Biology subjects

Xia, J.

Publications and source records attributed to Xia, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Linear NeuroPaint: An Efficient Baseline for Cross-Session Neural Alignment and Inpainting

Large-scale Neuropixels recordings sample many brain areas, but no single experimental session records every area of interest. NeuroPaint, a transformer-based autoencoder, integrates such recordings by aligning area-specific latent dynamics across sessions and "inpainting" activity in unrecorded areas. Could a linear model, which would be computationally efficient and potentially more interpretable, suffice to achieve this? To address this question, we introduce Linear NeuroPaint, a linear variant of NeuroPaint, and evaluate it on two multi-area Neuropixels datasets. Linear NeuroPaint achieves strong predictive performance on recorded areas, however, it is less accurate than nonlinear models at cross-area inpainting, despite extensive hyperparameter optimization. Moreover, its parameters are not readily interpretable: incomplete cross-session alignment leads parameter-defined neuron clusters to exhibit heterogeneous response profiles. Together, these results show that linear transformations are insufficient for cross-session alignment and cross-area prediction. Nevertheless, Linear NeuroPaint provides a computationally efficient baseline for benchmarking multi-session neural models.

neuroscience↗

bioRxiv2026

Aquaporin-9 and aquaporin-10 but not aquaporin-3 confer susceptibility to dimethylarsinic acid genotoxicity in human cells

Human metabolism converts inorganic arsenic to the pentavalent methylated species MMA(V) and DMA(V), the forms most people excrete, and the forms long read as the end of a detoxification pathway. Whether a transporter sets how much of these metabolites reaches the genome has not been tested in a mammalian cell. We expressed human AQP3, AQP7, AQP9 or AQP10 in HEK293T and MRC5-SV40 cells and measured gamma-H2AX by flow cytometry across dose series of As(V), MMA(V) and DMA(V), pairing every aquaporin with a GFP-Tubulin control and an untransfected mock acquired in the same replicate. As(V) was inactive in HEK293T cells and only weakly active in MRC5-SV40 cells to 20 micromolar, and both methylated species damaged DNA only in the millimolar range, DMA(V) being the more potent of the two in both cell lines. Against that weak baseline, AQP9 and AQP10 raised DMA(V)-induced gamma-H2AX in HEK293T cells by roughly 17 percentage points over the matched control, more than doubling the damage the same exposure produced in control cells, whereas AQP3 and AQP7 changed it not at all. AQP9 alone remained active with MMA(V). The ranking held in MRC5-SV40 fibroblasts at one-sixth the size, and within single wells the damage rose with the amount of AQP9 a cell carried while the control was flat. Aquaglyceroporins therefore discriminate among arsenic species, and AQP9 and AQP10 turn a weakly genotoxic metabolite into a substantially more genotoxic one.

pharmacology and toxicology↗

bioRxiv2026

Aquaporin-3 amplifies arsenite genotoxicity as a dose-dependent gene-by-environment interaction in human cells

Chronic exposure to inorganic arsenic affects more than 200 million people, and disease outcome varies widely among individuals with comparable intake. Explanations have centered on arsenic metabolism, which acts on arsenite that is already inside the cell. Uptake sits upstream of metabolism and sets how much arsenite reaches the genome, yet whether it acts as a gene-by-environment modifier of genotoxicity has been asserted far more often than it has been measured. We expressed human aquaporin-3 (AQP3), its point mutants and the paralogues AQP7, AQP9 and AQP10 in three human cell lines, and measured DNA damage as {gamma}H2AX by flow cytometry against a damage threshold re-derived from mock-transfected cells in every experiment. In lung fibroblasts, AQP3 raised the {gamma}H2AX-high fraction 2.36-fold at 5 M arsenite. Because a gene-by-environment interaction widens the genotype gap with dose while an independent genotoxin would not, the combination exceeds what the two factors would produce if they simply added by 6.36 percentage points, which is an interaction. The response required the AQP3 sequence, was suppressed by N-acetylcysteine in proportion to arsenite dose, was absent in RKO cells, and was shared with AQP9 and AQP10, which created an arsenite dose-response in a cell line that had none of its own. Low-input RNA sequencing of 135 ten-cell pools located the effect inside the cell: at an identical 1 M applied dose and within a single batch, AQP3 raised HMOX1 (induced when trivalent arsenic modifies KEAP1 thiols, and so a report of intracellular rather than applied exposure) 3.3-fold, a shift equivalent to 40% of the 1-to-10 M interval on the measured dose-response, while AQP3 without arsenite was indistinguishable from untreated. Duplex sequencing detected no consistent change in somatic mutation frequency from arsenite alone at any dose to 10 M, in an assay that resolved a 26-fold response to N-ethyl-N-nitrosourea; the arsenite-induced mutation frequency at the EGFR locus nonetheless differed 1.61-fold by AQP3 genotype. The interaction is therefore not unique to AQP3, and aquaglyceroporin complement belongs alongside metabolism among the host factors that set arsenic susceptibility.

