Capturing chromosome conformation

Cardiac enhancers: Gateway to the regulatory mechanisms of heart regeneration

The adult mammalian heart has limited regenerative capacity. Cardiac injury, such as a myocardial infarction (MI), leads to permanent scarring and impaired heart function. In contrast, neonatal mice and zebrafish possess the ability to repair injured hearts. Cardiac regeneration is driven by profound transcriptional changes, which are controlled by gene regulatory elements, such as tissue regeneration enhancer elements (TREEs). Here, we review recent studies on cardiac injury/regeneration enhancers across species. We further explore regulatory mechanisms governing TREE activities and their associated binding regulators. We also discuss the potential of TREE engineering and how these enhancers can be utilized for heart repair. Decoding the regulatory logic of cardiac regeneration enhancers presents a promising avenue for understanding heart regeneration and advancing therapeutic strategies for heart failure.

Chromosome-level assemblies of the White bream Parabramis pekinensis

White bream Parabramis pekinensis is an omnivorous fish belong to Cyprinidae that is widespread in Asia. In this study, we presented chromosome-level genome assemblies of P. pekinensis by using PacBio HiFi long reads and Hi-C technology. We assembled high-quality genome of 1.03 Gb with scaffold N50 length of 40.04 Mb, and a total of 98.31% of the assembled sequences were anchored to 24 chromosomes. BUSCO analysis revealed that the genome assembly has a high-level completeness of 98.35% gene coverage. A total of 26,542 protein-coding genes were predicted, of which 92.61% were functionally annotated. The phylogenetic analysis indicated that the lineage leading to P. pekinensis was diverged from the lineage to Megalobrama amblycephala approximately 7.6 million years ago. The high-quality genome assembly provide valuable resources for evolutionary study and genetic breeding of genus Parabramis.

Binder and monomer valencies determine the extent of collapse and reswelling of chromatin

Multivalent DNA-bridging protein-mediated collapse of chromatin polymers have long been established as one of the driving factors in chromatin organization inside cells. These multivalent proteins can bind to distant binding sites along the chromatin backbone and bring them together in spatial proximity, leading to collapsed conformations. Recently, it has been suggested that these proteins not only drive the collapse of the chromatin polymer but also reswelling at higher concentrations. In this study, we investigate the physical mechanisms underlying this unexpected reswelling behavior. We use the Langevin dynamics simulation of a coarse-grained homopolymer to investigate the effects of the valencies of both the binders and the monomers on the polymer conformations. We find that while the extent of collapse of the polymer is strongly dependent on the binder valency, the extent of reswelling is largely determined by the monomer valency. Furthermore, we also discovered two different physical mechanisms that drive the reswelling of the polymer-excluded volume effects and loss of long-range loops. Finally, we obtain a classification map to determine the regimes in which each of these mechanisms is the dominant factor leading to polymer reswelling.

Hidden origami in Trypanosoma cruzi nuclei highlights its non-random 3D genomic organization

The protozoan Trypanosoma cruzi is the causative agent of Chagas disease and is known for its polycistronic transcription, with about 50% of its genome consisting of repetitive sequences, including coding (primarily multigenic families) and non-coding regions (such as ribosomal DNA, spliced leader [SL], and retroelements, etc). Here, we evaluated the genomic features associated with higher-order chromatin organization in T. cruzi (Brazil A4 strain) by extensive computational processing of high-throughput chromosome conformation capture (Hi-C). Through the mHi-C pipeline, designed to handle multimapping reads, we demonstrated that applying canonical Hi-C processing, which overlooks repetitive DNA sequences, results in a loss of DNA-DNA contacts, misidentifying them as chromatin-folding (CF) boundaries. Our analysis revealed that loci encoding multigenic families of virulence factors are enriched in chromatin loops and form shorter and tighter CF domains than the loci encoding core genes. We uncovered a non-random three-dimensional (3D) genomic organization in which nonprotein-coding RNA loci (transfer RNAs [tRNAs], small nuclear RNAs, and small nucleolar RNAs) and transcription termination sites are preferentially located at the boundaries of the CF domains. Our data indicate 3D clustering of tRNA loci, likely optimizing transcription by RNA polymerase III, and a complex interaction between spliced leader RNA and 18S rRNA loci, suggesting a link between RNA polymerase I and II machineries. Finally, we highlighted a group of genes encoding virulence factors that interact with SL-RNA loci, suggesting a potential regulatory role. Our findings provide insights into 3D genome organization in T. cruzi, contributing to the understanding of supranucleosomal-level chromatin organization and suggesting possible links between 3D architecture and gene expression.IMPORTANCEDespite the knowledge about the linear genome sequence and the identification of numerous virulence factors in the protozoan parasite Trypanosoma cruzi, there has been a limited understanding of how these genomic features are spatially organized within the nucleus and how this organization impacts gene regulation and pathogenicity. By providing a detailed analysis of the three-dimensional (3D) chromatin architecture in T. cruzi, our study contributed to narrowing this gap. We deciphered part of the origami structure hidden in the T. cruzi nucleus, showing the unidimensional genomic features are non-randomly 3D organized in the nuclear organelle. We uncovered the role of nonprotein-coding RNA loci (e.g., transfer RNAs, spliced leader RNA, and 18S RNA) in shaping genomic architecture, offering insights into an additional epigenetic layer that may influence gene expression.

CTCF depletion decouples enhancer-mediated gene activation from chromatin hub formation

Enhancers and promoters interact in three-dimensional (3D) chromatin structures to regulate gene expression. Here we characterize the mechanisms that drive the formation and function of these structures in a lymphoid-to-myeloid transdifferentiation system. Based on analyses at base pair resolution, we demonstrate a close correlation between binding of regulatory proteins, formation of chromatin interactions and gene expression. Multi-way interaction analyses and computational modeling show that tissue-specific gene loci are organized into chromatin hubs, characterized by cooperative interactions between multiple enhancers, promoters and CTCF-binding sites. While depletion of CTCF strongly impairs the formation of these chromatin hubs, the effects of CTCF depletion on gene expression are modest and can be explained by rewired enhancer-promoter interactions. These findings demonstrate a role for enhancer-promoter interactions in gene regulation that is independent of cooperative interactions in chromatin hubs. Together, these results contribute to our understanding of the structure-function relationship of the genome during cellular differentiation.

