Over the past decades, vast progress in sequencing and imaging has transformed our understanding of chromatin organization in the cell nucleus and its relevance in development and disease. Imaging methods have regained popularity in recent years, as they inherently facilitate single-cell resolution and visualization of subnuclear spatial distances and morphology. An exceptional strength of imaging is the relative ease of designing multimodal experiments, as DNA and RNA fluorescence in situ hybridization (FISH) can be combined with immunofluorescencestaining for joint visualization of genomic loci, transcripts, and proteins. In this mini-review, we highlight recent imaging developments that advance our views on 3D genome organization, focusing primarily on oligonucleotide-based DNA FISH and emerging applications (e.g.chromatin tracing, live-cell imaging, lineage reconstruction, and optical pooled screening). To help novices navigate this rapidly expanding field, we provide a comprehensive overview of the main oligo-based FISH methods.

Plant genome biology is entering a new era defined by fully phased, chromosome-scale, telomere-to-telomere assemblies, enabled by the convergence of long-read sequencing technologies, improved assembly algorithms, and powerful scaffolding strategies. Gapless, haplotype-resolved genomes are now feasible even for polyploid species, shifting the bottleneck from assembly to annotation and interpretation. Genome annotation remains one of the greatest opportunities and challenges in plant biology. While ab initio methods still form the backbone of structural prediction, evidence-based frameworks that integrate RNA sequencing, chromatin accessibility, methylation, and 3D genome data are rapidly advancing the field. At the same time, artificial intelligence-driven protein-coding gene predictors are redefining ab initio gene finding, and large-scale orthology networks continue to improve functional inference. The next frontier is extending annotation beyond protein-coding genes into regulatory and structural dimensions, a goal increasingly enabled by single-cell and multi-omic technologies. Looking forward, the integration of AI, multi-omics, and large language models promises to standardize and automate workflows from DNA isolation to functional annotation. These innovations will accelerate fundamental plant biology discovery, enable next-generation biodiversity conservation, and transform strategies for crop improvement and biotechnology.

Cell differentiation is a complex process characterized by specific gene expression patterns regulated through enhancer-promoter interactions within the three-dimensional architecture of the nucleus. The precise role of cohesin loading dynamics in restructuring chromatin during pancreatic lineage commitment remains unclear. Here we show that knockdown of cohesin loader NIPBL disrupts enhancer-promoter interactions and CTCF-mediated loops, leading to widespread transcriptional dysregulation. Furthermore, the loss of cohesin-mediated loops is accompanied by increased contacts between Polycomb Repressive Complex (PRC) domains, highlighting the interplay between cohesin dynamics and PRC-mediated compartmentalization. Although RAD21 and SA1 cohesin levels remain stable at CTCF loop anchors, NIPBL is essential for maintaining long-range chromatin interactions at later differentiation stages. These findings establish cohesin loading as a critical regulator of 3D genome reorganization during cell fate determination, providing a mechanistic framework for understanding cohesinopathy-related developmental disorders.

Temporal dynamic and GhGLR4.8-mediated reorganization of 3D chromatin architecture during Fusarium oxysporum f. sp. vasinfectum infection in cotton.

Understanding how the 3D structure of the genome influences gene regulation is a growing area of interest, particularly in the context of alternative post-transcriptional regulatory events such as alternative splicing (AS) and alternative polyadenylation (APA). These processes are essential for generating transcript and protein diversity, and they are tightly coordinated with transcription. However, despite their biological importance, the relationship between chromatin interactions and alternative pre-messenger RNA regulation remains poorly understood. This gap largely stems from a lack of computational tools capable of integrating structural genomic data with RNA processing dynamics. Exploring how chromatin interactions and epigenetic landscapes shape these events is essential for uncovering the multilayered regulation of gene expression. To bridge this gap, we present EpGAT, a graph attention network-based model that integrates epigenetic read coverage and chromatin interaction data to predict and quantify AS and APA events. By explicitly modeling the spatial organization of the genome, EpGAT captures the regulatory influence of chromatin looping and long-range genomic interactions on RNA processing. The model's predictions are validated through rigorous cross-cell line and cross-chromosome evaluations, affirming its generalizability and reliability. Beyond prediction, EpGAT offers interpretability by tracing learned parameters back to genomic features, enabling the identification of active enhancers, mapping promoter-enhancer connectivity, and pinpointing the epigenetic factors most critical to specific RNA processing events. These capabilities make EpGAT a powerful tool for dissecting the complex interplay between genome architecture and transcriptomic regulation. More broadly, it provides a generalizable framework for multiple tasks to study the link between 3D genome organization, epigenetic signals, and RNA processing.

