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Haplotype-resolved 3D genome maps reveal RNAPII-mediated allelic regulation in hybrid rice.

To understand how the two parental genomes coordinate transcription in hybrids, chromatin architecture must be resolved at the haplotype level. Here, using phased Bridge-Linker Hi-C, we reconstructed a haplotype-resolved three-dimensional (3D) genome of the elite hybrid rice (Oryza sativa) line Shanyou 63 (SY63). We identified extensive allele-specific chromatin conformations. Furthermore, we generated allele-resolved RNAPII ChIA-PET maps and phased transcriptomes to explore how chromatin interactions contribute to allelic regulation. Although maternal and paternal homologs share broadly similar chromatin features, we detected widespread haplotype-biased RNAPII binding and chromatin looping at high resolution. These allele-specific RNAPII-mediated contacts were significantly associated with biased expression. Stronger RNAPII binding on one haplotype promoted the formation of long-range regulatory loops with distal genes, thereby contributing to allele-biased transcription at a subset of loci, even when promoter-proximal RNAPII occupancy was comparable between alleles. These results demonstrate that subtle differences in RNAPII engagement and 3D regulatory wiring between parental haplotypes can reshape transcriptional output in hybrids, providing new insights into the mechanisms underlying the allelic regulation of gene expression.

Allele-specific chromatin interactions

3D genome mapping identifies subgroup-specific chromosome conformations and tumor-dependency genes in ependymoma.

Ependymoma is a tumor of the brain or spinal cord. The two most common and aggressive molecular groups of ependymoma are the supratentorial ZFTA-fusion associated and the posterior fossa ependymoma group A. In both groups, tumors occur mainly in young children and frequently recur after treatment. Although molecular mechanisms underlying these diseases have recently been uncovered, they remain difficult to target and innovative therapeutic approaches are urgently needed. Here, we use genome-wide chromosome conformation capture (Hi-C), complemented with CTCF and H3K27ac ChIP-seq, as well as gene expression and DNA methylation analysis in primary and relapsed ependymoma tumors, to identify chromosomal conformations and regulatory mechanisms associated with aberrant gene expression. In particular, we observe the formation of new topologically associating domains ('neo-TADs') caused by structural variants, group-specific 3D chromatin loops, and the replacement of CTCF insulators by DNA hyper-methylation. Through inhibition experiments, we validate that genes implicated by these 3D genome conformations are essential for the survival of patient-derived ependymoma models in a group-specific manner. Thus, this study extends our ability to reveal tumor-dependency genes by 3D genome conformations even in tumors that lack targetable genetic alterations.

Child

MIA-Jet: Multi-scale Identification Algorithm of Chromatin Jets.

The mammalian genome is organized into large-scale chromosome territories, compartments, domains, and at the smallest scale, chromatin loops and stripes. The newest element is a chromatin jet, a diffused line perpendicular to the main diagonal in the Hi-C contact map, which was reported in quiescent mammalian lymphocytes supporting a two-sided symmetric cohesin loop extrusion model. A similar structure is observed in Repli-HiC data, where relatively thin and straight chromatin fountains indicate coupling of DNA replication forks. However, the precise biological implications of these jet-like structures are unknown due to the limitations in computational methods. We developed MIA-Jet, a multi-scale ridge detection algorithm that can accurately detect jets of variable lengths, widths, and angles. When tested on Hi-C, Repli-HiC, ChIA-PET, ChIA-Drop, and Micro-C data in mouse, human, roundworm, and zebrafish cells, MIA-Jet outperformed existing methods. In human cells, jets were enriched in cohesin loading sites and early replication initiation zones. Applying MIA-Jet to Hi-C data generated from protein-degraded cells revealed that jets are dependent on cohesin but not YY1, and jet signals are strengthened after depleting WAPL. We envision MIA-Jet to be broadly applicable to any 3D genome mapping data, thereby providing new insights into the functional roles of chromatin jets.

