Biology subjects

Hao, Y.

Publications and source records attributed to Hao, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Molecular dynamics of Brodmann Area 22 in development and autism

Challenges in verbal communication are a prominent feature of autism. However, gene regulatory programs in speech-related cortical regions remain poorly characterized. In parallel, it remains unclear whether the heterogeneous genetic factors underlying autism converge on shared neurobiological mechanisms. To address these gaps, we generated paired transcriptomic and epigenomic data from post-mortem human brain tissue across 100 donors. Here, we show that transcriptional differences in the speech-related Brodmann Area 22 in individuals with neurodevelopmental conditions, including autism, are strongest among those with a known genetic diagnosis. A similar but attenuated signature is observed in those without a genetic diagnosis. These transcriptional differences are most pronounced in neurons, with glutamatergic L4/5 intratelencephalic neurons affected across multiple modalities. Finally, multimodal analysis implicates altered RFX3-dependent networks as a central hub in autism, particularly among L4/5 intratelencephalic neurons in non-verbal individuals. Together, our study identifies regulatory architecture linking chromatin state, transcriptional output, and variation in verbal ability in autism.

neuroscience↗

bioRxiv2026

The human parasite, Toxoplasma gondii, is paralyzed without two components of the apical polar ring

The phylum Apicomplexa contains [~] 6000 known species of unicellular eukaryotic parasites. A unifying feature among the apicomplexans is the apical complex, which varies in complexity in different lineages, but always contains an annulus (a.k.a. the apical polar ring) into which the minus ends of an array of cortical microtubules are embedded. In Toxoplasma gondii, the apical complex also includes the conoid, which contains several signaling and structural proteins critical for parasite motility. The conoid extends and retracts through the apical polar ring in a calcium-dependent manner. Here we report the identification of several new apical polar ring components, including APR9, which is highly conserved among the apicomplexans and their free-living relative Chromera velia. The loss of APR9 alone has only a moderate impact on the parasite lytic cycle. However, the knockout of both APR9 and KinesinA (another apical polar ring component) paralyzes parasite and drastically impairs invasion, egress and the lytic cycle. The double-knockout displays multiple subcellular abnormalities, including the formation of an apical actin concentration, impaired conoid extension, and significantly reduced secretion of a major adhesin (MIC2) upon stimulation with a calcium ionophore. These findings reveal that the apical polar ring plays a critical role in parasite motility and contributes to multiple subcellular processes.

cell biology↗

bioRxiv2026

MolX: A Geometric Foundation Model for Protein-Ligand Modelling

Understanding how small molecules interact with protein binding pockets is central to structure-based drug discovery. Accurately modelling these interactions requires capturing the 3D geometry and physicochemical complementarity of binding interfaces, yet existing computational approaches encode proteins and ligands separately or rely on simplified structural representations that do not explicitly model cross-entity spatial relationships. Such decoupled representations restrict their capacity to capture interface-level geometric constraints that arise from protein-ligand coorganisation. Here we present MolX, a Graph Transformer foundation model that jointly learns geometric and chemical representations of protein pockets and ligands from large-scale 3D structural data. Integrating over 3 million protein pockets and 5 million molecules, MolX represents both entities as E(3)-equivariant graphs to preserve spatial geometry and chemical context. The architecture employs dual E(3)-equivariant graph Transformer encoders to model pocket and ligand embeddings, ensuring representations remain invariant to rotation, translation, and reflection. MolX is pretrained using a hybrid learning paradigm that combines supervised biochemical objectives, logP and energy-gap regression, with self-supervised geometric objectives, coordinate re-construction, and atom-type prediction, fostering generalisable molecular understanding. Across eight downstream benchmarks, including antibody-drug conjugates (ADC), proteolysis-targeting chimeras (PROTAC), molecular glue, and PCBA activity prediction, as well as binding affinity and physicochemical property regression, MolX achieves consistent state-of-the-art performance and strong cross-domain generalisation. Furthermore, MolX incorporates a sparse autoencoder module to decompose latent representations into interpretable biological components, thereby revealing the pocket-ligand interactions that drive prediction outcomes. Together, MolX establishes a scalable and interpretable foundation model for molecular representation learning, providing a unified framework for predicting and interpreting complex small-molecule-protein interactions.

