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PubMed2024

Network proximity analysis as a theoretical model for identifying potential novel therapies in primary sclerosing cholangitis.

Primary Sclerosing Cholangitis (PSC) is a progressive cholestatic liver disease with no licensed therapies. Previous Genome Wide Association Studies (GWAS) have identified genes that correlate significantly with PSC, and these were identified by systematic review. Here we use novel Network Proximity Analysis (NPA) methods to identify already licensed candidate drugs that may have an effect on the genetically coded aspects of PSC pathophysiology.Over 2000 agents were identified as significantly linked to genes implicated in PSC by this method. The most significant results include previously researched agents such as metronidazole, as well as biological agents such as basiliximab, abatacept and belatacept. This in silico analysis could potentially serve as a basis for developing novel clinical trials in this rare disease.

Cholangitis, Sclerosing↗

PubMed2026

Integrated Genomic and Proteomic Analysis Reveals T-B Lymphocyte Signatures in the MYCN Driven "Immune Desert" of Specific Neuroblastoma Subtypes.

AIMS: This study aims to systematically dissect how MYCN amplification shapes the immunosuppressive tumor microenvironment (TME) in high-risk neuroblastoma, elucidating key mechanisms underlying immune evasion. METHODS: We performed an integrated multi-omics analysis of bulk RNA-seq (n = 721), single-cell RNA-seq (n = 9), proteomic data (n = 49) and spatial transcriptomics (Visium, with external validation in melanoma). Analyses included unsupervised clustering, cell-cell communication inference, transcriptional regulatory network reconstruction, and spatial proximity assessment to map the immune landscape. RESULTS: A distinct molecular subtype (Class C), defined by MYCN amplification and poor prognosis, exhibited a comprehensive "immune desert" phenotype characterized by low immune scores and minimal leukocyte infiltration. Single-cell analysis confirmed significant depletion of T and B lymphocytes within the Class C TME. Dysregulated transcriptional networks were identified, including upregulation of REL and EOMES in T cells-with EOMES potentially driving exhaustion via regulation of Transient Receptor Potential (TRP) genes, and REL inhibition enhancing cytotoxic function in vitro. A unique immunosuppressive B-cell subset (B7) engaged in enhanced crosstalk with exhausted T cells and harbored a MYC-centered network linked to cell cycle dysregulation and poor survival. Spatial transcriptomics revealed significant proximity between B7-active regions and Treg/exhaustion-enriched areas, externally validated in melanoma. Proteomic data validated elevated REL expression in MYCN-amplified tumors. CONCLUSION: This work delineates the immunosuppressive architecture of MYCN-driven neuroblastoma, revealing novel regulatory nodes within specific lymphocyte compartments. Integrating single-cell, spatial, and proteomic evidence, we propose REL inhibition as a therapeutic candidate, the EOMES/TRP axis as a bioinformatically supported hypothesis, and the B7/MYC hub as a hypothesis supported by transcriptomic and spatial evidence.

Humans↗

PubMed2026

Integrative analysis of transcriptome and chromatin accessibility reveals promoter-proximal regulation and identifies candidate ABC transporters associated with cold stress responses in maize.

BACKGROUND: Low-temperature stress is a formidable environmental constraint that severely limits the growth and productivity of maize (Zea mays L.), particularly during the highly vulnerable early seedling stage. While cold tolerance is a critical agronomic objective, the integrated transcriptional and epigenetic regulatory mechanisms that govern this trait remain largely elusive. Characterizing these coordinated molecular networks is fundamental to the genetic enhancement of cold resilience in maize. METHODS: Using two maize inbred lines contrasting in chilling response (ZHB12 tolerant, B73 sensitive), we performed integrative time‑course RNA‑seq and ATAC‑seq to thoroughly and systematically characterize the precise dynamic interplay between gene expression and chromatin accessibility under cold stress conditions at the seedling stage. RESULTS: Physiological assessments confirmed that ZHB12 possesses superior cold tolerance, manifested by significantly attenuated electrolyte leakage and reduced foliar damage compared to B73. Transcriptomic profiling revealed a massive, time-dependent divergence in gene expression between the two genotypes, with a major regulatory transition identified at 24 h of cold exposure. Functional enrichment analysis demonstrated that ZHB12 preferentially activates a robust defense repertoire, including Photosystem II electron transport, diterpenoid biosynthesis, and ATP biosynthetic pathways. Notably, multiple ATP-binding cassette (ABC) transporter genes were coordinately upregulated under chilling, suggesting their potential involvement in cellular homeostasis. ATAC-seq analysis indicated that cold stress is associated with chromatin remodeling in ZHB12, with increased accessibility observed in proximal promoter regions. Integrative analysis identified a core set of dual-responsive genes, in which increased promoter accessibility coincided with transcriptional upregulation. These genes were predominantly enriched in transporter activity and transcriptional regulation, suggesting potential epigenetic link to the superior stress response of ZHB12. CONCLUSION: Our findings reveal extensive transcriptional and chromatin accessibility changes in ZHB12 under cold stress. The observed associations between promoter accessibility and gene activation, particularly in genes involved in transport processes, highlight candidate regulators potentially contributing to cold tolerance. This study provides a molecular framework and identifies high-value candidate genes that may inform future efforts in breeding cold-tolerant maize, pending functional validation.

