Biology subjects

Guo, J.

Publications and source records attributed to Guo, J..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

Endothelial MRG15 Is a Mechanosensitive Suppressor of Atherosclerosis

Disturbed blood flow induces early endothelial inflammation in atherosclerosis, yet the precise mechanisms of endothelial sensing of disturbed flow remain incompletely understood. In this study, we integrated proteomic profiling of human endothelial cells (ECs) subjected to disturbed flow with coronary artery disease risk related genes from large-scale genome-wide association studies (GWAS). We identified mortality factor 4-like protein 1 (MORF4L1, also called MRG15) as a critical modulator in the pathogenesis of atherosclerosis induced by disturbed flow. We show that the expression of MRG15 is markedly reduced in ECs of human aortic atherosclerotic plaques, as well as in ECs exposed to disturbed flow in mouse carotid artery and in cultured human umbilical vein endothelial cells (HUVECs). Endothelial-specific deletion of Mrg15 significantly worsened, while its overexpression attenuated endothelial inflammation and atherosclerotic lesions in turbulent blood flow- or Western diet-induced mouse atherosclerosis model. Single-cell transcriptomics showed that Mrg15 deficiency increased endothelial inflammation and intercellular adhesion molecule 1 (Icam1) expression, and enhanced integrin-mediated adhesion pathways. Mechanistically, MRG15 facilitated the recruitment of enhancer of zeste homolog 2 (EZH2) to maintain repressive histone H3 lysine 27 trimethylation (H3K27me3) marks on the promoters of ICAM1 and integrin subunit alpha 5 (ITGA5). Disturbed blood flow rapidly led to an elevation of protein neddylation, which subsequently induced neddylation-dependent degradation of MRG15 within endothelial cells. This degradation of MRG15 alleviated the transcriptional repression of ICAM1 and ITGA5, thereby enhancing monocyte adhesion to ECs. These findings highlight endothelial MRG15 as a mechanosensitive suppressor of atherosclerosis induced by disturbed flow. Consequently, MRG15 emerges as a promising novel therapeutic target for atherosclerosis.

molecular biology↗

bioRxiv2026

High-PepBinder: A pLM-Guided Latent Diffusion Framework for Affinity-Aware Target-Specific Peptide Design

Peptides, as therapeutic molecules, offer unique advantages in targeting complex protein surfaces, yet their rational design remains limited by the vastness of the sequence space and the constraints of traditional approaches. Here, we propose High-PepBinder, a sequence-only conditional diffusion framework for target-specific peptide generation. Guided by the target protein sequence, High-PepBinder adopts a dual encoder architecture that integrates protein language models (pLMs) with the diffusion model. This approach cascades the peptide generation model with an affinity classifier and enables the generation process to capture affinity-related features of the peptides through lightweight joint optimization. Due to the scarcity of protein-peptide affinity data, we constructed PepPBA, to our knowledge the most comprehensive dataset to date, and established a structure- and physics-based screening pipeline to prioritize top candidates. Results show that High-PepBinder demonstrates competitive performance across multiple peptide generation and affinity-related tasks. For representative targets, including KEAP1, XIAP, and EGFR, the generated peptides preserve key binding geometries and interface patterns of reference peptides in predicted complexes, while maintaining sequence diversity and favorable predicted properties. Overall, High-PepBinder contributes toward a general and sequence-only strategy for peptide design, offering a computational framework for expanding peptide discovery against challenging targets.

bioinformatics↗

bioRxiv2026

BaCas12a3 represents a new subtype of type V CRISPR effector with collateral activity toward tRNA

The CRISPR-Cas12 family encompasses diverse RNA-guided nucleases with both DNA-targeting and RNA-targeting subtypes. They can trigger antiviral activities mainly through either direct elimination invading nucleic acids, or activating broad collateral cleavage to induce abortive infection. Here, we report a novel type V CRISPR effector BaCas12a3 that causes growth inhibition through a unique tRNA-cleavage mechanism. Plasmid interference assays indicated that BaCas12a3 inhibits host growth arrest without invoking the DNA damage response, suggesting that the immune responses may not involve double strand breaks of DNA. Indeed, biochemical characterization of the BaCas12a3-crRNA ribonucleoprotein (RNP) unraveled that the effector is an RNA-activating nuclease that cleaves 3' terminus of tRNAs. Cryo-EM structures of BaCas12a3 reveal a conserved bilobed architecture featuring a unique nucleic acid-loading (NL) domain adjacent to the RuvC catalytic center. Structural and mutagenesis analyses show that the NL domain, together with a zinc ribbon domain, form a gated substrate groove. Target RNA binding induces conformational changes that open this groove and expose the RuvC active site, enabling specific tRNA cleavage while preventing other non-specific degradation. Our findings identified the NL domain aside the RuvC active site responsible for the tRNA recognition in BaCas12a3, expanding the functional diversity of CRISPR immunity.