bioinformatics↗

bioRxiv2026

Macrophage Iron Metabolism in Allografts and Tumors

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

immunology↗

bioRxiv2026

Graph-based RNA structural representation reveals determinants of subcellular localization

RNA subcellular localization is a key determinant of RNA function and regulation, yet existing computational approaches rely primarily on sequence or simplified structural descriptors, limiting their scalability to long transcripts, their ability to model inter-label dependencies, and their applicability across RNA types. Here, we present GRASP, a unified graph neural network framework for predicting RNA subcellular localization using a heterogeneous graph representation that is RNA substructure-aware. GRASP presents each RNA as a multi-scale graph comprising nucleotide nodes and secondary-structure-derived substructure nodes, connected by relational edges, enabling joint modeling of base-level interactions and regional structural context. The model further incorporates multi-label dependency learning to capture co-localization patterns across cellular compartments within a unified framework. Across multiple benchmark datasets and RNA types, GRASP consistently outperforms state-of-the-art sequence-based and structure-informed methods, achieving substantial improvements in accuracy, F1 score, and AUC while maintaining strong scalability to long transcripts. In addition, the graph-based representation provides biologically interpretable insights into structural determinants of RNA localization. The source code and data are available at https://github.com/ABILiLab/GRASP, and the web server is accessible at http://grasp.biotools.bio.

bioinformatics↗

bioRxiv2026

Unleashed condensation by recurrent mutations of an epigenetic regulator promotes cancer

The pathological mechanisms and significance for the prevalent hotspot mutations in disordered protein regions are poorly understood. ASXL1 is an obligate co-factor for BAP1 in H2AK119 deubiquitination. ASXL1 mutations are very frequent in myeloid malignancies, and are mostly C-terminal truncating mutations concentrated in a specific disordered region of ASXL1. ASXL1 truncations are gain-of-function mutations that promote myeloid malignancies, but the underlying mechanisms remain poorly understood. Here we show that the frequently truncated mutants of ASXL1 possess an intrinsic property of forming phase-separated biomolecular condensates, and this property is normally suppressed by the frequently deleted regions. A disease-mutant of the endogenous ASXL1 in leukemia cells forms dynamic nuclear co-condensates with other endogenous factors important for gene activation. The ASXL1 disease-mutants can greatly enhance H2A deubiquitination activity of BAP1 in cells and in vitro reconstituted system, enhance myeloid leukemia cell growth, and promote leukemogenesis in a mouse transplant model by turning on myeloid leukemogenic transcriptional programs. However, substitution of residues important for condensation disrupted or impaired all these abilities, suggesting that the condensation property is crucially important for the ASXL1 mutants in promoting cancer. Moreover, we discover that the conserved negative charges in the highly disordered and frequently deleted region on ASXL1 suppress the condensation of the wild type ASXL1. Charge-neutralizing mutations in this region restores condensation of the full-length ASXL1, and are sufficient to turn ASXL1 into a leukemogenic protein. Biochemical, biophysical, and simulation analyses suggest the intramolecular interactions normally mask the N-terminal region in engaging intermolecular interactions required for phase separation, and disease truncations escape from the regulatory interactions and unleash the phase separation property to form nuclear hubs to promote expression of tumorigenic gene programs. Finally, by showing a striking correlation of the mutation frequencies with the condensation properties and leukemogenesis activity for a series of human patient mutations, we suggest that dysregulation of condensation is a central mechanism for ASXL1 mutations in promoting myeloid malignancies. This suggests that dysregulation of condensation may be a key mechanism for some of the prevalent hotspot disease mutations in the disordered proteomes.

biochemistry↗

bioRxiv2026

SenCat: Cataloging human cell senescence through multiomic profiling of multiple senescent primary cell types