cell biology↗

bioRxiv2026

Deep reinforcement learning-driven discovery of a MsbA-targeted small-molecule antibiotic for the treatment of Acinetobacter baumannii infection

Antibiotics with new mechanisms are highly pursued to address the threat of infections caused by drug-resistant Gram-negative bacteria. Targeting MsbA, a key protein of the lipopolysaccharide biosynthesis pathway, represents a promising strategy to discover new classes of antibiotics. However, currently available MsbA-targeted molecules either lack sufficient potency or have unfavorable properties, necessitating expansion of chemical space. In this study, we chose the most promising cerastecin Cpd 4 as the template, and used two Artificial Intelligence (AI)-based tools, i.e. Link-INVENT and AutoMolDesigner for molecular design, performed chemical derivatization and antibacterial activity evaluation, which led to the discovery of Y-11 (MIC for A. baumannii: 0.5 g/mL). Encouragingly, Y-11 showed equivalent potency to Cpd4 for carbapenem-resistant A. baumannii, and less cytotoxicity and hemolysis as well as lower spontaneous resistance frequency. In vivo efficacy study demonstrated that Y-11 could effectively reduce bacterial loads in the mice infected by A. baumannii. The following mechanism study including molecular dynamics simulation, biochemical assay, and transmission electron microscope (TEM) analysis suggested that Y-11 inhibited the transport of lipooligosaccharide and impaired the formation of outer membrane, probably by competitively binding to the substrate binding site of MsbA and modulating ATPase activity. Taken together, we have discovered a MsbA-targeted small molecule Y-11 via AI-driven drug design, which provides a foundation for future antibiotic development.

biochemistry↗

bioRxiv2026

A 3D image atlas chronicling cellular and structural dynamics following lung injury identifies the aberrant expansion of endothelial cells that fail to form perfused vasculature

Intratracheally delivered bleomycin in mice is the most widely used in vivo model of pulmonary fibrosis, yet key aspects remain poorly defined, including sex-dependent responses and the temporal peak of injury. Standard 2D histology further overlooks regional heterogeneity and cannot resolve the 3D architecture or connectivity of endothelial cells (ECs). Here, we established a multi-scale 3D imaging pipeline integrating precision-cut lung slices from EC lineage-tracing mice, optical clearing, and AI-driven 3D segmentation to map cellular and structural dynamics from whole-lobe tile scans to single-cell resolution. We identified sex as a critical biological variable, with males exhibiting a delayed but more severe fibroproliferative response. Unsupervised K-means clustering identified three distinct tissue microenvironments: healthy parenchyma(KMC1), a myofibroblast-rich fibrotic core (KMC2), and a previously uncharacterized EC-dense perilesional region (KMC3) defined by massively expanded but non-perfused ECs that acquire a pro-inflammatory phenotype. This aberrant endothelial response precedes peak myofibroblast accumulation and persists beyond fibrotic resolution, leaving a vascular scar that extends into the large-vessel hierarchy. Together, this 3D image atlas, made publicly available as an interactive resource [https://mosaic-lung.com/], reveals the activated endothelium as an underexplored therapeutic target in pulmonary fibrosis.

