Biology subjects

Dong, Y.

Publications and source records attributed to Dong, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Integrative drug discovery for Parkinson disease with DIMER

Translating Parkinson disease (PD) genetics into therapeutic candidates requires approaches that account for interconnected disease mechanisms and their cellular context. Here we present DIMER (Direct and Indirect Module Evaluation for Repurposing and screening), a framework that connects network-based drug repurposing and target-directed virtual screening through shared disease-associated gene sets. Applying DIMER to PD, we integrated genetic risk and mechanism-associated gene sets with drug-target interactions, disease transcriptomes, and single nucleus expression profiles. Network analysis identified 423 repurposing candidates, with 71% of qualifying drug-gene set associations arising through targets outside the corresponding disease gene set. Transcriptional reversal analysis and cell type-resolved networks further distinguished candidates by their predicted effects on disease-associated expression and their cellular context, while target-set separation nominated potentially complementary drug combinations. For target-directed virtual screening, DIMER adapted a pretrained compound-protein interaction model to screening library chemistry and incorporated known-ligand similarity into compound ranking. Library adaptation improved compound-target pair classification performance, whereas ligand-informed ranking increased early enrichment of known active compounds. Consensus screening of 1.82 million compounds against seven PD-associated proteins yielded a shortlist of 22 compounds supported by at least five ranking runs. In a complementary experimental evaluation, four repurposing candidates (polydatin, fedratinib, sorafenib and venlafaxine) attenuated the loss of dopamine neuron marker signals in human midbrain organoids exposed to 6-hydroxydopamine. Together, these findings establish DIMER as a framework for translating disease-associated genes into pharmacological hypotheses and prioritizing candidates for experimental testing.

neuroscience↗

bioRxiv2026

Cell-intrinsic regulation of presynaptic release site patterning

Functional neuronal connectivity depends not only on synaptic partner choice but also on the number, strength, and spatial distribution of release sites between partners. How these features are regulated remains poorly understood. Here, using the C. elegans DA9 motor neuron, we identify the immunoglobulin superfamily cell adhesion molecules SYG-1 and SYG-2 as cell-autonomous regulators of presynaptic release-site patterning. SYG-2 regulates presynapse number, size, and spacing, whereas SYG-1 primarily regulates spacing. Endogenous localization and cell-specific knockout analyses reveal that SYG-2 recruits SYG-1 to the presynaptic domain through previously unrecognized cis interactions. Endogenous structure-function studies further demonstrate that the SYG-2 intracellular domain is required for presynaptic organization and can promote presynapse formation independently of its extracellular domain. Genetic and targeted actin-disruption experiments implicate the adaptor protein NCK-1 and local actin remodeling in SYG-2 intracellular signaling. Together, these findings reveal how cell adhesion molecules can act cell-intrinsically to pattern presynaptic release sites after synaptic partners have been established.

neuroscience↗

bioRxiv2026

Simultaneous multi-area recordings in macaque frontoparietal cortex during a manual object-interaction task

Dexterous hand control is essential for daily activities and a top restoration priority for people with tetraplegia, yet neurophysiological datasets suitable for studying and decoding naturalistic hand behavior remain scarce. Most available recordings constrain movements to a small number of degrees of freedom or cover only a single stereotypical grasp-and-hold structure. Moreover, previous brain-computer interface (BCI) studies have largely relied on signals from a single cortical area, even though dexterous hand control is distributed across an interconnected frontoparietal network. To address these limitations, we designed a paradigm that elicits rich hand movements across 40 distinct hand-object interaction conditions. We recorded simultaneous frontoparietal activity with hand kinematics from a rhesus macaque performing them. Neural activity was recorded from the primary motor cortex, anterior intraparietal area, and ventral premotor cortex using microelectrode arrays spanning 1,920 channels, while a multi-camera markerless motion-capture system acquired video from which kinematics were extracted offline. The dataset comprises data from 20 sessions, including processed neural features, synchronized 3D coordinates of hand and elbow keypoints, and trial-level metadata including task conditions and event timing. We further provide technical validation, including a neural decoding benchmark with multiple algorithms for continuous keypoint coordination reconstruction. We found that cross-day and cross-task decoding performance varied among algorithms. Variation in channel availability leads to different performance degradation curves in different algorithms. This task-rich dataset offers a valuable resource for investigating the neural mechanisms of dexterous hand control and for advancing the performance of motor BCIs.

neuroscience↗

bioRxiv2026

Innate immune stress pathway activation underlies heterochromatin dysfunction pathology