Toward decoding the mechanisms that shape sub-megabase-scale genome organization

Understanding genome organization at the kilobase to megabase scale is critical, as it encompasses genes and regulatory elements. Improvements in the resolution of experimental techniques have revealed novel structural motifs at this scale, including micro-compartments, nucleosome clutches, microdomains, and packing domains. Here we review recent progress on developing theories to explain these observations. Key advances include elucidating the role of nucleosome positioning and epigenetic modifications, the role and mechanisms of compartmentalization in local structure, and the interplay between loop extrusion and phase separation. This work has revealed probable mechanisms by which the observed structures emerge, but it remains unclear how these factors act together in the cell. To this end, recent studies have used chromatin conformation capture data in concert with diverse genomics datasets to create native-like models of chromatin at nucleosome resolution and below. While several roadblocks remain, this strategy promises to decode how molecular forces sum to shape chromatin structure and ultimately regulate transcription.

BINDER achieves accurate identification of hierarchical TADs by comprehensively characterizing consensus TAD boundaries

As crucial chromatin structures, hierarchical TADs play important roles in epigenetic organization, transcriptional activity, gene regulation, and cell differentiation. Currently, it remains a highly challenging task to accurately identify hierarchical TADs in a computational manner. The key bottleneck for existing TAD callers lies in the difficulty in the prediction of precise TAD boundaries. We solve this problem by introducing a novel algorithm, called BINDER, which conducts a boundary consensus approach, and then precisely locate hierarchical TAD boundaries by developing a multifaceted boundary characterization strategy. In comparison with other leading TAD callers, BINDER shows significant improvement in identifying hierarchical TADs and exhibits the strongest robustness with ultrasparse data, which supports the importance of boundary identification in calling hierarchical TADs. Applying BINDER to experimental data and mouse hematopoietic cases, we find that the hierarchical TADs identified by BINDER show strong biological relevance in their epigenetic organization, transcriptional activity, DNA motifs, and coregulation during cellular differentiation. BINDER discovers differences in the enrichment of two specific transcription factors, CHD1 and CHD2, at TAD boundaries with different hierarchies. It also observes variations in the gene expression of TADs with different hierarchies during cellular differentiation.

Altered 3D genome reorganization mediates precocious myeloid differentiation of aged hematopoietic stem cells in inflammation

Inflammation is a driving force of hematopoietic stem cells (HSCs) aging, causing irreversible exhaustion of functional HSCs. However, the underlying mechanism of HSCs erosion by inflammatory insult remains poorly understood. Here, we find that transient LPS exposure primes aged HSCs to undergo accelerated differentiation at the expense of self-renewal, leading to depletion of HSCs. Meanwhile, the central regulator nuclear factor kappa B (NF-κB) mediating functional impairment by inflammation insult induces differential transcriptional response in aged HSCs compared with young HSCs, with precocious activation of myeloid lineage genes. Altered compartmentalization and chromatin loop formation are associated with aging-related differential transcriptional response in HSCs upon lipopolysaccharide (LPS) stimulation. Mechanistically, enhancer and promoter regions of myeloid lineage genes in aged HSCs are more accessible and display more rapid and prominent CTCF occupancy upon LPS stimulation. Our study provides comprehensive resources for the three-dimensional (3D) genome structure of HSCs and sheds light into the ordered genome organization and the associated transcriptome signature underlying HSCs aging.

An era of immunological discoveries heralded by molecular biology

The Molecular Mechanisms of Immune Cell Development and Function (MMICDF) meeting sponsored by the Federation of American Societies of Experimental Biology (FASEB) occupies a special niche because of its focus on the molecular mechanisms that underpin immunological processes. This biennial meeting with small groupings of participants and interactive nature has provided a forum for intense, informative, and influential scientific discussions. The meeting is unique for its focus on molecular mechanisms that control the exceptional processes of DNA recombination, somatic hypermutation (SHM), and gene expression during immune cell development, activation, and differentiation. The organizers of the foundational meeting reflect on the coalescence of scientific advances that catalyzed its origin, review meeting highlights to celebrate its 20th anniversary, and project into the future.

Chrombus-XMBD: a graph convolution model predicting 3D-genome from chromatin features

The 3D conformation of the chromatin is crucial for transcriptional regulation. However, current experimental techniques for detecting the 3D structure of the genome are costly and limited to the biological conditions. Here, we described "ChrombusXMBD," a graph convolution model capable of predicting chromatin interactions ab initio based on available chromatin features. Using dynamic edge convolution with multihead attention mechanism, Chrombus encodes the 2D-chromatin features into a learnable embedding space, thereby generating a genome-wide 3D-contactmap. In validation, Chrombus effectively recapitulated the topological associated domains, expression quantitative trait loci, and promoter/enhancer interactions. Especially, Chrombus outperforms existing algorithms in predicting chromatin interactions over 1-2 Mb, increasing prediction correlation by 11.8%-48.7%, and predicts long-range interactions over 2 Mb (Pearson's coefficient 0.243-0.582). Chrombus also exhibits strong generalizability across human and mouse-derived cell lines. Additionally, the parameters of Chrombus inform the biological mechanisms underlying cistrome. Our model provides a new, generalizable analytical tool for understanding the complex dynamics of chromatin interactions and the landscape of cis-regulation of gene expression.

Polymer model integrates imaging and sequencing to reveal how nanoscale heterochromatin domains influence gene expression

Chromatin organization regulates gene expression, with nanoscale heterochromatin domains playing a fundamental role. Their size varies with microenvironmental stiffness and epigenetic interventions, but how these factors regulate their formation and influence transcription remains unclear. To address this, we developed a sequencing-informed copolymer model that simulates chromatin evolution through diffusion and active epigenetic reactions. Our model predicts the formation of nanoscale heterochromatin domains and quantifies how domain size scales with epigenetic reaction rates, showing that epigenetic and compaction changes primarily occur at domain boundaries. We validated these predictions via Hi-C and super-resolution imaging of hyperacetylated melanoma cells and identified differential expression of metastasis-related genes through RNA-seq. We validated our findings in hMSCs, where epigenetic reaction rates respond to microenvironmental stiffness. Conclusively, our simulations reveal that heterochromatin domain boundaries regulate gene expression and epigenetic memory. These findings demonstrate how external cues drive chromatin organization and transcriptional memory in development and disease.

KMT2C deficiency drives transdifferentiation of double-negative prostate cancer and confer resistance to AR-targeted therapy

Double-negative prostate cancer (DNPC), characterized by an androgen receptor (AR)- and neuroendocrine-null phenotype, frequently emerges following androgen deprivation therapy (ADT). However, our understanding of the origins and regulatory mechanisms of DNPC remains limited. Here, we discover that tumors with KMT2C mutation or loss are highly susceptible to transitioning into DNPC following ADT. We clarify that DNPC primarily stems from luminal cell transdifferentiation rather than basal cell transformation. Antiandrogen treatment induces KMT2C binding at enhancers of a subset of AR-regulated genes, preserving the adenocarcinoma lineage. KMT2C maintains ASPP2 expression via enhancer-promoter communication post-AR inhibition, while its inactivation reduces ASPP2, triggering ΔNp63-dependent transdifferentiation. This DNPC transition maintains fatty acid (FA) synthesis through ΔNp63-mediated SREBP1c transactivation, fueling DNPC growth via HRAS palmitoylation and MAPK signaling activation. These findings highlight KMT2C as an epigenetic checkpoint against DNPC development and suggest the therapeutic potential of targeting fatty acid synthesis.