bioengineering↗

bioRxiv2026

Adipose GPD2 Couples Glycolytic Signals to Epigenetic Control of Metabolic Homeostasis

The glycerol-3-phosphate shuttle (G3PS) is a classic reducing equivalent transferring system, yet its role in adipose metabolism remains poorly understood. Here, we identify mitochondrial glycerol-3-phosphate dehydrogenase (GPD2), the core enzyme of G3PS, as a critical orchestrator of adipose thermogenesis and systemic metabolic homeostasis. Adipocyte-specific GPD2 knockout mice exhibited impaired thermogenic capacity and energy expenditure, rendering them susceptible to obesity and metabolic dysfunction. Mechanistically, GPD2 deficiency elevated cytosolic NADH, which suppressed glycolysis and decreased the levels of key metabolites, such as acetyl-CoA, thereby diminishing H3K27ac at thermogenic gene loci and silencing these genes. NADH depletion with an NADH oxidase rescued both glycolysis and thermogenic gene expression. In support of this mechanism, we defined a previously undescribed enhancer of Ucp1 whose H3K27ac was tightly controlled by GPD2. Remarkably, replenishing the acetyl-CoA pool or directly restoring H3K27ac at the Ucp1 enhancer reversed UCP1 expression in GPD2-deficient adipocytes. Importantly, we find that human adipose GPD2 expression is inversely correlated with BMI, WHR, and HOMA-IR, underscoring its clinical relevance. Collectively, our findings establish GPD2 as an essential node in the metabolic-epigenetic axis that governs thermogenic activation and energy balance.

biochemistry↗

bioRxiv2026

A horizontally transferred fungal deubiquitinase facilitates insecticides resistance in whitefly

Horizontal gene transfer (HGT) has enabled insects to acquire novel genetic material that can fuel adaptation to environmental change. However, the role of HGT in the evolution of insecticide resistance remains poorly characterised. Here, we identify BtUCH19, a fungal gene that has integrated into the genome of the global pest Bemisia tabaci and functions as a deubiquitinating enzyme (DUB). We show that compared to endogenous DUB, BtUCH19 specifically removes K63-linked ubiquitin chains from a cytochrome P450, CYP4C64, thereby stabilizing this key detoxification enzyme in vivo. Sustained CYP4C64 abundance enhances metabolic detoxification of two commonly used insecticides thiamethoxam (TMX) and clothianidin (CLO) to their low-toxicity products TMX-Urea and CLO-Urea. Consequently, BtUCH19 drives insecticide resistance through a novel "HGT-PTM-Metab" axis. Our work reveals the instrumental role of a HGT in orchestrating ubiquitin-proteasome system (UPS)-mediated protein level regulation of a key detoxification pathway. These findings offer new insights into the intricate mechanisms underlying co-evolutionary biology, and provide a new molecular target for Integrated Pest Management (IPM).

zoology↗

bioRxiv2026

Somatic copy-number alteration signatures reveal sex-divergent aging trajectories accelerated in cancer