molecular biology↗

bioRxiv2026

Joint Segmental Duplication Co-option Drives Human-specific Transcriptional Readthrough and Expression Fine-tuning of NPEPPS-TBC1D3

Segmental duplication (SD) is a major driver of functional changes in evolution and disease. Many genes embedded within SDs, such as NPEPPS and TBC1D3, display substantial copy number variation (CNV) across individuals. Yet, the precise identification of the functional copies and their transcriptional outputs remains largely unstudied. Focusing on NPEPPS and TBC1D3, we illustrate human-specific expression fine-tuning mechanisms associated with readthrough transcripts. We identified a human-specific NPEPPS-TBC1D3 digenic genomic structure that originated from a joint SD pair and became fixed across populations. Experiments demonstrate that this structure generates NPEPPS-TBC1D3 readthrough transcripts, which are the predominant isoforms of TBC1D3 expression in various cell types, fine-tuning its protein level. Furthermore, a human-specific hypomethylation signal within an upstream CpG island of NPEPPS precisely pinpoints the expressed TBC1D3 paralog. Moreover, we reveal transcriptional readthrough events are [~]3-fold enriched for joint-SD-associated transcriptional readthrough (JSDTR) and identify 109 JSDTR gene pairs, including neurodevelopmentally important pairs and clinically interesting SERF1A/B-SMN1/2. Taken together, our findings comprehensively describe an example of how a joint SD event shaped evolution and suggest that JSDTR is a broad mechanism for the emergence of new functions.

genetics↗

bioRxiv2026

Mapping kinase-dependent tumor immune adaptation with multiplexed single-cell CRISPR screens

Immune dysfunction in cancer is enacted by multiple programs, including tumor cell-intrinsic responses to distinct immune subpopulations. A subset of these immune evasion programs can be systematically recapitulated through direct tumor-immune interactions in vitro. Here, we present an integrated, high-throughput single-cell CRISPR screening framework focused on the protein kinome for mapping the tumor-intrinsic regulation of T cell-driven immune pressure in glioblastoma (GBM). We combine pooled CRISPR interference and activation (CRISPRi/a) with immune-matched NY-ESO-1 antigen-specific allogeneic GBM-T cell co-culture and massively multiplexed single-cell transcriptomics to systematically quantify how genetic perturbation reshapes baseline tumor state and adaptive responses across graded effector-to-target ratios. We further leverage deep generative models for analyzing pooled CRISPR screens to decipher the effects of genetic perturbations on the mechanisms of tumor resistance. This framework resolves distinct modules of immune evasion and survival, including the regulation of the antigen-presentation machinery, interferon/NF-{kappa}B signaling, oxidative stress resilience, and checkpoint/cytokine programs, while identifying perturbations that reroute the continuous tumor transcriptional trajectory induced by T cell engagement. A secondary chemical screen in patient-derived GBM cultures identified putative kinase targets of immune evasion phenotypes (e.g., EPHA2 and PDGFRA), whose inhibition leads to the blockade of evasive programs and enhances T cell-mediated GBM killing. Together, this workflow provides a scalable blueprint for comprehensive charting of the genetic control of tumor-immune interactions.

genomics↗

bioRxiv2026

Codon Deoptimization of Multispecific Biologics Reduces Mispairing During Transient Mammalian Protein Expression