Unveiling chromatin dynamics with virtual epigenome

The three-dimensional organization of chromatin is essential for gene regulation and cellular function, with epigenome playing a key role. Hi-C methods have expanded our understanding of chromatin interactions, but their high cost and complexity limit their use. Existing models for predicting chromatin interactions rely on limited ChIP-seq inputs, reducing their accuracy and generalizability. In this work, we present a computational approach, EpiVerse, which leverages imputed epigenetic signals and advanced deep learning techniques. EpiVerse significantly improves the accuracy of cross-cell-type Hi-C prediction, while also enhancing model interpretability by incorporating chromatin state prediction within a multitask learning framework. Moreover, EpiVerse predicts Hi-C contact maps across an array of 39 human tissues, which provides a comprehensive view of the complex relationship between chromatin structure and gene regulation. Furthermore, EpiVerse facilitates unprecedented in silico perturbation experiments at the "epigenome-level" to unveil the chromatin architecture under specific conditions. EpiVerse is available on GitHub: https://github.com/jhhung/EpiVerse .

Dissecting cardiovascular disease-associated noncoding genetic variants using human iPSC models

Advancements in genomics have revealed hundreds of loci associated with cardiovascular diseases, highlighting the role genetic variants play in disease pathogenesis. Notably, most variants lie within noncoding genomic regions that modulate transcription factor binding, chromatin accessibility, and thereby the expression levels and cell type specificity of gene transcripts. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a powerful tool to delineate the pathogenicity of such variants and elucidate the underlying transcriptional mechanisms. Our review discusses the basics of noncoding variant-mediated pathogenesis, the methodologies utilized, and how hiPSC-based heart models can be leveraged to dissect the mechanisms of noncoding variants.

Three-dimensional regulatory hubs support oncogenic programs in glioblastoma

Dysregulation of enhancer-promoter communication in the three-dimensional (3D) nucleus is increasingly recognized as a potential driver of oncogenic programs. Here, we profiled the 3D enhancer-promoter networks of patient-derived glioblastoma stem cells to identify central regulatory nodes. We focused on hyperconnected 3D hubs and demonstrated that hub-interacting genes exhibit high and coordinated expression at the single-cell level and are associated with oncogenic programs that distinguish glioblastoma from low-grade glioma. Epigenetic silencing of a recurrent hub-with an uncharacterized role in glioblastoma-was sufficient to cause downregulation of hub-connected genes, shifts in transcriptional states, and reduced clonogenicity. Integration of datasets across 16 cancers identified "universal" and cancer-type-specific 3D hubs that enrich for oncogenic programs and factors associated with worse prognosis. Genetic alterations could explain only a small fraction of hub hyperconnectivity and increased activity. Overall, our study provides strong support for the potential central role of 3D regulatory hubs in controlling oncogenic programs and properties.

A telomere-to-telomere genome assembly of cotton provides insights into centromere evolution and short-season adaptation

Cotton (Gossypium hirsutum L.) is a key allopolyploid crop with global economic importance. Here we present a telomere-to-telomere assembly of the elite variety Zhongmian 113. Leveraging technologies including PacBio HiFi, Oxford Nanopore Technology (ONT) ultralong-read sequencing and Hi-C, our assembly surpasses previous genomes in contiguity and completeness, resolving 26 centromeric and 52 telomeric regions, 5S rDNA clusters and nucleolar organizer regions. A phylogenetically recent centromere repositioning on chromosome D08 was discovered specific to G. hirsutum, involving deactivation of an ancestral centromere and the formation of a unique, satellite repeat-based centromere. Genomic analyses evaluated favorable allele aggregation for key agronomic traits and uncovered an early-maturing haplotype derived from an 11 Mb pericentric inversion that evolved early during G. hirsutum domestication. Our study sheds light on the genomic origins of short-season adaptation, potentially involving introgression of an inversion from primitively domesticated forms, followed by subsequent haplotype differentiation in modern breeding programs.

Comparing chromatin contact maps at scale: methods and insights

Comparing chromatin contact maps is an essential step in quantifying how three-dimensional (3D) genome organization shapes development, evolution, and disease. However, methods often disagree, and no gold standard exists for comparing pairs of maps. Here, we evaluate 25 ways to compare contact maps using Micro-C and Hi-C data from two cell types and in silico-generated contact maps. We identify similarities and differences between the methods and quantify their robustness to common sources of biological and technical variation, including losses and gains of CTCF-binding sites, changes in contact intensity or patterns, and noise. We find that global comparison methods, such as mean squared error, are suitable for initial screening; however, biologically informed methods are necessary for identifying how maps diverge and for proposing specific functional hypotheses. We provide a reference guide, codebase, and thorough evaluation for rapidly comparing chromatin contact maps at scale to enable biological insights into 3D genome organization.

Organization and Dynamics of Chromosomes

How long thread-like eukaryotic chromosomes fit tidily in the small volume of the nucleus without significant entanglement is just beginning to be understood, thanks to major advances in experimental techniques. Several polymer models, which reproduce contact maps that measure the probabilities that two loci are in spatial contact, have predicted the 3D structures of interphase chromosomes. Data-driven approaches, using contact maps as input, predict that mitotic helical chromosomes are characterized by a switch in handedness, referred to as perversion. By using experimentally derived effective interactions between chromatin loci in simulations, structures of conventional and inverted nuclei have been accurately predicted. Polymer theory and simulations show that the dynamics of individual loci in chromatin exhibit subdiffusive behavior but the diffusion exponents are broadly distributed, which accords well with experiments. Although coarse-grained models are successful, many challenging problems remain, which require the creation of new experimental and computational tools to understand genome biology.