There is an urgent need to comprehensively catalog senescence markers across cell types in an organism in order to characterize senotypes and senescent cell heterogeneity. Here, we profiled the transcriptomes and proteomes in 14 different primary human cell types undergoing over 30 senescence paradigms to create a senescence catalog we termed SenCat. We found that, while senescent cells from all primary tissue types did not share a single unique marker, they did activate shared specific metabolic and damage-response pathways implicated in tissue repair. Machine learning analysis of the SenCat transcriptomic and proteomic datasets successfully identified independent sets of senescent human cells, and senescent-like cells in mouse lung and kidney. In sum, SenCat represents a much-needed resource to identify senescent cells across tissues in the body. HIGHLIGHTSO_LIIdentifying senescent cells in organisms in vivo remains a challenge C_LIO_LIWe created SenCat: a catalog transcriptomes and proteomes of senescent primary cells C_LIO_LIMachine learning (ML) analysis of SenCat identified robust senescence scores C_LIO_LIML-derived senescence scores uncovered senescent-like cell dynamics in vivo C_LI

molecular biology↗

bioRxiv2026

Task-Dependent Effects of Channel Density on Multivariate Pattern Analysis and Spatial Representational Similarity Analysis: Evidence from Three EEG Datasets

Despite the widespread use of EEG decoding and representational similarity analysis (RSA), the extent of the impact of electrode density on these multivariate approaches has not been systematically evaluated, particularly across different cognitive domains. Here, we systematically compared four electrode configurations (19, 32, 64, and 128 channels) across three EEG datasets encompassing visual perception, visual search, and emotional processing. All datasets were recorded at 128 channels and subsequently reduced to 64, 32, and 19 channels via electrode subset selection based on the international 10-20 system. Time-resolved decoding and spatial RSA were computed for each configuration with paired statistical evaluation. Decoding sensitivity demonstrated clear task dependence: in the color-harmony paradigm, performance improved markedly with higher densities, consistent with spatially distributed perceptual representations, whereas decoding in the icon-search and dot-probe tasks remained stable across densities, indicating diminishing returns of additional electrodes although all configuration yielded robust decoding accuracies that above chance level. RSA results were comparatively robust, with relative representational similarity structures largely preserved even for 16 channel counts. These findings demonstrate that low-density setups can be sufficient, offering practical guidance for EEG channel selection and supporting the use of low-density EEG in real-world applications, including wearable systems, mobile EEG recordings, and clinical or rehabilitation settings.

neuroscience↗

bioRxiv2026

Pan-genome and multi-omics analyses reveal the genomic basis of symbiotic evolution in the mycoheterotrophic medicinal orchid Gastrodia elata

Mycoheterotrophy represents an extreme evolutionary strategy in which plants abandon photosynthesis and become obligately dependent on fungal partners for carbon and nutrients. Gastrodia elata, a medicinal orchid forming long-term symbioses with Armillaria and Mycena, provides a compelling system to investigate the genomic basis of obligate plant-fungus mutualism. Here, we generate a chromosome-level genome assembly (1.09 Gb) of a dark-red G. elata accession and construct a pan-genome from 12 Gastrodia accessions to dissect the evolutionary consequences of mycoheterotrophy. Phylogenomic analyses reveal pervasive hybridization across cultivated germplasm and demonstrate that tuber morphology more accurately reflects intraspecific relationships than stem color, challenging the traditional color-based taxonomy. Comparative genomic analyses reveal a pronounced degeneration of photosynthetic capacity. We detect no intact nuclear-encoded rbcS loci, which would preclude assembly of the Rubisco holoenzyme and thus canonical Calvin-Benson carbon fixation. Notably, a subset of photosynthesis-related genes is retained and transcriptionally active, suggesting their co-option into non-photosynthetic regulatory roles. Despite millions of years of intimate association with fungal partners, we detect no evidence of fungal-derived horizontal gene transfer based on a multi-step phylogenomic validation pipeline, indicating that G. elata-fungus mutualism is sustained through metabolic exchange rather than genetic integration. We further identify the Gastrodia antifungal protein (GAFP) gene family as a key molecular innovation underlying symbiotic homeostasis. The recently derived Class 1 GAFP lineage exhibits distinct domain architecture, tandem expansion, and elevated expression, consistent with enhanced regulation of fungal overgrowth. Finally, we delineate a specialized nutrient-acquisition framework adapted to obligate heterotrophy, in which fungal trehalose hydrolysis supplies hexose carbon via an expanded sugar transporter protein (STP) repertoire, while organic nitrogen is assimilated through amino acid and oligopeptide transporters coupled with urease-mediated conversion, compensating for the loss of nitrate uptake and reduction pathways. Together, these results establish a pan-genomic blueprint for symbiotic adaptation and reductive genome evolution in G. elata.

