Transcriptional activation during cell reprogramming correlates with the formation of 3D open chromatin hubs

Integrated promoter-capture Hi-C and Hi-C analysis reveals fine-tuned regulation of the 3D chromatin architecture in colorectal cancer

Introduction

Hi-C is a widely used technique for mapping chromosomal interactions within a 3D genomic framework, however, its resolution is often constrained by sequencing depth, making it challenging to detect fine-scale interactions. To overcome this limitation, Promoter-Capture Hi-C (PCHi-C), as it selectively enriches for promoter-associated interactions, was employed. This study integrates PCHi-C and Hi-C datasets from colorectal cancer (CRC) models investigate chromosomal interaction dynamics across various regulatory levels, from cis-regulatory elements to topologically associated domains (TADs). The primary goal is to examine how genomic structural alterations shape the epigenomic landscape in CRC and to assess their potential role in colorectal cancer susceptibility.

Methods

PCHi-C and Hi-C datasets from multiple colorectal cancer (CRC) studies were integrated to enhance the resolution of chromatin interaction mapping. The analysis focused on identifying fine-scale interactions within topologically associated domains (TADs) while incorporating histone modification landscapes (H3K27ac, H3K4me3) and transcriptomic signatures from CRC cell lines and the TCGA database. For experimental validation, ChIP-quantitative PCR was performed at the promoters of target genes using the highly malignant colorectal cell line HT29 and compared it to an embryonic cell line NT2D1.

Results

Our integrated analysis revealed significant genomic structural instability in CRC cells, closely associated with tumor-suppressive transcriptional programs. We identified nine dysregulated genes, including long non-coding RNAs (MALAT1, NEAT1, FTX, and PVT1), small nucleolar RNAs (SNORA26 and SNORA71A), and protein-coding genes (TMPRSS11D, TSPEAR, and DSG4), all of which exhibited a substantial increase in expression in CRC cell lines compared to human embryonic stem cells (hESCs). Additionally, we observed enriched activation-associated histone modifications (H3K27ac and H3K4me3) at the potential enhancer regions of these genes, indicating possible transcriptional activation. ChIP-quantitative PCRs conducted using in the highly malignant CRC cell line HT29, compared to the embryonic cell line NT2D1, further validated these findings, reinforcing the link between altered chromosomal interactions and gene dysregulation in CRC.

Discussion

This study sheds light on the dynamic 3D genome organization in CRC, highlighting critical structural changes associated with disease-associated loci. The identification of nine dysregulated genes points to potential biomarkers for colorectal cancer, with implications for diagnostic and therapeutic strategies. The combination of Hi-C and PCHi-C offers a refined approach for detecting chromosomal interactions at a higher resolution, laying the foundation for future studies on cancer-associated chromatin architecture.

HiCForecast: dynamic network optical flow estimation algorithm for spatiotemporal Hi-C data forecasting

MOTIVATION

The exploration of the 3D organization of DNA within the nucleus in relation to various stages of cellular development has led to experiments generating spatiotemporal Hi-C data. However, there is limited spatiotemporal Hi-C data for many organisms, impeding the study of 3D genome dynamics. To overcome this limitation and advance our understanding of genome organization, it is crucial to develop methods for forecasting Hi-C data at future time points from existing timeseries Hi-C data.

RESULT

In this work, we designed a novel framework named HiCForecast, adopting a dynamic voxel flow algorithm to forecast future spatiotemporal Hi-C data. We evaluated how well our method generalizes forecasting data across different species and systems, ensuring performance in homogeneous, heterogeneous, and general contexts. Using both computational and biological evaluation metrics, our results show that HiCForecast outperforms the current state-of-the-art algorithm, emerging as an efficient and powerful tool for forecasting future spatiotemporal Hi-C datasets.

AVAILABILITY AND IMPLEMENTATION

HiCForecast is publicly available at https://github.com/OluwadareLab/HiCForecast.

SEE: A Method for Predicting the Dynamics of Chromatin Conformation Based on Single-Cell Gene Expression

The dynamics of chromatin conformation involve continuous and reversible changes within the nucleus of a cell, which participate in regulating processes such as gene expression, DNA replication, and damage repair. Here, SEE is introduced, an artificial intelligence (AI) method that utilizes autoencoder and transformer techniques to analyze chromatin dynamics using single-cell RNA sequencing data and a limited number of single-cell Hi-C maps. SEE is employed to investigate chromatin dynamics across different scales, enabling the detection of (i) rearrangements in topologically associating domains (TADs), and (ii) oscillations in chromatin interactions at gene loci. Additionally, SEE facilitates the interpretation of disease-associated single-nucleotide polymorphisms (SNPs) by leveraging the dynamic features of chromatin conformation. Overall, SEE offers a single-cell, high-resolution approach to analyzing chromatin dynamics in both developmental and disease contexts.

