Biology subjects

Qian, C.

Publications and source records attributed to Qian, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Closing the phenotyping gap: non-invasive electromagnetic induction enables high-throughput screening of crop root function in the field

Crop root systems play a critical role in water uptake and yield improvement under drought. However, a lack of methods to measure root system function at scale, particularly in the field, poses significant challenges to explore them in crop improvement programs. To address this bottleneck, we introduce a novel approach to directly screen water uptake and root activity in the field through integrating electromagnetic induction (EMI) sensing, inversion modelling and machine learning. This study was conducted as an on-farm field experiment comprising a factorial combination of 13 sorghum genotypes and three row spacings with three replications. Time-lapse EMI surveys were conducted from flowering to maturity using a customised DualEM-21S sensing system. Artificial neural network models were developed to predict 3D soil moisture ({theta}) using depth-specific true soil electrical conductivity estimated from EMI inversion algorithms, and the prediction accuracy was evaluated. Crop water use and functional root traits were derived from changes in {theta} profiles between successive EMI surveys using cubic splines fitted within a linear mixed model framework. Results indicate that dynamics of {theta} can be predicted with high accuracy (R2 = 0.83). There was a significant positive correlation between the EMI-derived crop water use and root length density at the depths without water stress. The functional root traits were significantly affected by growth stages, genotypes, row spacings, and their interactions. In general, narrower row spacing resulted in deeper rooting depth by flowering, which was associated with a larger canopy and higher grain number. In contrast, wider row spacing promoted greater post-flowering root growth, leading to increased post-flowering water use and, consequently, larger grain weight. Overall, our approach enables rapid characterisation of variation in crop water use, rooting depth and root growth in the field. It provides a valuable framework for understanding the dynamic interactions between root function and yield traits across variable field environments, with potential to accelerate genotype selection and optimise crop design in breeding and agronomy programs.

plant biology↗

bioRxiv2026

Longitudinal diffusion tensor imaging identifies coordinated white matter remodeling during cocaine self-administration in mice

White matter microstructural alterations are increasingly recognized as a feature of cocaine use disorder (CUD), yet the longitudinal progression and biological underpinnings of these changes remain poorly understood. Although rodent intravenous self-administration (IVSA) provides a translational model of voluntary cocaine use, longitudinal diffusion tensor imaging (DTI) has not previously been combined with cocaine IVSA in mice. Here, we established a longitudinal IVSA-DTI framework to characterize white matter microstructural remodeling during cocaine self-administration and early withdrawal. Male C57BL/6 mice underwent DTI at baseline, following 11 consecutive days of cocaine (0.5 mg/kg/infusion) or saline IVSA, and after a 7-day withdrawal period immediately following a cocaine-seeking test (n = 4/group). Fractional anisotropy (FA) was evaluated longitudinally using atlas-based region-of-interest analyses and whole-brain diffusion maps. Cocaine-treated mice acquired robust operant responding and exhibited coordinated longitudinal FA alterations across interconnected hippocampal-associated white matter pathways. The most consistent changes occurred within the bilateral dorsal hippocampal commissure, fornix, and fimbria, with cocaine-treated mice demonstrating increased FA during self-administration relative to baseline while saline controls exhibited smaller or opposing longitudinal changes. Difference-in-differences maps further demonstrated cocaine-associated FA alterations within hippocampal pathways and localized regions of the corpus callosum after accounting for longitudinal changes in saline controls. These findings establish the feasibility of combining longitudinal DTI with cocaine IVSA in mice and demonstrate coordinated white matter microstructural remodeling during voluntary cocaine exposure. This framework provides a translational platform for future studies integrating longitudinal neuroimaging with genetically modified mouse models, tractography, and histological validation to investigate the mechanisms underlying cocaine-associated white matter plasticity.

neuroscience↗

bioRxiv2026

Chronic stress promotes sex-divergent Type 1, 2 and 17 responses in brain resident lymphocytes.