genomics↗

bioRxiv2026

MANTIS: Analytics toolkit for spatial metabolomics with matching spatial transcriptomics data

MotivationJoint Spatial Metabolomics (SM) and Spatial Transcriptomics (ST) profiling is a powerful approach to fine-mapping of metabolic states associated with tissue function. Current computational tools for analysis of "SM+ST" data focus primarily on alignment and integration of the two modalities, with limited support for probing biological relationships between the two molecular layers. ResultsWe present MANTIS, a statistical framework for analyzing co-registered SM+ST profiles at single cell or spot resolution, along with spatial domain or cell type information, to discover metabolite spatial patterns and gene-metabolite relationships. It employs an autocorrelation-preserving permutation strategy to assess statistical significance, yielding calibrated inference under spatial dependence. It disentangles different sources of spatial patterns and correlations, viz., those arising from regional preferences, cell type associations, or other unknown factors. It introduces the use of spatial cross-correlation and spatial partial correlation statistics for quantifying gene-metabolite associations. Across data sets spanning different spatial technologies, tissues and species, MANTIS provides more specific and interpretable discoveries than existing methods through rigorous statistical testing and explicitly modeling confounding structure. To our knowledge, MANTIS is the first toolkit to unify spatial metabolomics, spatial transcriptomics, cell type information and spatial domains within a single framework that emphasizes spatial statistics, hypothesis testing and confounder correction. Availability and ImplementationFreely available on the web at https://github.com/yuhaotuo/MANTIS.

bioinformatics↗

bioRxiv2026

Ultra-fast genetic recovery of dead fish through cross-family germline stem cell transplantation

AbstactThe conservation of genetic resources from aquaculture species and endangered fish is increasingly challenged by large body size, long reproductive cycles, and limited opportunities for timely intervention after death. Here, we establish and validate an ultra-fast genetic platform based on germline stem cell transplantation to enable postmortem genetic recovery in fish. Using grass carp (Ctenopharyngodon idella) as a representative warm-water species, we systematically quantified the relationships among postmortem tissue freshness, germline stem cell viability, and transplantation efficiency, and demonstrated that low-temperature preservation plays a decisive role in maintaining germline activity after death. Germline stem cells isolated from deceased grass carp were transplanted into germ-cell-depleted zebrafish recipients, where they rapidly colonized recipient gonads, underwent proliferation and differentiation, and generated functional donor-derived gametes within three months. These gametes supported successful fertilization and normal embryonic development, ultimately yielding viable grass carp offspring. Our results reveal an intrinsic postmortem resilience of germline stem cells and demonstrate that cross-species transplantation into small, fast-maturing hosts can dramatically accelerate genetic recovery. This strategy overcomes key biological and logistical constraints associated with conventional breeding-based rescue approaches and provides a rapid, scalable, and broadly applicable framework for postmortem genetic resource conservation in aquaculture and endangered fish species.

zoology↗

bioRxiv2025

Human heart organoids reveal a regenerative strategy for mitochondrial disease

The human heart is among the most complex tissues to replicate in vitro, with vascular, neuronal, and immune elements shaping its development and function. Here we describe cardiomorphs, self-organising human cardiac organoids that recapitulate the cellular diversity, structural organisation, vascularisation, and innervation of the myocardium and mature along a developmental trajectory from early cardiogenesis to adult tissue. Using patient-derived cardiomorphs, we establish the first three-dimensional human tissue model of Kearns-Sayre syndrome (KSS), a rare mitochondrial disorder characterised by large-scale mtDNA deletions. KSS-cardiomorphs faithfully reproduce disease-associated metabolic, contractile, and ultrastructural hallmarks. Leveraging this platform, we identify Betaxolol, an FDA-approved selective {beta}1-adrenergic antagonist, as a modulator of mitochondrial quality control. Betaxolol increases intracellular oxygenation, selectively eliminates dysfunctional mitochondria via mitophagy, and promotes biogenesis of functional organelles, restoring contractility in KSS tissues. This dual-action, mutation-agnostic mechanism suggests a therapeutic principle with broad relevance to mitochondrial disease, cardiac pathology, and age-associated decline.