Polymer Physics Models Reveal Structural Folding Features of Single-Molecule Gene Chromatin Conformations

Here, we employ polymer physics models of chromatin to investigate the 3D folding of a 2 Mb wide genomic region encompassing the human LTN1 gene, a crucial DNA locus involved in key cellular functions. Through extensive Molecular Dynamics simulations, we reconstruct in silico the ensemble of single-molecule LTN1 3D structures, which we benchmark against recent in situ Hi-C 2.0 data. The model-derived single molecules are then used to predict structural folding features at the single-cell level, providing testable predictions for super-resolution microscopy experiments.

Transcription regulates the spatio-temporal dynamics of genes through micro-compartmentalization

Although our understanding of the involvement of heterochromatin architectural factors in shaping nuclear organization is improving, there is still ongoing debate regarding the role of active genes in this process. In this study, we utilize publicly-available Micro-C data from mouse embryonic stem cells to investigate the relationship between gene transcription and 3D gene folding. Our analysis uncovers a nonmonotonic - globally positive - correlation between intragenic contact density and Pol II occupancy, independent of cohesin-based loop extrusion. Through the development of a biophysical model integrating the role of transcription dynamics within a polymer model of chromosome organization, we demonstrate that Pol II-mediated attractive interactions with limited valency between transcribed regions yield quantitative predictions consistent with chromosome-conformation-capture and live-imaging experiments. Our work provides compelling evidence that transcriptional activity shapes the 4D genome through Pol II-mediated micro-compartmentalization.

Gene regulation during meiosis

Meiosis is essential for gamete production in all sexually reproducing organisms. It entails two successive cell divisions without DNA replication, producing haploid cells from diploid ones. This process involves complex morphological and molecular differentiation that varies across species and between sexes. Specialized genomic events like meiotic recombination and chromosome segregation are tightly regulated, including preparation for post-meiotic development. Research in model organisms, notably yeast, has shed light on the genetic and molecular aspects of meiosis and its regulation. Although mammalian meiosis research faces challenges, particularly in replicating gametogenesis in vitro, advances in genetic and genomic technologies are providing mechanistic insights. Here we review the genetics and molecular biology of meiotic gene expression control, focusing on mammals.

Enhancer-driven 3D chromatin domain folding modulates transcription in human mammary tumor cells

The genome is organized in functional compartments and structural domains at the sub-megabase scale. How within these domains interactions between numerous cis-acting enhancers and promoters regulate transcription remains an open question. Here, we determined chromatin folding and composition over several hundred kb around estrogen-responsive genes in human breast cancer cell lines after hormone stimulation. Modeling of 5C data at 1.8 kb resolution was combined with quantitative 3D analysis of multicolor FISH measurements at 100 nm resolution and integrated with ChIP-seq data on transcription factor binding and histone modifications. We found that rapid estradiol induction of the progesterone gene expression occurs in the context of preexisting, cell type-specific chromosomal architectures encompassing the 90 kb progesterone gene coding region and an enhancer-spiked 5' 300 kb upstream genomic region. In response to estradiol, interactions between estrogen receptor α (ERα) bound regulatory elements are reinforced. Whereas initial enhancer-gene contacts coincide with RNA Pol 2 binding and transcription initiation, sustained hormone stimulation promotes ERα accumulation creating a regulatory hub stimulating transcript synthesis. In addition to implications for estrogen receptor signaling, we uncover that preestablished chromatin architectures efficiently regulate gene expression upon stimulation without the need for de novo extensive rewiring of long-range chromatin interactions.

