Biology subjects

Dai, Q.

Publications and source records attributed to Dai, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

CellMethMarker provides an integrated database of human cell- and tissue-type-specific DNA methylation markers

Cell- and tissue-type-specific DNA methylation markers provide epigenetic signatures of cellular identity and are widely used to infer cellular origin from bulk and single-cell methylomes. Existing resources mainly emphasize disease-associated biomarkers, methylome atlases, genomic annotations or RNA-based cell markers, leaving an unmet need for an integrated region-level resource dedicated to such markers. Here we present CellMethMarker (http://gu-zhanglab.hfcas.ac.cn/CellMethMarker), a curated database integrating 347,514 de novo markers derived from uniformly processed whole-genome and reduced-representation bisulfite sequencing datasets, 2,203,507 literature-derived marker records and harmonized metadata for 2,810 samples. CellMethMarker enables cell- and tissue-centered marker retrieval, coordinate-based search, genome-browser visualization, interactive methylation analysis and data download. In an independent single-cell methylome atlas, these markers recover the expected cell-type-associated methylation patterns, and a platform-matched reference built from them lowers the mean deconvolution error from 0.365 to 0.144. CellMethMarker therefore links region-level DNA methylation variation to cellular identity and supports methylome-based cell-type annotation and deconvolution.

bioinformatics↗

bioRxiv2026

Efferocytosis Remodels Osteoclast Metabolism and Enhances Antibacterial Defense

Osteoclasts are metabolically specialized for bone resorption, but how apoptotic-cell uptake shapes their immune function remains unclear. During Staphylococcus aureus bone infection, osteoclasts engulfed apoptotic neutrophils. In osteoclast cultures, apoptotic-neutrophil exposure reduced multinucleation and resorption, induced host-defense programs, and enhanced antibacterial activity, whereas macrophages showed no comparable antibacterial response. MERTK was required for efficient osteoclast efferocytosis. Ctsk-Cre-mediated Mertk deletion increased bacterial burden and bone loss, whereas transplantation of MERTK-competent bone marrow restored osteoclast efferocytosis and reduced infection-associated bone damage. Transcriptomic and extracellular flux analyses revealed enhanced glycolytic activity and altered lactate handling in efferocytic osteoclasts. Lactate supplementation reduced osteoclast formation without reproducing the antibacterial phenotype. Inhibiting lactate production or export attenuated antibacterial activity in efferocytic osteoclasts, whereas blocking lactate uptake enhanced it. These findings identify osteoclast efferocytosis as an immune adaptation that links apoptotic-neutrophil clearance to metabolic remodeling and antibacterial defense in bone.

cell biology↗

bioRxiv2026

A One-Step Chemoselective Strategy for Hydroxymethylcytosine Sequencing in DNA and RNA

5-Hydroxymethylcytosine (5hmC) is a relatively stable chemical mark formed by oxidation of 5-methylcytosine in DNA, while its RNA counterparts, 5-hydroxymethylcytidine (hm5C) and 2'-O-methyl-5-hydroxymethylcytidine (hm5Cm), have recently emerged as potential regulators of post-transcriptional processes. Existing 5hmC enrichment methods rely on anti-bodies or enzymatic {beta}-glucosyltransferase labeling, are largely DNA-specific, and are not readily applicable to RNA. Here we report bisulfite-assisted labeling by thiol sequencing (BALT-seq), a one-step chemoselective strategy that installs a biotin-thioether handle directly onto hydroxymethylcytosine in DNA or RNA under mild acidic bisulfite conditions, without using enzymes. Mechanistic studies show that thiol capture of the bisulfite-activated 5hmC intermediate competes with canonical cytosine-5-methylenesulfonate formation, yielding a stable adduct that DNA polymerases bypass efficiently and that resists APOBEC-mediated deamination. In mouse embryonic stem cells, BALT-seq produces genome-wide 5hmC profiles highly concordant with 5hmC-Seal, TAB-seq, and oxBS-seq, recovers expected gene-body and chromatin-state enrichment, and extends to low-input cell-free DNA. On RNA, BALT-seq enriches hm5C/hm5Cm-containing transcripts more effectively than antibody-based hMeRIP and reveals structured modification landscapes across tRNA species and LINE/LTR repeat families. BALT-seq thus establishes a unified, enzyme-free chemical platform for hydroxymethylcytosine profiling across DNA, cell-free DNA, and RNA.