Zea mays↗

PubMed2026

Volumetric DNA microscopy for mapping spatial transcriptomes in three dimensions.

The architecture and function of biological systems are inherently three-dimensional, yet most existing spatial transcriptomic technologies remain restricted to thin tissue sections, limiting their capacity to resolve cellular organization and microenvironments within intact tissue volumes. To address this limitation, we developed volumetric DNA microscopy, a scalable, optics-free approach for spatial transcriptome profiling directly within intact biological specimens. The method encodes spatial information into DNA molecules that form a dense intermolecular network in situ, enabling the reconstruction of three-dimensional spatial relationships through short-read sequencing and computational analysis. Here we detail the complete workflow including in situ cDNA synthesis, spatial encoding through DNA nanoball formation, dual-scale proximity bridging between neighboring nanoballs and spatial reconstruction via geodesic spectral embedding. Sequencing libraries can be generated within 7-8 d by a competent graduate-level molecular biologist, followed by standardized downstream computational analysis. Because the workflow requires only routine molecular biology reagents and a benchtop sequencer, volumetric DNA microscopy provides a versatile platform for exploring genetic and morphological features in intact tissues.

Spatial Transcriptomics↗

PubMed2026

Molecular co-accessibility identifies coordinated regulation between distant cis-regulatory elements.

In metazoans, gene expression is typically regulated by a cis-regulatory landscape (CRL) composed of a promoter and multiple enhancers. How these cis-regulatory elements (CREs) coordinate their function across large genomic distances remains unclear. For example, is the simultaneous activation of multiple enhancers required to promote transcription? Here, we combined single-molecule footprinting with long-read sequencing to quantify how often chromatin accessibility and transcription factor binding co-occur across entire CRLs in the Drosophila genome. Analysis of thousands of individual DNA molecules at each locus revealed that CREs form a specific network with shared single-molecule chromatin accessibility profiles. Co-accessibility is not limited to adjacent CREs and is frequently observed between CREs brought into proximity by chromatin looping. Co-accessible CREs exhibit strong coordination in their cell-type-specific accessibility, linking enhancer activity with transcriptional activation. Our data uncover dependencies between CREs genome-wide and suggest that coordinated enhancer activation is a widespread mechanism regulating gene expression.

Animals↗

PubMed2026

Spatial clustering and transmission networks of multidrug-resistant tuberculosis in Rwanda: a national retrospective genomic and spatial epidemiological study.

BACKGROUND: Approximately 96% of rifampicin resistance/multidrug-resistant tuberculosis (RR/MDR-TB) cases in Rwanda result from direct transmission rather than acquired resistance. However, the nationwide spatial distribution and transmission dynamics of RR/MDR-TB remain poorly characterised. This study aims to analyse spatial patterns of RR/MDR-TB in Rwanda and explore relationships between spatial proximity and RR/MDR-TB strains' genetic relatedness. METHODS: We conducted a retrospective analysis of 249 confirmed RR-TB cases across Rwanda from 2017 to 2024, using the known geolocations of patients' residences. Spatial and space-time clustering was assessed using Kulldorff's scan statistics. Demographic and socioeconomic determinants were evaluated using multivariable regression. For 201 cases with whole-genome sequencing data, we performed transmission analysis using a 5-SNP threshold to define recent transmission clusters and investigated spatial relationships within genetically related strains. RESULTS: Significant spatial clustering of RR/MDR-TB was identified in 21 sectors, mainly in Nyarugenge, southern Gasabo and western Kicukiro (relative risk: 10.06; p<0.001). Our multivariable analysis showed that population density is positively associated with case notification rates. Molecular analysis revealed 88.5% of cases belonged to genotype clusters defined using a 12-SNP threshold, with 73.6% forming clusters at a strict 5-SNP threshold. Spatial K-function analysis of the six major clusters revealed heterogeneous transmission patterns, characterised by both tightly clustered outbreaks and regional transmission networks that spanned administrative boundaries. Most clusters (5/6) extended beyond Kigali, indicating that transmission networks operate across administrative divides. CONCLUSION: RR/MDR-TB in Rwanda shows significant spatial clustering with transmission occurring through both localised and regional networks. Integrating genomic and spatial data reveals transmission patterns that extend beyond household contacts and administrative boundaries. These findings underscore the need to implement geographically targeted interventions that address community-level transmission to control RR/MDR-TB in Rwanda effectively.