Epigenetic inhibition of CTCF by HN1 promotes dedifferentiation and stemness of anaplastic thyroid cancer

Anaplastic thyroid cancer (ATC) is one of the deadliest cancers, whose important malignant feature is dedifferentiation. Chromatin remodeling is critical for tumorigenesis and progression, while its roles and regulator in facilitating dedifferentiation of ATC had been poorly understood. In our study, an emerging function of hematological and neurological expressed 1 (HN1) in promoting dedifferentiation of ATC cells was uncovered. HN1 expression was negatively correlated with the thyroid differentiation markers both at mRNA and protein level. Knockdown of HN1 in ATC cells effectively upregulated the thyroid differentiation markers and impeded the sphere formation capacity, accompanying with the loss of cancer stemness. In contrast, overexpression of HN1 drove the gain of stemness and the loss of thyroid differentiation markers. Nude mouse and zebrafish xenograft models showed that inhibition of HN1 in ATC cells effectively hindered tumor growth due to the loss of cancer stemness. Further study showed that HN1 was negatively correlated with CTCF in an independent thyroid-cancer cohort, and inhibition of HN1 enhanced the expression of CTCF in ATC cells. Overexpression of CTCF significantly reversed the dedifferentiation phenotypes of ATC cells, whereas simultaneously inhibiting HN1 and CTCF was unable to recover the level of thyroid differentiation markers. The combination of ATAC-seq and ChIP-seq analysis confirmed that CTCF regulated genes relating with thyroid gland development through influencing their chromatin accessibility. HN1 inhibited the acetylation of H3K27 at the promoter of CTCF by recruiting HDAC2, thereby inhibiting the transcriptional activation of CTCF. These findings demonstrated an essential role of HN1 in regulating the chromatin accessibility of thyroid differentiation genes during ATC dedifferentiation.

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.

Photochemically induced chloromethylation/cyclization of benzimidazole derivatives with CCl4/CHCl3

Herein, it is reported that a series of trichloromethyl/dichloromethyl substituted benzimidazole derivatives have been synthesized by dechlorination of CCl4/CHCl3 to form polychloromethyl radicals and cyclization with an unactivated olefin under a purple LED lamp. The protocol features a wide substrate scope, high atom economy, and excellent regioselectivity, and is easy to scale up.

Quantifying the large-scale chromosome structural dynamics during the mitosis-to-G1 phase transition of cell cycle

Cell cycle is known to be regulated by the underlying gene network. Chromosomes, which serve as the scaffold for gene expressions, undergo significant structural reorganizations during mitosis. Understanding the mechanism of the cell cycle from the chromosome structural perspective remains a grand challenge. In this study, we applied an integrated theoretical approach to investigate large-scale chromosome structural dynamics during the mitosis-to-G1 phase transition. We observed that the chromosome structural expansion and adaptation of the structural asphericity do not occur synchronously and attributed this behaviour to the unique unloading sequence of the two types of condensins. Furthermore, we observed that the coherent motions between the chromosomal loci are primarily enhanced within the topologically associating domains (TADs) as cells progress to the G1 phase, suggesting that TADs can be considered as both structural and dynamical units for organizing the three-dimensional chromosome. Our analysis also reveals that the quantified pathways of chromosome structural reorganization during the mitosis-to-G1 phase transition exhibit high stochasticity at the single-cell level and show nonlinear behaviours in changing TADs and contacts formed at the long-range regions. Our findings offer valuable insights into large-scale chromosome structural dynamics after mitosis.

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.

Multiscale 3D genome reorganization during skeletal muscle stem cell lineage progression and aging

Little is known about three-dimensional (3D) genome organization in skeletal muscle stem cells [also called satellite cells (SCs)]. Here, we comprehensively map the 3D genome topology reorganization during mouse SC lineage progression. Specifically, rewiring at the compartment level is most pronounced when SCs become activated. Marked loss in topologically associating domain (TAD) border insulation and chromatin looping also occurs during early activation process. Meanwhile, TADs can form TAD clusters and super-enhancer-containing TAD clusters orchestrate stage-specific gene expression. Furthermore, we uncover that transcription factor PAX7 is pivotal in enhancer-promoter (E-P) loop formation. We also identify cis-regulatory elements that are crucial for local chromatin organization at Pax7 locus and Pax7 expression. Lastly, we unveil that geriatric SC displays a prominent gain in long-range contacts and loss of TAD border insulation. Together, our results uncover that 3D chromatin extensively reorganizes at multiple architectural levels and underpins the transcriptome remodeling during SC lineage development and SC aging.

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.