Toward a multiomics framework for understanding symbiotic nitrogen fixation.

Xiaoyaosan and isoliquiritigenin remodel depression-associated chromatin 3D structure and phase separation of NF-κB p65.

Single-cell Hi-C (scHi-C) provides unprecedented insight into 3D genome organization, but its sparse and noisy data pose challenges in accurately detecting A/B compartments, which are crucial for understanding chromatin structure and gene regulation. We presented scDIAGRAM, a data-driven method for annotating A/B compartments in single cells using direct statistical modeling and graph community detection. Unlike existing approaches, scDIAGRAM infers chromatin compartments directly from individual scHi-C matrix without imputation or external reference features, and subsequently assigns A/B labels using conventional genomic annotations. Accuracy and robustness of scDIAGRAM were illustrated through simulated scHi-C datasets and a human cell line. We applied scDIAGRAM to real scHi-C datasets from the mouse brain cortex, mouse embryonic development, and human acute myeloid leukemia, demonstrating its ability to capture compartmental shifts associated with transcriptional variation. This robust framework offers new insights into the functional roles of chromatin compartments at single-cell resolution across various biological contexts.

Mammalian sex is determined by opposing networks of ovarian and testicular genes that are well characterized; however, its epigenetic regulation is still largely unknown. Here we explore the 3D chromatin landscape of sex determination in vivo by profiling fluorescence-activated cell-sorted embryonic mouse gonadal populations in both sexes before and after sex determination. Through conventional Hi-C analyses, we show that chromatin structures, particularly topologically associating domains, remain largely unchanged during sex determination, suggesting a preformed configuration. We further integrate Hi-C data with ChIP-seq experiments using METALoci, a spatial autocorrelation analysis that identifies three-dimensional (3D) regulatory hubs across the genome. We uncover a prominent rewiring of chromatin interactions during sex determination, affecting the 3D regulatory hubs of hundreds of genes that display time-specific and sex-specific expression. By combining predictive approaches and validations in transgenic mice, we identify a 3D regulatory hub for the protesticular gene Fgf9. The deletion of this gonad-specific hub allows mutant mice to survive through development, overcoming lung lethality associated with Fgf9 loss of function while exhibiting male-to-female sex reversal. Through the reconstruction of gene regulatory networks, we identify a function for Meis genes, which act redundantly to specify sexual identity during ovarian and testicular development. Our results underscore the dynamic role of the 3D genome during sex determination, highlighting the potential of epigenomic approaches to uncover regulators of developmental processes.

Global epigenetic resetting in the gonadal primordial germ cells (PGCs) enables transition from early PGCs to gametogenesis and eventual restoring of totipotency after fertilization. This reprogramming process involves global DNA demethylation, changes in nuclear morphology and remodeling of repressive histone modifications. Here, using combined cytological and Hi-C-based methods, we reveal that, following the epigenetic reprogramming and concomitant with their commitment to gametogenesis, premeiotic gonadal germ cells display a distinct chromosome and genome architecture. This involves separation of individual chromosomes, anchoring of centromeres at the nuclear periphery, reduction in interchromosome interactions and disentangling of chromosome ends. Furthermore, genome-wide contact mapping documents remodeling of the three-dimensional (3D) genome architecture across all observable levels, including disruption of topologically associating domains (TADs), loss of detectable loops and reduced active-active compartment interactions. We further show that the diminished TADs correlate with the reduced levels of CCCTC-binding factor, thus providing an in vivo physiological model to understand genome folding principles. Lastly, we show that PGC-like cells, derived from embryonic stem cells, do not exhibit the same chromatin organization as embryonic germ cells. Collectively, our findings uncover the existence of a distinct chromatin architecture in premeiotic male and female gonadal germ cells and show that, alongside global DNA demethylation, the germline epigenetic reprogramming involves erasure of memory at the genome architectural level through profound reorganization of the 3D genome.

