Biology subjects

Xie, W.

Publications and source records attributed to Xie, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Endosperm secretion remodels the maternal seed coat

In flowering plants and mammals, maternal tissues must accommodate the growth of the offspring they enclose. The maternal seed coat expands around the developing embryo and endosperm. Endosperm pressure and hormonal signals coordinate seed-coat development1,2, but whether the endosperm directly promotes maternal cell elongation remains unclear. Here we show that the coenocytic Arabidopsis endosperm directly supplies cell-wall-loosening proteins to maternal seed-coat walls. The seed-size-regulating HAIKU-WRKY10 pathway activates an endosperm secretory programme enriched in cell-wall-associated proteins. These proteins spread through a shared extracellular domain across multiple inner seed-coat layers, revealing an extensive functional maternal-filial interface through which the endosperm reaches maternal cells it does not directly contact. Among these proteins, three expansins are necessary and sufficient for maternal cell elongation and seed growth. The endosperm therefore promotes its own growth by enabling expansion of the maternal tissues that enclose it. Paternal DNA methylation and maternal Polycomb activity jointly regulate this programme, with Polycomb also required for timely shutdown of expansin expression. These findings link parental epigenetic states to maternal tissue expansion through proteins supplied by the offspring. This cross-generational control of growth parallels epigenetically regulated signaling from mammalian extraembryonic tissues3, suggesting a shared strategy for adapting the maternal environment to offspring development.

plant biology↗

bioRxiv2026

Creator 1.0: Phylogeny-Guided Stagewise Pretraining for Plant Genome Foundation Models across 1,000 Species

Genomic language models have advanced DNA sequence analysis, but their applicability to plant-specific tasks and representation changes during pretraining remain poorly characterized. Here, we present Creator 1.0, a 2-billion-parameter parameter plant genome foundation model pretrained on 1,000 plant genomes using phylogeny-guided stagewise pretraining (PGSP). Training comprised 83 consecutive stages and produced 52 cumulative checkpoints associated with distinct plant orders. On GENEB, the stage 83 checkpoint ranked first among 46 models across 10 plant-related tasks, with a mean Matthews correlation coefficient (MCC) of 0.565, and fourth across all 100 tasks. Evaluation of 52 checkpoints on six plant lncRNA tasks identified different optimal stages under full-data, 10-shot and 1-shot settings, corresponding to stages 71, 72 and 29, respectively. Checkpoint performance varied across tasks, without consistent advantages for corresponding plant orders. These findings demonstrate the competitive performance of Creator 1.0 and highlight the potential of PGSP to provide task-adaptable checkpoints for plant genomic applications.

genomics↗

bioRxiv2026

Fine-tuning an intracellular allosteric pocket programs GPCR signaling bias

Biased signaling of G protein-coupled receptors (GPCRs) offers a route for precise therapeutics with fewer adverse effects. Intracellular allosteric ligands can impose such bias, yet how subtle chemical changes within these pockets reshape receptor-transducer coupling and downstream signaling remains unclear. Here, we systematically fine-tuned the intracellular allosteric pocket of neurotensin receptor 1 (NTSR1) through chemical modification of the {beta}-arrestin-biased ligand SBI-553. Minor changes to the ligand scaffold altered transducer-coupling preferences, generating distinct profiles of G-protein and {beta}-arrestin signaling. Cryo-electron microscopy structures of NTSR1-{beta}-arrestin2 complexes bound to designed allosteric probes revealed ligand-dependent remodeling of the intracellular cavity that reshapes the receptor-effector interface. Alanine scanning identified transducer-sensitive residues within and beyond the immediate ligand-contact region. In mice, SBI-553 and N065 produced distinct physiological profiles, with N065 improving survival in a lethal endotoxemia model. Finally, phosphoproteomic profiling revealed partially overlapping but distinct downstream signaling profiles among the three modulators. Together, these findings establish the intracellular allosteric pocket as a tunable determinant of transducer coupling and show that closely related modulators can generate distinct signaling and physiological profiles.

pharmacology and toxicology↗

bioRxiv2026

Median Preoptic Brs3-Expressing Neurons Regulate Heat-Evoked Defensive Escalation