Insights into the cell fate decision-making processes from chromosome structural reorganizations

The cell fate decision-making process, which provides the capability of a cell transition to a new cell type, involves the reorganizations of 3D genome structures. Currently, the high temporal resolution picture of how the chromosome structural rearrangements occur and further influence the gene activities during the cell-state transition is still challenging to acquire. Here, we study the chromosome structural reorganizations during the cell-state transitions among the pluripotent embryonic stem cell, the terminally differentiated normal cell, and the cancer cell using a nonequilibrium landscape-switching model implemented in the molecular dynamics simulation. We quantify the chromosome (de)compaction pathways during the cell-state transitions and find that the two pathways having the same destinations can merge prior to reaching the final states. The chromosomes at the merging states have similar structural geometries but can differ in long-range compartment segregation and spatial distribution of the chromosomal loci and genes, leading to cell-type-specific transition mechanisms. We identify the irreversible pathways of chromosome structural rearrangements during the forward and reverse transitions connecting the same pair of cell states, underscoring the critical roles of nonequilibrium dynamics in the cell-state transitions. Our results contribute to the understanding of the cell fate decision-making processes from the chromosome structural perspective.

Integrative studies of 3D genome organization and chromatin structure

The structural organization of the genome is emerging as a crucial regulator of the cell state, affecting gene transcription, DNA replication, and repair. Over the last twenty years, increasing evidence prompted the development of new experimental techniques to study genome structure. In parallel with the complexity of the novel techniques, computational approaches have become an essential tool in any structural genomics laboratory to analyze and model the data. For biologists to be able to apply the most appropriate modeling approach, it is fundamental to understand the conceptual bases of distinct methods and the insights they can provide. Here, we will discuss recent advances that were possible thanks to 3D genome modeling, discuss their limitations and highlight future perspectives.

The Impact of Space and Time on the Functional Output of the Genome

Over the past two decades, it has become clear that the multiscale spatial and temporal organization of the genome has important implications for nuclear function. This review centers on insights gained from recent advances in light microscopy on our understanding of transcription. We discuss spatial and temporal aspects that shape nuclear order and their consequences on regulatory components, focusing on genomic scales most relevant to function. The emerging picture is that spatiotemporal constraints increase the complexity in transcriptional regulation, highlighting new challenges, such as uncertainty about how information travels from molecular factors through the genome and space to generate a functional output.

The Physics of DNA Folding: Polymer Models and Phase-Separation

Within cell nuclei, several biophysical processes occur in order to allow the correct activities of the genome such as transcription and gene regulation. To quantitatively investigate such processes, polymer physics models have been developed to unveil the molecular mechanisms underlying genome functions. Among these, phase-separation plays a key role since it controls gene activity and shapes chromatin spatial structure. In this paper, we review some recent experimental and theoretical progress in the field and show that polymer physics in synergy with numerical simulations can be helpful for several purposes, including the study of molecular condensates, gene-enhancer dynamics, and the three-dimensional reconstruction of real genomic regions.

ZFP541 maintains the repression of pre-pachytene transcriptional programs and promotes male meiosis progression

The DSB machinery, which induces the programmed DNA double-strand breaks (DSBs) in the leptotene and zygotene stages during meiosis, is suppressed before the onset of the pachytene stage. However, the biological significance and underlying mechanisms remain largely unclear. Here, we report that ZFP541 is indispensable for the suppression of DSB formation after mid-pachytene. The deletion of Zfp541 in mice causes the aberrant recruitment of DSB machinery to chromosome axes and generation of massive DSBs in late pachytene and diplotene spermatocytes, leading to meiotic arrest at the diplotene stage. Integrated analysis of single-cell RNA sequencing (scRNA-seq) and chromatin immunoprecipitation (ChIP) sequencing data indicate that ZFP541 predominantly binds to promoters of pre-pachytene genes, including meiotic DSB formation-related genes (e.g., Prdm9 and Mei1) and their upstream activators (e.g., Meiosin and Rxra), and maintains their repression in pachytene spermatocytes. Our results reveal that ZFP541 functions as a transcriptional regulator in pachytene spermatocytes, orchestrating the transcriptome to ensure meiosis progression.