Resolving 3-Dimensional Genomic Landscape of CD4+ T Cells in the Peripheral Blood of Patients with Psoriasis

A precise regulation of gene expression depends on the accuracy of the 3-dimensional (3D) structure of chromatin; however, the effects of the 3D genome on gene expression in psoriasis remain unknown. In this study, we conducted Hi-C and RNA sequencing on CD4+ T cells collected from 5 patients with psoriasis and 3 healthy controls and constructed a comprehensive 3D chromatin interaction map to delineate the genomic hierarchies, including A/B compartments, topologically associated domains, and chromatin loops. Then, the specific superenhancers related to psoriasis were identified by Hi-C and H3K27ac chromatin immunoprecipitation sequencing data. Subsequently, comprehensive analyses were carried out on the differentially expressed genes that are associated with altered topologically associated domains, loops, and superenhancers in psoriasis. Finally, we screened the candidate target genes and examined the potential functional SNP in psoriasis affected by disruptions of the spatial organization. This study provides a comprehensive reference for examining the 3D genome interactions in psoriasis and elucidating the interplay between spatial organization disruption and gene regulation. We hope that our findings can help clarify the mechanisms underlying the pathogenesis of psoriasis and shed light on the role of 3D genomic structure, therefore informing potential therapeutic approaches.

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.

Discovery of therapeutic targets in cardiovascular diseases using high-throughput chromosome conformation capture (Hi-C)

Epigenetic changes have been associated with several cardiovascular diseases. In recent years, epigenetic inheritance based on spatial changes has gradually attracted attention. Alterations in three-dimensional chromatin structures have been shown to regulate gene expression and influence disease onset and progression. High-throughput Chromosome Conformation Capture (Hi-C) is a powerful method to detect spatial chromatin conformation changes. Since its development, Hi-C technology has been widely adopted for discovering novel therapeutic targets in cardiovascular research. In this review, we summarize key targets identified by Hi-C in cardiovascular diseases and discuss their potential implications for epigenetic therapy.

Incorporating multiscale methylation effects into nucleosome-resolution chromatin models for simulating mesoscale fibers

Histone modifications play a crucial role in regulating chromatin architecture and gene expression. Here we develop a multiscale model for incorporating methylation in our nucleosome-resolution physics-based chromatin model to investigate the mechanisms by which H3K9 and H3K27 trimethylation (H3K9me3 and H3K27me3) influence chromatin structure and gene regulation. We apply three types of energy terms for this purpose: short-range potentials are derived from all-atom molecular dynamics simulations of wildtype and methylated chromatosomes, which revealed subtle local changes; medium-range potentials are derived by incorporating contacts between HP1 and nucleosomes modified by H3K9me3, to incorporate experimental results of enhanced contacts for short chromatin fibers (12 nucleosomes); for long-range interactions we identify H3K9me3- and H3K27me3-associated contacts based on Hi-C maps with a machine learning approach. These combined multiscale effects can model methylation as a first approximation in our mesoscale chromatin model, and applications to gene systems offer new insights into the epigenetic regulation of genomes mediated by H3K9me3 and H3K27me3.

scHiGex: predicting single-cell gene expression based on single-cell Hi-C data

A novel biochemistry experiment named HiRES has been developed to capture both the chromosomal conformations and gene expression levels of individual single cells simultaneously. Nevertheless, when compared to the extensive volume of single-cell Hi-C data generated from individual cells, the number of datasets produced from this experiment remains limited in the scientific community. Hence, there is a requirement for a computational tool that can forecast the levels of gene expression in individual cells using single-cell Hi-C data from the same cells. We trained a graph transformer called scHiGex that accurately and effectively predicts gene expression levels based on single-cell Hi-C data. We conducted a benchmark of scHiGex that demonstrated notable performance on the predictions with an average absolute error of 0.07. Furthermore, the predicted levels of gene expression led to precise categorizations (adjusted Rand index score 1) of cells into distinct cell types, demonstrating that our model effectively captured the heterogeneity between individual cell types. scHiGex is freely available at https://github.com/zwang-bioinformatics/scHiGex.

From Lesions to Lessons: Two Decades of Filamentous Plant Pathogen Genomics

Many filamentous microorganisms, such as fungi and oomycetes, have evolved the ability to colonize plants and cause devastating crop diseases. Coevolutionary conflicts with their hosts have shaped the genomes of these plant pathogens. Over the past 20 years, genomics and genomics-enabled technologies have revealed remarkable diversity in genome size, architecture, and gene regulatory mechanisms. Technical and conceptual advances continue to provide novel insights into evolutionary dynamics, diversification of distinct genomic compartments, and facilitated molecular disease diagnostics. In this review, we discuss how genomics has advanced our understanding of genome organization and plant-pathogen coevolution and provide a perspective on future developments in the field. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Single-Cell Hi-C Technologies and Computational Data Analysis

Single-cell chromatin conformation capture (scHi-C) techniques have evolved to provide significant insights into the structural organization and regulatory mechanisms in individual cells. Although many scHi-C protocols have been developed, they often involve intricate procedures and the resulting data are sparse, leading to computational challenges for systematic data analysis and limited applicability. This review provides a comprehensive overview, quantitative evaluation of thirteen protocols and practical guidance on computational topics. It is first assessed the efficiency of these protocols based on the total number of contacts recovered per cell and the cis/trans ratio. It is then provided systematic considerations for scHi-C quality control and data imputation. Additionally, the capabilities and implementations of various analysis methods, covering cell clustering, A/B compartment calling, topologically associating domain (TAD) calling, loop calling, 3D reconstruction, scHi-C data simulation and differential interaction analysis is summarized. It is further highlighted key computational challenges associated with the specific complexities of scHi-C data and propose potential solutions.

Roles for the 3D genome in the cell cycle, DNA replication, and double strand break repair

Large eukaryotic genomes are packaged into the restricted area of the nucleus to protect the genetic code and provide a dedicated environment to read, copy and repair DNA. The physical organisation of the genome into chromatin loops and self-interacting domains provides the basic structural units of genome architecture. These structural arrangements are complex, multi-layered, and highly dynamic and influence how different regions of the genome interact. The role of chromatin structures during transcription via enhancer-promoter interactions is well established. Less understood is how nuclear architecture influences the plethora of chromatin transactions during DNA replication and repair. In this review, we discuss how genome architecture is regulated during the cell cycle to influence the positioning of replication origins and the coordination of DNA double strand break repair. The role of genome architecture in these cellular processes highlights its critical involvement in preserving genome integrity and cancer prevention.