Heterochromatin loss disrupts nuclear architecture, gene regulation and repetitive element silencing, and is associated with diverse human diseases. However, mechanisms linking heterochromatin dysfunction to pathological phenotypes remain unclear. Using genetic interaction screening and genomic analyses in C. elegans, we identify secondary activation of the Intracellular Pathogen Response (IPR), an innate immune stress pathway, as a major contributor to heterochromatin mutant phenotypes. Constitutive IPR activation phenocopies slow growth and indirect transcriptional changes observed in these mutants. Depletion of genetic enhancers further increased, whereas suppressor RNAi attenuated IPR activation, with direct heterochromatin targets remaining substantially deregulated. Notably, many suppressors encode active chromatin components, and mild reduction of RNA polymerase II activity ameliorates growth defects in C. elegans HP1 mutants and human HP1-deficient cells. Our findings reveal secondary stress response activation as an important mechanism linking heterochromatin dysfunction to pathology and identify transcriptional dampening as a potential therapeutic strategy for mitigating these effects.

genetics↗

bioRxiv2026

FFPERescuer: deep unsupervised domain adaptation for the reconstruction of gene expression profiles derived from formalin-fixed paraffin-embedded samples

Formalin-fixed paraffin-embedded (FFPE) tumor tissues often suffer from RNA degradation, posing a long-standing challenge for reliable transcriptomic profiling. Here, we propose FFPERescuer, a deep learning framework employing unsupervised domain adaptation, to rectify distorted gene expression data. FFPERescuer comprises a partial encoder that maps a small subset of genes to high-level representations and a decoder to reconstruct full gene expression profiles. On simulated data with varying noise levels, FFPERescuer faithfully recovered gene expression profiles, achieving high Pearson correlation coefficients (PCCs > 0.85) with the ground truth. In FF-FFPE-matched cohorts, FFPERescuer significantly enhanced expression profile concordance, with average PCCs increased by 23% (P < 0.05). Applying to cancer subtyping, FFPERescuer improved classification accuracy from 67% to 92%, recapitulated subtype-specific biological properties lost in the FFPE-derived data, and enhanced survival associations. Our studies provide a powerful framework for reliable transcriptomic profiling from FFPE-archived tumor samples that are widely available in the clinic.

bioinformatics↗

bioRxiv2026

Developmental pleiotropy revealed by mosaic heterozygous Snrpb deletion underlies CCMS-like axial skeletal defects

Cerebro-Costo-Mandibular Syndrome (CCMS) is a rare congenital disorder due to pathogenic variants in the core spliceosomal gene SNRPB. Affected individuals present with axial skeletal abnormalities, including cleft palate, micrognathia, posterior rib gaps, and a bell-shaped thorax. The molecular basis of these axial defects remains poorly understood, limiting the development of targeted interventions. To study the temporal and molecular requirements of SNRPB during axial development, we generated a mouse model of CCMS using an inducible Cre-lox system to conditionally delete Snrpb. Mosaic deletion of exons 2-3 of Snrpb after gastrulation resulted in the full spectrum of CCMS-like abnormalities, including micrognathia, posterior rib gaps and a reduced thoracic cavity. Despite normal somite morphology and patterning, transcriptomic analysis of E9.5 mutant somites revealed upregulation of p53 pathway genes and mis-expression of retinoic acid (RA) signaling components, consistent with reduced RA signaling. Alternatively spliced genes in Snrpb mutant somites were associated with post-transcriptional regulation, including chromatin modifiers. To test if RA pathway supplementation can rescue axial defects, we performed dietary RA supplementation; however, this failed to rescue mutant phenotypes, suggesting that p53 activation and chromatin dysregulation additionally contribute to disease pathogenesis. Together, these findings establish the first in vivo model of CCMS-associated axial skeletal abnormalities and indicate that Snrpb dysfunction disrupts the early specification of axial skeletal identity without overtly altering somite patterning.

developmental biology↗

bioRxiv2026

VGLL3 Links Pericyte Hypercontractility to Perivascular Fibrosis of the Cerebral Microcirculation, a Novel Vasculopathy Leading to Distinct Long-Term Cerebral Autoregulation Dysfunction After Subarachnoid Hemorrhage