Rwanda↗

PubMed2026

Dual proximity-based interactome mapping of FKBP51 and FKBP52 uncovers shared metabolic networks.

The 51 kDa FK506-binding protein (FKBP51) has been studied for its involvement in regulating multiple biological systems, particularly as a regulator of steroid hormone receptors, but roles in metabolism, pain response, cell survival, protein turnover, autophagy, immune response, and insulin signaling have also been described. Genetic variants of FKBP51 are associated with various stress-related mental disorders. While recent research has clarified aspects of these processes, the complete range of FKBP51 interactions remains undetermined. FKBP52, a closely related homolog, also affects similar pathways. Recent studies have identified new protein partners for FKBP51 and FKBP52, suggesting an even broader interactome with transient associations. To further characterize interactions, TurboID-based proximity labeling was performed in HeLa cells. Proteomic analysis confirmed known FKBP51 and FKBP52 interactions, while also identifying additional shared and unique binding partners with strong enrichment in metabolic pathways, amino acid biosynthesis, and carbon metabolism. Although FKBP51 and FKBP52 proximal proteins were primarily cytosolic, FKBP51 showed additional associations with exosomal proteins while FKBP52 engaged with additional nuclear proteins. These findings highlight the overlapping roles in metabolic signaling and differentiate pathway-specific partners.

Tacrolimus Binding Proteins↗

PubMed2025

The signed two-space proximity model for learning representations in protein-protein interaction networks.

MOTIVATION: Accurately predicting complex protein-protein interactions (PPIs) is crucial for decoding biological processes, from cellular functioning to disease mechanisms. However, experimental methods for determining PPIs are computationally expensive. Thus, attention has been recently drawn to machine learning approaches. Furthermore, insufficient effort has been made toward analyzing signed PPI networks, which capture both activating (positive) and inhibitory (negative) interactions. To accurately represent biological relationships, we present the Signed Two-Space Proximity Model (S2-SPM) for signed PPI networks, which explicitly incorporates both types of interactions, reflecting the complex regulatory mechanisms within biological systems. This is achieved by leveraging two independent latent spaces to differentiate between positive and negative interactions while representing protein similarity through proximity in these spaces. Our approach also enables the identification of archetypes representing extreme protein profiles. RESULTS: S2-SPM's superior performance in predicting the presence and sign of interactions in SPPI networks is demonstrated in link prediction tasks against relevant baseline methods. Additionally, the biological prevalence of the identified archetypes is confirmed by an enrichment analysis of Gene Ontology (GO) terms, which reveals that distinct biological tasks are associated with archetypal groups formed by both interactions. This study is also validated regarding statistical significance and sensitivity analysis, providing insights into the functional roles of different interaction types. Finally, the robustness and consistency of the extracted archetype structures are confirmed using the Bayesian Normalized Mutual Information (BNMI) metric, proving the model's reliability in capturing meaningful SPPI patterns. AVAILABILITY: S2-SPM is implemented and freely available under the MIT license at https://github.com/Nicknakis/S2SPM.

Protein Interaction Mapping↗

PubMed2026

Genome-wide mapping of stress-responsive lncRNA, uc.104, reveals the chromatin-mediated regulation of stress and plasticity-related genes in the hippocampus of chronic restraint rats.