Codon optimization is utilized in biologics design to maximize protein expression. Selecting the host organisms most frequently used codons for each amino acid can significantly enhance recombinant protein expression yields. However, non-optimal codons in mRNA can be critical for functional protein production through inducing pauses in or attenuating protein translation. In our study, we have investigated the effect of deoptimizing serine codons in biologics by shifting them from the five most frequently used codons to the least (TCG). Rare serine codons were strategically inserted into the coding sequences of the constant regions in a trispecific antibody (Protein 1), a bispecific antibody (Protein 2), and multiple non-proprietary bispecific antibodies. We observed that inserting 1-2 rare serine codons within an open reading frame led to expression changes that reduced the formation of mispaired 2x light chain and half-molecule species. Protein purity was drastically increased by incorporating two deoptimized serine codons into a single chain. Notably, we observed a negative correlation between total protein expression yield and final product purity. Taken together, our work demonstrates that incorporation of deoptimized serine codons into a single chain can significantly influence multispecific biologic pairing and enhance final product purity. Our findings align with existing literature showing that rare codon usage modulates translation kinetics and protein folding. Future investigation is warranted to enable a priori identification of the rate-limiting chain in multispecific biologics, thereby guiding strategic codon deoptimization prior to expression.

bioengineering↗

bioRxiv2026

Salmonella SPI2 evades detection by NAIP/NLRC4 despite utilization of a detectable needle

Salmonella enterica serovar Typhimurium uses two type 3 secretion (T3S) systems to reprogram host cells. Whereas activity of the SPI1 T3S can be detected by the NAIP/NLRC4 inflammasome, the SPI2 T3S is not detected. In this study, we demonstrate that the SPI2 needle protein, SsaG, can be detected by the NAIP-NLRC4 inflammasome when artificially delivered to the cytosol in mouse macrophages. Surprisingly, this detection occurs primarily through NAIP2, which normally detect rod proteins. However, we found that during infection with live S. Typhimurium, this detection fails to trigger the downstream pyroptotic pathway. We investigate the hypothesis that the SPI2 effector protein SpvC inhibits NLRC4 activation. In mouse macrophages, spvC mutants were detected under SPI2-inducing conditions in an NLRC4-dependent manner. However, this masking effect of SpvC is not seen in vivo, where SpvC contributes to S. Typhimurium virulence in mice independent from NLRC4. We also hypothesized that S. Typhimurium may minimize SsaG detection by limiting protein expression. In support of this, overexpressing SsaG causes limited NLRC4-dependent clearance in vivo. Therefore, the SPI2 may evade NAIP/NLRC4 inflammasome detection by precisely controlling the quantity of detectable SsaG needle protein expressed.

immunology↗

bioRxiv2026

Natural variation of gibberellin levels in maize tissues across North America

Gibberellins (GA) are endogenous phytohormones that regulate growth and development throughout the plant lifecycle. While GA has been extensively studied under controlled conditions for their fundamental role in plant adaptation and agronomic trait development, field-based data on their natural variation across diverse agricultural genotypes and environments remains limited. To address this knowledge gap, we analyzed bioactive gibberellin A1 (GA1) and gibberellin A4 (GA4) across multiple maize hybrids grown in diverse field environments using high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS). This study provides comprehensive quantitation of GA1 and GA4 levels in maize tissues across diverse commercial hybrids grown under standard agricultural practices, revealing hormonal variation due to genetic background and environmental conditions. Our findings demonstrate that GA1 and GA4 concentrations from conventional maize samples varied across tissue types and field sites. Analysis of variance components indicated that the site variation was statistically significant at the 5% significance level in five out of ten GA and tissue combinations, while the genetic component was significant only for GA4 in grain samples. Notably, significant interaction between hybrid and site was observed for both GA1 and GA4 in stalk tissue. Positive correlations between GA1 and GA4 were observed consistently across tissues except root. These results underscore the common metabolic pathways involved in regulating GA levels in maize and provide the first comprehensive dataset of GA1 and GA4 variation under real-world agricultural conditions. Our findings offer insights into the interplay between genetics, environment, and hormonal regulation in maize and suggest potential targets for breeding programs aimed at improving agronomic traits such as yield.