Cell cycle dynamics and developmental dynamics of the 3D genome: toward linking the two timescales

In the mammalian cell nucleus, chromosomes are folded differently in interphase and mitosis. Interphase chromosomes are relatively decondensed and display at least two unique layers of higher-order organization: topologically associating domains (TADs) and cell-type-specific A/B compartments, which correlate well with early/late DNA replication timing (RT). In mitosis, these structures rapidly disappear but are gradually reconstructed during G1 phase, coincident with the establishment of the RT program. However, these structures also change dynamically during cell differentiation and reprogramming, and yet we are surprisingly ignorant about the relationship between their cell cycle dynamics and developmental dynamics. In this review, we summarize the recent findings on this topic, discuss how these two processes might be coordinated with each other and its potential significance.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Modeling the 3D genome of plants

Chromosomes are the carriers of inheritable traits and define cell function and development. This is not only based on the linear DNA sequence of chromosomes but also on the additional molecular information they are associated with, including the transcription machinery, histone modifications, and their three-dimensional folding. The synergistic application of experimental approaches and computer simulations has helped to unveil how these organizational layers of the genome interplay in various organisms. However, such multidisciplinary approaches are still rarely explored in the plant kingdom. Here, we provide an overview of our current knowledge on plant 3D genome organization and review recent efforts to integrate cutting-edge experiments from microscopy and next-generation sequencing approaches with theoretical models. Building on these recent approaches, we propose possible avenues to extend the application of theoretical modeling in the characterization of the 3D genome organization in plants.

Predicting genome organisation and function with mechanistic modelling

Fitting-free mechanistic models based on polymer simulations predict chromatin folding in 3D by focussing on the underlying biophysical mechanisms. This class of models has been increasingly used in conjunction with experiments to study the spatial organisation of eukaryotic chromosomes. Feedback from experiments to models leads to successive model refinement and has previously led to the discovery of new principles for genome organisation. Here, we review the basis of mechanistic polymer simulations, explain some of the more recent approaches and the contexts in which they have been useful to explain chromosome biology, and speculate on how they might be used in the future.

Deciphering the molecular mechanism of the cancer formation by chromosome structural dynamics

Cancer reflects the dysregulation of the underlying gene network, which is strongly related to the 3D genome organization. Numerous efforts have been spent on experimental characterizations of the structural alterations in cancer genomes. However, there is still a lack of genomic structural-level understanding of the temporal dynamics for cancer initiation and progression. Here, we use a landscape-switching model to investigate the chromosome structural transition during the cancerization and reversion processes. We find that the chromosome undergoes a non-monotonic structural shape-changing pathway with initial expansion followed by compaction during both of these processes. Furthermore, our analysis reveals that the chromosome with a more expanding structure than those at both the normal and cancer cell during cancerization exhibits a sparse contact pattern, which shows significant structural similarity to the one at the embryonic stem cell in many aspects, including the trend of contact probability declining with the genomic distance, the global structural shape geometry and the spatial distribution of loci on the chromosome. In light of the intimate structure-function relationship at the chromosomal level, we further describe the cell state transition processes by the chromosome structural changes, suggesting an elevated cell stemness during the formation of the cancer cells. We show that cell cancerization and reversion are highly irreversible processes in terms of the chromosome structural transition pathways, spatial repositioning of chromosomal loci and hysteresis loop of contact evolution analysis. Our model draws a molecular-scale picture of cell cancerization from the chromosome structural perspective. The process contains initial reprogramming towards the stem cell followed by the differentiation towards the cancer cell, accompanied by an initial increase and subsequent decrease of the cell stemness.

Three-dimensional genome organization via triplex-forming RNAs

An increasing number of long noncoding RNAs (lncRNAs) have been proposed to act as nuclear organization factors during interphase. Direct RNA-DNA interactions can be achieved by the formation of triplex helix structures where a single-stranded RNA molecule hybridizes by complementarity into the major groove of double-stranded DNA. However, whether and how these direct RNA-DNA associations influence genome structure in interphase chromosomes remain poorly understood. Here we theorize that RNA organizes the genome in space via a triplex-forming mechanism. To test this theory, we apply a computational modeling approach of chromosomes that combines restraint-based modeling with polymer physics. Our models suggest that colocalization of triplex hotspots targeted by lncRNAs could contribute to large-scale chromosome compartmentalization cooperating, rather than competing, with architectural transcription factors such as CTCF.