Spatial organization of the genome plays a vital role in defining cell identity and regulating gene expression. The three-dimensional (3D) genome structure can be measured by sequencing-based techniques such as Hi-C usually on the cell population level or by imaging-based techniques such as chromatin tracing at the single-cell level. Chromatin tracing is a multiplexed DNA fluorescence in situ hybridization (FISH)-based method that can directly map the 3D positions of genomic loci along individual chromosomes at single-molecule resolution. However, few computational tools are available for statistical differential analysis of chromatin tracing data, which are inherently high-dimensional, highly variable and contain many missing values. Here, we present Dory, a statistical method for identifying differential spatial patterns between two groups of chromatin traces. Dory quantifies pairwise spatial distances among genomic regions in a chromatin trace and applies multi-level statistical tests to detect significant structural differences between the two groups of traces. It produces a differential score matrix highlighting region pairs with significant distance difference. Applying Dory to multiple chromatin tracing datasets, we found that the detected chromatin structural changes were associated with alterations in A/B compartments and promoter-enhancer interactions correlated with differential gene expression. Dory is a robust and user-friendly computational tool for quantitative analysis of imaging-based 3D genome data that enables systematic exploration of chromatin architecture and its roles in gene regulation.

The three-dimensional (3D) organization of cis-regulatory elements (CREs) is critical in transcription control. However, capturing transcriptome, epigenome and 3D genome from the same single cells remains challenging. Here we present scHiCAR (single-cell Hi-C with assay for transposase-accessible chromatin and RNA sequencing), a plate-based combinatorial barcoding method that simultaneously profiles mRNA, open chromatin and chromosome conformation capture from the same cells. Compared to existing single-cell 3D genome methods, scHiCAR more efficiently enriches long-range cis-interactions anchored at candidate CREs (cCREs). Applied to 1.62 million mouse brain cells and complemented with a deep-learning-based loop caller, scHiCAR accurately defines cell-type-specific transcriptomes, accessible cCREs and 5-kb-resolution enhancer-promoter pairs across 22 brain cell types. scHiCAR also performs robustly in challenging tissues such as skeletal muscle, enabling trimodal single-cell-level analysis of gene regulation dynamics during muscle stem cell regeneration. By providing a scalable and cost-effective system for single-cell trimodal analysis of gene-regulatory landscapes in complex tissues, scHiCAR reveals gene-locus-specific regulatory roles of 3D genome reorganization in transcriptional control.

Epigenetic clocks have successfully estimated biological age by identifying CpG sites whose DNA methylation levels correlate with chronological age. However, these statistical models provide limited mechanistic insight into the biological underpinnings of ageing. While they capture the "pace" of ageing, they fail to quantify the "resilience" of biological systems-the capacity to recover, reorganize, and maintain homeostasis under stress. To overcome this limitation, we introduce EpiAge-R (Epigenetic Age with Resilience), a mechanistic framework that shifts the focus from passive correlation to active recovery potential. The EpiAge-R framework integrates multilayered biological information-including long-read methylation sequencing, chromatin context, histone modification balance, 3D genome topology, and mitochondrial dynamics-into a unified Resilience Index. By distinguishing between degenerative methylation drift (damage) and adaptive repair processes (resilience), EpiAge-R aligns with nonlinear multi-omics ageing trajectories. This framework provides a quantitative foundation for next-generation biomarkers and precision longevity interventions, aiming to define optimal health rather than statistical normality.