plant biology↗

bioRxiv2025

Assembly and glycosylation of Helicobacter pylori sheathed flagella

The bacterial flagellum is a complex nanomachine essential for motility, colonization, and invasion in diverse species. Helicobacter pylori has evolved elaborate sheathed flagella that enable migration through the highly viscous gastric mucus layer to reach its colonization niche on the gastric epithelium, yet the molecular basis for these unique adaptations has remained elusive. Here, we use in-situ single particle cryo-electron microscopy to determine near-atomic structures of the flagellar filament within the membranous sheath of H. pylori. The major flagellin FlaA constitutes the bulk of the filament, whereas the minor flagellin FlaB contributes critically to the hook-proximal region. Both FlaA and FlaB form a conserved core surrounded by variable surface-exposed domains. Our structures further reveal that pseudaminic-acid glycans decorate these domains, where they mediate inter- and intra-subunit contacts that stabilize the filament and confer a negatively charged surface. Together, these findings support a model in which the filament rotates independently of the membranous sheath to drive H. pylori motility and provide a molecular framework for understanding how the sheathed flagellum enables colonization and persistence within the gastric niche. Significance StatementWe present the first in-situ near-atomic structure of the sheathed flagellar filament in Helicobacter pylori, revealing distinctive adaptations that underpin the pathogens unique motility and persistent infection. Our in-situ structures show that the two flagellins, FlaA and FlaB, assemble into an extended and exceptionally stable filament through an extensive hydrogen-bonding network. Pseudaminic acid glycans decorate the surface-exposed domains, where they stabilize inter-subunit packing and render the surface negatively charged and hydrophilic. These findings, which provide insight into the assembly of the flagellar filament and its relationship to the surrounding sheath, provide a structural framework for developing strategies to disrupt H. pylori motility and infection.

microbiology↗

bioRxiv2025

Mast cell extracellular granules are bioactive condensates driven by heparin and polyamine

Biomolecular condensates are membraneless bodies that organize biochemical reactions typically within cells. However, the roles of condensates in extracellular space--where conditions differ substantially from intracellular space--remain poorly understood. Here, we report mast cell extracellular granules (MCEGs), a stable membraneless entity, are condensates assembled via electrostatic interactions between glycosaminoglycans and polyamines. Disrupting polyamine synthesis or trafficking blocks MCEG formation and compromises the storage of proteases and cytokines. Granules reconstituted with heparin and spermine are sufficient to enrich mediators such as CPA3 and TNF, maintaining an elevated pH and higher concentrations of calcium and zinc compared to the extracellular milieu. This unique environment enhances CPA3 enzymatic activity. Furthermore, the granules increase TNF binding and its bioactivity toward endothelial cells. Together, we reveal MCEGs as functionally active biomolecular condensates with distinct biochemical and immunological properties; MCEGs are formed through sugar-metabolite interactions, expanding the mechanisms of condensate assembly beyond classical protein-protein and protein-RNA interactions.

cell biology↗

bioRxiv2025

TUPAD: A Tn5-Mediated, Pre-amplification/Adapter-Dimer-Free Platform for Ultra-Uniform, One-Step PGT Profiling with High Stability and Broad Compatibility

High-throughput sequencing stands as a cornerstone of clinical molecular diagnostics, particularly in preimplantation genetic testing (PGT)--a key application where the selection of chromosomally normal embryos is critical to enhancing in vitro fertilization (IVF) success rates. A fundamental challenge inherent to PGT, however, lies in the ultra-low gDNA input (typically <100 pg) from embryo biopsies. To mitigate this limitation, traditional workflows rely on whole genome amplification (WGA) technologies, such as MDA, PicoPlex, and MALBAC. Yet these WGA-based protocols inherently entail pre-amplification of gDNA prior to standard library construction---a step that introduces significant coverage bias and compromised uniformity. These are intrinsic flaws irreparable by downstream library preparation or bioinformatics analysis, ultimately leading to clinical uncertainty in the interpretation of copy number variations (CNVs). In this study, we developed TUPAD (Tn5-Mediated, Uniform Pre-amplification-free and Adapter-Dimer-Free Library preparation), a transformative technology that bypasses the limitations of traditional WGA. By engineering a novel adapter-dimer-free transposon system, TUPAD enables high-efficiency library construction from as little as 1 picogram (pg) of gDNA. This breakthrough allows for a pre-amplification-free workflow, effectively eliminating the primary source of amplification bias. Compared to existing WGA standards, these advantages are fully retained in embryo biopsy and positive sample testing, TUPAD consistently generates highly uniform library data, significantly enhancing the detection limit and accuracy of CNVs and other genomic variants. Beyond these performance advantages, TUPAD also cuts wet-lab processing time by 50%. Practical validation confirms TUPAD results are stable, reliable, with proven practical utility in PGT testing.