Animals confronted with increasing heat must switch from exploratory behavior to vigorous actions that limit further exposure, but the forebrain circuits controlling this transition are poorly understood. We exposed male mice to progressively stronger floor heating while providing continuous access to a climbing mesh separated from the heating plate. Higher plate settings shifted behavior from rearing toward wall-directed digging and climbing, with jumping at the highest setting, and increased c-Fos labeling in the median preoptic nucleus. Neurons expressing bombesin receptor subtype 3 showed greater c-Fos recruitment under strong heating, and their population calcium signals increased when mice entered the plate-controlled zone and decreased when they left. Optogenetic activation without heating produced place avoidance, vigorous actions, and increased locomotion. Inhibition reduced locomotion and, during strong heating, shifted behavior from climbing and jumping toward rearing and weakened avoidance of a localized heat source. These findings identify median preoptic Brs3-expressing neurons as regulators of behavioral escalation and heat avoidance.

neuroscience↗

bioRxiv2026

Seasonal influenza vaccine strain selection by quantifying viral fitness

The long-standing challenge of seasonal influenza vaccines providing poor protection is attributed to the rapid and continuous evolution of the virus. In theory, the recommendation of vaccine strain is to predict the dominant strain with best fitness in the upcoming season. Here, we develop FutureFlu, a biologically-grounded framework that quantifies the fitness score of influenza variants in upcoming seasons, by integrating metrics on three levels: molecular genetic divergence, individual immune escape, and population-scale transmission dynamics. The fitness scores of influenza variants present strong positive correlation with their actual observed frequencies in the next seasons. Validation across 24 seasons of three influenza subtypes shows FutureFlu recommends antigenically matched vaccine strains more frequently than annual recommendations, particularly for challenging subtypes: 83.3% versus 45.8% seasons for A/H3N2, and 75.0% versus 33.3% seasons for B/Victoria. Furthermore, FutureFlu significantly outperforms the currently used methods in vaccine strain selection whether or not there is available antigenic data from hemagglutination inhibition (HI) assay, which provides a valuable supplement for WHO vaccine recommendation. To support global public health implementation, an open online platform (futureflu.com.cn) has been established to offer real-time viral fitness predictions and vaccine recommendations.

evolutionary biology↗

bioRxiv2026

ASOCompass: Context- and Chemistry-Aware Activity Prediction for Transferable Antisense Oligonucleotide Screening

Antisense oligonucleotide (ASO) activity is jointly influenced by nucleotide sequence, chemical modification, target-RNA context, dose, delivery protocol, and cellular environment. Most existing computational screening methods model only a subset of these factors, limiting their ability to predict experimentally measured activity across heterogeneous screening conditions and previously unseen biological contexts. We introduce ASOCompass, a context-and chemistry-aware framework for ASO activity prediction and candidate ranking. ASOCompass integrates contextualized ASO and target-RNA sequence representations with position-specific molecular representations of chemical modifications. It further incorporates dose and delivery information together with prototype-adapted transcriptomic representations of target genes and cell lines. To encourage chemically and biophysically informative representations, the model is jointly trained on auxiliary molecular-property and sequence-derived thermodynamic prediction tasks. We evaluate ASOCompass on ASO Atlas, a large patent-derived dataset of RNase H-mediated gapmer ASOs, under held-out drug, target-gene, cell line, and joint gene-cell line settings. ASOCompass achieves an overall Spearman correlation of 0.5970, improving over the strongest ASO-specific baseline by 0.0421, and consistently performs best across all four distribution shifts. When adapted to unseen SOD1 and KLKB1 targets, ASOCompass also provides more accurate candidate ranking across different annotation budgets, reaching correlations of 0.830 and 0.696 with 1,024 target-specific labels. Additional analyses suggest that molecular-property supervision improves modification-specific ranking, while the auxiliary thermodynamic task produces representations more closely aligned with measured inhibition. These results demonstrate the potential of jointly modeling sequence, chemistry, and experimental-biological context for transferable ASO screening.

bioinformatics↗

bioRxiv2026

GAMETE maps the genetic architecture of chromatin accessibility in rice pollen at single-nucleus resolution