cell biology↗

bioRxiv2025

Mining of natural diversity enables efficient and expressible peptide asparaginyl ligases

Peptide asparaginyl ligases (PALs) are powerful tools for protein engineering but are limited by natural rarity and poor expression. We mined 23 cyclotide-rich Viola species, uncovering 29 new PALs that expanded the known repertoire to 47. A dual-objective screen identified VdiPAL1 as the best-performed natural PAL, with twice efficiency of wt-VyPAL2 and 12 mg L-1 soluble expression in E. coli. A broad P2 specificity including Trp/Ile/Leu/Phe/Tyr/Met was discovered across diverse PALs, which enables sequential click-compatible liposome dual-functionalization. 1.8L[A] crystal structure of VdiPAL1 reveals a pre-organized near-attack conformation (NAC), supported by constant-pH MD simulations linking pH-dependent reactivity to NAC geometry. Our homology- and structure-based design yielded VyOpt1, a quintuple mutant of VyPAL2 with over 24-fold improved expression via enhanced cap-domain foldability in a single design-test cycle. This work expands the PAL family and demonstrates a transferable cap-domain-based engineering strategy, highlighting natural diversity as a powerful driver of enzyme discovery and optimization. TOC summaryMining of cyclotide-rich Viola genus expanded the total number of natural peptide asparaginyl ligases (PALs) to 47, including the discovery of highly expressible VdiPAL1. Its high-resolution structure provided new insights for mechanism, and its sequence guided us to a generalized PAL engineering strategy, leading to 24-fold increment in VyPAL2 expression.

biochemistry↗

bioRxiv2025

Neuronal APOE4 reduction with an APOE-I3-targeting ASO protects against neurodegeneration and neuroinflammation in an Alzheimer's disease mouse model

Apolipoprotein E4 (APOE4) is the strongest genetic risk factor for late-onset Alzheimers disease (AD). Within the central nervous system (CNS), APOE is produced by a variety of cell types, with differential roles in AD pathogenesis. Studies have shown that APOE4 produced by neurons plays a central role in promoting the development of major AD pathologies, including p-tau accumulation, neuroinflammation, and neurodegeneration, highlighting its role as an upstream initiating factor that affects other cell types and downstream AD-related pathologies. Here, we demonstrate that antisense oligonucleotides (ASOs) targeting APOE-I3, a neuron-specific splicing variant of APOE mRNA, effectively reduce APOE expression in neurons in vitro and in vivo. Treating PS19 tauopathy mice expressing APOE4 with this APOE-I3-targeting ASO reduces neuronal APOE4, rescues neurodegeneration, and diminishes neuroinflammation. Strikingly, the extent of neuronal APOE4 reduction predicts the efficacy of rescuing neurodegeneration. Single nucleus RNA-sequencing demonstrated that APOE-I3-targeting ASO treatment decreases disease associated neuronal and glial subtypes and increases a disease-protective microglial subtype. These findings suggest that preferential knockdown of neuronal APOE4 with an APOE-I3-targeting ASO protects against key hallmarks of AD pathology, elucidating a potential therapeutic approach for treating APOE4-driven AD.

neuroscience↗

bioRxiv2025

Reconstructing developmental and disease progression with sample-level embeddings

Single-cell genomics is transformative for characterizing cellular heterogeneity, but many translational questions require comparing samples rather than individual cells. Typical analyses compare "case" and "control" groups, ignoring sample-level variation within them. Here we present scSLIDE, a framework that transforms each samples single-cell data into a compact profile describing where its cells fall in high-dimensional space. By comparing these density profiles, scSLIDE calculates embeddings to characterization variation across samples. Applied to COVID-19 infection, Alzheimers disease, and zebrafish embryogenesis, we show that scSLIDE can be used to cluster patients, reconstruct sample-level disease trajectories, and identify coordinated cellular programs across samples. We discover independent axes of infection and severity, a molecular disease progression that aligns with pathology-based estimates of neurodegeneration, and embryonic "pseudostages" varying across and within timepoints. In each case, we demonstrate how case-control analyses collapse rich biological variation into binary labels, and how sample-level embedding represents a powerful analytical alternative.