molecular biology↗

bioRxiv2025

EMCF ecosystem: Towards pretrained foundation model for electron microscopy image analysis

Volume electron microscopy (vEM) enables nanoscale visualization of three-dimensional (3D) cellular ultrastructure, providing critical insights into physiological processes and pathological alterations. However, its application to large-scale biological tissues remains constrained by two major bottlenecks: prolonged image acquisition and inefficient data processing. Here, we present EMCF ecosystem (EMCFsys), an integrated ecosystem designed to overcome these challenges through three key components: a large-scale benchmark dataset (EMCFD) comprising 4,002,802 high-quality images across 14 EM modalities and 6 biological kingdoms; a foundation image restoration model (EMCellFiner); and a scalable image analysis foundation model (EMCellFound). Together, these modules systematically enhance image quality and substantially improve analysis efficiency. Our results show that EMCellFiner outperforms specialist models in restoring degraded images, even surpassing original ground truth sharpness in certain artifact regions, and reduces imaging time by 16-fold by enabling low-resolution and low dwell time acquisition. EMCellFound exhibits exceptional feature discriminability, outperforms specialist models in classification, semantic segmentation and instance segmentation. It also enables high-precision 3D reconstruction of organelles (e.g., endoplasmic reticulum) with minimal labeled data (0.01% of total volume). We validated the EMCFsys on unseen datasets across diverse biological contexts and imaging platforms. By publicly releasing both the dataset and models, we establish a scalable paradigm for automated, high-throughput vEM data interpretation, accelerating exploration of lifes nanoscale structure and function across biology.

cell biology↗

bioRxiv2025

MS4MS: LLMs-driven Multi-agent System for Small-molecule Identification via LC-MS/MS

Small molecule identification is central to research fields such as drug discovery, but in complex systems like Traditional Chinese Medicine (TCM), traditional mass spectrometry analysis methods remain constrained by bottlenecks including insufficient database coverage, fragmented analysis workflows, and poor result interpretability. To address these limitations, we developed MS4MS, a large language model-driven multi-agent system that enables an end-to-end automated pipeline from raw data to small molecule identification. Validation on a public benchmark demonstrates that MS4MS achieves state-of-the-art performance in molecular formula prediction. Furthermore, its innovative small molecule identification agent enables efficient and interpretable compound elucidation. Verification using herbal extracts indicates MS4MSs outstanding performance regarding analytical coverage and the discrimination of isomers. Consequently, MS4MS offers a novel, accurate, interpretable, and high-throughput end-to-end automated strategy for small molecule identification, overcoming the analytical bottlenecks of traditional mass spectrometry in natural products and complex TCM systems.

bioinformatics↗

bioRxiv2025

CARP Protects Against Doxorubicin-induced Cardiotoxicity through NRF1-driven Mitochondrial Homeostasis

AimsDoxorubicin (DOX), a highly effective anthracycline chemotherapeutic agent, is limited by its dose-dependent cardiotoxicity. This study investigates the cardioprotective mechanisms of cardiac adriamycin responsive protein (CARP) and its underlying mechanisms in DOX-induced cardiotoxicity (DIC). Methods and resultsCardiac-specific CARP transgenic and wild-type mice were subjected to a DIC model. Cardiac function was assessed via echocardiography, histopathology, and transmission electron microscopy (TEM). In vitro, DOX-treated cardiomyocytes overexpressing CARP were analyzed for oxidative stress (ROS levels), mitochondrial function (mtDNA copy number etc.), and mitochondrial-related proteins (Western blot). CARP-NRF1 interaction was validated by co-immunoprecipitation (Co-IP), and NRF1 siRNA knockdown was performed to assess CARPs role in mitochondrial homeostasis. CARP overexpression markedly alleviated DOX-induced cardiac dysfunction and mitochondrial damage, restoring mitochondrial dynamics and mitophagy. Mechanistically, CARP directly interacted with NRF1, and NRF1 knockdown ameliorated CARP-mediated cardioprotection in DIC. ConclusionCARP safeguards against DIC by maintaining mitochondrial homeostasis via NRF1 signaling, positioning it as a promising therapeutic target for DOX-induced cardiomyopathy.