Somatic copy-number alterations (CNAs) accumulate with age and contribute to age-related pathologies, but their systematic characterization at single-cell resolution has been limited by the throughput-resolution trade-off in single-cell whole-genome sequencing. Here, we developed ultra-CNA, a high-resolution single-cell analysis pipeline that extends CNA detection to 10-kb bin resolution and jointly profiles copy-number and single-nucleotide variation (SNV). Re-analyzing the Tasc-WGS dataset (Liu et al., 2022; previously analyzed at 200-kb resolution) of 32,526 lymphocytes from 16 healthy donors aged 0.7 to 79 years, we constructed a multi-dimensional CNA spectrum stratified by chromosomal context, copy-number state, size, and clonality. Small (<1 Mb), rare, predominantly loss-type CNAs accumulated progressively and stochastically with age. Sex-chromosome loss showed divergent kinetics: chromosome X loss cells in females accumulated at +0.10 percentage points per year, versus +0.03 for chromosome Y loss cells in males. Sex chromosome loss also had specific consequences for autosomal SNV burden: in younger donors, loss cells carried fewer autosomal SNVs than non-loss cells, whereas in older donors (>30 years), loss cells exceeded non-loss cells in both sexes. Female X-loss cells additionally exhibited elevated 45S rDNA copy number, supporting biologically distinct consequences of X loss and LOY. Clock-like SBS1 and SBS5 mutational signatures co-accumulated with age across both sexes. Applying KL-divergence non-negative matrix factorization to the channelized CNA spectra, we constructed an aging clock validated by leave-one-sample-out cross-validation. Applied to a matched esophageal cohort, the clock detected accelerated aging from normal squamous epithelium through Barretts esophagus to esophageal adenocarcinoma, with cancer-associated spectra additionally enriched for large, highly clonal events. Ultra-CNA thus provides a scalable framework for quantifying somatic genomic aging from blood and for detecting accelerated aging in cancer.

genomics↗

bioRxiv2026

Physics-informed self-supervised learning enables spectra-free multiplexed imaging on standard fluorescence microscopes

Multiplexed fluorescence imaging is limited by spectral overlap and the small number of excitation or emission channels available on standard microscopes, restricting most laboratories to low-plex imaging. Here we introduce physics-informed spectra-free multiplexed imaging (PhySMI), a self-supervised framework for underdetermined spectral unmixing that enables highly multiplexed imaging without dense spectral measurements after training. By embedding the spectral forward-mixing process into a self-consistent architecture, PhySMI recovers physically plausible source decompositions from unlabeled data without paired ground-truth labels while suppressing stochastic acquisition noise. PhySMI resolves five subcellular structures from only three excitation channels, overcoming the conventional channel-number limit while preserving spectral fidelity and minimizing crosstalk (<0.5%). The framework also generalizes across imaging systems, enabling zero-shot deployment on standard fluorescence microscopes. In live cells, PhySMI enables fast five-color imaging of dynamic multi-organelle interactions with improved temporal resolution and reduced photobleaching and phototoxicity relative to conventional spectral imaging. These results establish a general strategy for physics-informed learning in underdetermined imaging inverse problems and represent a step toward a general-purpose framework for highly multiplexed fluorescence imaging on standard microscopy platforms.

biophysics↗

bioRxiv2026

MSAgent: An Evidence Grounded Agentic Framework for LLM-driven Scientific Exploration in Mass Spectrometry-based Metabolomics

Mass spectrometry (MS) is a cornerstone high-throughput technology for molecular discovery, yet the reliable elucidation of chemical structures remains a formidable, expert-dependent bottleneck. Currently, achieving a reliable molecular identification from raw mass spectra necessitates a manual assembly--a labor-intensive ordeal of heuristic reasoning and the tedious integration of siloed computational tools, perpetuating a profound throughput gap between rapid data acquisition and the glacial pace of structural annotation. Here we present MSAgent, an autonomous agentic framework that bridges the gap between computational automation and expert intuition by emulating the cognitive logic of human specialists. By orchestrating a MSToolbox of over 50 domain-specific tools via Large Language Models (LLMs), MSAgent dynamically unifies the analytical pipeline into a scalable, evidence-grounded workflow, allowing for intent-aware planning, cross-resources outputs synthesis, and visual mechanistic interpretation within traceable reasoning chains and evidence-backed analytical reports. We evaluated MSAgent across multiple open benchmarks, including the established community challenges - Critical Assessment of Small Molecule Identification (CASMI) 2016/2022, CANOPUS, and LLM-oriented test cases. On CASMI, MSAgent consistently boosts retrieval performance by over 10% MRR across diverse benchmarks while ensuring high reliability--improving or preserving ranks in 95% of cases. For more challenging molecular de novo tasks on CANOPUS, MSAgent builds upon the outputs of baseline models with consistent refinement, yielding over a 40% average gain in Tanimoto similarity for ground-truth recovery. In addition, MSAgent demonstrates remarkable advantages in eliminating the hallucination phenomenon over LLMs without domain tool support, producing better-calibrated confidence (Pearson r = 0.438 vs -0.219 for gpt-4o). It improves exact-match rate by 38.8% over gpt-4o in candidate discrimination tasks, and achieved a 64% success rate in recommending high-quality candidate structures with Tanimoto similarity more than 0.7, where gpt-4o predominantly selected candidates with similarity below 0.3. Our work enables high-throughput mass spectrometry data to be analyzed in an intent-driven and automated manner, lowering the analysis barrier for no-expert to deliver molecular identification result with transparent analytical process, and accelerating discovery in metabolism and related fields by bridging the gap between experimental data acquisition and computational interpretation.