Generalization of the sci-L3 method to achieve high-throughput linear amplification for replication template strand sequencing, genome conformation capture, and the joint profiling of RNA and chromatin accessibility

Single-cell combinatorial indexing (sci) methods have addressed major limitations of throughput and cost for many single-cell modalities. With the incorporation of linear amplification and three-level barcoding in our suite of methods called sci-L3, we further addressed the limitations of uniformity in single-cell genome amplification. Here, we build on the generalizability of sci-L3 by extending it to template strand sequencing (sci-L3-Strand-seq), genome conformation capture (sci-L3-Hi-C), and the joint profiling of RNA and chromatin accessibility (sci-L3-RNA/ATAC). We demonstrate the ease of adapting sci-L3 to these new modalities by only requiring a single-step modification of the original protocol. As a proof of principle, we show our ability to detect sister chromatid exchanges, genome compartmentalization, and cell state-specific features in thousands of single cells. We anticipate sci-L3 to be compatible with additional modalities, including DNA methylation (sci-MET) and chromatin-associated factors (CUT&Tag), and ultimately enable a multi-omics readout of them.

Uncovering topologically associating domains from three-dimensional genome maps with TADGATE

Topologically associating domains (TADs) are essential components of three-dimensional (3D) genome organization and significantly influence gene transcription regulation. However, accurately identifying TADs from sparse chromatin contact maps and exploring the structural and functional elements within TADs remain challenging. To this end, we develop TADGATE, a graph attention auto-encoder that can generate imputed maps from sparse Hi-C contact maps while adaptively preserving or enhancing the underlying topological structures, thereby facilitating TAD identification. TADGATE captures specific attention patterns with two types of units within TADs and demonstrates TAD organization relates to chromatin compartmentalization with diverse biological properties. We identify many structural and functional elements within TADs, with their abundance reflecting the overall properties of these domains. We applied TADGATE to sparse and noisy Hi-C contact maps from 21 human tissues or cell lines. That improved the clarity of TAD structures, allowing us to investigate conserved and cell-type-specific boundaries and uncover cell-type-specific transcriptional regulatory mechanisms associated with topological domains. We also demonstrated TADGATE's capability to fill in sparse single-cell Hi-C contact maps and identify TAD-like domains within them, revealing the specific domain boundaries with distinct heterogeneity and the shared backbone boundaries characterized by strong CTCF enrichment and high gene expression levels.

Bridging scales in chromatin organization: Computational models of loop formation and their implications for genome function

Chromatin loop formation plays a crucial role in 3D genome interactions, with misfolding potentially leading to irregular gene expression and various diseases. While experimental tools such as Hi-C have advanced our understanding of genome interactions, the biophysical principles underlying chromatin loop formation remain elusive. This review examines computational approaches to chromatin folding, focusing on polymer models that elucidate chromatin loop mechanics. We discuss three key models: (1) the multi-loop-subcompartment model, which investigates the structural effects of loops on chromatin conformation; (2) the strings and binders switch model, capturing thermodynamic chromatin aggregation; and (3) the loop extrusion model, revealing the role of structural maintenance of chromosome complexes. In addition, we explore advanced models that address chromatin clustering heterogeneity in biological processes and disease progression. The review concludes with an outlook on open questions and current trends in chromatin loop formation and genome interactions, emphasizing the physical and computational challenges in the field.

A New Blood-Based Epigenetic Diagnostic Biomarker Test (EpiSwitch®® NST) with High Sensitivity and Positive Predictive Value for Colorectal Cancer and Precancerous Polyps

BACKGROUND/OBJECTIVES

Colorectal cancer (CRC) arises from the epithelial lining of the colon or rectum, often following a progression from benign adenomatous polyps to malignant carcinoma. Screening modalities such as colonoscopy, faecal immunochemical tests (FIT), and FIT-DNA are critical for early detection and prevention, but non-invasive methods lack sensitivity to polyps and early CRC. Chromosome conformations (CCs) are potent epigenetic regulators of gene expression. We have previously developed an epigenetic assay, EpiSwitch®®, that employs an algorithmic-based CCs analysis. Using EpiSwitch®® technology, we have shown the presence of cancer-specific CCs in peripheral blood mononuclear cells (PBMCs) and primary tumours of patients with melanoma and prostate cancer. EpiSwitch®®-based commercial tests are now available to diagnose prostate cancer with 94% accuracy (PSE test) and response to immune checkpoint inhibitors across 14 cancers with 85% accuracy (CiRT test). Methods/Results/Conclusions: Using blood samples collected from n = 171 patients with CRC, n = 44 patients with colorectal polyps and n = 110 patients with a 'clear' colonoscopy we performed whole Genome DNA screening for CCs correlating to CRC diagnosis. Our findings suggest the presence of two eight-marker CC signatures (EpiSwitch®® NST) in whole blood that allow diagnosis of CRC and precancerous polyps, respectively. Independent validation cohort testing demonstrated high accuracy in identifying colorectal polyps and early versus late stages of CRC with an exceptionally high sensitivity of 79-90% and a high positive prediction value of 60-84%. Linking the top diagnostic CCs to nearby genes, we have built pathways maps that likely underline processes contributing to the pathology of polyp and CRC progression, including TGFβ, cMYC, Rho GTPase, ROS, TNFa/NFκB, and APC.

Microscopy methods for the in vivo study of nanoscale nuclear organization

Eukaryotic genomes are highly compacted within the nucleus and organized into complex 3D structures across various genomic and physical scales. Organization within the nucleus plays a key role in gene regulation, both facilitating regulatory interactions to promote transcription while also enabling the silencing of other genes. Despite the functional importance of genome organization in determining cell identity and function, investigating nuclear organization across this wide range of physical scales has been challenging. Microscopy provides the opportunity for direct visualization of nuclear structures and has pioneered key discoveries in this field. Nonetheless, visualization of nanoscale structures within the nucleus, such as nucleosomes and chromatin loops, requires super-resolution imaging to go beyond the ~220 nm diffraction limit. Here, we review recent advances in imaging technology and their promise to uncover new insights into the organization of the nucleus at the nanoscale. We discuss different imaging modalities and how they have been applied to the nucleus, with a focus on super-resolution light microscopy and its application to in vivo systems. Finally, we conclude with our perspective on how continued technical innovations in super-resolution imaging in the nucleus will advance our understanding of genome structure and function.

A guide to studying 3D genome structure and dynamics in the kidney

The human genome is tightly packed into the 3D environment of the cell nucleus. Rapidly evolving and sophisticated methods of mapping 3D genome architecture have shed light on fundamental principles of genome organization and gene regulation. The genome is physically organized on different scales, from individual genes to entire chromosomes. Nuclear landmarks such as the nuclear envelope and nucleoli have important roles in compartmentalizing the genome within the nucleus. Genome activity (for example, gene transcription) is also functionally partitioned within this 3D organization. Rather than being static, the 3D organization of the genome is tightly regulated over various time scales. These dynamic changes in genome structure over time represent the fourth dimension of the genome. Innovative methods have been used to map the dynamic regulation of genome structure during important cellular processes including organism development, responses to stimuli, cell division and senescence. Furthermore, disruptions to the 4D genome have been linked to various diseases, including of the kidney. As tools and approaches to studying the 4D genome become more readily available, future studies that apply these methods to study kidney biology will provide insights into kidney function in health and disease.