molecular biology↗

bioRxiv2025

Scalable and systematic hierarchical virus taxonomy with vConTACT3

Viruses are key players in diverse ecosystems, but studying their impacts is technically and taxonomically challenging. Taxonomic complexities derive from undersampling, diverse DNA and RNA genomes with multiple evolutionary origins, and lack of a universal barcode gene. While virus ecogenomics has expanded access to and understanding of the virosphere, available classification tools poorly scale to modern discovery-based datasets, lack taxonomic resolution, and/or are unable to classify novel sequence space. Here we develop, benchmark, and release vConTACT3, a machine learning-based tool that improves scalability and accuracy, adds extensive user-requested features, expands classification to both eukaryote and prokaryote viruses for 4/6 officially recognized realms, and establishes accurate hierarchical taxonomy from genus to order. Application to 48,069 public virus genomes provided new taxonomy assignments for thousands of taxa, revealed support for fewer taxonomic ranks than currently available, and systematically identified taxonomically problematic areas across the virosphere.

bioinformatics↗

bioRxiv2025

A multi-tissue atlas of genetic regulatory effects in sheep

Characterizing the impact of genomic variants on genome function and ultimately complex traits in livestock is essential for the development of sustainable precision agriculture and comparative genomics. Here, as part of the Farm animal Genotype-Tissue Expression (FarmGTEx) project, we present the pilot phase of the SheepGTEx resource through analyzing 6,761 RNA-sequencing samples of 51 primary tissues in a multi-breed population of sheep. We identify millions of regulatory variants associated with seven types of molecular phenotypes, and fine-map 322,468 primary and 114,017 non-primary effects, revealing a high degree of regulatory allelic heterogeneity. We systematically characterize the pleiotropic effects of these variants on molecular phenotypes, assess their context-specific regulatory patterns across tissues, breeds, sexes, and developmental stages, as well as explore their evolutionary constraints across mammals. Finally, we demonstrate the substantial potential of the SheepGTEx resource (https://sheepgtex.farmgtex.org), by providing examples of regulatory mechanisms underpinning 34 complex traits, population divergence between European and Asian breeds, and adaptive evolution in sheep over the past ten millennia.

genomics↗

bioRxiv2025

DCBK: A Fragment-Based Hybrid Simulation and Machine Learning Framework for Predicting Ligand Dissociation Kinetics

Predicting small-molecule dissociation kinetics remains challenging due to the high computational cost of simulating rare unbinding events and the limited scalability of existing approaches. Here, we introduce DCBK (Divide-and-Compute Binding Kinetics), a physics-informed, fragment-resolved framework for predicting ligand dissociation across diverse protein-ligand systems. DCBK integrates steered molecular dynamics and umbrella sampling to reconstruct unbinding pathways and free energy profiles, followed by BRICS-based ligand fragmentation. Fragment-level energetic and structural features are combined with machine learning trained on experimental kinetics data, enabling efficient prediction of dissociation rate constant (koff) values. Validation across five protein families demonstrates strong agreement with experiments, with ablation and unseen-target analyses highlighting the contribution of fragment-level features and the frameworks transferability. Importantly, DCBK allows dissociation kinetics to be interpreted in terms of fragment-level contributions, offering mechanistic insight and guiding ligand modification to optimize residence time. This interpretable and extensible framework links molecular structure, energetics, and kinetics, providing actionable insights for lead optimization and rational drug design.

molecular biology↗

bioRxiv2025

CellBin:a generalist framework to process spatial omics data to cell level

Spatial omics has rapidly expanded with increasingly diverse imaging modalities, molecular targets, and chip sizes. However, no general framework currently exists to construct cell level matrices that are robust across platforms and omics types. Here we present CellBin, a universal and scalable frame-work that unifies image stitching, cell segmentation, and spot-to-cell mapping for multiple spatial omics technologies. CellBin integrates a multi-field weighted stitching algorithm for large-area images, a family of U-Net-based models trained across diverse staining modalities, and an optimized computational architecture for high-throughput processing. Across five technological platforms and three omics data types, CellBin achieves robust segmentation and accurate single-cell matrix construction, consistently outperforming seven state-of-the-art methods in F1-score, cell size precision, and annotation accuracy. By providing a generalizable, cross-platform solution, CellBin bridges multiple spatial omics, enabling unified, high-resolution cell level analyses across technologies.

bioinformatics↗