bioinformatics↗

bioRxiv2026

Ribosome biogenesis bottlenecks reveal vulnerabilities in cancer

Cell growth requires elevated protein synthesis, which depends on the production of ribosomes. Ribosome biogenesis is a complex, multi-step pathway in which newly transcribed precursor ribosomal RNA (rRNA) undergoes coordinated processing and assembly in the nucleolus to produce the small and large ribosomal subunits (SSU and LSU).1-3 Oncogene activation stimulates rRNA transcription and processing, giving rise to enlarged nucleoli that produce thousands of ribosomes every minute.4,5 However, efficient ribosome production requires tight coordination across numerous maturation steps, and it remains unclear if elevated rDNA transcription is proportionally converted into mature ribosomes, or whether imperfect coordination constrains the output yield. Here, we quantify pre-rRNA transcription (input) and compare it with newly-assembled cytoplasmic ribosomes (output), revealing that oncogene activation reduces the efficiency of ribosome production. Using a quantitative pulse-chase sequencing approach with mathematical modeling to resolve rRNA maturation kinetics, we found that oncogene activation creates late-stage processing bottlenecks, characterized by delayed precursor maturation and increased degradation. Perturbation of late-stage ribosome biogenesis factors preferentially impaired oncogene-driven cell growth, and limited tumor growth in mouse models, suggesting that these bottlenecks represent selective vulnerabilities in cancer, created by imbalanced biosynthetic flux. Together, these findings reveal that oncogene-driven ribosome production is imperfectly coordinated across maturation steps, and suggest that capacity limits in multi-step assembly pathways may be therapeutically exploitable in cancer and other diseases.

cell biology↗

bioRxiv2026

Light-sheet excitation-encoded volumetric spectroscopy for fast multiplexed imaging and quantitative physicochemical mapping in cells

Understanding how cellular organization relates to function requires imaging approaches that resolve structural and physicochemical information throughout three-dimensional volumes. Here we introduce light-sheet excitation spectroscopic microscopy (LS-ExSM), a method that captures full excitation spectra with [~]10 nm spectral resolution at each voxel for multiplexed imaging and quantitative spectroscopic readout. Excitation-wavelength encoding makes this spectroscopic readout compatible with single-objective wide-field light-sheet imaging while maintaining high spectral fidelity. Combined with sparse volumetric sampling and deep-learning-based reconstruction, LS-ExSM achieves high-speed volumetric imaging while preserving structural and spectral information. We demonstrate six-color volumetric imaging of live cells at near-second temporal resolution with minimal crosstalk, enabling visualization and quantitative analysis of dynamic organelle interactions in three dimensions. We further apply LS-ExSM to three-dimensional mapping of lipid-droplet polarity at near-diffraction-limited resolution. Together, these results establish excitation-encoded volumetric spectroscopy as a route to whole-cell imaging of subcellular organization and physicochemical state.

cell biology↗

bioRxiv2026

A PSMA-Targeted Up-conversion Nanoplatform for Deep-Tissue dual activation Photodynamic and Sonodynamic Therapy of Castration Resistant Prostate Cancer.