Artificial design of the genome: from sequences to the 3D structure of chromosomes

Genome design is the foundation of genome synthesis, which provides a new platform for deepening our understanding of biological systems by exploring the fundamental components and structure of the genome. Artificial genome designs can endow unnatural genomes with desired functions. We provide a comprehensive overview of genome design principles ranging from DNA sequences to the 3D structure of chromosomes. Furthermore, we highlight applications of genome design in gene expression, genome structure, genome function, and biocontainment, and discuss the potential of artificial intelligence (AI) in genome design.

Rok from B. subtilis: Bridging genome structure and transcription regulation

Bacterial genomes are folded and organized into compact yet dynamic structures, called nucleoids. Nucleoid orchestration involves many factors at multiple length scales, such as nucleoid-associated proteins and liquid-liquid phase separation, and has to be compatible with replication and transcription. Possibly, genome organization plays an intrinsic role in transcription regulation, in addition to classical transcription factors. In this review, we provide arguments supporting this view using the Gram-positive bacterium Bacillus subtilis as a model. Proteins BsSMC, HBsu and Rok all impact the structure of the B. subtilis chromosome. Particularly for Rok, there is compelling evidence that it combines its structural function with a role as global gene regulator. Many studies describe either function of Rok, but rarely both are addressed at the same time. Here, we review both sides of the coin and integrate them into one model. Rok forms unusually stable DNA-DNA bridges and this ability likely underlies its repressive effect on transcription by either preventing RNA polymerase from binding to DNA or trapping it inside DNA loops. Partner proteins are needed to change or relieve Rok-mediated gene repression. Lastly, we investigate which features characterize H-NS-like proteins, a family that, at present, lacks a clear definition.

Analysis of Functional cis-Regulatory Elements Reveals Novel Transcriptional Regulatory Mechanisms in Gonadal Development

INTRODUCTION

Recent studies have demonstrated that the production of bidirectional enhancer-derived transcripts (eRNAs) is a characteristic of an active cis-regulatory element (CRE). Higher levels of eRNAs synthesis correlate with the activation of histone modifications, a potentially valuable tool for deciphering the complexity of the gene regulatory network.

METHOD

To understand the changes of CREs during gonadal development in mice, we collected gonadal WT1-positive cells from the piggyBac-Wt1-mCherry-2A-EGFP (PBWt1-RG) reporter strain at E13.5, E16.5, and P0 in both sexes and conducted cap analysis of gene expression (CAGE) analysis, which is capable to capture transcription start sites (TSSs). We compared the levels of intergenic bidirectional RNAs, i.e., potentially eRNAs, according to sex at each stage (testis somatic cells vs. ovary somatic cells at E13.5, E16.5, and P0) and stage in each sex (E13.5 vs. E16.5, E16.5 vs. P0, and E13.5 vs. P0 in testis somatic cells or ovary somatic cells). Intergenic RNAs with significant changes (|Log2FC| > 1, p < 0.05) were selected.

RESULTS

The TSS profile of intergenic RNAs changed more profoundly in testis somatic cells than in ovary somatic cells, suggesting that embryonic testicular development is driven by larger changes in the transcriptional regulatory network than ovarian development. Based on the profiles of the predicted transcription factors (TFs) that would bind to the active CREs during gonadal development, the NR4A, EGR, and TCF3 families would be novel TFs to play pivotal roles in gonadal development.

CONCLUSION

Identifying active CREs using eRNAs would provide a means to comprehensively understand the transcriptional regulatory system, leading to valuable insights into the gonadal development of male and female individuals.

Long G4-rich enhancers target promoters via a G4 DNA-based mechanism

Several studies have now described instances where G-rich sequences in promoters and enhancers regulate gene expression through forming G-quadruplex (G4) structures. Relatedly, our group recently identified 301 long genomic stretches significantly enriched for minimal G4 motifs (LG4s) in humans and found the majority of these overlap annotated enhancers, and furthermore, that the promoters regulated by these LG4 enhancers are similarly enriched with G4-capable sequences. While the generally accepted model for enhancer:promoter specificity maintains that interactions are dictated by enhancer- and promoter-bound transcriptional activator proteins, the current study tested an alternative hypothesis: that LG4 enhancers interact with cognate promoters via a direct G4:G4 DNA-based mechanism. This work establishes the nuclear proximity of LG4 enhancer:promoter pairs, biochemically demonstrates the ability of individual LG4 single-stranded DNAs (ssDNAs) to directly interact target promoter ssDNAs, and confirms that these interactions, as well as the ability of LG4 enhancers to activate target promoters in culture, are mediated by G4 DNA.

Gene Doping Detection From the Perspective of 3D Genome

Since the early 20th century, the concept of doping was first introduced. To achieve better athletic performance, chemical substances were used. By the mid-20th century, it became gradually recognized that the illegal use of doping substances can seriously endangered athletes' health and compromised the fairness of sports competitions. Over the past 30 years, the World Anti-Doping Agency (WADA) has established corresponding rules and regulations to prohibit athletes from using doping substances or restrict the use of certain drugs, and isotope, chromatography, and mass spectrometry techniques were accredited to detect doping substances. With the development of gene editing technology, many genetic diseases have been effectively treated, but enabled by the same technology, doping has also the potential to pose a threat to sports in the form of gene doping. WADA has explicitly indicated gene doping in the Prohibited List as a prohibited method (M3) and approved qPCR detection. However, gene doping can easily evade detection, if the target genes' upstream regulatory elements are considered, the task became more challenging. Hi-C experiment driven 3D genome technology, through perspectives such as topologically associating domain (TAD) and chromatin loop, provides a more comprehensive and in-depth understanding of gene regulation and expression, thereby better preventing the potential use of 3D genome level gene doping. In this work, we will explore gene doping from a different perspective by analyzing recent studies on gene doping and explore related genes under 3D genome.