genomics↗

bioRxiv2026

Time-Resolved Phenotypic and Transcriptomic Responses of Primary Canine Dermal Fibroblasts to Prolonged Hypothermic Stress

Prolonged low-temperature exposure may extend the preservation window of mammalian cells but can also disrupt cellular homeostasis and ultimately compromise cell viability. This study investigated the time-dependent phenotypic and transcriptomic responses of primary canine dermal fibroblasts to sustained hypothermic stress. Passage-three fibroblasts were continuously maintained at 15 for up to 15 days, with samples collected on Days 0, 3, 6, 9, 12, and 15. Cellular morphology, metabolic activity and viability, and apoptosis were evaluated using bright-field microscopy, Cell Counting Kit-8 assays, and Annexin V-FITC/propidium iodide flow cytometry, respectively. RNA sequencing was performed to characterize dynamic transcriptional changes throughout the exposure period. Early low-temperature exposure was associated with relatively preserved cellular morphology and viability, suggesting a transient adaptive response. With increasing exposure duration, fibroblasts exhibited progressive morphological deterioration, reduced metabolic activity, loss of adhesion, and increased apoptosis. Time-series transcriptomic analysis further revealed temporally coordinated and stage-dependent gene-expression programs associated with metabolic regulation, cellular stress responses, structural homeostasis, and cell survival. Integration of phenotypic and transcriptomic data demonstrated that the response of primary canine dermal fibroblasts to 15 was dynamic rather than linear, progressing from early adaptation to cumulative dysfunction during prolonged exposure. These findings provide a framework for defining the low-temperature tolerance of primary canine dermal fibroblasts and may inform the optimization of protocols for their short- to medium-term preservation and transportation.

cell biology↗

bioRxiv2026

From external-input sensitivity to resident persistence: community assembly in a sink p-trap model

Microbial habitats that receive repeated external input may not remain shaped by that input forever if local retention allows resident communities to build up over time. Here, we used a controlled bench-scale sink p-trap system to examine how community assembly unfolded during initial establishment in new, bleach-treated p-traps. Two p-traps received repeated handwashing-water input, while one received tap water as baseline. The treated p-traps, but not the control, showed clear successional change toward later resident-like states. Nested-model comparisons further showed that recent external input had its greatest influence early in succession, but the p-traps own prior state remained the stronger predictor throughout. Final-day post-flush trajectories indicated short-term displacement from pre-flush positions, with later time points tending to move back toward late-stage resident centroids. Together, these results show that repeated inoculation does not necessarily keep communities under continued outside influence. Instead, retentive microbial habitats can shift over time from early sensitivity to external input toward persistence shaped more by local history.

ecology↗

bioRxiv2025

Rapid robust high-fidelity 3D neuronal extraction from multi-view projections

Recent developments in imaging facilitate large-scale three-dimensional (3D) neuronal recording. While these huge amounts of data shed new light on population-level neural coding, it is much harder to extract neuronal calcium dynamics from 3D volumes than 2D images with the existence of noise and scattering. Here, we presented DeepWonder3D, a general end-to- end pipeline for rapid and robust 3D neuronal extraction with high fidelity. Instead of processing voxel by voxel, DeepWonder3D works on the multi-view projections of 3D imaging data obtained either digitally or optically through specific point spread functions (PSFs) for general applicability to diverse techniques, including point-scanning microscopy, light- field microscopy, and two-photon synthetic aperture microscopy. Integrating denoising, resolution registration, background removal, neuronal extraction, and multi-view fusion into a unified pipeline tailored for large-scale high-resolution datasets contaminated by noise and scattering, DeepWonder3D outperforms state-of-the-art methods in 3D localization accuracy with a 10-fold reduction in computational costs, validated by numerical simulations and a hybrid two-photon/light-field imaging system. With the RUSH3D mesoscope, DeepWonder3D achieves rapid high-fidelity 3D calcium extraction of tens of thousands of neurons across the mouse cortex within hours.

