Jeannie T. Lee

Here, we expound on the view that Xist RNA directly controls Polycomb repressive complex 2 (PRC2) recruitment, off-loading to chromatin, catalytic activity, and eviction from chromatin. RNA-PRC2 interactions also control RNA polymerase II transcription pausing. Dynamic RNA folding determines PRC2 activity. Disparate studies and interpretations abound but can be reconciled.

Supercomputing in the biological sciences: Toward Zettascale and Yottascale simulations

Molecular simulations of biological systems tend to be significantly more compute-intensive than those in materials science and astrophysics, due to important contributions of long-range electrostatic forces and large numbers of time steps (>1E9) required. Simulations of biomolecular complexes of microseconds to milliseconds are considered state-of-the-art today. However, these time scales are miniscule in comparison to physiological time scales relevant to molecular machine activity, drug action, and elongation cycles for protein synthesis, RNA synthesis, and DNA synthesis (seconds to days). While an exascale supercomputer has simulated an entire virus for nanoseconds, this supercomputer would need to be 10 billion times faster to simulate that virus for 3 hours of physiological time, demonstrating the insatiable need for computing power. With growing interest in computational drug design from the pharmaceutical sector, the biological sciences are positioned to be an industry driver in computing.

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.

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.

A critical role for X-chromosome architecture in mammalian X-chromosome dosage compensation

To regulate gene expression, the macromolecular components of the mammalian interphase nucleus are spatially organized into a myriad of functional compartments. Over the past decade, increasingly sophisticated genomics, microscopy, and functional approaches have probed this organization in unprecedented detail. These investigations have linked chromatin-associated noncoding RNAs to specific nuclear compartments and uncovered mechanisms by which these RNAs establish such domains. In this review, we focus on the long non-coding RNA Xist and summarize new evidence demonstrating the significance of chromatin reconfiguration in creating the inactive X-chromosome compartment. Differences in chromatin compaction correlate with distinct levels of gene repression on the X-chromosome, potentially explaining how human XIST can induce chromosome-wide dampening and silencing of gene expression at different stages of human development.

Embracing exascale computing in nucleic acid simulations

This mini-review reports the recent advances in biomolecular simulations, particularly for nucleic acids, and provides the potential effects of the emerging exascale computing on nucleic acid simulations, emphasizing the need for advanced computational strategies to fully exploit this technological frontier. Specifically, we introduce recent breakthroughs in computer architectures for large-scale biomolecular simulations and review the simulation protocols for nucleic acids regarding force fields, enhanced sampling methods, coarse-grained models, and interactions with ligands. We also explore the integration of machine learning methods into simulations, which promises to significantly enhance the predictive modeling of biomolecules and the analysis of complex data generated by the exascale simulations. Finally, we discuss the challenges and perspectives for biomolecular simulations as we enter the dawning exascale computing era.

Multi-omics analysis reveals the dynamic interplay between Vero host chromatin structure and function during vaccinia virus infection

The genome folds into complex configurations and structures thought to profoundly impact its function. The intricacies of this dynamic structure-function relationship are not well understood particularly in the context of viral infection. To unravel this interplay, here we provide a comprehensive investigation of simultaneous host chromatin structural (via Hi-C and ATAC-seq) and functional changes (via RNA-seq) in response to vaccinia virus infection. Over time, infection significantly impacts global and local chromatin structure by increasing long-range intra-chromosomal interactions and B compartmentalization and by decreasing chromatin accessibility and inter-chromosomal interactions. Local accessibility changes are independent of broad-scale chromatin compartment exchange (~12% of the genome), underscoring potential independent mechanisms for global and local chromatin reorganization. While infection structurally condenses the host genome, there is nearly equal bidirectional differential gene expression. Despite global weakening of intra-TAD interactions, functional changes including downregulated immunity genes are associated with alterations in local accessibility and loop domain restructuring. Therefore, chromatin accessibility and local structure profiling provide impactful predictions for host responses and may improve development of efficacious anti-viral counter measures including the optimization of vaccine design.