3D genome mapping

Beyond genes: EpiSwitch® and Orion platform-powered 3D genome architecture biomarkers reveal shared biology across ME/CFS, long COVID, PTSD, rheumatoid arthritis, and multiple sclerosis.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Long COVID (LC19), post-traumatic stress disorder (PTSD), rheumatoid arthritis (RA), and multiple sclerosis (MS) are clinically distinct disorders that share substantial symptom overlap, including persistent fatigue, cognitive impairment, autonomic dysfunction, and immune dysregulation. Although these conditions differ in diagnosis and clinical presentation, their underlying biological mechanisms remain poorly understood and may involve convergent regulatory pathways. METHODS: The EpiSwitch® 3D genomics platform and Orion knowledgebase were used to integrate chromosome conformation signatures with genome-wide association study (GWAS)-derived datasets across ME/CFS, LC19, PTSD, RA, and MS. Three-dimensional genomic anchors were mapped to coding genes and analysed using STRING protein-protein interaction networks and Cytoscape-based systems biology approaches. Disease-specific anchor datasets were generated and compared at both gene and network levels to identify shared biological processes and regulatory mechanisms. RESULTS: Analysis of the ME/CFS dataset identified 552 unique 3D genomic anchors mapped to 567 genes, with analogous disease-specific anchor sets generated for LC19, PTSD, RA, and MS. Direct overlap between disease-associated genes was limited; however, higher-order network analyses revealed substantial interconnectivity and convergence across conditions. Shared biological pathways included immune and cytokine signalling, interferon responses, mitochondrial function, metabolic regulation, and neuroendocrine processes. Highly connected hub genes included immune regulatory nodes such as LAG3 and components of the mTOR signalling pathway, implicating T-cell exhaustion, chronic immune activation, and immunometabolic dysregulation as common mechanisms underlying these disorders. CONCLUSIONS: These findings support a systems-level model in which clinically overlapping fatigue-associated syndromes arise from perturbations of interconnected regulatory networks rather than discrete disease-specific pathways. Despite limited genetic overlap, substantial convergence at the network level suggests shared biological architecture across ME/CFS, LC19, PTSD, RA, and MS. The identification of common regulatory pathways provides a mechanistic framework for the development of cross-disease diagnostic and therapeutic strategies. By capturing dynamic regulatory states, 3D genomic biomarkers offer significant potential for objective blood-based diagnostics, patient stratification, and the identification of shared therapeutic targets across complex chronic disorders. These findings support the application of precision medicine approaches and may accelerate the development of novel interventions for fatigue-associated multisystem diseases.

Humans

Reconstructing the 3D genome organization of Neanderthals reveals that chromatin folding shaped phenotypic and sequence divergence.

Changes in gene regulation were a major driver of the divergence of archaic hominins (AHs)-Neanderthals and Denisovans-and modern humans (MHs). The three-dimensional (3D) folding of the genome is critical for regulating gene expression; however, its role in recent human evolution has not been explored because the degradation of ancient samples does not permit experimental determination of AH 3D genome folding. To fill this gap, we apply novel deep learning methods for inferring 3D genome organization from DNA sequence to Neanderthal, Denisovan, and diverse MH genomes. Using the resulting 3D contact maps across the genome, we identify 167 distinct regions with diverged 3D genome organization between AHs and MHs. We show that these 3D-diverged loci are enriched for genes related to the function and morphology of the eye, supra-orbital ridges, hair, lungs, immune response, and cognition. Despite these specific diverged loci, the 3D genome of AHs and MHs is more similar than expected based on sequence divergence, suggesting that the pressure to maintain 3D genome organization constrained hominin sequence evolution. We also find that 3D genome organization constrained the landscape of AH ancestry in MHs today: regions more tolerant of 3D variation are enriched for introgression in modern Eurasians. Finally, we identify loci where modern Eurasians have inherited novel 3D genome folding patterns from AH ancestors and validate folding differences in a high-frequency locus using Hi-C, revealing a putative molecular mechanism for phenotypes associated with archaic introgression. In summary, our application of deep learning to predict archaic 3D genome organization illustrates the potential of inferring molecular phenotypes from ancient DNA to reveal previously unobservable biological differences.

Journal Article

AQuA Tools: clear and reliable BEDPE operations for 3D genomics.