BACKGROUND: Cerebral ischemia following subarachnoid hemorrhage (SAH) has traditionally been considered transient because functional alterations of the cerebral microcirculation are thought to be self-limiting. However, we identified a previously unrecognized vasculopathy, perivascular fibrosis of the cerebral microcirculation (PFCM), characterized by excessive type I collagen deposition after SAH. This study investigated the mechanisms underlying PFCM and its subsequent effects on cerebral hemodynamics. METHODS: In vivo SAH was modeled in mice by autologous blood injection, whereas oxygenated hemoglobin (OxyHb) exposure was used to mimic SAH in vitro. Pericyte-deficient mice (Pdgfr{beta}+/-) and pericyte-specific vestigial-like family member 3 (VGLL3) conditional knockout mice (Vgll3{Delta}PC) were generated. Pericyte contractility was measured by nanoindentation and traction force microscopy. Molecular mechanisms were examined using Western blotting, immunofluorescence, CUT&Tag, RNA-seq, transmission electron microscopy, and molecular docking. PFCM, impaired dilation of the cerebral microcirculation, and cerebral autoregulation were assessed by two-photon imaging, transcranial Doppler with continuous blood pressure monitoring, super-resolution ultrasound imaging, and photoacoustic imaging. RESULTS: After SAH, mice developed long-term cerebral autoregulation dysfunction marked by impaired dilation of the cerebral microcirculation, with the abnormality being most evident within the relatively lower blood pressure range. The marked reduction in PFCM in Pdgfr{beta}+/- mice indicated that pericytes were the principal cellular contributors. Mechanistically, OxyHb-induced cytoskeletal remodeling in vitro increased pericyte contractility and promoted nuclear translocation of SAH-upregulated VGLL3. This was followed by increased genomic occupancy, Col1a1 transcriptional activation, and type I collagen deposition. Pericyte-specific VGLL3 knockout abolished PFCM and, consequently, significantly alleviated long-term cerebral autoregulation dysfunction. CONCLUSIONS: Our findings identify PFCM mediated by pericytic VGLL3 as a novel vasculopathy leading to long-term cerebral autoregulation dysfunction after SAH.

neuroscience↗

bioRxiv2026

Potato Agent: AI-Driven Data and Knowledge Exploration on an Agent-Ready Potato Multi-Omics Platform

Potato is an important non-cereal food crop worldwide. However, the limited number of functionally validated genes remains a major bottleneck to favorable allele stacking and genome design breeding in potato. Rapid advances in AI agents offer a promising means to support crop breeding by translating natural-language questions into coordinated data analysis and knowledge retrieval. Their reliable use for potato breeding, however, is constrained by fragmented multi-omics resources that lack consistent curation and machine-accessible interfaces. Here, we constructed an agent-ready potato multi-omics database integrating genomic resources from 150 potato accessions, 259 bulk RNA-seq samples, and 14 spatial transcriptomic datasets into a pangenome, a tissue expression atlas, co-expression networks, and spatial expression maps accessible through open APIs. We developed 39 potato-specific Agent Skills for reproducible bioinformatics analysis and comprehensive data and knowledge exploration, enabling natural-language questions to be translated into standardized data-retrieval and analysis tasks. By integrating direct evidence from potato studies, functions of homologous genes in Arabidopsis, rice, and maize, and tissue expression patterns, we generated genome-wide functional predictions for 37,658 genes in the DM reference genome. We further developed Potato Agent as a multi-user, browser-based platform with isolated workspaces and online result preview, reducing the technical burden of agent deployment and providing direct access to integrated data, knowledge, and workflows. Case studies demonstrated its capabilities in reproducible bioinformatics analysis, agent-assisted identification of a tuber development regulator, scientific data visualization, and haplotype-aware promoter analysis and sgRNA design. Together, the agent-ready database and Potato Agent provide an integrated infrastructure for functional gene discovery and hybrid breeding in potato.

plant biology↗

bioRxiv2026

Virtual spatial transcriptomics from histopathology enables prognostic and therapeutic response prediction in cancer

Spatial transcriptomics reveals cellular heterogeneity, intercellular communication, and tissue organization, but its cost and limited accessibility restrict clinical use. Here, we present VISTA, a model that integrates multi-scale histological features and spatial context to infer spatial gene expression from H&E-stained tissue images. Across leave-one-section-out cross-validation and independent validation, VISTA robustly predicted thousands of genes and outperformed state-of-the-art methods. Beyond expression reconstruction, VISTA enabled clinically relevant downstream analyses. In TCGA breast cancer samples, it identified survival-associated genes, stratified prognostic risk groups, and revealed adverse tumor-associated spatial subtypes. In our in-house intrahepatic cholangiocarcinoma cohort, it preserved tumor-normal organization and identified CLDN4 and CYP3A4 as complementary spatial biomarkers. In HER2+ breast cancer, it predicted pathological response to neoadjuvant trastuzumab-based therapy and linked response-associated regions to immune and cytokine-related programs. These results support virtual spatial transcriptomics from routine histopathology for oncology applications.