Chronic stress significantly impacts hippocampal function through transcriptional and epigenetic mechanisms. While the roles of lncRNAs in stress-related transcriptional and epigenetic regulation have recently been recognized, their genome-wide functions controlling the transcriptional network remain largely unclear. Evidence indicates that the lncRNA uc.104 is involved in stress responses; however, its genome-wide chromatin interactions and gene regulatory effects are yet to be explored. To examine this, we combined chromatin isolation by RNA purification sequencing (ChIRP-seq) and RNA sequencing (RNA-seq) in the hippocampus from handled control and chronic restraint stress (CRS) rats. ChIRP-seq identified 6,664 uc.104 binding peaks under CRS, including 6,517 enriched and 149 reduced. Many peaks were mapped to intronic and promoter-proximal regions of protein-coding genes. Integration of ChIRP-seq with RNA-seq data revealed 1,839 differentially expressed genes associated with uc.104 binding sites, with 106 high-confidence overlaps. Several genes (Gabra3, Htr7, Irs1, Gpr37, Clu, Hspa1b, Ppp3r2, Nfasc, Pcdhac2, and Cysltr2) identified as regulatory targets of uc.104, have been directly implicated in stress responses, synaptic plasticity, and neuroinflammation. Gene ontology and Synapse GO (SynGO) analyses revealed significant enrichment for processes involving dendritic spine formation, synapse organization, and pre- and postsynaptic signaling. Protein-protein interaction analysis identified hub genes, including EGFR, CDC42, IGF1R, CTNNB1, CALM1, CALM3, POLR2A, MDM2, TBP, and CSNK1E, several of which have been linked to stress-responsive pathways. Together, our findings reveal that uc.104 binding to chromatin near stress- and synapse-related genes may act as a regulator of stress-responsive transcriptional networks in the hippocampus. By linking uc.104 occupancy to stress and synaptic responsive genes, this study highlights uc.104 as a potential mediator of stress-induced hippocampal malfunctions.

Animals↗

PubMed2026

CRISPR-Enabled functional genomics in hPSCs-derived neural models for autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a genetically heterogeneous neurodevelopmental condition in which hundreds of individually rare risk variants converge on a small number of shared biological pathways, including synaptic scaffolding, chromatin remodeling, excitation-inhibition balance, and cellular energy metabolism. Translating this genetic heterogeneity into mechanistic insight requires experimental systems capable of interrogating individual gene functions in human-relevant neural contexts at scale. CRISPR-enabled functional genomics in human pluripotent stem cell (hPSC)-derived neural models, spanning neural progenitors, cortical and inhibitory neurons, astrocytes, microglia, and brain organoids, provides precisely this capability. By integrating pooled perturbation screens with multimodal readouts including single-cell and spatial transcriptomics, chromatin accessibility profiling, proximity labeling proteomics, multi-electrode array electrophysiology, and metabolic flux analysis, these platforms enable systematic, causal mapping of ASD gene function at system resolution. Early applications have already revealed convergent mechanisms: BAF complex disruption expands the ventral progenitor pool and biases its fate toward oligodendrocyte and interneuron lineages; ADNP loss impairs microglial synaptic pruning through altered endocytic trafficking; and mTOR pathway dysregulation in PTEN- and TSC2-perturbed models links genetic risk directly to metabolic and mitochondrial dysfunction. Computational frameworks including MIMOSCA and SCEPTRE enable causal network reconstruction and pseudotime inference from these datasets, moving the field from gene lists toward pathway-level models of ASD pathobiology. Translational applications leverage isogenic iPSC panels and variant-level base and prime editing to stratify ASD variants by functional impact, informing gene therapy design for haploinsufficient targets such as CHD8 and SCN2A via AAV or antisense oligonucleotide delivery. Remaining challenges, including model developmental immaturity, batch variability, and the difficulty of modeling polygenic risk, are addressed by a roadmap integrating spatial perturbomics, AI-driven causal inference, and population-scale standardized biobanks. This review synthesizes the current state of CRISPR-based functional genomics in human stem cell neural models as a coherent experimental framework for converting ASD genetic associations into mechanistic understanding and therapeutic opportunity.

Humans↗

PubMed2026

PRISM-G: an interpretable privacy scoring framework for assessing risk in synthetic human genome data.