MOTIVATION: The genome interacts with itself within the volume of the cell nucleus to process information. These interactions mediate signal integration, gene regulation, and cell identity. The identification of new therapeutic targets from non-coding disease-associated variants relies critically on correctly assigning variants to genes through 3D interactions. Experimental techniques in 3D genomics, such as HiC and HiChIP, allow the mapping of interactions through sequencing. Bioinformatics for 3D genomics contends primarily with contact matrices that contain interaction frequencies for all possible element pairs, and BEDPE files that store element pairs that interact. Whereas the tools available for processing linear genomic data are mature, operating on contact matrices and BEDPE files remains cumbersome, opaque, and error-prone, as researchers have had to shoehorn tools originally designed for linear data. A genome arithmetic designed from the ground up for 3D genomics does not yet exist. RESULTS: We present AQuA Tools, a suite of shell- and R-based command-line tools that provide a set of core operations on contact matrices and BEDPE files motivated by key questions in population genetics, cancer research, and precision medicine. We have designed our core operations to be clear, reliable, intuitive and versatile. Core operations can be chained together along with standard UNIX commands. Our goal is to make AQuA Tools easy for the novice to learn and the go-to choice for power users. We hope our tools will motivate more researchers to use 3D genomic data in their projects. AVAILABILITY AND IMPLEMENTATION: We provide and maintain AQuA Tools at https://github.com/axiotl/aqua-tools.

Genomics

3D chromatin structures precede genome activation in Drosophila embryogenesis.

3D chromatin structure is critical for the regulation of gene expression during development. Here we used Micro-C assays at 100-bp resolution to map genome organization in Drosophila melanogaster throughout the first half of embryogenesis. These high-resolution contact maps reveal fine-scale features such as loops and boundaries delineating topologically associating domains. Notably, we observe that 3D chromatin structures form prior to zygotic genome activation and persist during successive mitotic cycles. Integrative analysis with 149 public chromatin immunoprecipitation sequencing (ChIP-seq) datasets identifies four classes of chromatin structuring elements, including a distinct group enriched for GAGA-associated factor (GAF) and Zelda binding, associated with developmental-gene regulation. These elements are mitotically retained and exhibit sequence and structure similarity between D. melanogaster and D. virilis. We propose that 3D chromatin organization in the pre-cellular embryo facilitates deployment of developmentally regulated genes during Drosophila embryogenesis.

Animals

Effects of Lamina-Chromatin Attachment on Super Long-Range Chromatin Interactions.

The interactions between chromatin and lamin proteins localized on the nuclear envelope play a crucial role in the three-dimensional (3D) organization of the genome. This study investigates the influence of lamin associated domains (LADs) on genome organization at the chromosome level using 3D polymer models of mouse embryonic fibroblasts (MEFs) and embryonic stem cells (mESCs). By integrating genome-wide LAD maps from DamID assays, we simulated chromatin conformations with and without LAD attachment to the nuclear envelope. Our results show that incorporating LAD-lamin interactions yields a radial chromatin distribution consistent with experimental observations. Moreover, LAD-lamin interactions induce significant super long-range chromatin contacts across distant genomic regions. These findings suggest two distinct mechanisms driving induction of chromatin interactions by LAD-lamin attachment.

3D single cell conformations

Enhancer activation from transposable elements in extrachromosomal DNA.

Extrachromosomal DNA (ecDNA) drives oncogene amplification and intratumoral heterogeneity in aggressive cancers. While transposable element (TE) reactivation is common in cancer, its role on ecDNA remains unexplored. Here, we map the 3D architecture of MYC-amplified ecDNA in colorectal cancer cells and identify 68 ecDNA-interacting elements (EIEs)-genomic loci enriched for TEs that are frequently integrated onto ecDNA. We focus on an L1M4a1#LINE/L1 fragment co-amplified with MYC, which functions only in the ecDNA amplified context. Using CRISPR-CATCH, CRISPR interference, and reporter assays, we confirm its presence on ecDNA, enhancer activity, and essentiality for cancer cell fitness. These findings reveal that repetitive elements can be reactivated and co-opted as functional rather than inactive sequences on ecDNA, potentially driving oncogene expression and tumor evolution. Our study uncovers a mechanism by which ecDNA harnesses repetitive elements to shape cancer phenotypes, with implications for diagnosis and therapy.

Journal Article

Four-dimensional molecular mapping from a spatial snapshot reveals the dynamics of hair follicle organogenesis.