BackgroundDissecting the genetic basis of cell-type-specific gene regulation during gametogenesis remains a major challenge. Population-level studies mask cellular heterogeneity, while the extreme data sparsity of single-cell profiling has precluded robust genetic mapping. ResultsWe present GAMETE (Genetic Architecture Mapping of Epigenetic Traits at single-nucleus resolution), an integrated framework combining MPS-ATAC-seq, a high-throughput single-nucleus ATAC-seq method, with robust computational approaches for genotype inference and genetic mapping from sparse single-nucleus data. Applying GAMETE to hybrid rice pollen, we simultaneously profiled chromatin accessibility and inferred the genotypes of 4,887 individual haploid nuclei, revealing distinct chromatin landscapes across pollen cell types. This uncovered an unexpected elevation of chromatin accessibility at gypsy retrotransposons in microspores preceding their silencing in sperm cells, exposing a surveillance gap that may contribute to genome expansion. The synchronized profiling enabled us to construct a single-cell recombination map, map segregation distortion loci and trace their developmental origins, and identify 16,113 chromatin accessibility QTLs (caQTLs), 48.6% of which exhibited pronounced cell-type specificity. Analysis of introgression lines supported a cell-type-specific trans-acting caQTL regulating the pollen-essential gene DTM1. ConclusionsThis work establishes GAMETE as a broadly applicable framework for dissecting the genetic architecture of chromatin accessibility during gametogenesis without the need for subsequent generations.

genomics↗

bioRxiv2026

Seeing the world in a grain of sand: Fine global and local representations in foveal and parafoveal vision

Foveal vision enables primates to perceive small objects with remarkable precision by resolving both fine-global form and fine-local detail. Yet current coarse-to-fine and local-to-global frameworks, derived largely from parafoveal recordings and large-object representations, posit that V1 encodes local detail whereas IT represents global form, leaving the neuronal basis of foveal object representation unresolved. Here we show that fine-global form and fine-local detail are encoded parallelly as early as V1 and preserved across V2, V4 and IT at both foveal (1{degrees}-2{degrees}) and parafoveal (2{degrees}-6{degrees}) retinal eccentricities. Coarse-global features dominate parafoveal vision and higher cortical areas. Response latencies revealed a rapid processing sequence, with 2-6 ms separating coarse-global, fine-local, and fine-global processing within parafoveal V1, V2 and V4. These findings establish a cortical neuronal framework to resolve fine-global form of small objects in foveal vision along primate ventral visual stream, supporting fine-scale perception during reading and fine object recognition. Highlights O_LIFoveal two-photon imaging across V1, V2, V4, and IT C_LIO_LIGlobal and local processing examined across eccentricity C_LIO_LIFine and coarse global representations emerge as early as V1 C_LIO_LIFine global and local representations are preserved from V1 up to IT C_LIO_LITightly timed coarse-to-fine-to-fine processing within each cortex C_LIO_LIFast coarse-global dominates parafoveal and higher cortical areas C_LI

neuroscience↗

bioRxiv2026

Experience shapes infants' electrophysiological responses to faces from 3 to 9 months

The types of faces that infants see impact their developing ability to engage with and individuate people from familiar and unfamiliar social groups, a phenomenon known as perceptual narrowing. However, the neural mechanisms that underlie infants processing of different faces as a function of experience remain poorly understood. To address this gap, the present study analyzes electroencephalography data collected while 3-month-olds (N=24), 6-month-olds (N=26), and 9-month-olds (N=18) viewed female and male faces of a familiar or unfamiliar social group. Infants neural responses to faces differed by group familiarity from 3 months of age, with increased responses to the more familiar face types in early components (P1, N290), and to the more unfamiliar face types in later components (P400, Nc). Face sex and group familiarity interacted to shape N290 and P400 amplitudes at 3- and 9-months. Specifically, N290 amplitudes were greater in response to female faces of a familiar group at 3 months, and to male faces of a familiar group at 9 months. In contrast, P400 amplitudes were greater in response to male faces of an unfamiliar group at 3 months old, and greatest in response to both female faces of a familiar group and to male faces of an unfamiliar group at 9 months. Source reconstruction of the Nc revealed greater reconstructed current density in response to faces of an unfamiliar social group across all ages. These findings contribute to a growing body of knowledge examining how perceptual experiences shape infants understanding of their social world.