genomics↗

bioRxiv2026

ProtFinder: An efficient machine learning framework for protein model selection on real data

Model selection is a fundamental step in phylogenetic analysis that determines the best-fit model of sequence evolution for a given multiple sequence alignment. Popular model selection methods, such as ModelFinder, rely on statistical information criteria, such as the Bayesian Information Criterion (BIC) or the Akaike Information Criterion (AIC). However, these approaches are computationally expensive and the use of information criteria has been the subject of ongoing discussion. Recently, machine learning has emerged as a promising approach for phylogenetic model selection in both nucleotide and protein sequence analyses. ModelDetector is currently the only machine learning-based method for amino acid substitution model selection. However, because ModelDetector was trained on simulated data, it does not perform well on real datasets. Another limitation is that it does not support different rate heterogeneity across sites (RHAS) models. To overcome these limitations, we introduce ProtFinder, an efficient machine learning framework for protein model selection that predicts amino acid substitution models, RHAS models, and amino acid frequency models. To enable ProtFinder to work with real datasets, we employed a transfer learning strategy consisting of three stages: (1) initial training on large-scale simulated data, (2) joint training on both simulated and real data, and (3) final fine-tuning using real data only. Experimental results show that ProtFinder outperformed ModelDetector in amino acid substitution model selection. ProtFinder achieved comparable accuracy to the maximum likelihood method ModelFinder for substitution model selection on medium and large MSAs. It performs slightly better than ModelFinder in RHAS model selection and substantially outperforms it in amino acid frequency model determination. Notably, ProtFinder is up to 1,400 times faster than ModelFinder in terms of inference time, making it particularly suitable for medium and large datasets.

evolutionary biology↗

bioRxiv2026

The vitellogenesis pathway of the tick host Ixodes scapularis regulates Rickettsia buchneri transcriptional state and persistence

Obligate endosymbionts relying on transovarial transmission must coordinate with host reproduction, yet the regulatory mechanisms remain poorly understood. Here we show that the vitellogenesis pathway of the tick Ixodes scapularis regulates the transcriptional state of its endosymbiont Rickettsia buchneri (Rb), separately from its abundance. In males, Rb DNA remained detectable, but bacterial transcription was strongly reduced across all examined genes, with markedly lower RNA/DNA ratios. In females, Rb was restricted to ovarian tissues (developing oocytes and interstitial cells), with no detection in salivary glands or midgut by TEM, FISH, or PCR. After blood feeding, Rb density within size-matched early-stage oocytes was significantly reduced. We further characterized two gene families mediating vitellogenesis: vitellogenin synthesis genes (Vgs, n = 20) and vitellogenin receptor genes (Vgr, n = 15). Vgs proteins showed conserved domain organization, whereas Vgr paralogs showed greater structural diversification. RNAi silencing of Vgs20 or Vgr12 altered Rb transcriptional profiles in both tick cells and ticks, although changes in bacterial load were not consistent between the two systems. Antibiotic depletion of Rb increased expression of both host genes. Together, these findings show that tick vitellogenesis pathways contribute to Rb regulation during reproduction and identify the I. scapularis-Rb system as a useful model for studying host control of obligate endosymbionts. IMPORTANCEMaternally inherited bacterial symbionts are commonly characterized by bacterial abundance. This study shows that bacterial abundance alone does not necessarily reflect symbiont functional state. In the blacklegged tick, the inherited symbiont Rickettsia buchneri persists in males but exhibits little transcriptional activity. In females, the host reproductive pathway determines whether the symbiont is active: silencing one component of this pathway changed bacterial gene expression without changing bacterial abundance. Hosts therefore regulate not only the abundance of inherited symbionts, but also their functional state. The same bacterial abundance can correspond to very different functional states. Understanding inherited symbioses therefore requires considering bacterial function alongside bacterial abundance.

microbiology↗

bioRxiv2026

Evaluation of harmonization methods to mitigate assay and cohort effects in plasma p-tau217