Chromatin Network Analyses: Towards Structure-Function Relationships in Epigenomics

Recent technological advances have allowed us to map chromatin conformation and uncover the genome's spatial organization of the genome inside the nucleus. These experiments have revealed the complexities of genome folding, characterized by the presence of loops and domains at different scales, which can change across development and in different cell types. There is strong evidence for a relationship between the topological properties of chromatin contacts and cellular phenotype. Chromatin can be represented as a network, in which genomic fragments are the nodes and connections represent experimentally observed spatial proximity of two genomically distant regions in a specific cell type or biological condition. With this approach we can consider a variety of chromatin features in association with the 3D structure, investigating how nuclear chromatin organization can be related to gene regulation, replication, malignancy, phenotypic variability and plasticity. We briefly review the results obtained on genome architecture through network theoretic approaches. As previously observed in protein-protein interaction networks and many types of non-biological networks, external conditions could shape network topology through a yet unidentified structure-function relationship. Similar to scientists studying the brain, we are confronted with a duality between a spatially embedded network of physical contacts, a related network of correlation in the dynamics of network nodes and, finally, an abstract definition of function of this network, related to phenotype. We summarise major developments in the study of networks in other fields, which we think can suggest a path towards better understanding how 3D genome configuration can impact biological function and adaptation to the environment.

Four-Dimensional Chromosome Structure Prediction

Chromatin conformation plays an important role in a variety of genomic processes, including genome replication, gene expression, and gene methylation. Hi-C data is frequently used to analyze structural features of chromatin, such as AB compartments, topologically associated domains, and 3D structural models. Recently, the genomics community has displayed growing interest in chromatin dynamics. Here, we present 4DMax, a novel method, which uses time-series Hi-C data to predict dynamic chromosome conformation. Using both synthetic data and real time-series Hi-C data from processes, such as induced pluripotent stem cell reprogramming and cardiomyocyte differentiation, we construct smooth four-dimensional models of individual chromosomes. These predicted 4D models effectively interpolate chromatin position across time, permitting prediction of unknown Hi-C contact maps at intermittent time points. Furthermore, 4DMax correctly recovers higher order features of chromatin, such as AB compartments and topologically associated domains, even at time points where Hi-C data is not made available to the algorithm. Contact map predictions made using 4DMax outperform naïve numerical interpolation in 87.7% of predictions on the induced pluripotent stem cell dataset. A/B compartment profiles derived from 4DMax interpolation showed higher similarity to ground truth than at least one profile generated from a neighboring time point in 100% of induced pluripotent stem cell experiments. Use of 4DMax may alleviate the cost of expensive Hi-C experiments by interpolating intermediary time points while also providing valuable visualization of dynamic chromatin changes.

Chromatin Conformation in Development and Disease

Chromatin domains and loops are important elements of chromatin structure and dynamics, but much remains to be learned about their exact biological role and nature. Topological associated domains and functional loops are key to gene expression and hold the answer to many questions regarding developmental decisions and diseases. Here, we discuss new findings, which have linked chromatin conformation with development, differentiation and diseases and hypothesized on various models while integrating all recent findings on how chromatin architecture affects gene expression during development, evolution and disease.

Understanding 3D genome organization by multidisciplinary methods

Understanding how chromatin is folded in the nucleus is fundamental to understanding its function. Although 3D genome organization has been historically difficult to study owing to a lack of relevant methodologies, major technological breakthroughs in genome-wide mapping of chromatin contacts and advances in imaging technologies in the twenty-first century considerably improved our understanding of chromosome conformation and nuclear architecture. In this Review, we discuss methods of 3D genome organization analysis, including sequencing-based techniques, such as Hi-C and its derivatives, Micro-C, DamID and others; microscopy-based techniques, such as super-resolution imaging coupled with fluorescence in situ hybridization (FISH), multiplex FISH, in situ genome sequencing and live microscopy methods; and computational and modelling approaches. We describe the most commonly used techniques and their contribution to our current knowledge of nuclear architecture and, finally, we provide a perspective on up-and-coming methods that open possibilities for future major discoveries.

3D reconstruction of genomic regions from sparse interaction data

Chromosome conformation capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterize short- and long-range enhancer-promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organization from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalization, detection of significant interactions and reconstruction of the full 3D organization of the genomic region despite of the data sparseness. Specifically, it builds, with as low as the 2-3% of the data from the matrix, reliable 3D models of similar accuracy of those based on dense interaction matrices. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organizational features such as the formation of different networks of active gene communities.