As the first sequenced non-mammalian amniote, the chicken (Gallus gallus) has served as a major source of cost-effective and protein-enriched foods since domestication. However, how structural variations (SVs) affect 3D genome reorganization to influence domestication and production traits remains unclear in chickens. Here, fifteen de novo chromosome-level genome assemblies are newly generated, along with high-throughput chromosome conformation capture (Hi-C), ATAC and RNA sequencing data. By integrating 13 published assemblies, the first pan-3D genome resource is constructed, spanning genes, SVs, and chromatin architectures, to investigate the dynamic characteristics of the 3D genome at different levels and the roles of SVs in the conservation and reorganization of chromatin architectures. Furthermore, candidate SVs and their linked genes are identified for domestication and production traits based on 1,735 resequencing accessions. Notably, the 240-bp and 81-bp SVs in the TSHR and DIO2 genes are considered the key targets in artificial selection for seasonal reproduction, and a 266-bp deletion upstream of the KLF3 gene affects carcass performance by rewriting the chromatin loop interaction network. Finally, SVs significantly improve the predictive accuracy in genomic selection models. Collectively, this study presents a comprehensive pan-3D resource to advance functional genomic research and breeding practice for the community.

Chromatin loops play a crucial role in gene regulation and cellular function, providing key insights into understanding the 3D structure of the genome and its impact on cellular homeostasis. Nanopore sequencing technology, with its advantages in simultaneously detecting sequences and methylation patterns, brings new opportunities for studying 3D genome structures. We introduce NanoLoop, the first algorithmic framework attempting to predict genome-wide chromatin interactions using Nanopore data. In experiments across four human lymphoblastoid cell lines, NanoLoop demonstrated excellent predictive performance and cross-cell line generalization capabilities. We also discovered four distinct methylation patterns at loop anchors that influence histone modification levels and determine various loop types. NanoLoop further predicted previously uncharacterized long-range chromatin loops, highlighting the potential link between DNA methylation and 3D genome organization and providing new insights into the complex regulatory relationships between epigenetic modifications and 3D genome organization.

The basal ganglia are a group of forebrain nuclei critical for motor control and reward processing, and their dysfunction contributes to neurological and neuropsychiatric disorders. Here, we present the first multimodal single-cell epigenomic atlas of the human basal ganglia across major subregions and cell types. We jointly profiled DNA methylation and 3D chromatin conformation in 197,003 nuclei from eight basal ganglia subregions using multi-omic sequencing (snm3C-seq), and integrated these data with existing DNA methylation and chromatin conformation sequencing datasets to build a unified atlas of 261,331 cells spanning 31 subclasses and 59 groups. This atlas reveals extensive cell-type- and region-specific differential methylation, enriched for distinct transcription factor motifs, and validated by MERFISH spatial transcriptomics, which uncovered epigenetic gradients linked to transcriptional output. Compared to neuronal cells, non-neuronal cells exhibit distinct 3D genome organization including smaller chromatin compartments, increased long-range inter-compartment contacts, shorter loops, and stronger CG hypomethylation in A compartments. We further identified genes that display compartment switches, are strongly correlated with compartment scores, and exhibit differential domain boundaries and chromatin looping across basal ganglia cell types. We identified multiple medium spiny neuron subtypes defined by distinct hypomethylated signature genes, with 3D genome embeddings emphasizing dorsal, ventral, and hybrid populations. By integrating chromatin accessibility and histone modification profiles, we reconstructed cell-type-resolved enhancer-promoter links and gene regulatory networks, providing a comprehensive epigenomic framework for interpreting genetic risk loci and regulatory architecture in the human basal ganglia.