genomics↗

bioRxiv2025

Neuronal APOE4 drives damaging lipid accumulation via contact-dependent neuron-oligodendrocyte-microglia interaction in Alzheimer's disease

Apolipoprotein E4 (APOE4) confers the greatest genetic risk for developing Alzheimers disease (AD). With APOE4 broadly expressed in the brain, its cell-type-specific roles in AD pathogenesis are only beginning to be defined. Here, we show that neuronal APOE4 expression drives damaging lipid accumulation in hippocampal neurons, oligodendrocytes, and microglia, with preferential buildup of peroxidized lipids in microglia in a tauopathy mouse model. Neuron-specific removal of APOE4 abolished this lipid phenotype, whereas neuron-specific expression of APOE4 was sufficient to recapitulate it, demonstrating that neuronal APOE4 is both necessary and sufficient for lipid accumulation. Strikingly, the association between lipid burden, microgliosis, and neurodegeneration was strongest in mice with neuron-specific APOE4 expression. Single-nucleus RNA sequencing revealed neuronal APOE4-vulnerable neuron populations, as well as enrichment of disease-associated microglia and oligodendrocytes, all promoting lipid pathology. Primary mouse co-culture experiments showed that neuronal APOE4 drives microglial lipid accumulation via contact-dependent mechanisms involving uptake of lipids from neurons and oligodendrocytes. These findings establish neuronal APOE4 as a key driver of lipid accumulation via neuron-oligodendrocyte-microglia interactions, providing mechanistic insight into APOE4-driven lipid pathology in AD.

neuroscience↗

bioRxiv2025

Dynamic alterations of DNA methylation and transcriptome in adaptation to and recovery from the space environment

Space exploration presents tremendous health challenges. Here, we report time series of multi-omic and phenotypic profiles of seventeen astronauts from six China Manned Space missions with continuous spaceflight durations ranging from 13 to 180 days. We revealed a key role of DNA methylation regulation in reshaping gene expression patterns to adapt to the space environment. Long-duration spaceflight showed more alterations in epigenetic modifications correlated with alternative splicing and protein acetylation. During recovery, an "overrange rebound" phenomenon was observed, furthermore, a mathematical model was established to describe this implying important phenomenon. Moreover, we revealed the correlations between molecular alterations and phenotypic changes such as coagulation activation and bone intensity loss. Additionally, we performed ground-based simulation experiments to estimate the impacts of individual stressors in the space environment on DNA methylation. In summary, our study highlights the importance and complexity of epigenetic regulation in adaptation to and recovery from the space environment.

genomics↗

bioRxiv2025

Neuronal APOE4 alone is sufficient to drive tau pathology, neurodegeneration, and neuroinflammation in an Alzheimer's disease mouse model

Apolipoprotein E4 (APOE4), the strongest genetic risk factor for late-onset Alzheimers disease (AD), exacerbates tau tangles, amyloid plaques, neurodegeneration, and neuroinflammation--the pathological hallmarks of AD. While astrocytes are the primary producers of APOE in the CNS, neurons increase APOE expression under stress and aging. Prior work established that neuronal APOE4 is essential for AD pathogenesis, but whether it is sufficient to drive disease remained unknown. We generated a PS19 tauopathy mouse model selectively expressing APOE4 in neurons. Neuronal APOE4 alone proved sufficient to promote pathological tau accumulation and propagation, neurodegeneration, and neuroinflammation to levels comparable to a tauopathy model with human APOE4 knocked-in globally. Single-nucleus RNA sequencing further revealed similar transcriptomic changes in neurons and glia of both models. Together, these findings demonstrate that neuronal APOE4 alone can initiate and propagate AD pathologies, underscoring its pivotal role in disease pathogenesis and its potential as a therapeutic target.

neuroscience↗