T helper cytokines such as IFN{gamma} and IL-17 are dysregulated in a subset of patients with depression and are associated with poor responses to treatment. Both IFN{gamma} and IL-17 have been shown to regulate neural circuits involved in behavioral changes implicated in depression. However, the cellular source and the regulatory mechanisms governing these cytokines in this context remain incompletely understood. We analyzed brain lymphocytes in response to unpredictable chronic mild stress (UCMS), a model of depression with strong face and construct validity. We confirmed that UCMS induced depressive-like behavior in both male and female mice. Interestingly, UCMS preferentially reduced regional synaptic density in female and neuron counts in male hippocampi. Using single cell RNAseq, we identified T helper cytokine signatures to be enriched in distinct lymphocyte lineages expressing tissue resident markers and are regulated by both sex and chronic stress. Female brain-resident {gamma}{delta}T cells are significantly enriched for type 2 and type 17 signatures and have higher expression of inflammasome genes such as Nlrp3 and Il1b whereas male {beta}T cells and NKT cells are enriched for type 1 signatures and have elevated Cxcr3 and Il27ra expression. Chronic stress amplified the sex differences and preferentially increased the type 1 response including IFN{gamma} production in males at both the transcriptome and protein level. Type 17 response (e.g. IL-17A and IL-17F production) is also increased in response to UCMS, however with sex-divergent polarization: IL-22 is decreased in female and increased in male brain lymphocytes. Mechanistically, we found that UCMS suppressed P4ha1 in male and Zfp36 in female brain tissue resident lymphocytes. P4HA1 was previously shown to restrict mitochondrial function and limit type 1 responses in CD8 T cells, whereas ZFP36 is a suppressor of inflammatory cytokine translation. Consistent with this finding, ex vivo CD3-dependent stimulation of brain immune cells showed stress-dependent increase in cytokine production with sex-specific effects. Our study provides the cellular and molecular framework for chronic stress-induced tissue resident lymphocyte dysregulation and its sex bias in the brain, with implications for depressive disorders marked by inflammation.

immunology↗

bioRxiv2026

scMaize: A Single-Cell Foundation Model and Integrated Atlas for Maize

Single-cell transcriptomics has resolved cell-type-specific gene expression in plants, yet maize still lacks an integrated reference and species-specific foundation models. We present scMaize, combining scMaizeAtlas, an integrated atlas of 385,675 cells from 20 projects and 66 samples across seven tissues with hierarchical annotation, with two Transformer-based foundation models pretrained on this atlas. scMaizeExp serves as an expression-only baseline, while scMaizeGO incorporates Gene Ontology (GO) functional embeddings as an inductive bias. Although global expression-prediction accuracy was comparable, the GO prior improved rank-order prediction, strengthened attention toward functionally coherent gene modules, and enhanced embedding topology, with scMaizeGO achieving 86.0% cell-type and 97.1% tissue classification accuracy. Zero-shot evaluation demonstrated the cross-species generalizability of scMaizeGO representations, and few-shot fine-tuning enabled accurate cross-species classification with minimal labeled data. Root perturbation-condition analysis showed that the model encoded treatment-specific cellular states beyond cell-type identity, with the GO prior amplifying perturbation signals approximately threefold. Expression projection identified condition-responsive genes enriched for known stress pathways, and attention analysis revealed predominantly condition-specific changes in gene-gene attention that were weakly associated with expression-projection changes. An online platform (https://www.scmaize.com) provides atlas exploration, model access, and zero-code analysis tools. scMaize establishes a framework demonstrating that species-specific pretraining with functional priors enables transferable, perturbation-aware representations for crop single-cell genomics.

plant biology↗

bioRxiv2026

Validation of MHPC512: A Publicly Available Special-Purpose Supercomputer for Molecular Dynamics Simulations of Biomolecular Systems

MHPC512 is a massively parallel, special-purpose supercomputer designed primarily for atomic-level molecular dynamics (MD) simulations of biomolecular systems. It comprises 512 processor units interconnected by a high-speed three-dimensional torus network and employs a custom chip architecture that uses 35-bit fixed-point arithmetic to accelerate computation while controlling precision loss within an acceptable margin. The preprocessor is compatible with GROMACS and AMBER input formats and supports widely used biomolecular force fields (including CHARMM, AMBER, and OPLS/AA), the Neutral Territory method for short-range nonbonded interactions, the k-space Gaussian Split Ewald method for long-range electrostatics, and multiple thermostats, barostats, and integrators. We present a three-tier validation protocol--comparing static energy and virial components, examining ensemble distributions (NVE, NVT, NPT), and evaluating long-time statistical properties--demonstrating that MHPC512 reproduces results consistent with GROMACS and AmberTools. Application examples, including bulk water, dipeptide conformational sampling, folding of fast-folding peptides, membrane-protein systems, lipid self-assembly, and GPCR conformational transitions, further confirm its reliability. MHPC512 has been deployed at multiple supercomputing centers and is publicly accessible, representing a significant advance in high-throughput, large-scale biomolecular MD simulations.