Understanding organ formation requires capturing molecular information simultaneously in three-dimensional (3D) space and across developmental time. To this end, we developed 3D DNase-Enhanced Expression Profiling (3DEEP), a tissue-clearing approach that removes genomic DNA to extend spatial transcriptomic profiling hundreds of microns into intact tissues. We applied 3DEEP to neonatal mouse skin, capturing hundreds of developing hair follicles across their organogenesis trajectory. Ordering follicles by molecularly inferred developmental age transformed this single spatial snapshot into a four-dimensional (3D + time) molecular map of organogenesis. This map revealed developmental dynamics spanning stem cell compartment stratification, emergence of new cell subtypes within the follicle, and cascading structural transformations leading to hair canal formation. Comparative analysis of Foxn1-deficient nude mice, a hairlessness model, revealed organ-wide changes in developmental dynamics, including delayed molecular progression, reduced coordination, and increased developmental instability, preceding overt structural defects. This work demonstrates how deep-tissue spatial transcriptomics can uncover hidden dynamics of organ formation.

Animals

Genome topology analysis and transcriptomics of human osteoclasts reveals enhancer-promoter interactions at loci for bone traits and diseases.

Genome-wide association studies (GWAS) relevant to osteoporosis have identified hundreds of loci; however, understanding how these variants influence the phenotype is complicated because most reside in non-coding DNA sequence that serves as transcriptional enhancers and repressors. To advance knowledge on these regulatory elements in osteoclasts (OCs), we performed Micro-C analysis, which informs on the genome topology of these cells and integrated the results with transcriptome and GWAS data to further define loci linked to BMD. Using blood cells isolated from 4 healthy participants aged 31-61 yr, we cultured OC in vitro and generated a Micro-C chromatin conformation capture dataset. We characterized chromatin loops (CLs) in OC from among more than 69 million chromatin interactions identified in the genome. Of the CL identified in OC, >16 000 were unique compared to precursor cells. When sentinel single nucleotide polymorphisms from osteoporosis and bone-related GWAS and those in linkage disequilibrium at r 2 > 0.6 were mapped to CL for OC, 12 588 of these variants were observed within chromatin contact regions. Notable in differential gene ontology enrichment analyses of the topology data for OC and precursors were pathways regulating pluripotency of stem cells, Wnt signaling, nucleotide-binding oligomerization domain (NOD)-like receptor signaling and chemokine signaling. These data, in combination with other 3D genome architecture and epigenetic data (eg, histone modifications and chromatin accessibility), will be useful in modeling to predict genome-wide, which enhancers regulate which genes in OC. This data will therefore also be informative for resolving GWAS hits. In conclusion, we have generated a high-resolution genome topology dataset for human OC and have used this to identify CLs relevant to studies of the genetics of osteoporosis. This data will serve as a powerful resource to inform future functional studies of OC biology.

BMD

A full-proteome, interaction-specific characterization of mutational hotspots across human cancers.

Rapid accumulation of cancer genomic data has led to the identification of an increasing number of mutational hotspots with uncharacterized significance. Here we present a biologically informed computational framework that characterizes the functional relevance of all 1107 published mutational hotspots identified in approximately 25,000 tumor samples across 41 cancer types in the context of a human 3D interactome network, in which the interface of each interaction is mapped at residue resolution. Hotspots reside in network hub proteins and are enriched on protein interaction interfaces, suggesting that alteration of specific protein-protein interactions is critical for the oncogenicity of many hotspot mutations. Our framework enables, for the first time, systematic identification of specific protein interactions affected by hotspot mutations at the full proteome scale. Furthermore, by constructing a hotspot-affected network that connects all hotspot-affected interactions throughout the whole-human interactome, we uncover genome-wide relationships among hotspots and implicate novel cancer proteins that do not harbor hotspot mutations themselves. Moreover, applying our network-based framework to specific cancer types identifies clinically significant hotspots that can be used for prognosis and therapy targets. Overall, we show that our framework bridges the gap between the statistical significance of mutational hotspots and their biological and clinical significance in human cancers.

Genomics

Mapping Focal and Generalized Effects of Common Genetic Variants on Human Brain Structure.