G-quadruplex folding in Xist RNA antagonizes PRC2 activity for stepwise regulation of X chromosome inactivation

How Polycomb repressive complex 2 (PRC2) is regulated by RNA remains an unsolved problem. Although PRC2 binds G-tracts with the potential to form RNA G-quadruplexes (rG4s), whether rG4s fold extensively in vivo and whether PRC2 binds folded or unfolded rG4 are unknown. Using the X-inactivation model in mouse embryonic stem cells, here we identify multiple folded rG4s in Xist RNA and demonstrate that PRC2 preferentially binds folded rG4s. High-affinity rG4 binding inhibits PRC2's histone methyltransferase activity, and stabilizing rG4 in vivo antagonizes H3 at lysine 27 (H3K27me3) enrichment on the inactive X chromosome. Surprisingly, mutagenizing the rG4 does not affect PRC2 recruitment but promotes its release and catalytic activation on chromatin. H3K27me3 marks are misplaced, however, and gene silencing is compromised. Xist-PRC2 complexes become entrapped in the S1 chromosome compartment, precluding the required translocation into the S2 compartment. Thus, Xist rG4 folding controls PRC2 activity, H3K27me3 enrichment, and the stepwise regulation of chromosome-wide gene silencing.

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.

Human Coronavirus Infection Reorganizes Spatial Genomic Architecture in Permissive Lung Cells

Chromatin conformation capture followed by next-generation sequencing in combination with large-scale polymer simulations (4DHiC) produces detailed information on genomic loci interactions, allowing for the interrogation of 3D spatial genomic structures. Here, Hi-C data was acquired from the infection of fetal lung fibroblast (MRC5) cells with α-coronavirus 229E (CoV229E). Experimental Hi-C contact maps were used to determine viral-induced changes in genomic architecture over a 48-hour time period following viral infection, revealing substantial alterations in contacts within chromosomes and in contacts between different chromosomes. To gain further structural insight and quantify the underlying changes, we applied the 4DHiC polymer simulation method to reconstruct the 3D genomic structures and dynamics corresponding to the Hi-C maps. The models successfully reproduced experimental Hi-C data, including the changes in contacts induced by viral infection. Our 3D spatial simulations uncovered widespread chromatin restructuring, including increased chromosome compactness and A-B compartment mixing arising from infection. Our model also suggests increased spatial accessibility to regions containing interferon-stimulated genes upon infection with CoV229E, followed by chromatin restructuring at later time points, potentially inducing the migration of chromatin into more compact regions. This is consistent with previously observed suppression of gene expression. Our spatial genomics study provides a mechanistic structural basis for changes in chromosome architecture induced by coronavirus infection in lung cells.

Hi-BDiSCO: folding 3D mesoscale genome structures from Hi-C data using brownian dynamics

The structure and dynamics of the eukaryotic genome are intimately linked to gene regulation and transcriptional activity. Many chromosome conformation capture experiments like Hi-C have been developed to detect genome-wide contact frequencies and quantify loop/compartment structures for different cellular contexts and time-dependent processes. However, a full understanding of these events requires explicit descriptions of representative chromatin and chromosome configurations. With the exponentially growing amount of data from Hi-C experiments, many methods for deriving 3D structures from contact frequency data have been developed. Yet, most reconstruction methods use polymer models with low resolution to predict overall genome structure. Here we present a Brownian Dynamics (BD) approach termed Hi-BDiSCO for producing 3D genome structures from Hi-C and Micro-C data using our mesoscale-resolution chromatin model based on the Discrete Surface Charge Optimization (DiSCO) model. Our approach integrates reconstruction with chromatin simulations at nucleosome resolution with appropriate biophysical parameters. Following a description of our protocol, we present applications to the NXN, HOXC, HOXA and Fbn2 mouse genes ranging in size from 50 to 100 kb. Such nucleosome-resolution genome structures pave the way for pursuing many biomedical applications related to the epigenomic regulation of chromatin and control of human disease.

Large-scale data-driven and physics-based models offer insights into the relationships among the structures, dynamics, and functions of chromosomes

The organized three-dimensional chromosome architecture in the cell nucleus provides scaffolding for precise regulation of gene expression. When the cell changes its identity in the cell-fate decision-making process, extensive rearrangements of chromosome structures occur accompanied by large-scale adaptations of gene expression, underscoring the importance of chromosome dynamics in shaping genome function. Over the last two decades, rapid development of experimental methods has provided unprecedented data to characterize the hierarchical structures and dynamic properties of chromosomes. In parallel, these enormous data offer valuable opportunities for developing quantitative computational models. Here, we review a variety of large-scale polymer models developed to investigate the structures and dynamics of chromosomes. Different from the underlying modeling strategies, these approaches can be classified into data-driven ('top-down') and physics-based ('bottom-up') categories. We discuss their contributions to offering valuable insights into the relationships among the structures, dynamics, and functions of chromosomes and propose the perspective of developing data integration approaches from different experimental technologies and multidisciplinary theoretical/simulation methods combined with different modeling strategies.