Molecular Biology↗

bioRxiv2026

Addiction-Like Severity Predicts Prolonged Oxycodone Withdrawal-Induced Allodynia in Genetically Diverse Rats

Opioid withdrawal is associated with heightened pain sensitivity, including allodynia. Although opioid-induced allodynia is well-documented in humans and animal models, the relationship between the severity of opioid withdrawal-induced allodynia and individual addiction-like behaviors remains poorly understood. To address this gap, Heterogeneous Stock rats underwent long access (12 hours/day) intravenous oxycodone self-administration, followed by measurement of mechanical sensitivity at six timepoints across three weeks of abstinence. Rats were stratified by an Addiction Index derived from individual differences in the escalation of oxycodone intake, motivation to consume oxycodone, tolerance to oxycodones analgesic effects, and acute withdrawal-induced mechanical pain sensitivity. Here, we show that oxycodone withdrawal induces significant and prolonged allodynia for up to three weeks, with High Addiction Index rats exhibiting greater intensity and longer duration of pain sensitivity than Low Addiction Index rats. Results remained consistent even when excluding allodynia from the Addiction Index, highlighting the robustness of the association between addiction-like severity and protracted allodynia. Linear regression associations revealed that self-administration behaviors, particularly oxycodone intake escalation and motivation to seek oxycodone, predicted subsequent withdrawal-induced allodynia severity. These findings demonstrate that greater addiction-like severity is associated with more intense and prolonged withdrawal-induced pain, supporting mechanical allodynia as a marker of addiction severity. These results motivate future work to define the mechanisms linking addiction severity to protracted opioid withdrawal-induced pain, with the goal of informing targeted clinical interventions for individuals most susceptible to severe abstinence-related allodynia.

pharmacology and toxicology↗

bioRxiv2026

High-Field Multinuclear MRI Reveals Sodium Relaxation Heterogeneity in Cortical Organoids

Sodium magnetic resonance imaging (23Na MRI) provides a unique opportunity to probe ionic microenvironments in neural tissue because sodium ions play central roles in membrane electrophysiology, ion transport, and cellular homeostasis. Unlike conventional proton ({superscript 1}H) MRI, which primarily reflects water distribution and tissue structure, {superscript 2}3Na MRI is sensitive to ionic compartmentation and quadrupolar interactions arising from the spin-3/2 nature of the sodium nucleus. However, sodium MRI remains technically challenging due to intrinsically low signal sensitivity and rapid biexponential relaxation, particularly when imaging small biological systems. Here, we establish a high-field multinuclear MRI platform for imaging human cerebral organoids at 14 Tesla. Cerebral organoids derived from human induced pluripotent stem cells provide a simplified three-dimensional neural tissue model that enables investigation of ionic microenvironments without vascular or systemic confounds. Using a dual-tuned {superscript 1}H/{superscript 2}3Na radiofrequency coil, we performed co-registered structural, diffusion, and sodium imaging of individual fixed organoids. High-resolution {superscript 1}H MRI (33-100 m) revealed pronounced microstructural heterogeneity, while multi-echo {superscript 2}3Na MRI (300-400 m) enabled voxel-wise characterization of quadrupolar relaxation behavior. Bi-exponential analysis of the sodium signal decay identified distinct relaxation components (T2*short {approx} 1 ms and T2*long {approx} 12 ms) and revealed spatial heterogeneity in sodium microenvironments across the organoid tissue. These results demonstrate the feasibility of quantitative sodium relaxometry in cortical organoids and establish a multinuclear imaging platform for investigating ionic microenvironment dynamics in three-dimensional neural tissue models.

bioengineering↗

bioRxiv2026

Discovery and Biosynthesis of Nitrilobacillins by Post-translational Introduction of C-Terminal Nitrile Groups