Dynamic 3D genome reorganization during senescence: defining cell states through chromatin

Cellular senescence, a cell state characterized by growth arrest and insensitivity to growth stimulatory hormones, is accompanied by a massive change in chromatin organization. Senescence can be induced by a range of physiological signals and pathological stresses and was originally thought to be an irreversible state, implicated in normal development, wound healing, tumor suppression and aging. Recently cellular senescence was shown to be reversible in some cases, with exit being triggered by the modulation of the cell's transcriptional program by the four Yamanaka factors, the suppression of p53 or H3K9me3, PDK1, and/or depletion of AP-1. Coincident with senescence reversal are changes in chromatin organization, most notably the loss of senescence-associated heterochromatin foci (SAHF) found in oncogene-induced senescence. In addition to fixed-cell imaging, chromatin conformation capture and multi-omics have been used to examine chromatin reorganization at different spatial resolutions during senescence. They identify determinants of SAHF formation and other key features that differentiate distinct types of senescence. Not surprisingly, multiple factors, including the time of induction, the type of stress experienced, and the type of cell involved, influence the global reorganization of chromatin in senescence. Here we discuss how changes in the three-dimensional organization of the genome contribute to the regulation of transcription at different stages of senescence. In particular, the distinct contributions of heterochromatin- and lamina-mediated interactions, changes in gene expression, and other cellular control mechanisms are discussed. We propose that high-resolution temporal and spatial analyses of the chromatin landscape during senescence will identify early markers of the different senescence states to help guide clinical diagnosis.

Machine and Deep Learning Methods for Predicting 3D Genome Organization

Three-dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, topologically associating domains (TADs), and A/B compartments, play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers and transcription factor binding site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, and TAD boundaries) and analyze their pros and cons. We also point out obstacles to the computational prediction of 3D interactions and suggest future research directions.

Multicontact statistics distinguish models of chromosome organization

Chromosome organization can be modeled using various approaches, ranging from mechanistic bottom-up models to models inferred directly from experimental data. Many such models can recapitulate experimental Hi-C data for pairwise contact probabilities, meaning that these data cannot always be used to distinguish different models. Here, we consider two illustrative example models for bacterial chromosome organization: one a bottom-up model for loop extrusion, the other a data-driven maximum entropy model inferred from Hi-C data. We find that despite predicting similar pairwise contact frequencies, the models predict qualitatively different features on three-point contact maps. We explain these differences by constructing analytical approximations for three-point contact probabilities in each model. Finally, we apply our analytical approximations to previously published experimental multicontact data from human chromosomes, and find that these data are well described by the loop extruder approximation. Our work illustrates how multicontact statistics can be used to compare and test models for chromosome organization.

Using Chromosome Conformation Capture Combined with Deep Sequencing (Hi-C) to Study Genome Organization in Bacteria

Genome organization is fundamental to all living organisms. Long DNA molecules are organized in hierarchical orders to be accommodated into eukaryotic nuclei or bacterial cells, which are thousands of folds shorter. Over the past two decades, chromosome conformation capture (3C) techniques substantially advanced our understanding of genome folding inside cells. 3C involves crosslinking and proximity ligation, and quantifies the physical contacts between two DNA regions within the genome. Coupled with high-throughput sequencing, 3C-seq and Hi-C techniques detect genome-wide DNA interactions, providing a comprehensive view of global genome organization. Here, we describe a detailed method to prepare Hi-C libraries using Bacillus subtilis, which includes procedures of crosslinking chromatin, digesting the crosslinked genome, labeling DNA ends with biotin, ligating DNA, and preparing the DNA library for sequencing using an Illumina platform.

The Evolution of Next-Generation Sequencing Technologies

The genetic information that dictates the structure and function of all life forms is encoded in the DNA. In 1953, Watson and Crick first presented the double helical structure of a DNA molecule. Their findings unearthed the desire to elucidate the exact composition and sequence of DNA molecules. Discoveries and the subsequent development and optimization of techniques that allowed for deciphering the DNA sequence has opened new doors in research, biotech, and healthcare. The application of high-throughput sequencing technologies in these industries has positively impacted and will continue to contribute to the betterment of humanity and the global economy. Improvements, such as the use of radioactive molecules for DNA sequencing to the use of florescent dyes and the implementation of polymerase chain reaction (PCR) for amplification, led to sequencing a few hundred base pairs in days, to automation, where sequencing of thousands of base pairs in hours became possible. Significant advances have been made, but there is still room for improvement. Here, we look at the history and the technology of the currently available next-generation sequencing platforms and the possible applications of such technologies to biomedical research and beyond.

ParSite is a multicolor DNA labeling system that allows for simultaneous imaging of triple genomic loci in living cells

The organization of the human genome in space and time is critical for transcriptional regulation and cell fate determination. However, robust methods for tracking genome organization or genomic interactions over time in living cells are lacking. Here, we developed a multicolor DNA labeling system, ParSite, to simultaneously track triple genomic loci in the U2OS cells. The tricolor ParSite system is derived from the T. thermophilus ParB/ParSc (TtParB/ParSc) system by rational design. We mutated the interface between TtParB and ParSc and generated a new pair of TtParBm and ParSm for genomic DNA labeling. The insertions of 16 base-pair palindromic ParSc and ParSm into genomic loci allow dual-color DNA imaging in living cells. A pair of genomic loci labeled by ParSite could be colocalized with p53-binding protein 1 (53BP1) in response to CRISPR/Cas9-mediated double-strand breaks (DSBs). The ParSite permits tracking promoter and terminator dynamics of the APP gene, which spans 290 kilobases in length. Intriguingly, the hybrid ParS (ParSh) of half-ParSc and half-ParSm enables for the visualization of a third locus independent of ParSc or ParSm. We simultaneously labeled 3 loci with a genomic distance of 36, 89, and 352 kilobases downstream the C3 repeat locus, respectively. In sum, the ParSite is a robust DNA labeling system for tracking multiple genomic loci in space and time in living cells.

Mapping the 3D genome architecture

The spatial organization of the genome plays a critical role in regulating gene expression, cellular differentiation, and genome stability. This review provides an in-depth examination of the methodologies, computational tools, and frameworks developed to map the three-dimensional (3D) architecture of the genome, focusing on both ligation-based and ligation-free techniques. We also explore the limitations of these methods, including biases introduced by restriction enzyme digestion and ligation inefficiencies, and compare them to more recent ligation-free approaches such as Genome Architecture Mapping (GAM) and Split-Pool Recognition of Interactions by Tag Extension (SPRITE). These techniques offer unique insights into higher-order chromatin structures by bypassing ligation steps, thus enabling the capture of complex multi-way interactions that are often challenging to resolve with traditional methods. Furthermore, we discuss the integration of chromatin interaction data with other genomic layers through multimodal approaches, including recent advances in single-cell technologies like sci-HiC and scSPRITE, which help unravel the heterogeneity of chromatin architecture in development and disease.