Replication dynamics identifies the folding principles of the inactive X chromosome

Chromosome-wide late replication is an enigmatic hallmark of the inactive X chromosome (Xi). How it is established and what it represents remains obscure. By single-cell DNA replication sequencing, here we show that the entire Xi is reorganized to replicate rapidly and uniformly in late S-phase during X-chromosome inactivation (XCI), reflecting its relatively uniform structure revealed by 4C-seq. Despite this uniformity, only a subset of the Xi became earlier replicating in SmcHD1-mutant cells. In the mutant, these domains protruded out of the Xi core, contacted each other and became transcriptionally reactivated. 4C-seq suggested that they constituted the outermost layer of the Xi even before XCI and were rich in escape genes. We propose that this default positioning forms the basis for their inherent heterochromatin instability in cells lacking the Xi-binding protein SmcHD1 or exhibiting XCI escape. These observations underscore the importance of 3D genome organization for heterochromatin stability and gene regulation.

Techniques for and challenges in reconstructing 3D genome structures from 2D chromosome conformation capture data

Chromosome conformation capture technologies that provide frequency information for contacts between genomic regions have been crucial for increasing our understanding of genome folding and regulation. However, such data do not provide direct evidence of the spatial 3D organization of chromatin. In this opinion article, we discuss the development and application of computational methods to reconstruct chromatin 3D structures from experimental 2D contact data, highlighting how such modeling provides biological insights and can suggest mechanisms anchored to experimental data. By applying different reconstruction methods to the same contact data, we illustrate some state-of-the-art of these techniques and discuss our gene resolution approach based on Brownian dynamics and Monte Carlo sampling.

Mesoscale, long-time mixing of chromosomes and its connection to polymer dynamics

Chromosomes are arranged in distinct territories within the nucleus of animal cells. Recent experiments have shown that these territories overlap at their edges, suggesting partial mixing during interphase. Experiments that knock-down of condensin II proteins during interphase indicate increased chromosome mixing, which demonstrates control of the mixing. In this study, we use a generic polymer simulation to quantify the dynamics of chromosome mixing over time. We introduce the chromosome mixing index, which quantifies the mixing of distinct chromosomes in the nucleus. We find that the chromosome mixing index in a small confinement volume (as a model of the nucleus), increases as a power-law of the time, with the scaling exponent varying non-monotonically with self-interaction and volume fraction. By comparing the chromosome mixing index with both monomer subdiffusion due to (non-topological) intermingling of chromosomes as well as even slower reptation, we show that for relatively large volume fractions, the scaling exponent of the chromosome mixing index is related to Rouse dynamics for relatively weak chromosome attractions and to reptation for strong attractions. In addition, we extend our model to more realistically account for the situation of the Drosophila chromosome by including the heterogeneity of the polymers and their lengths to account for microphase separation of euchromatin and heterochromatin and their interactions with the nuclear lamina. We find that the interaction with the lamina further impedes chromosome mixing.

Compartmentalization with nuclear landmarks yields random, yet precise, genome organization

The 3D organization of eukaryotic genomes plays an important role in genome function. While significant progress has been made in deciphering the folding mechanisms of individual chromosomes, the principles of the dynamic large-scale spatial arrangement of all chromosomes inside the nucleus are poorly understood. We use polymer simulations to model the diploid human genome compartmentalization relative to nuclear bodies such as nuclear lamina, nucleoli, and speckles. We show that a self-organization process based on a cophase separation between chromosomes and nuclear bodies can capture various features of genome organization, including the formation of chromosome territories, phase separation of A/B compartments, and the liquid property of nuclear bodies. The simulated 3D structures quantitatively reproduce both sequencing-based genomic mapping and imaging assays that probe chromatin interaction with nuclear bodies. Importantly, our model captures the heterogeneous distribution of chromosome positioning across cells while simultaneously producing well-defined distances between active chromatin and nuclear speckles. Such heterogeneity and preciseness of genome organization can coexist due to the nonspecificity of phase separation and the slow chromosome dynamics. Together, our work reveals that the cophase separation provides a robust mechanism for us to produce functionally important 3D contacts without requiring thermodynamic equilibration that can be difficult to achieve.