neuroscience↗

bioRxiv2025

A simple library preparation modification significantly reduces barcode crosstalk in ONT multiplexed sequencing

Barcode crosstalk is a potential source of error in indexed multiplex sequencing that can mimic cross-contamination and generate false-positive signals, particularly in experiments with low-biomass samples and imbalanced designs. Here we identify and quantify barcode crosstalk in multiplexed Oxford Nanopore sequencing and introduce post-ligation pooling (PLP). PLP is a drop-in library-preparation modification that prevents barcode crosstalk, rather than simply mitigating its effects. These results highlight the potential for barcode crosstalk to have detrimental effects in multiplexed long-read sequencing and establish PLP as an immediately adoptable mitigation, especially where negative controls and low-abundance signals inform biological interpretation.

genomics↗

bioRxiv2025

Ultra-mild bisulfite outperforms EM-seq for 5-methylcytosine detection with low input DNA

We present Ultra-Mild Bisulfite Sequencing (UMBS-seq), a method for 5-methylcytosine (5mC) detection that minimizes DNA degradation and background noise. UMBS-seq outperforms conventional bisulfite and enzymatic methyl-sequencing (EM-seq) methods in library yield, complexity, and conversion efficiency when applied to low-input DNA samples. In particular, its effectiveness with low-input cell-free DNA (cfDNA) and hybridization-based target capture highlight its potential for clinical applications, including 5mC biomarker detection and early disease diagnosis.

genomics↗

bioRxiv2025

Three-dimensional spatial transcriptomics at isotropic resolution enabled by generative deep learning

Mapping the complete three-dimensional (3D), transcriptome-wide spatial architecture of tissues and organs remains a fundamental challenge in biology. Typically, studies approximate 3D structures by profiling serial two-dimensional (2D) tissue sections, resulting in incomplete and anisotropic reconstructions. Here, we demonstrate that organ-wide, isotropic-resolution 3D gene expression landscapes can be effectively inferred from sparse 2D spatial transcriptomics data using artificial intelligence. Our framework, isoST, leverages stochastic differential equations (SDEs) to model the intrinsic biological continuity of gene expression along tissue depth, enabling the integration of discrete 2D measurements into coherent 3D transcriptomic maps. isoST is applied across diverse biological systems, including the brain, kidney, spinal cord, and gastrulating embryos, accurately reconstructing anatomical structures and molecular patterns that are only partially resolved in 2D analyses. isoST enables the comprehensive characterization of tissue niches at full 3D resolution, uncovering radial and spherical gene expression gradients associated with disease progression that are often distorted or missed in 2D approaches. Furthermore, isoST is extended to integrate histological imaging for reducing experimental complexity and to reconstruct high-resolution developmental spatial trajectories over time. Together, isoST provides a practical and scalable solution toward comprehensive high-resolution 3D spatial transcriptomic atlases.

bioinformatics↗

bioRxiv2025

TRPM7 Annexin A1 Mechanosensitive Pathway Drives Capillary Infiltration by Circulating Tumor Cells