Genome-wide association studies (GWAS) have advanced the quest to understand how specific genetic variants influence human brain structure and function. Recent work has identified hundreds of common variants associated with subcortical brain volumes, sparking interest in how these genetic markers overlap across brain networks. While this can be estimated by hierarchical clustering of the genetic correlation matrix to identify modular patterns of shared architecture, no brain-wide maps of these effects are available. To address this, we computed polygenic scores (PGS) from loci associated with ten brain volume regions of interest (ROIs): nine major subcortical structures and intracranial volume, with each locus weighted by its association with regional volume. In an independent sample from the discovery GWAS, we performed large-scale segmentation of 3D volumetric T1-weighted MRI scans using voxel-based morphometry (VBM) to map 3D profile of regions where gray matter volume (GMV) was associated with each PGS. We found statistically significant, localized effects for PGS defined for the amygdala, thalamus, and basal ganglia, but PGS for brainstem volume was associated with widespread differences throughout the brain. These brain-wide maps reveal patterns consistent with both localized and distributed genetic influences, offering a novel approach to interpret the genomic architecture of brain structure.

GWAS

Genome assembly of Astatotilapia latifasciata uncovers B chromosome-linked chromatin reorganization.

B chromosomes (Bs) are supernumerary genomic elements found in many eukaryotes, yet their full sequence composition, functional potential, and regulatory impact on the host genome remain unclear. Here, we present a chromosome-level genome assembly of the cichlid fish Astatotilapia latifasciata, integrating PacBio long reads, Illumina short reads, and Hi-C chromatin contact maps to resolve both A and B chromosomes. The 0.93 Gb assembly (N50 = 36.2 Mb) includes a 34 Mb B chromosome containing 789 predicted protein-coding genes and a markedly higher density of transposable elements (TEs), especially long terminal repeats (LTR) retrotransposons. Transcriptome profiling revealed that B-linked genes are predominantly transcriptionally repressed relative to their A chromosome paralogs. Hi-C-based chromatin modeling uncovered distinct 3D structural configurations associated with the B chromosome, including fewer topologically associating domains (TADs), reduced loop formation, and altered compartmentalization. These changes are linked to long-range chromatin interactions and genomic rearrangements, suggesting that the B chromosome reshapes the nuclear architecture of the host genome. Our study proposes a potential regulatory role of Bs in genome and provides a genomic resource for investigating chromosome evolution in cichlids.

Animals

Fetal signatures in the 3D genome of iPSC-derived neurons and their implications for disease modeling.

Induced pluripotent stem cells (iPSCs) have revolutionized neuroscience, providing an approach to generate patient-specific neurons for modeling of neurological diseases. However, it remains unclear how closely iPSC-derived neurons replicate the chromatin architecture of authentic brain neurons. Here, we uniformly processed newly generated Hi-C data from iPSC-derived neurons and neurons isolated from the human postmortem brain, together with previously published data sets comprising 228 human and 89 mouse Hi-C and snm3C-seq samples from different cell subtypes. These data were merged into 96 high-coverage contact maps used to examine chromatin features ranging from chromatin compartments and topologically associating domains (TADs) to chromatin loops, Polycomb-mediated contacts, and frequently interacting regions (FIREs). We find that iPSC-derived neurons largely retain the chromatin state of undifferentiated cells and resemble fetal rather than mature neurons. iPSC-derived neurons exhibit unusually strong compartmentalization, an enrichment of developmental genes at TAD borders, and a marked reduction of long-range repressive Polycomb-mediated contacts that typically silence early fetal programs. Although immature, iPSC-derived neurons offer advantages for modeling interactions between disease-associated SNPs and target genes, as many psychiatric disorders have neurodevelopmental origins. Integrating iPSC-derived and postmortem neuronal data sets therefore provides complementary insights into the chromatin landscape underlying disease-associated interactions. Our study offers a valuable Hi-C resource for the community and provides a detailed comparison of chromatin architecture throughout neuronal maturation, underscoring its importance for validating neuronal models and providing a robust framework for future studies.

Journal Article

Optimization of Structure-Guided Development of Chemical Probes for the Pseudoknot RNA of the Frameshift Element in SARS-CoV-2.