Photodynamic therapy (PDT) for prostate cancer is limited by the shallow penetration of visible light into deep-seated tumors. In contrast, sonodynamic therapy (SDT) enables noninvasive deep-tissue activation using ultrasound, while near-infrared photodynamic therapy (NIR-PDT) enhances tissue penetration through up-conversion-mediated activation. Based on these advantages, we developed a prostate-specific membrane antigen (PSMA)-targeted nanotheranostic platform (UCNPs@mSiO2/HPPH@TCS) to compare NIR-PDT and SDT in vitro for penetration-enhanced and targeted prostate cancer therapy. The nanoformulation consists of NaYF4:Yb3+, Er3+ up-conversion nanoparticles coated with mesoporous silica for high loading of HPPH (Photochlor), which functions as both photosensitizer and sonosensitizer, and a PSMA-targeted chitosan shell for selective tumor targeting. Physicochemical characterization confirms a uniform core-shell structure ([~]63 nm). Tissue-mimicking depth studies demonstrate that SDT and NIR-PDT achieve greater penetration than conventional 665 nm PDT in thicker tissue layers. Intracellular reactive oxygen species (ROS) analysis shows that SDT generates higher total ROS levels, whereas NIR-PDT produces greater singlet oxygen generation. Three-dimensional spheroid models further validate efficacy, demonstrating rapid spheroid collapse via apoptosis, with SDT inducing earlier apoptosis and more uniform penetration than PDT. Collectively, the results suggest SDT provides superior overall therapeutic efficacy compared with NIR-PDT, highlighting the potential of this nanoplatform for precision prostate cancer therapy.

cancer biology↗

bioRxiv2026

Single-cell full-length transcriptome of human lung reveals genetic effects on isoform regulation beyond gene-level expression

Genetic regulation of splicing uniquely contributes to trait-associated genome-wide association studies (GWAS) signals. However, quantitative trait loci (QTL) analysis using short-read sequencing of bulk tissues fails to capture full-length and cell-type-specific isoforms. Here, we present an isoform-level lung cell atlas from 129 never-smoking Korean women using single-cell long-read RNA-sequencing, identifying abundant unannotated and cell-type-specific isoforms. Isoform-level signatures of 37 lung cell types display a larger difference and therefore improve cell-type classification compared to gene-level expression. Notably, isoform-QTLs (isoQTLs) detect unannotated and/or cell-type-specific isoforms with independent genetic regulation from expression-QTL (eQTL), supported by enriched splicing functional elements. IsoQTLs nominate susceptibility isoforms from previously unexplained lung function and cancer GWAS loci, via eQTL-independent signals. We highlight a potentially functional novel variant of PPIL6 in multiciliated cells underlying lung cancer risk through alternative splicing. This isoform-level resource advances our understanding of cell-type-specific isoform regulation and its contribution to lung traits and diseases.

genetics↗

bioRxiv2026

Macrophage Iron Metabolism in Allografts and Tumors

Macrophages are present at high frequencies in transplanted organs and solid tumors. These infiltrating macrophages are highly tuned by tissue niche signals. However, the underlying mechanisms that orchestrate the activation of distinct macrophage populations remain unclear. Here, using heart transplantation and tumor implantation models, we found that macrophages in cardiac allografts exhibited higher intracellular iron (Fe2+) level and higher expression of the iron transporter SLC11A1 than those in the solid tumors. In mice, the myeloid-specific deletion of Slc11a1 alleviated the proinflammatory state of macrophages and cardiac allografts rejection. Together, our findings identify SLC11A1 as a new player in immune response regulation, implicating SLC11A1 as a therapeutic target for both allograft and tumor rejection. This preprint reports initial findings; additional experiments are ongoing and will be included in a future full manuscript.

immunology↗

bioRxiv2026

Rapid diversification of a natural Heterosigma akashiwo virus population during a host bloom