INTRODUCTIONThe growing number of assay platforms measuring blood-based biomarkers (BBMs) for Alzheimers disease (AD) has introduced challenges in interpretability and comparability across assays. Differences across studies also limit comparability of data. To address these challenges, a systematic evaluation of harmonization methods is needed to support BBM data integration within or across studies. METHODSTwo multisite studies, Alzheimers Disease Neuroimaging Initiative (ADNI, n = 219) and Human Connectome Project (HCP, n = 111), were used to evaluate harmonization methods for mitigating assay and cohort effects in plasma p-tau217 measurements. Methods includes various normalization, regression, and standardization approaches, including the recently developed CentiMarker. Assay effects were evaluated using repeated-measures data across assay platforms within each cohort, whereas cohort effects were assessed using pooled ADNI and HCP data. Harmonization performance was evaluated using distributional statistics and downstream modeling of p-tau217. RESULTSQuantile normalization and quantile mapping methods were most effective for mitigating assay effects, whereas conditional quantile mapping performed best for pooled multi-cohort data. These methods also preserved biological variability. In contrast, simple means adjustment and reference-based z-score standardization were least effective for mitigating assay effects, while simple means adjustment, z-score standardization, and quantile normalization were least effective for mitigating cohort effects. CentiMarker had minimal impact on assay or cohort effects. DISCUSSIONBased on our evaluation, we recommend (conditional) quantile mapping for p-tau217 studies integrating data across multiple assays or cohorts. In contrast, we caution against using CentiMarker and z-score-based methods, as they limit comparability and do not effectively mitigate technical variability.

neuroscience↗

bioRxiv2026

PathoBench: an open community-driven benchmark registry for pathogen bioinformatics tools

SummaryThe proliferation of pathogen bioinformatics pipelines has outpaced the communitys ability to compare them on common ground. Self-reported performance numbers, ad-hoc evaluation datasets, and inconsistent metrics make pipeline selection difficult for clinical and public-health researchers. We present PathoBench, an open web platform that addresses this gap through three coordinated mechanisms: (i) a curated registry of 26 standard benchmark datasets across 10 human pathogens, each with persistent identifiers and direct download links; (ii) pathogen-specific evaluation metrics that submissions must report, allowing direct head-to-head comparison only on the same dataset; and (iii) a credibility framework combining mandatory dataset attestation, ORCID-linked attribution, public peer comments, and administrator verification. As a case study, four published Mycobacterium tuberculosis drug-resistance pipelines were evaluated against the WHO TB mutation catalogue, demonstrating the frameworks discriminating power. PathoBench is open for community contributions across all ten supported pathogens. Availability and implementationPathoBench is freely available at https://pathobench.vercel.app. Source code is released under the MIT license at https://github.com/BPHL-Molecular/pathobench. The platform requires no installation for end users; programmatic access is available via a Supabase REST API. Contactyibo.dong@flhealth.gov Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2026

Conversion of a Viral Glycan Shield into a Binding Anchor via Causal-Driven Antibody Optimization

Therapeutic antibodies are challenged by rapidly evolving pathogens that exploit glycosylation to shield epitopes. SARS-CoV-2 JN.1 exemplifies this, escaping antibodies through the N354-linked glycan. However, targeting glycosylated epitopes remains vacant, as scarce and heterogeneous glycan structures render existing approaches ineffective. Here, we introduce the Antibody Evolution Nexus with Causal-Driven Simulation (AENCS), integrating molecular simulation with causal inference. Applying AENCS to restore S309 efficacy against JN.1, we identified ACC01, exhibiting [~]24-fold improved neutralization. With limited prior knowledge of the N354 glycosylation site, ACC01 stabilized this glycan conformation, facilitating the determination of its cryo-EM structure. Causal dissection revealed how this glycan shield is functionally inverted into a binding anchor through multi-layered interactions. This mechanistic conversion, combined with the conservation of N354 glycosylation, enabled ACC01 to maintain potent activity against the latest variant NB.1.8.1. Collectively, AENCS demonstrates causal-driven antibody engineering can illuminate cryptic glycosylated epitopes, providing viable paradigms for exploring this vacant frontier.

bioengineering↗

bioRxiv2026

Prenatal e-cigarette exposure induces region- and cell type-specific metabolic and developmental reprogramming