neuroscience↗

bioRxiv2026

High-throughput, organ-scale 3D tubule tracking using TubuleMAP

Advances in tissue clearing and lightsheet microscopy enable mesoscale imaging of intact and convoluted tubular networks, yet analytical tools to map tubule continuity and assess injury patterns within and across tubules are limited. Here, we introduce TubuleMAP, a semi-automated pipeline for 3D tubule tracking and reconstruction that adapts to various morphological and staining patterns, leverages parallel processing of terabyte-scale data for large-scale analysis of tubular networks, and uses a napari interface for human oversight. Using TubuleMAP, we reconstruct 1,000 intact mouse nephrons in [~]1-millimeter-thick kidney slab with [~]400-fold higher throughput and <1% human effort compared to prior approaches. These reconstructions enable analysis of mesoscale nephron organization, quantitative profiling of pathologic morphologies, whole-nephron cytometry, and identification of rare morphologies at unprecedented scales. We demonstrate generalizability by reconstructing all seminiferous tubules in a mouse testis within a day. TubuleMAP is released as an open-source Python package.

bioengineering↗

bioRxiv2026

A Long-Context Generative Foundation Model Deciphers RNA Design Principles

Programmable design of RNA sequences with defined functions remains a central challenge in biology. Despite recent advances, existing RNA generative models lack robust controllable design capabilities and are constrained by short context windows, limiting their capacity to model the complex evolutionary manifold of full-length transcripts. Here, we introduce EVA (Evolutionary Versatile Architect), a long-context generative RNA foundation model trained on over 114 million full-length RNA sequences spanning the full breadth of evolutionary diversity. By integrating a Mixture-of-Experts architecture with an 8,192-token context window, EVA learns a unified, evolution-consistent representation of RNA sequence space that captures both global transcript structure and fine-grained functional elements. EVA establishes a unified framework for a broad spectrum of RNA design tasks within a single architecture, ranging from mutational fitness prediction to context-aware sequence engineering. We demonstrate EVAs versatility through the de novo design and targeted optimization of diverse RNA classes, including tRNAs, aptamers, and CRISPR guide RNAs, as well as mRNA and circular RNA therapeutics. In systematic evaluations, EVA achieves state-of-the-art performance across seven of nine established benchmarks, improving structural modeling accuracy by up to an order of magnitude compared to existing approaches. EVA is fully open-source at the following repository: https://github.com/GENTEL-lab/EVA.

molecular biology↗

bioRxiv2026

3D chromatin compartment of round spermatids encodes the spatiotemporal program of histone-to-protamine exchange in spermiogenesis

Sperm formation requires a radical chromatin reorganization, where nucleosomes are replaced by transition proteins (TNPs) and subsequently by protamines (PRM1 and PRM2). Although essential for fertility, the regulatory logic governing this exchange is unknown, but its presumed to be stochastic and unregulated. Using endogenously tagged PRM mouse models and stage-resolved, genome-wide profiling, we revise the order of histone-to-protamine exchange and show that the chromatin remodeling process is highly programmed. Imaging and biochemical experiments reveal a direct histone-to-PRM1 exchange, while TNPs appear after PRM1 but precede PRM2 incorporation. This temporal uncoupling of PRM1 and PRM2 incorporation coincides with dynamic, region-specific chromatin remodeling that is not governed by histone acetylation but is instructed by the three-dimensional nuclear architecture of round spermatids. Therefore, by integrating ATAC-seq, CUT&Tag, and Hi-C, we define a compartment-encoded "blueprint" that prescribes the assembly of the mature sperm epigenome and establishes a complex molecular hierarchy for the histone-to-protamine exchange.