MOTIVATION: Synthetic genomic data promises broader data access, but unresolved privacy risks remain a major concern. Existing evaluations often rely on similarity-based metrics that measure proximity between real and synthetic genomes, overlooking additional mechanisms through which genomic information may leak. RESULTS: We introduce PRISM-G, a model-agnostic framework that quantifies privacy exposure in synthetic genomic data across three complementary components: proximity to real genomes in genetic-coordinate space, replay of familial or population-structure patterns, and trait-linked exposure through rare variants and membership-inference signals. These components are normalized and combined through a risk-averse aggregation into a single 0-100 PRISM-G score. By pairing PRISM-G with downstream utility metrics, the framework also enables analysis of privacy-utility trade-offs across generative models. We evaluated PRISM-G on synthetic cohorts generated by a generative adversarial network (GAN), a restricted Boltzmann machine (RBM), and a logic-based SAT solver (Genomator). Our results show that privacy vulnerabilities arise along different axes across models and marker densities, demonstrating that a single similarity-based metric is insufficient to characterize genomic privacy risk. AVAILABILITY AND IMPLEMENTATION: The source code of PRISM-G is available at https://github.com/alejocrojo09/prismg.

Humans↗

PubMed2026

Proximity labeling puts ZFP36L1 as central hub for posttranscriptional regulation networks in T cells.

Effective T cell responses against pathogens require a rapid yet tightly controlled remodeling of the proteome, and RNA binding proteins (RBPs) are key in this process. For instance, the RBP ZFP36L1 prevents excessive protein production and thereby limits immunopathology. ZFP36L1 is primarily known to mediate mRNA decay, but it can also regulate other processes. How its mode of action relates to its interaction partners is, however, not well-understood. Here, we mapped the ZFP36L1 interactome in primary human T cells. Using proximity labeling, we identified known and new interactors that regulate 3'UTR-mediated RNA degradation, deadenylation, stress granule/p-body formation, as well as 5'UTR-mediated translation repression and mRNA decapping. Snapshot analysis uncovered the ZFP36L1 interactome dynamics and RNA (in)dependency throughout T cell activation. Intriguingly, proximity labeling also uncovered regulators of ZFP36L1 protein expression. This included the helicase UPF1, which not only interacts with ZFP36L1 protein but that may also promote its protein expression. Altogether, this comprehensive interactome map underlines the versatility of interactions with ZFP36L1 and their possible role in cellular function.

Humans↗

PubMed2026

Transcriptional perturbation of LINE-1 elements reveals their cis-regulatory potential.

Long interspersed element-1 (LINE-1 or L1) retrotransposons constitute the largest transposable element family in mammalian genomes and contribute prominently to inter- and intra-individual genetic variation. Although most L1 elements are inactive, some evolutionary younger elements remain intact and genetically competent for transcription and occasionally retrotransposition. Despite being generally more abundant in gene-poor regions, intact or full-length L1s (FL-L1) are also enriched around specific classes of genes and on the eutherian X chromosome. How proximal FL-L1 may affect nearby gene expression remains unclear. Here, we examine this systematically using engineered mouse embryonic stem cells (ESCs) in which expression of one active L1 subfamily is perturbed. We find that FL-L1 activation leads to the misregulation of ~1024 genes, whereas FL-L1 repression affects ~81 genes. In most cases (68%), misexpressed genes contain an intronic FL-L1 or lie near a FL-L1 (< 260 kb). Gene ontology analysis shows that upon L1 activation, upregulated genes are enriched for neuronal function-related terms, suggesting that some L1 elements may have evolved to control neuronal gene networks. These results illustrate the cis-regulatory potential of FL-L1 elements and suggest a broader role for L1s than originally anticipated.

Animals↗

PubMed2026

VirBinn improves viral genome binning from metagenomic Hi-C through graph diffusion.

MOTIVATION: Metagenomic Hi-C provides in situ proximity signals that can improve genome binning and enable virus-host-association analysis. However, viral genome recovery remains difficult because virus-virus Hi-C contact matrices are extremely sparse. Viral genomes are small, often low-abundance, and frequently assemble into short contigs, leaving many true within-genome links unobserved and causing viral bins to fragment. RESULTS: We present VirBinn, a graph-diffusion framework for viral binning from metagenomic Hi-C. VirBinn enhances virus-virus connectivity through two complementary mechanisms: random-walk-with-restart enhancement on the sparse virus-virus contact graph and host-guided diffusion that propagates viral seeds through the host network to infer indirect virus-virus associations. The enhanced views are integrated and clustered using Leiden community detection to produce viral metagenome-assembled genomes (vMAGs). On dataset-specific simulation benchmarks with ground truth, VirBinn consistently recovers more high-quality vMAGs than Hi-C-based and shotgun-based baselines and substantially increases the number of near-complete genomes. On four real metagenomic Hi-C datasets spanning human gut, pig gut, sheep gut (long-read assembly), and wastewater, VirBinn yields more high-completeness vMAGs under CheckV and produces bins with strong within-cluster contact support. Finally, host linkage analysis using reconstructed host MAGs reveals habitat-specific host-association patterns and plausible host taxonomic profiles. AVAILABILITY AND IMPLEMENTATION: VirBinn is available at https://github.com/dyxstat/VirBinn. The scripts to reproduce the results and figures in this article are available at https://github.com/dyxstat/Reproduce_VirBinn.