Prenatal e-cigarette exposure (PeCE) is increasingly prevalent and has been associated with adverse neurodevelopmental outcomes, yet how maternal vaping perturbs early brain development remains poorly understood. We integrated spatial transcriptomics, snRNA-seq and lipidomics to define neonatal rat brain responses to PeCE in rats at regional and cellular resolution. PeCE induced pronounced spatial heterogeneity in vulnerability, with the striatum exhibiting the strongest developmental transcriptional disruption. PeCE disrupts lipid metabolic homeostasis and induced molecular signatures suggestive of enhance Ca2+ signaling, dopaminergic responsiveness and region-specific synaptic stress programs. In the striatum, PeCE induced transcriptional programs consistent with altered lipid utilization, silent synapse-like molecular features, suppressed dendritic spine development and delayed D1-medium spiny neuron maturation. PeCE-sensitive genes were enriched in human autism spectrum disorders and neurodevelopment risk loci. Together, these findings identify disrupted metabolic and developmental reprogramming as a central feature of neonatal brain vulnerability to maternal vaping and provide a mechanistic framework linking PeCE to neurodevelopmental disease risk.

neuroscience↗

bioRxiv2026

Unlocking Your Programmable and Creative RNA Sequence Designer with RDiffusion

RNA, a pillar of the central dogma, has shaped three billion years of evolution. Despite cataloging tens of millions of non-coding RNAs and annotating millions, we have barely scratched the surface of the vast, unexplored RNA sequence space. Here, we introduce RDiffusion, a discrete-diffusion-based generative transformer model for RNA sequence design. Conditioned on diverse biological features, such as desired function, family type, secondary and tertiary structure, or binding protein partners, it can guide the generation of novel RNA sequences tailored to specific design specifications. We evaluate RDiffusion across a broad spectrum of RNA design tasks and find that it not only surpasses all baseline methods in design success rate and sequence diversity but also achieves advanced performance on downstream tasks. To demonstrate its translational potential, we applied RDiffusion with a customized seed-screening pipeline to de novo design therapeutic MicroRNA(miRNA) mimics in osteoarthritis (OA). This strategy identified mimic 0-4 as a lead candidate targeting SDC4 to preserve ECM homeostasis and cartilage integrity, with robust efficacy validated in clinical OA samples. Altogether, RDiffusion holds strong potential to serve as a cornerstone for RNA generation and representation learning, establishing a generalizable AI-driven paradigm for RNA therapeutic discovery.

bioengineering↗

bioRxiv2026

Generalisable tissue-wide molecular reconstruction from histology

Spatial transcriptomics technologies measure gene expression within intact tissues but remain difficult to scale across large tissue sections and patient cohorts. Consequently, many studies rely on tissue microarrays (TMAs) or sparse spatial profiling designs, where molecular measurements are available for only limited tissue regions and are often generated using heterogeneous gene panels. Existing H&E to spatial gene expression prediction methods remain challenged by sparse molecular measurements, partially overlapping gene panels and tissue-wide reconstruction across heterogeneous spatial datasets. Here, we present GHIST+, a framework for tissue-wide reconstruction of single-cell molecular states from H&E histology. GHIST+ integrates cellular morphology, local tissue context and shared tissue representations to extend sparse molecular measurements into tissue-wide molecular maps across heterogeneous spatial datasets. Across multiple cancer types and GTEx breast tissues, GHIST+ reconstructs biologically meaningful tissue-wide molecular organisation from sparse TMA-derived measurements while preserving spatial tissue structure, cell-type organisation and age-associated tissue states across cancer and non-cancer settings. GHIST+ establishes a scalable framework for transforming sparse spatial profiling experiments into tissue-wide molecular maps, enabling cohort-scale molecular reconstruction from routine histology under heterogeneous spatial transcriptomic settings.

bioinformatics↗

bioRxiv2026

A BRRF1-CCR4-NOT axis underlies conserved transcriptome-wide loss of splicing fidelity during gammaherpesvirus reactivation

Gammaherpesvirus reactivation drives a collapse of host mRNA splicing fidelity that extends across the transcriptome, with exon skipping affecting up to [~]57% of expressed genes, exceeding the effects of depletion of any of 186 splicing factors. Combining five Epstein-Barr virus (EBV) and Kaposis sarcoma-associated herpesvirus (KSHV) reactivation systems across B cell and epithelial models with deep poly(A)+ RNA sequencing of purified lytic cells, we find that most induced isoforms are predicted to undergo nonsense-mediated decay or to lose conserved protein domains, broadly compromising cell cycle, innate immune and RNA-processing pathways. The phenotype arises independently of viral DNA replication, indicating early host remodeling. A screen of EBV early genes identifies BRRF1 as a key driver: through a CIY(Y/E) motif conserved in KSHV ORF49, BRRF1 engages the nuclear CCR4-NOT complex through its CNOT9 and CNOT1 subunits, hijacking this canonically cytoplasmic deadenylation hub for nuclear disruption of host splicing.

pathology↗