Despite the ecological importance of viruses, our understanding of their evolutionary dynamics in natural environments remains limited. This gap is particularly pronounced for giant dsDNA viruses of the phyla Nucleocytoviricota and Mirusviricota. Most knowledge on their population genetic dynamics is derived from a small number of laboratory-based experiments, whereas patterns in nature are rarely observed. To overcome this limitation, we traced genetic structure and transcription status of Heterosigma akashiwo virus (HaV) using high-frequency, time-resolved sampling during a host bloom in a coastal area of Japan, by integrating cell counting, metabarcoding, metagenomic and metatranscriptomic sequencing. Our study revealed that HaV dominated the giant virus community in most samples, with the relative abundances of up to 56%. Despite the high abundances, the HaV population exhibited a relatively low level of microdiversity but with a high pN/pS ratio compared to other giant viruses in the study site. Microdiversity increased during the early sampling period, reached a maximum at mid-sampling, and decreased during the later period, consistent with rapid diversification during viral expansion, possibly driven by both in situ mutations and the succession of pre-existing minor variants. Several accessory genes, including a glycosyltransferase and an endonuclease, were highly expressed, providing functional evidence consistent with host interaction-driven selective pressure during the bloom. Together, these results indicate that HaV population dynamics during algal blooms are shaped by host-driven selection acting on standing genetic variation.

ecology↗

bioRxiv2026

Classical enhancers couple cis-regulatory logic with transcriptional condensates and 3D genome architecture

Deciphering the regulatory logic of enhancers remains a central question in understanding cell- and tissue-specific gene expression in multicellular organisms. This is particularly pertinent at multipartite enhancer clusters such as super-enhancers, where multiple enhancers contribute to the expression of a single gene. Gene expression has been studied largely through sequence-dependent recruitment of transcription factors (TF) and co-activators, whereas 3D chromatin structure has been attributed to architectural proteins such as cohesion and CTCF1-3. However, the contribution of DNA sequence encoded in enhancers to shaping higher-order genome organization remains poorly understood. Here we show that classical enhancers, embedded within multipartite super-enhancer structures, act as determinant regulatory elements that initiate the gene regulatory cascade by linking DNA sequence recognition to 3D chromatin architecture. Classical enhancers are more evolutionarily conserved and display stronger regulatory activity than facilitator elements, which lack intrinsic enhancer activity but potentiate classical enhancer function. We show that classical enhancers are selectively bound by specific TFs with strong intrinsically disordered regions, such as NFE2L2 in liver cancer cells, capable of driving transcriptional condensate formation through phase separation. NFE2L2 depletion reduced enhancer activity and induced widespread chromatin reorganization, characterized by increased cohesin and CTCF occupancy at super-enhancer boundaries and beyond. This "cohesin clogging" impaired DNA loop extrusion, led to formation of smaller topologically associated domains, and weakened enhancer-promoter contacts. These findings highlight that sequence-specific TFs have multifaceted roles beyond transcriptional control, establishing a direct mechanistic link between enhancer sequence, TF binding, condensate formation, and 3D genome organization, with the regulatory logic being encoded in the DNA sequence itself.

genomics↗

bioRxiv2026

NORAD orchestrates KLC1-mediated SFPQ transport via liquid-liquid phase separation

Neuronal function requires precise long-distance axonal transport mediated by molecular motors and RNA-binding proteins like SFPQ, though regulatory mechanisms remain poorly defined. We identify long non-coding RNA NORAD as a master regulator of this process through liquid-liquid phase separation (LLPS). While SFPQ and kinesin-1 mediate cargo delivery, the specific RNA coordinating their interaction was unknown. We demonstrate NORAD directly binds kinesin light chain 1 (KLC1) and promotes SFPQ condensation into dynamic LLPS droplets, enabling efficient transport. CRISPR-assisted mapping and functional assays show NORAD depletion disrupts granule dynamics, impairs neuroprotective mRNA localization, and induces axonal degeneration. In vitro reconstitution confirms NORAD-KLC1 synergy enhances SFPQ phase separation, and neuron-specific knockout mice exhibit motor deficits with reduced neuronal density. These findings establish the first evidence of lncRNA NORAD-mediated LLPS in axonal transport, revealing a new paradigm for RNA-guided neuronal maintenance.

molecular biology↗