Successful metastatic dissemination requires tumor cells to overcome significant physical barriers. When circulating tumor cells (CTCs) become lodged in capillary beds, studies reveal that only a small subset can adapt to fluid shear stress (FSS) within the constricted vasculature. These rare, mechanically resilient cells may subsequently extravasate and form metastatic lesions, but details on this adaptation of the physical environment and its molecular basis are not well understood. Utilizing a microfluidics platform that mimics microcirculatory dynamics, we discover that only breast cancer cells with high metastatic potential maintain directional migration under physiologically relevant FSS conditions. This highlights the mechanical selection process of metastatic precursors during hematogenous dissemination. We identify the TRPM7-Annexin A1-actin signaling pathway as essential for overcoming physical barriers and regulating cell motility under capillary FSS. FSS prompts cytoskeletal reorganization and actin disassembly, restricting cell movement. Cancer cells respond to this by increasing mechanical loading, activating TRPM7 and triggering calcium influx, which then activates Annexin A1. This calcium-dependent protein, Annexin A1, interacts with the actin cortex to prevent FSS-induced actin disassembly, thus aiding migration. Experiments conducted in mouse liver capillaries validate the critical role of this pathway in cancer cell motility. Additionally, we propose a mechano-pharmacological strategy using FTY720 to target the TRPM7 pathway, highlighting its therapeutic potential to modify CTC receptor specificity and inhibit distant metastasis.

cancer biology↗

bioRxiv2025

Unsupervised multi-animal tracking for quantitative ethology

Quantitative ethology necessitates accurate tracking of animal locomotion, especially for population-level analyses involving multiple individuals. However, current methods rely on laborious annotations for supervised training and have restricted performance in challenging conditions. Here we present an unsupervised deep-learning method for multi-animal tracking (UDMT) that achieves state-of-the-art performance without requiring human annotations. By synergizing a bidirectional closed-loop tracking strategy, a spatiotemporal transformer network, and three sophisticatedly designed modules for localization refining, bidirectional ID correction, and automatic parameter tuning, UDMT can track multiple animals accurately in various challenging conditions, such as crowding, occlusion, rapid motion, low contrast, and cross-species experiments. We demonstrate the versatility of UDMT on five different kinds of model animals, including mice, rats, Drosophila, C. elegans, and Betta splendens. Combined with a head-mounted miniaturized microscope, we illustrate the power of UDMT for neuroethological interrogations to decipher the correlations between animal locomotion and neural activity. UDMT will facilitate advancements in ethology by providing a high-performance, annotation-free, and accessible tool for multi-animal tracking.

animal behavior and cognition↗

bioRxiv2024

CADET: Enhanced transcriptome-wide association analyses in admixed samples using eQTL summary data

A transcriptome-wide association study (TWAS) is a popular statistical method for identifying genes whose genetically-regulated expression (GReX) component is associated with a trait of interest. Most TWAS approaches fundamentally assume that the training dataset (used to fit the gene expression prediction model) and testing GWAS dataset are from the same ancestrally homogenous population. If this assumption is violated, studies have shown a marked negative impact on expression prediction accuracy as well as reduced power of the downstream genetrait association test. These issues pose a particular problem for admixed individuals, whose genomes represent a mosaic of multiple continental ancestral segments. To resolve these issues, we present CADET, which enables powerful TWAS of admixed cohorts leveraging the local-ancestry (LA) information of the cohort along with summary-level eQTL data from reference panels of different ancestral groups. CADET combines multiple polygenic risk score models based on the summary-level eQTL reference data to predict LA-aware GReX components in admixed test samples. Using simulated data, we compare the imputation accuracy, power, and type I error rate of our proposed LA-aware approach to LA-unaware methods for performing TWASs. We show that CADET performs optimally in nearly all settings regardless of whether the genetic architecture of gene expression is dependent or independent of ancestry. We further illustrate CADET by performing a TWAS of 29 common blood biochemistry phenotypes within an admixed cohort from the UK Biobank and identify 18 hits unique to our LA-aware strategy with the majority of hits supported by existing GWAS findings.

genetics↗

bioRxiv2024

Vcam1+ Fibro-adipogenic Progenitors Mark Fatty Infiltration in Chronic Limb Threatening Ischemia