Genome modeling: From chromatin fibers to genes

The intricacies of the 3D hierarchical organization of the genome have been approached by many creative modeling studies. The specific model/simulation technique combination defines and restricts the system and phenomena that can be investigated. We present the latest modeling developments and studies of the genome, involving models ranging from nucleosome systems and small polynucleosome arrays to chromatin fibers in the kb-range, chromosomes, and whole genomes, while emphasizing gene folding from first principles. Clever combinations allow the exploration of many interesting phenomena involved in gene regulation, such as nucleosome structure and dynamics, nucleosome-nucleosome stacking, polynucleosome array folding, protein regulation of chromatin architecture, mechanisms of gene folding, loop formation, compartmentalization, and structural transitions at the chromosome and genome levels. Gene-level modeling with full details on nucleosome positions, epigenetic factors, and protein binding, in particular, can in principle be scaled up to model chromosomes and cells to study fundamental biological regulation.

Epigenetic-structural changes in X chromosomes promote Xic pairing during early differentiation of mouse embryonic stem cells

X chromosome inactivation center (Xic) pairing occurs during the differentiation of embryonic stem (ES) cells from female mouse embryos, and is related to X chromosome inactivation, the circadian clock, intra-nucleus architecture, and metabolism. However, the mechanisms underlying the identification and approach of X chromosome pairs in the crowded nucleus are unclear. To elucidate the driving force of Xic pairing, we developed a coarse-grained molecular dynamics model of intranuclear chromosomes in ES cells and in cells 2 days after the onset of differentiation (2-day cells) by considering intrachromosomal epigenetic-structural feature-dependent mechanics. The analysis of the experimental data showed that X-chromosomes exhibit the rearrangement of their distributions of open/closed chromatin regions on their surfaces during cell differentiation. By simulating models where the excluded volume effects of closed chromatin regions are stronger than those of open chromatin regions, such rearrangement of open/closed chromatin regions on X-chromosome surfaces promoted the mutual approach of the Xic pair. These findings suggested that local intrachromosomal epigenetic features may contribute to the regulation of cell species-dependent differences in intranuclear architecture.

Spectral Decomposition of Mappings of Molecular Genetic Information in the System Basis of Single Nucleotide Functions

This paper presents and visualizes examples of large amounts of genetic information using a new class of cognitive computer graphics algorithms. These algorithms are related to the semiotics of perception and allow the interpretation of those properties of nucleotide sequences that are difficult to perceive by simple reading or by standard means of statistical analysis. This article summarizes previously presented algorithms for visualizing long nucleic acids based on the primary Hadamard–Walsh function system. The described methods allow us to produce one-dimensional mappings of nucleic acids by levels corresponding to their scale-integral physicochemical parameters and construct a spectral decomposition of the nucleotide composition. An example of the spectral decomposition of parametric representations of molecular genetic structures is given. In addition, a multiscale composition of genetic functional mappings visualizing the structural features of nucleic acids is discussed.

Unveiling RCOR1 as a rheostat at transcriptionally permissive chromatin

RCOR1 is a known transcription repressor that recruits and positions LSD1 and HDAC1/2 on chromatin to erase histone methylation and acetylation. However, there is currently an incomplete understanding of RCOR1’s range of localization and function. Here, we probe RCOR1’s distribution on a genome-wide scale and unexpectedly find that RCOR1 is predominantly associated with transcriptionally active genes. Biochemical analysis reveals that RCOR1 associates with RNA Polymerase II (POL-II) during transcription and deacetylates its carboxy-terminal domain (CTD) at lysine 7. We provide evidence that this non-canonical RCOR1 activity is linked to dampening of POL-II productive elongation at actively transcribing genes. Thus, RCOR1 represses transcription in two ways—first, via a canonical mechanism by erasing transcriptionally permissive histone modifications through associating with HDACs and, second, via a non-canonical mechanism that deacetylates RNA POL-II’s CTD to inhibit productive elongation. We conclude that RCOR1 is a transcription rheostat.

The classical neuronal-gene corepressor RCOR1/CoREST is paradoxically enriched in transcriptionally active chromatin. Here the authors show RCOR1 is recruited during promoter-proximal pausing and negatively regulates the nascent-transcript synthesis. They also show that an RCOR1-LSD1- HDAC1 complex removes lysine acetylation from RNA polymerase II to repress transcription.