DNA methylation is a conserved epigenetic modification crucial for silencing genes and transposable elements (TEs). However, the mechanisms that cause silencing remain unclear, partly because methyl reader protein mutants in both plants and animals show minimal transcriptional changes. To explore the possibility of redundancy among these silencing mechanisms, we generated combinatorial mutants of H1.1, H1.2, ADCP1, MOM1, MBD2, MBD5, and MBD6 lacking key methyl readers and related silencing pathways. We observed massive derepression of genes and TEs at DNA-methylated loci, showing that these pathways account for 73% of silencing compared to DNA methylation-free mutants. We also observed that immune response genes were upregulated, causing an imbalance between growth and defense. Loss of downstream silencing pathways further disrupted 3D genome organization, leading to increased euchromatin-heterochromatin interactions. These findings highlight the cooperative action of multiple downstream mechanisms in DNA methylation-mediated silencing and genome organization.

Studying the three-dimensional (3D) structure of a genome, including chromatin loops and Topologically Associating Domains (TADs), is essential for understanding how the genome is organized, such as gene activation, cell development, protein-protein interaction, etc. Hi-C protocol enables us to study 3D genome structure and organization. Chromatin 3D structure changes dynamically over time, and modeling these continuous changes is crucial for downstream analysis in various domains such as disease diagnosis, vaccine development, etc. The high expense and impracticality of continuous genome sequencing, particularly what evolves between two timestamps, limit the most effective genomic analysis. It is crucial to develop a straightforward and cost-efficient method for constantly generating genomic data between two timestamps in order to address these constraints. In this study, we developed HiCInterpolate, a 4D spatiotemporal interpolation architecture that accepts two timestamp Hi-C contact matrices to interpolate intermediate Hi-C contact matrices at high resolution. HiCInterpolate predicts the intermediate Hi-C contact map using a deep learning-based flow predictor, and a feature encoder and decoder architecture similar to U-Net. In addition, HiCInterpolate supports downstream analysis of multiple 3D genomic features, including A/B compartments, chromatin loops, TADs, and 3D genome structure, through an integrated analysis pipeline. Across multiple evaluation metrics, including PSNR, SSIM, GenomeDISCO, HiCRep, and LPIPS, HiCInterpolate achieved consistently strong performance. Biological validation further demonstrated preservation of key chromatin organization features, such as chromatin loops, A/B compartments, and TADs. Together, these results indicate that HiCInterpolate provides a robust computer vision-based framework for high-resolution interpolation of intermediate Hi-C contact matrices and facilitates biologically meaningful downstream analyses. HiCInterpolate is publicly available at https://github.com/OluwadareLab/HiCInterpolate .

SUMMARYHistone modifications underpin the cell-type-specific gene regulatory networks that drive the remarkable cellular heterogeneity of the adult mammalian brain. Here, we profiled four histone modifications jointly with transcriptome in 2.5 million nuclei across multiple adult mouse brain regions. By integrating these data with existing maps of chromatin accessibility, DNA methylation, and 3D genome organization, we established a unified regulatory framework for over 100 brain cell subclasses. This integrative epigenomic atlas annotates 81% of the genome, defining distinct active, primed, and repressive states. Notably, active chromatin states marked by combinatorial histone modifications more precisely identify functional enhancers than chromatin accessibility alone, while Polycomb- and H3K9me3-mediated repression contributes prominently to cell-type-specific regulation. Finally, this multi-modal resource enables deep learning models to predict epigenomic features and gene expression from DNA sequences. This work provides a comprehensive annotation of the mouse brain regulatory genome and a framework for interpreting non-coding variation in complex tissues.

3D genome mapping technologies ChIA-PET, HiChIP, PLAC-seq, HiCAR, and ChIATAC yield pairwise contacts and a one-dimensional signal indicating protein binding or chromatin accessibility. However, a lack of computational tools to quantify the reproducibility of these enrichment-based 3C data prevents rigorous data quality assessment and interpretation. We developed HiChIA-Rep, an algorithm incorporating both 1D and 2D signals to measure similarity via graph signal processing methods. HiChIA-Rep can distinguish biological replicates from non-replicates, cell lines, and protein factors, outperforming tools designed for Hi-C data. With a large amount of multi-ome datasets being generated, HiChIA-Rep will likely be a fundamental tool for the 3D genomics community.