genomics↗

bioRxiv2026

Phenotypic Bioactivity Prediction as Open-set Biological Assay Querying

The traditional drug discovery pipeline is severely bottlenecked by the need to design and execute bespoke biological assays for every new target and compound--a process that is both time-consuming and prohibitively expensive. While machine learning has accelerated virtual screening, current models remain confined to "closed-set" paradigms, unable to generalize to entirely novel biological assays without target-specific experimental data. Here, we present OpenPheno, a groundbreaking multimodal foundation model that fundamentally redefines bioactivity prediction as an open-set, visual-language question-answering (QA) task. By integrating chemical structures (SMILES), universal phenotypic profiles (Cell Painting images), and natural language descriptions of biological assays, OpenPheno unlocks the highly coveted "profile once, predict many" paradigm. Instead of conducting countless target-specific wet-lab experiments, researchers only need to capture a single, low-cost Cell Painting image of a novel compound. OpenPheno then evaluates this universal phenotypic "fingerprint" against the text-based description of any unseen assay, predicting bioactivity in a zero-shot manner. On 54 entirely unseen assays, it achieves strong zero-shot performance (mean AUROC 0.75), exceeding supervised baselines trained with full labeled data, and few-shot adaptation further improves predictions. In the most stringent setting where both compounds and assays are novel, OpenPheno maintains robust generalization (mean AUROC 0.66), opening up a new paradigm for a highly scalable, cost-effective, and universal engine for next-generation drug discovery.

bioinformatics↗

bioRxiv2026

Spatial Mechanomics for Tissue-Scale Biomechanical Mapping and Multi-omics Integration

Tissue mechanical properties are spatially heterogeneous and tightly coupled to cellular function, developmental patterning, and disease progression, yet spatially resolved characterization of viscoelastic and microrheological behavior across intact tissues remains limited. Here we introduce spatial mechanomics, a framework for tissue-wide acquisition, quantitative extraction, and computational representation of location-resolved mechanical states. Using BioAFM-based spatial sampling with multi-protocol microrheology, we acquire force responses at defined tissue coordinates and fit physically interpretable viscoelastic models to extract elastic, viscous, and frequency-dependent parameters at each position. These parameters are assembled into per-niche mechanomic feature vectors and reconstructed into tissue-scale mechanomic atlases that resolve heterogeneous mechanical organization. We implement these capabilities in MechScape, an open-source computational platform that supports force curve fitting, spatial feature matrix construction, unsupervised domain discovery, and cross-modal alignment with histological and molecular measurements. Application to murine myocardial tissue reveals that spatial mechanomics identifies distinct mechanical states, quantifies condition-dependent remodeling across all measured parameters, and resolves spatially coherent mechanical domains. This work establishes spatial mechanomics as a quantitative approach for tissue-scale biomechanical mapping and provides a generalizable framework for integrating mechanics as an omics layer in multi-modal tissue analysis.

bioinformatics↗

bioRxiv2026

MAP: A Knowledge-driven Framework for Predicting Single-cell Responses for Unprofiled Drugs

Predicting how cells respond to chemical perturbations is one of the goals for building virtual cells, yet experimentally profiled compounds cover only a small fraction of this space. Existing models struggle to generalize to unprofiled compounds, as they typically treat drugs as isolated identifiers without encoding their mechanistic relationships. We present MAP, a framework that integrates structured biological knowledge into cellular perturbation modeling and supports zero-shot prediction for small molecules with scarce or absent perturbation profiles. Specifically: (i) we construct MAP-KG, a large-scale knowledge graph tailored for cellular perturbation modeling that unifies 14 public resources, spanning 187k drugs, 23k genes, and 694k mechanistic relationships; (ii) we propose a knowledge-driven pre-training strategy that aligns molecular structures, protein sequence features, and textual mechanistic descriptions into a unified embedding space via contrastive learning, producing mechanism-aware and transferable gene and compound embeddings. The resulting knowledge-informed gene and drug representations are then coupled with a pretrained single-cell foundation model to condition perturbation response prediction; (iii) we evaluate MAP under two zero-shot generalization regimes: unseen cell type-drug combinations and the stricter setting of unprofiled drugs, where it improves top-50 DEG Pearson delta correlation by up to +13.3% and +12.2%, respectively, over the strongest baselines across three benchmarks. We further perform pathway-level functional analysis via GSEA for in-silico screening, where MAP predicts coherent, mechanism-consistent programs on unprofiled candidate drugs, and prioritizes 4 of 5 approved anti-cancer drugs in A-549 (non-small cell lung cancer).