Nitrile-containing natural products are produced in all kingdoms of life. Despite the wide application of nitrile-containing peptide scaffolds in medicinal chemistry, the presence of the nitrile group is unprecedented in ribosomally synthesized and post-translationally modified peptides (RiPPs). In this work, we report the identification and characterization of a RiPP biosynthetic gene cluster (BGC), where an asparagine synthetase-like (AS-like) protein encoded in the BGC converts the C-terminal carboxylate of the precursor peptide to a nitrile. Furthermore, a multinuclear nonheme iron-dependent oxidative enzyme (MNIO) and an -ketoglutarate-dependent HExxH motif-containing enzyme (KG-HExxH) perform stereoselective {beta}-hydroxylation of aspartate and proline residues, respectively. Structure prediction-guided mechanistic evaluation of the nitrile synthetase provided insights into the possible mechanism of catalysis. These findings extend our understanding of the structural diversity of RiPPs and demonstrate the catalytic versatility of AS-like enzymes in natural product biosynthesis.

biochemistry↗

bioRxiv2026

Development of a genetically encoded fluorescent indicator for facilitating deorphanization of GPR52

GPR52 is an orphan G protein-coupled receptor implicated in psychiatric and neurodegenerative disorders, but its endogenous ligand remains unidentified, limiting the exploration of its physiological functions and therapeutic potential. We pioneered a novel methodology for orphan GPCR ligand discovery utilizing the GPCR-activation-based (GRAB) strategy by developing GPR52-1.0, a genetically encoded fluorescent sensor. GPR52-1.0 exhibits excellent membrane trafficking and high sensitivity in HEK293T cells, cultured neurons, and acute mouse brain slices. Notably, it detects neuronal activity-dependent endogenous ligand release in the striatum, with responses abolished by a specific antagonist. This sensor provides a powerful tool for identifying GPR52s endogenous ligand(s) and enables real-time monitoring of its activation. Our work lays the foundation for uncovering GPR52s physiological roles and supports future efforts to develop GPR52-targeted therapeutics.

neuroscience↗

bioRxiv2026

Targeting FGFR signaling overcomes therapeutic resistance and immune evasion in oncogenic PIK3CA-driven serous-like endometrial cancer

Serous endometrial cancer (SEC) is an aggressive subtype of endometrial cancer (EC) with poor prognosis and limited treatment options. Here, we developed a clinically relevant, immunocompetent serous-like mouse model incorporating oncogenic PIK3CA mutation, Trp53 loss, and MYC overexpression. Using this model together with human EC cell lines, patient-derived organoids (PDOs), xenografts, and patient datasets, we investigated mechanisms underlying resistance to PI3K-targeted therapy. Single-cell profiling reveals that FGFR1/2 upregulation associates with intrinsic resistance, whereas FGFR3 characterizes acquired resistance. Dual FGFR and PI3K inhibition produced superior tumor control compared with either agent alone. Mechanistically, FGFR signaling promotes immune evasion by downregulating MHC-I/HLA-mediated antigen presentation and enriching M2-type tumor-associated macrophages. FGFR inhibition reversed these changes and synergized with anti-PD-1 therapy to enhance antitumor immune responses and establish durable immune memory. Collectively, these findings identify FGFR signaling as a key driver of therapeutic resistance and immune escape in SEC and support FGFR-targeted combination strategies.

cancer biology↗

bioRxiv2026

3D Cell-Matrix Mechanical Interaction Models for Cancer Invasion and Drug Evaluation

Cancer cells breach the extracellular matrix (ECM) using both protease-driven degradation and force-driven physical remodeling, yet most anti-metastatic drug screens still rely on biochemical assays that overlook cell-matrix mechanical reciprocity. Here, we present a fully synthetic 3D invasion platform based on cellular force-responsive polyisocyanide (PIC) hydrogels that isolates biophysical invasion mechanisms. Cell-generated forces align and densify the PIC fibrous network, reproducing hallmark matrix remodeling seen in the tumor microenvironment. A constitutive model, parameterized by the critical stress for strain stiffening effect, links matrix nonlinear elasticity to pericellular stiffening, long-range mechanotransmission, and intercellular coupling. Using this system, we show that breast cancer cells invade by pulling and pushing the network even when matrix metalloproteinases are inhibited, revealing a physical bypass of protease blockade. Accordingly, broad-spectrum metalloproteinase inhibitors that suppress invasion in Matrigel fail to inhibit invasion here, exposing a limitation of current drug-evaluation pipelines. In co-culture, cancer-associated fibroblasts markedly accelerate invasion by generating aligned fiber tracks through higher contractility, implicating CAF-driven mechanical remodeling as a key route for breaching barriers during metastasis. The platform is thermoresponsive, compatible with standard Transwell formats, enables direct imaging of fiber architecture and invasion fronts, and decouples biophysical from biochemical cues for mechanism-aware, animal-free assessment of anti-metastatic therapies.