Skeletal muscle health and function is a critical determinant of clinical outcomes in patients with peripheral arterial disease (PAD). Herein, we identify fatty infiltration, the ectopic deposition of adipocytes in skeletal muscle, as a histological hallmark of end-stage PAD, also known as chronic limb threatening ischemia (CLTI). Leveraging single cell transcriptome mapping in mouse models of PAD, we identify a pro-adipogenic mesenchymal stromal cell population marked by expression of Vcam1 (termed Vcam1+ FAPs) that expands in the ischemic limb. Mechanistically, we identify Sfrp1 and Nr3c1 as regulators of Vcam1+ FAP adipogenic differentiation. Loss of Sfrp1 and Nr3c1 impair Vcam1+ FAP differentiation into adipocytes in vitro. Finally, we show that Vcam1+ FAPs are enriched in human CLTI patients. Collectively, our results identify a pro-adipogenic FAP subpopulation in CLTI patients and provide a potential therapeutic target for muscle regeneration in PAD.

genomics↗

bioRxiv2024

Chemical Space Localization for Unknown Metabolite Annotation via Semantic Similarity of Mass Spectral Language

Untargeted analysis using liquid chromatography{square}mass spectrometry (LC-MS) allows quantification of known and unknown compounds within biological systems. However, in practical analysis of complex biological system, the majority of compounds often remain unidentified. Here, we developed a novel deep learning-based compound annotation approach via semantic similarity analysis of mass spectral language. This approach enables the prediction of structurally related compounds for unknowns. By considering the chemical space, these structurally related compounds provide valuable information about the potential location of the unknown compounds and assist in ranking candidates obtained from molecular structure databases. Validated with two independent benchmark datasets obtained by chemical standards, our method has consistently demonstrated superior performance compared to existing compound annotation methods. A case study of the tomato ripening process indicates that DeepMASS has significant potential for metabolic biomarker identification in real biological systems. Overall, the presented method shows considerable promise in annotating metabolites, particularly in revealing the "dark matter" in untargeted analysis.

bioinformatics↗

bioRxiv2024

Fast adaptive super-resolution lattice light-sheet microscopy for rapid, long-term, near-isotropic subcellular imaging

Lattice light-sheet microscopy (LLSM) provides a crucial observation window into intra- and inter-cellular physiology of living specimens with high speed and low phototoxicity, however, at the diffraction-limited resolution or anisotropic super-resolution with structured illumination. Here we present the meta-learning-empowered reflective lattice light-sheet virtual structured illumination microscopy (Meta-rLLS-VSIM), which instantly upgrades LLSM to a near-isotropic super resolution of [~]120-nm laterally and [~]160-nm axially, more than twofold improvement in each dimension, without any modification of the optical system or sacrifice of other imaging metrics. Moreover, to alleviate the tremendous demands on training data and time necessitated by existing deep-learning (DL) methods, we devised an adaptive online training approach by synergizing the front-end imaging system and back-end meta-learning framework, which reduced the total time for data acquisition and model training down to tens of seconds. With this method, a new model can be well-trained with tenfold less data and three orders of magnitude less time than current standard supervised learning. We demonstrate the versatile functionalities of Meta-rLLS-VSIM by imaging a variety of bioprocesses with ultrahigh spatiotemporal resolution for long duration of hundreds of multi-color volumes, characterizing the dynamic regulation of contractile ring filaments during mitosis and the growth of pollen tubes, and delineating the nanoscale distributions, dispersion, and interaction pattern of multiple organelles in embryos and eukaryotic cells.

biophysics↗

bioRxiv2024

Time-lapse Image Super-resolution Neural Network with Reliable Confidence Evaluation for Optical Microscopy