bioinformatics↗

bioRxiv2026

Sympathetic Control of Sensory Neuron Fate and Function

Sensory neurons in the dorsal root ganglia (DRG) serve as conduits for transmitting peripheral stimuli to the central nervous system, playing an essential role in sensory perception and coordinated movement. This study reveals that sympathetic innervation is critical for these neurons survival and functional integrity. Using a surgical microsympathectomy model in mice, we found that targeted sympathetic denervation of the lumbar DRGs triggered robust neuronal death, peaking four days post-surgery. This cellular loss is evidenced by reduced spinal projections, decreased nerve density in the skin, and impaired sensory and motor functions. We further identified norepinephrine (NE) as a vital neuroprotective agent; continuous NE supplementation effectively prevented cell death. Additionally, macrophage activation following denervation proved protective, as macrophage depletion exacerbated neuronal loss. It is suggested that the loss of sympathetic input disrupted mitochondrial homeostasis, releasing Smac/DIABLO, activating Caspase-3, and leading to cell death. These findings highlight the sympathetic nervous systems novel role in maintaining sensory neuron viability through tonic adrenergic support.

neuroscience↗

bioRxiv2026

ZCWPW1 organizes telomeric architecture to drive meiotic chromosome movements

Meiotic homolog pairing relies on programmed DNA recombination and large-scale chromosome movements, yet, how these genetic and mechanical events are coordinated remains unclear. ZCWPW1 is a histone reader that recognizes PRDM9-deposited chromatin marks. We identify an unexpected role for ZCWPW1 as a regulator of rapid prophase movements (RPMs). Using super-resolution imaging, we show that ZCWPW1 is strongly enriched at subtelomeric regions of mouse spermatocytes, where it stabilizes TRF1, LINC complex components, dynein, and meiosis-specific cohesin (STAG3). Loss of ZCWPW1 disrupts telomere architecture, weakens telomere-LINC- motor coupling, and abolishes chromosome movement, leading to defective synapsis and pairing, and persistence of DSBs. These defects are more severe than, and mechanistically independent of, those observed in Prdm9-/- spermatocytes. Together, our findings reveal that ZCWPW1 acts independently of PRDM9 as a chromatin-based intranuclear regulator of telomere architecture and telomere-led chromosome movements, thereby linking telomeric chromatin state to nuclear force transmission required for faithful meiotic progression. Significance StatementMeiotic pairing requires recombination and telomere-led chromosome movements, yet no chromatin factor has been shown to regulate both. We identify ZCWPW1 as the first chromatin-based regulator of rapid prophase movements. ZCWPW1 organizes telomeric chromatin and promotes cohesin and motor assembly at telomeres that for force transmission across the nuclear envelope. Loss of ZCWPW1 disrupts the telomere-nuclear envelope mechanical coupling, impairing motion and altering recombination. This function doesnt rely on PRDM9 despite their co-evolution and co-expression, challenging the prevailing view that ZCWPW1 only acts downstream of PRDM9 in DNA repair. Our findings show that chromatin readers can function as structural regulators of genome organization, revealing a conserved mechanism integrating chromosome structure, motion, and repair to ensure proper pairing and fertility.

cell biology↗

bioRxiv2025

Discovery and Characterization of a Hydroxypyridone-3-carboxamide Analog as an Antiviral Lead against Orthopoxviruses

Orthopoxviruses remain a persistent global health concern due to the ongoing circulation of mpox, the possibility of the re-emergence of smallpox, and the threats posed by many poxviruses that infect animals and/or humans. The limited availability of antiviral drugs, the unproven efficacy in humans, and the emergence of resistant mutants underscore the need for new and better therapeutics. In this study, we identify and characterize ZW-2038, a hydroxypyridone-3-carboxamide analog, as an antiviral compound against vaccinia virus (VACV), monkeypox virus (MPXV), and cowpox virus (CPXV). Discovered through a focused in-house small-molecule screen, ZW-2038 exhibited low micromolar potency and high selectivity in primary human fibroblasts. The compound also reduced viral replication under physiomimetic conditions including human and monkey intestinal organoids (enteroids) and ex vivo mouse lung tissue models. Mechanistically, ZW-2038 suppresses VACV DNA replication and downstream post-replicative gene expression, albeit without inhibiting MPXV resolvase (Mpr) in vitro. These findings, along with in vitro safety profiling and mice pharmacokinetics studies, characterize ZW-2038 as a promising yet suboptimal antiviral lead against orthopoxviruses warranting future development.

microbiology↗