Three-dimensional regulatory hubs support oncogenic programs in glioblastoma

Dysregulation of enhancer-promoter communication in the context of the three-dimensional (3D) nucleus is increasingly recognized as a potential driver of oncogenic programs. Here, we profiled the 3D enhancer-promoter networks of primary patient-derived glioblastoma stem cells (GSCs) in comparison with neuronal stem cells (NSCs) to identify potential central nodes and vulnerabilities in the regulatory logic of this devastating cancer. Specifically, we focused on hyperconnected 3D regulatory hubs and demonstrated that hub-interacting genes exhibit high and coordinated expression at the single-cell level and strong association with oncogenic programs that distinguish IDH-wt glioblastoma patients from low-grade glioma. Epigenetic silencing of a recurrent 3D enhancer hub-with an uncharacterized role in glioblastoma-was sufficient to cause concordant downregulation of multiple hub-connected genes along with significant shifts in transcriptional states and reduced clonogenicity. By integrating published datasets from other cancer types, we also identified both universal and cancer type-specific 3D regulatory hubs which enrich for varying oncogenic programs and nominate specific factors associated with worse outcomes. Genetic alterations, such as focal duplications, could explain only a small fraction of the detected hyperconnected hubs and their increased activity. Overall, our study provides computational and experimental support for the potential central role of 3D regulatory hubs in controlling oncogenic programs and properties.

A genome-wide nucleosome-resolution map of promoter-centered interactions in human cells corroborates the enhancer-promoter looping model

The enhancer-promoter looping model, in which enhancers activate their target genes via physical contact, has long dominated the field of gene regulation. However, the ubiquity of this model has been questioned due to evidence of alternative mechanisms and the lack of its systematic validation, primarily owing to the absence of suitable experimental techniques. In this study, we present a new MNase-based proximity ligation method called MChIP-C, allowing for the measurement of protein-mediated chromatin interactions at single-nucleosome resolution on a genome-wide scale. By applying MChIP-C to study H3K4me3 promoter-centered interactions in K562 cells, we found that it had greatly improved resolution and sensitivity compared to restriction endonuclease-based C-methods. This allowed us to identify EP300 histone acetyltransferase and the SWI/SNF remodeling complex as potential candidates for establishing and/or maintaining enhancer-promoter interactions. Finally, leveraging data from published CRISPRi screens, we found that most functionally verified enhancers do physically interact with their cognate promoters, supporting the enhancer-promoter looping model.

A long noncoding eRNA forms R-loops to shape emotional experience-induced behavioral adaptation

Emotional experiences often evoke neural plasticity that supports adaptive changes in behavior, including maladaptive plasticity associated with mood and substance use disorders. These adaptations are supported in part by experience-dependent activation of immediate-early response genes, such as Npas4 (neuronal PAS domain protein 4). Here we show that a conserved long noncoding enhancer RNA (lnc-eRNA), transcribed from an activity-sensitive enhancer, produces DNA:RNA hybrid R-loop structures that support three-dimensional chromatin looping between enhancer and proximal promoter and rapid Npas4 gene induction. Furthermore, in mouse models, Npas4 lnc-eRNA and its R-loop are required for the development of behavioral adaptations produced by chronic psychosocial stress or cocaine exposure, revealing a potential role for this regulatory mechanism in the transmission of emotional experiences.

Comprehensive Predictions of Mef2-Mediated Chromatin Loops, Which May Inhibit Ubx Binding by Blocking Low-Affinity Binding Sites

Gene regulation depends on the interaction between chromatin-associated factors, such as transcription factors (TFs), which promote chromatin loops to ensure tight contact between enhancer and promoter regions. So far, positive interactions that lead to gene activation have been the main focus of research, but regulations related to blocking or inhibiting factor binding are also essential to maintaining a defined cellular status. To understand these interactions in greater detail, I investigated the possibility of the muscle differentiation factor Mef2 to prevent early Hox factor binding, leading to the proper timing of regulatory processes and the activation of differentiation events. My investigations relied on a collection of publicly available genome-wide binding data sets of Mef2 and Ubx (as the Hox factor), Capture-C interactions, and ATAC-seq analysis in Mef2 mutant cells. The analysis indicated that Mef2 can form possible chromatin loops to Ubx-bound regions. These regions contain low-affinity Ubx binding sites, and the chromatin architecture is independent of Mef2's function. High levels of Ubx may disrupt the loops and allow specific Ubx bindings to regulate defined targets. In summary, my investigations highlight that the use of many publicly available data sets enables computational approaches to make robust predictions and, for the first time, suggest a molecular function of Mef2 as a preventer of Hox binding, indicating that it may act as a timer for muscle differentiation.

PfMORC protein regulates chromatin accessibility and transcriptional repression in the human malaria parasite, Plasmodium falciparum

The environmental challenges the human malaria parasite, Plasmodium falciparum, faces during its progression into its various lifecycle stages warrant the use of effective and highly regulated access to chromatin for transcriptional regulation. Microrchidia (MORC) proteins have been implicated in DNA compaction and gene silencing across plant and animal kingdoms. Accumulating evidence has shed light on the role MORC protein plays as a transcriptional switch in apicomplexan parasites. In this study, using the CRISPR/Cas9 genome editing tool along with complementary molecular and genomics approaches, we demonstrate that PfMORC not only modulates chromatin structure and heterochromatin formation throughout the parasite erythrocytic cycle, but is also essential to the parasite survival. Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments suggests that PfMORC binds to not only sub-telomeric regions and genes involved in antigenic variation but may also play a role in modulating stage transition. Protein knockdown experiments followed by chromatin conformation capture (Hi-C) studies indicate that downregulation of PfMORC impairs key histone marks and induces the collapse of the parasite heterochromatin structure leading to its death. All together these findings confirm that PfMORC plays a crucial role in chromatin structure and gene regulation, validating this factor as a strong candidate for novel antimalarial strategies.

A mini-review of single-cell Hi-C embedding methods

Single-cell Hi-C (scHi-C) techniques have significantly advanced our understanding of the 3D genome organization, providing crucial insights into the spatial genome architecture within individual nuclei. Numerous computational and statistical methods have been developed to analyze scHi-C data, with embedding methods playing a key role. Embedding reduces the dimensionality of complex scHi-C contact maps, making it easier to extract biologically meaningful patterns. These methods not only enhance cell clustering based on chromatin structures but also facilitate visualization and other downstream analyses. Most scHi-C embedding methods incorporate strategies such as normalization and imputation to address the inherent sparsity of scHi-C data, thereby further improving data quality and interpretability. In this review, we systematically examine the existing methods designed for scHi-C embedding, outlining their methodologies and discussing their capabilities in handling normalization and imputation. Additionally, we present a comprehensive benchmarking analysis to compare both embedding techniques and their clustering performances. This review serves as a practical guide for researchers seeking to select suitable scHi-C embedding tools, ultimately contributing to the understanding of the 3D organization of the genome.