Targeting the RNA genome of SARS-CoV-2 is a viable option for antiviral drug development. We explored three ligand binding sites of the core pseudoknot RNA of the SARS-CoV-2 frameshift element. We iteratively optimized ligands, based on improved affinities, targeting these binding sites and report on structural and dynamic properties of the three identified binding sites. Available experimental 3D structures of the pseudoknot element were compared to SAXS and NMR data to validate its dominant folding state in solution. In order to experimentally map in silico predicted binding sites, NMR assignments of the majority of nucleobases were achieved by segmental labeling of the pseudoknot RNA and isotope-filtered NMR experiments at 1.2 GHz, demonstrating the value of NMR spectroscopy to supplement modelling and docking data. Optimized ligands with enhanced affinity were shown to specifically inhibit frameshifting without affecting 0-frame translation in cell-free translation assays, establishing the frameshift element as target for drug-like ligands of low molecular weight.

SARS-CoV-2

Epigenetic alterations in rheumatoid arthritis: multilayer mechanisms and translational opportunities.

Rheumatoid arthritis (RA) is a chronic inflammatory disease driven by immune dysregulation, in which genetic susceptibility and environmental exposures promote persistent synovitis, progressive joint damage, and systemic comorbidities. Recent epigenomic studies show several recurring abnormalities. Many RA susceptibility variants lie outside protein-coding sequence and map to immune-cell and synovial fibroblast regulatory elements, linking inherited risk to enhancer activity, methylation quantitative trait effects, and distal gene control. Blood-based epigenome-wide association studies identify disease-associated DNA methylation signatures, but these signals require careful control for leukocyte composition, smoking, treatment exposure, and disease stage. RA fibroblast-like synoviocytes also display stable methylome remodeling, including relative hypomethylation at loci involved in inflammation, migration, matrix degradation, and apoptosis resistance, while TET3-associated 5-hydroxymethylcytosine has emerged as a functional contributor to chemokine production and invasive stromal behavior. Histone modifications, chromatin accessibility, and 3D genome organization define pathogenic regulatory states and connect non-coding risk loci to effector genes in immune and stromal compartments. Finally, miRNAs, lncRNAs, circRNAs, snoRNAs, extracellular RNAs, and m6A-related pathways add post-transcriptional and chromatin-linked layers with potential biomarker value. We synthesize these findings and discuss translational opportunities for diagnosis, stratification, flare monitoring, and therapeutic targeting, while emphasizing incomplete replication, uneven evidence across epigenetic layers, biospecimen variability, and the need for causal, longitudinal, cell-type-resolved validation.

Humans

Extracellular Vesicles From Glioblastoma Cells Reflect 2D vs. 3D Culture Adaptation and Resistance to Temozolomide.

Glioblastoma (GBM) is an aggressive brain tumor marked by extensive heterogeneity, resistance to therapy, and dismal prognosis. Extracellular vesicles (EVs) have emerged as key players in GBM biology, mediating intercellular communication and therapy adaptation. However, the exact functions and molecular impact of EVs in GBM remain incompletely understood. In this study, we performed a comparative proteomic analysis of U87MG GBM cells grown in two-dimensional (2D) monolayers and three-dimensional (3D) spheroids following temozolomide (TMZ) treatment, alongside characterization of EVs derived from both culture systems. 3D-spheroids secreted more EVs of smaller size and exhibited a more TMZ-resistant, stem-like proteome under TMZ-induced genotoxic stress. In contrast, 2D cell cultures demonstrated greater proteome remodeling, with EVs enriched in protein families involved in DNA repair, oxidative stress adaptation, and methylation processes. Notably, several methyltransferases were decreased intracellularly but selectively retained in EVs, suggesting active sorting to influence the tumor microenvironment or modulate epigenetic states in recipient cells. EVs also carried adhesion molecules and signaling proteins linked to migration, invasion, and Wnt pathway activation, as well as metabolic enzymes connecting serine metabolism and redox control to TMZ resistance. Mapping EV and cellular proteomes onto The Cancer Genome Atlas (TCGA) dataset identified prognostic protein families associated with either poor or favorable patient outcomes. Our data demonstrate that EV cargo composition mirrors TMZ-induced phenotypic adaptation and reveals molecular mechanisms underlying therapeutic resistance. These EV-associated signatures may serve as clinically actionable biomarkers for patient stratification and offer potential targets to overcome chemoresistance in GBM.

Humans