Genome, Viral↗

PubMed2025

CaLMPhosKAN: prediction of general phosphorylation sites in proteins via fusion of codon aware embeddings with amino acid aware embeddings and wavelet-based Kolmogorov-Arnold network.

MOTIVATION: The mapping from codon to amino acid is surjective due to codon degeneracy, suggesting that codon space might harbor higher information content. Embeddings from the codon language model have recently demonstrated success in various protein downstream tasks. However, predictive models for residue-level tasks such as phosphorylation sites, arguably the most studied Post-Translational Modification (PTM), and PTM sites prediction in general, have predominantly relied on representations in amino acid space. RESULTS: We introduce a novel approach for predicting phosphorylation sites by utilizing codon-level information through embeddings from the codon adaptation language model (CaLM), trained on protein-coding DNA sequences. Protein sequences are first reverse-translated into reliable coding sequences by mapping UniProt sequences to their corresponding NCBI reference sequences and extracting the exact coding sequences from their GenBank format using a dynamic programming-based global pairwise alignment. The resulting coding sequences are encoded using the CaLM encoder to generate codon-aware embeddings, which are subsequently integrated with amino acid-aware embeddings obtained from a protein language model, through an early fusion strategy. Next, a window-level representation of the site of interest, retaining the full sequence context, is constructed from the fused embeddings. A ConvBiGRU network extracts feature maps that capture spatiotemporal correlations between proximal residues within the window. This is followed by a prediction head based on a Kolmogorov-Arnold network (KAN) using the derivative of gaussian wavelet transform to generate the inference for the site. The overall model, dubbed CaLMPhosKAN, performs better than the existing approaches across multiple datasets. AVAILABILITY AND IMPLEMENTATION: CaLMPhosKAN is publicly available at https://github.com/KCLabMTU/CaLMPhosKAN.

Codon↗

PubMed2026

Structure-resolved virus-host interactomics by cross-linking mass spectrometry.

Viruses depend on host protein networks to replicate, assemble progeny, and spread between cells and organisms. Defining these virus-host protein interactions is challenging because they are highly dependent on infection stage, cell type, species, and because mechanistic interpretation requires information about structural interfaces and conformational states. Cross-linking mass spectrometry (XL-MS) addresses these challenges by adding a spatial and structural dimension to virus-host interactomics in native systems. In this review, we discuss how XL-MS has advanced from targeted analysis of viral protein complexes to structure-resolved mapping of virion architecture and infected-cell virus-host interactomes. We highlight how XL-MS complements AP-MS, cryo-EM/cryo-ET, quantitative proteomics, genetic perturbation, and structure prediction to connect physical proximity with molecular mechanisms. Finally, we discuss current limitations in sensitivity, chemical coverage, temporal resolution, and model interpretation, and outline how future quantitative and integrative XL-MS workflows may enable systems-level structural virology.

Mass Spectrometry↗

PubMed2025

The molecular basis of lamin-specific chromatin interactions.

In the cell nucleus, chromatin is anchored to the nuclear lamina, a network of lamin filaments and binding proteins that underly the inner nuclear membrane. The nuclear lamina is involved in chromatin organization through the interaction of lamina-associated domains within the densely packed heterochromatin regions. Using cryo-focused ion beam milling in conjunction with cryo-electron tomography, we analyzed the distribution of nucleosomes at the lamin-chromatin interface at the nanometer scale. Depletion of lamins A and C reduced nucleosome concentration at the nuclear periphery, while B-type lamin depletion contributed to nucleosome density in proximity to the lamina but not further away. We then investigated whether specific lamins can mediate direct interactions with chromatin. Using cryo-electron microscopy, we identified a specific binding motif of the lamin A tail domain that interacts with nucleosomes, distinguishing it from the other lamin isoforms. Furthermore, we examined chromatin structure dynamics using a genome-wide analysis that revealed lamin-dependent macroscopic-scale alterations in gene expression and chromatin remodeling. Our findings provide detailed insights into the dynamic and structural interplay between lamin isoforms and chromatin, molecular interactions that shape chromatin architecture and epigenetic regulation.

Nucleosomes↗