Chromatin and Epigenetic Rearrangements in Embryonic Stem Cell Fate Transitions

A major event in embryonic development is the rearrangement of epigenetic information as the somatic genome is reprogrammed for a new round of organismal development. Epigenetic data are held in chemical modifications on DNA and histones, and there are dramatic and dynamic changes in these marks during embryogenesis. However, the mechanisms behind this intricate process and how it is regulating and responding to embryonic development remain unclear. As embryos develop from totipotency to pluripotency, they pass through several distinct stages that can be captured permanently or transiently in vitro. Pluripotent naïve cells resemble the early epiblast, primed cells resemble the late epiblast, and blastomere-like cells have been isolated, although fully totipotent cells remain elusive. Experiments using these in vitro model systems have led to insights into chromatin changes in embryonic development, which has informed exploration of pre-implantation embryos. Intriguingly, human and mouse cells rely on different signaling and epigenetic pathways, and it remains a mystery why this variation exists. In this review, we will summarize the chromatin rearrangements in early embryonic development, drawing from genomic data from in vitro cell lines, and human and mouse embryos.

Computational Stem Cell Biology: Open Questions and Guiding Principles

Computational biology is enabling an explosive growth in our understanding of stem cells and our ability to use them for disease modeling, regenerative medicine, and drug discovery. We discuss four topics that exemplify applications of computation to stem cell biology: cell typing, lineage tracing, trajectory inference, and regulatory networks. We use these examples to articulate principles that have guided computational biology broadly and call for renewed attention to these principles as computation becomes increasingly important in stem cell biology. We also discuss important challenges for this field with the hope that it will inspire more to join this exciting area.

Dynamic 3D Chromatin Reorganization during Establishment and Maintenance of Pluripotency

Higher-order chromatin structure is tightly linked to gene expression and therefore cell identity. In recent years, the chromatin landscape of pluripotent stem cells has become better characterized, and unique features at various architectural levels have been revealed. However, the mechanisms that govern establishment and maintenance of these topological characteristics and the temporal and functional relationships with transcriptional or epigenetic features are still areas of intense study. Here, we will discuss progress and limitations of our current understanding regarding how the 3D chromatin topology of pluripotent stem cells is established during somatic cell reprogramming and maintained during cell division. We will also discuss evidence and theories about the driving forces of topological reorganization and the functional links with key features and properties of pluripotent stem cell identity.

Engineering cell fate: Applying synthetic biology to cellular reprogramming

Cellular reprogramming drives cells from one stable identity to a new cell fate. By generating a diversity of previously inaccessible cell types from diverse genetic backgrounds, cellular reprogramming is rapidly transforming how we study disease. However, low efficiency and limited maturity have limited the adoption of in vitro-derived cellular models. To overcome these limitations and improve mechanistic understanding of cellular reprogramming, a host of synthetic biology tools have been deployed. Recent synthetic biology approaches have advanced reprogramming by tackling three significant challenges to reprogramming: delivery of reprogramming factors, epigenetic roadblocks, and latent donor identity. In addition, emerging insight from the molecular systems biology of reprogramming reveal how systems-level drivers of reprogramming can be harnessed to further advance reprogramming technologies. Furthermore, recently developed synthetic biology tools offer new modes for engineering cell fate.

4D nucleome modeling

The intrinsic dynamic nature of chromosomes is emerging as a fundamental component in regulating DNA transcription, replication, and damage-repair among other nuclear functions. With this increased awareness, reinforced over the last ten years, many new experimental techniques, mainly based on microscopy and chromosome conformation capture, have been introduced to study the genome in space and time. Owing to the increasing complexity of these cutting-edge techniques, computational approaches have become of paramount importance to interpret, contextualize, and complement such experiments with new insights. Hence, it is becoming crucial for experimental biologists to have a clear understanding of the diverse theoretical modeling approaches available and the biological information each of them can provide.

Understanding and Engineering Chromatin as a Dynamical System across Length and Timescales

Connecting the molecular structure and function of chromatin across length and timescales remains a grand challenge to understanding and engineering cellular behaviors. Across five orders of magnitude, dynamic processes constantly reshape chromatin structures, driving spaciotemporal patterns of gene expression and cell fate. Through the interplay of structure and function, the genome operates as a highly dynamic feedback control system. Recent experimental techniques have provided increasingly detailed data that revise and augment the relatively static, hierarchical view of genomic architecture with an understanding of how dynamic processes drive organization. Here, we review how novel technologies from sequencing, imaging, and synthetic biology refine our understanding of chromatin structure and function and enable chromatin engineering. Finally, we discuss opportunities to use these tools to enhance understanding of the dynamic interrelationship of chromatin structure and function.