cancer biology↗

bioRxiv2026

Targeting PI3Kβ-dependent cancer with a novel small molecule inhibitor, GT220

PI3K{beta} is a critical oncogenic driver in cancers harboring PTEN loss or PIK3CB alterations, yet effective and selective PI3K{beta}-targeted therapies remain elusive. Here, we report the development and preclinical characterization of GT220, a highly selective and potent small-molecule PI3K{beta} inhibitor developed through integrated artificial-intelligence-driven design with medicinal chemistry and pharmacologic optimization. GT220 exhibits exceptional biochemical selectivity for PI3K{beta}, binding with sub-nanomolar affinity and with minimal activity against other class I PI3K isoforms or the broader protein kinome. In cellular models, GT220 potently suppresses AKT phosphorylation and selectively inhibits viability of PTEN-deficient cancer cells, while sparing PTEN/PIK3CB wild-type and PI3K-dependent cells. In vivo, GT220 achieves a favorable tumor exposure with sustained PI3K{beta} pathway inhibition and demonstrates robust antitumor efficacy and good tolerability in PTEN-deficient breast cancer xenograft models. In contrast, GT220 shows no antitumor activity or pathway inhibition in PTEN-wild-type or PI3K-dependent tumors, underscoring its context-dependent mechanism of action. Collectively, these findings establish GT220 as a promising next-generation PI3K{beta} inhibitor and provide a strong preclinical rationale for precision targeting of PI3K{beta}-dependent cancers.

cancer biology↗

bioRxiv2025

Labile iron overload reprograms microglia and neurons for lipid droplet synthesis in the aging brain

Lipid-droplet (LD) accumulation emerges in microglia and neurons with age. Because neither cell type is specialized for lipid storage, LDs are linked to dysfunction. The upstream drivers of LD formation and their effects on neighboring cells remain unclear. Here, we identify a mitochondrial-iron axis that promotes LD formation in aging microglia via reactive oxygen species (ROS), which secondarily reshapes neuronal iron handling. LD-enriched microglia show reduced mitochondrial mass and increased labile iron, ROS, and lipid peroxidation. Chelating labile iron or scavenging ROS suppresses LD formation. Conditioned media from iron-stressed microglia alter neuronal iron homeostasis, indicating transcellular coupling. In primary neurons, iron overload increases LDs and activates coordinated iron, ROS, and lipogenesis programs, whereas antioxidant treatment attenuates iron-driven LD accumulation. Together, these findings position iron overload as an upstream regulator of ROS-dependent LD biogenesis in microglia and neurons and reveal a microglia-neuron axis that regulates neuronal iron metabolism during aging.

immunology↗

bioRxiv2025

TMEM100 attenuates NF-κB activation via disrupting the PRDX1-GNAI2 complex to alleviate acute lung injury

Acute lung injury (ALI) is a severe and diffuse inflammatory disorder of interstitial lung. Emerging evidence suggests that TMEM100 is closely associated with lung development and function. However, its role in ALI remains unclear. In this study, we observed a significant downregulation of TMEM100 expression in both mouse lung tissues with ALI and lipopolysaccharide (LPS)-induced pulmonary vascular endothelial cells (PVECs). Overexpression of TMEM100 markedly attenuates LPS-induced lung injury and inflammation, while also restoring the imbalance between proliferation and apoptosis in PVECs. Mechanistically, TMEM100 interacts with both PRDX1 and GNAI2, disrupting the PRDX1-GNAI2 complex and thereby inhibiting LPS-induced NF-{kappa}B activation, which contributes to its anti-inflammatory effects. These findings highlight the protective role of TMEM100 in endotoxin-induced ALI and provide a theoretical basis for understanding its biological functions and potential applications in ALI gene therapy.

immunology↗

bioRxiv2025

A human arteriovenous differentiation roadmap reveals vein developmental mechanisms and vascular effects of viruses