Single image super-resolution (SISR) neural networks for optical microscopy have shown great capability to directly transform a low-resolution (LR) image into its super-resolution (SR) counterpart, enabling low-cost long-term live-cell SR imaging. However, when processing time-lapse data, current SISR models failed to exploit the important temporal dependencies between neighbor frames, often resulting in temporally inconsistent outputs. Besides, SISR models are subject to inference uncertainty that is hard to accurately quantify, therefore it is difficult to determine to what extend can we trust the inferred SR images. Here, we first build a large-scale, high-quality fluorescence microscopy dataset for the time-lapse image super-resolution (TISR) task, and conducted a comprehensive evaluation on two essential components of TISR neural networks, i.e., propagation and alignment. Second, we devised a deformable phase-space alignment (DPA) based TISR neural network (DPA-TISR), which adaptively enhances the cross-frame alignment in the phase domain and outperforms existing state-of-the-art SISR and TISR models. Third, we combined the Bayesian training scheme and Monte Carlo dropout with DPA-TISR, developing Bayesian DPA-TISR, and designed an expected calibration error (ECE)minimization framework to obtain a well-calibrated confidence map along with each output SR image, which reliably implicates potential inference errors. We demonstrate the unique characteristics of Bayesian DPA-TISR underlie the ultralong-term live-cell SR imaging capability with high spatial fidelity, superb temporal consistency, and accurate confidence quantification on a wide variety of bioprocesses.

biophysics↗

bioRxiv2024

Notch dimerization provides robustness against environmental insults and is required for vascular integrity.

The Notch intracellular domain (NICD) regulates gene expression during development and homeostasis in a transcription factor complex that binds DNA either as monomer, or cooperatively as dimers. Mice expressing Notch dimerization-deficient (NDD) alleles of Notch1 and Notch2 have defects in multiple tissues that are sensitized to environmental insults. Here, we report that cardiac phenotypes and DSS (Dextran Sodium Sulfate) sensitivity in NDD mice can be ameliorated by housing mice under hypo-allergenic conditions (food/bedding). However, compound heterozygote NDD mice (N1RA/-; N2RA/-) in hypo-allergenic conditions subsequently develop severe hydrocephalus and hemorrhages. Further analysis revealed multiple vascular phenotypes in NDD mice including leakage, malformations of brain vasculature, and vasodilation in kidneys, leading to demise around P21. This mouse model is thus a hypomorphic allele useful to analyze vascular phenotypes and gene-environment interactions. The possibility of a non-canonical Notch signal regulating barrier formation in the gut, skin, and blood systems is discussed.

developmental biology↗

bioRxiv2024

Notch dimerization contributes to maintenance of intestinal homeostasis by a mechanism involving HDAC2.

A tri-protein complex containing NICD, RBPj and MAML1 binds DNA as monomer or, cooperatively, as dimers to regulate transcription. Mice expressing Notch dimerization-deficient (DD) alleles of Notch1 and Notch2 (NDD) are sensitized to environmental insults but otherwise develop and age normally. Transcriptomic analysis of colonic spheroids uncovered no evidence of dimer-dependent target gene miss-regulation, confirmed impaired stem cell maintenance in-vitro, and discovered an elevated signature of epithelial innate immune response to symbionts, the likely underlying cause for heightened sensitivity in NDD mice. TurboID followed by quantitative nano-spray MS/MS mass-spectrometry analyses in a human colon carcinoma cell line expressing either NOTCH2DD or NOTCH2 revealed an unbalanced interactome, with reduced interaction of NOTCH2DD with the transcription machinery but relatively preserved interaction with the HDAC2 interactome suggesting modulation via cooperativity. To ask if HDAC2 activity contributes to Notch loss-of-function phenotypes, we used the HDAC2 inhibitor Valproic acid (VPA) and discovered it could prevent the intestinal consequences of gamma secretase inhibitor (DBZ or DAPT) treatment in mice and spheroids, suggesting synergy between HDAC activity and pro-differentiation program in intestinal stem cells.

developmental biology↗