Extracellular signals and cell-fate trajectories during vein development remain elusive, despite trailblazing insights into artery development. Here we exploit human pluripotent stem cell differentiation and mouse embryology to present a model that answers longstanding questions: vein endothelial cell (EC) differentiation unfolds in two steps driven by opposing extracellular signals. First, VEGF differentiates mesoderm into "primed" ECs, newly-defined progenitors that co-express certain arterial (SOX17) and venous (APLNR) markers. Second, primed ECs execute vein differentiation upon VEGF/ERK inhibition; however, upon VEGF activation they can instead form artery ECs. The arteriovenous plasticity of primed ECs was supported by intersectional lineage tracing. Future venous genes including NR2F2 harbor poised chromatin in primed ECs, but are only transcribed upon VEGF/ERK inhibition. SOXF transcription factors, including SOX17, confer primed ECs with vein differentiation competence. Collectively, this two-step vein differentiation model--entailing primed EC intermediates and VEGF/ERK inhibition to trigger vein differentiation--has implications for VEGF-modulating therapies.

developmental biology↗

bioRxiv2025

A systematic review of climate-change driven range shifts in mosquito vectors

As global temperatures rise, concerns about shifting mosquito ranges--and accompanying changes in the transmission of malaria, dengue, and other diseases--are mounting. However, systematic evidence for climate-driven changes in mosquito ranges remains limited. We conducted a systematic review of studies documenting expansions or contractions in medically important mosquito species. In total, 178 studies on six continents identified range expansions in 118 mosquito species. While over a third of these studies cited warming as a driver, fewer than 10% performed statistical tests of the role of climate. Instead, most expansions were linked to human-aided dispersal (e.g., trade, travel), land-use changes, and urbanization. Although several studies reported poleward or upward expansions consistent with climate warming, none demonstrated warm-edge contractions driven by rising temperatures, which are theoretically predicted in some settings. Rather than expanding into newly suitable areas, many expansions appear to be filling preexisting thermally suitable habitats. Our findings highlight the need for long-term mosquito monitoring, rigorous climate-attribution methods, and better documentation of confounding factors like land-use change and vector control efforts to disentangle climate-driven changes from other anthropogenic factors.

ecology↗

bioRxiv2025

Lignature: A Comprehensive Database of Ligand Signatures to Predict Cell-Cell Communication

Ligand-receptor interactions mediate intercellular communication, inducing transcriptional changes that regulate physiological and pathological processes. Ligand-induced transcriptomic signatures can be used to predict active ligands; however, the absence of a comprehensive set of ligand-response signatures has limited their practical application in predicting ligand-receptor interactions. To bridge this gap, we developed Lignature, a curated database encompassing intracellular transcriptomic signatures for 362 human ligands, significantly expanding the repertoire of ligands with available intracellular response signatures. Lignature compiles signatures from published transcriptomic datasets and established resources such as CytoSig and ImmuneDictionary, generating both gene- and pathway-based signatures for each ligand. We applied Lignature to predict active ligands driving transcriptomic changes in controlled in vitro experiments and real-world single-cell sequencing datasets. Lignature outperformed existing methods such as NicheNet, achieving higher accuracy in identifying active ligands at both the gene and pathway levels. These results establish Lignature as a robust platform for ligand signaling inference, providing a powerful tool to explore ligand-receptor interactions across diverse experimental and physiological contexts.

bioinformatics↗

bioRxiv2025

MetaLigand: A database for predicting non-peptide ligand mediated cell-cell communication

Non-peptide ligands (NPLs), including lipids, amino acids, carbohydrates, and non-peptide neurotransmitters and hormones, play a critical role in ligand-receptor-mediated cell-cell communication, driving diverse physiological and pathological processes. To facilitate the study of NPL-dependent intercellular interactions, we introduce MetaLigand, an R-based and web-accessible tool designed to infer NPL production and predict NPL-receptor interactions using transcriptomic data. MetaLigand compiles data for 233 NPLs, including their biosynthetic enzymes, transporter genes, and receptor genes, through a combination of automated pipelines and manual curation from comprehensive databases. The tool integrates both de novo and salvage synthesis pathways, incorporating multiple biosynthetic steps and transport mechanisms to improve prediction accuracy. Comparisons with existing tools demonstrate MetaLigands superior ability to account for complex biogenesis pathways and model NPL abundance across diverse tissues and cell types. Furthermore, analysis of single-nucleus RNA-seq datasets from age-related macular degeneration samples revealed that distinct retinal cell types exhibit unique NPL profiles and participate in specific NPL-mediated pathological cell-cell interactions. Finally, MetaLigand supports single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics data, enabling the visualization of predicted NPL production levels and heterogeneity at single-cell resolution.

bioinformatics↗