Biology subjects

Dai, Z.

Publications and source records attributed to Dai, Z..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Molecular Imaging of the TGF-β Activating Integrin αvβ6 Detects Chronic Lung Allograft Dysfunction

TGF-{beta}-activating integrins promote solid-organ fibrosis, suggesting their use as a molecular marker of disease. Chronic lung allograft dysfunction (CLAD), a progressive fibrotic complication that limits lung transplant survival, is driven by intragraft TGF-{beta} activation. However, the expression patterns of TGF-{beta}-activating integrins remain undefined in lung transplants. Single-cell RNA sequencing in a mouse CLAD model revealed high levels of the TGF-{beta}-activating integrin v{beta}6, which was mainly localized to fibrosis-associated Krt8+ transitional alveolar cells (AT1/2), while tolerant transplants lacked both v{beta}6 expression and Krt8+AT1/2 cells. Molecular imaging with a newly developed positron emission tomography radiotracer specific for v{beta}6, [64Cu]Cu-DOTA-A20-K16R, showed significantly higher uptake in CLAD versus tolerant transplants. In contrast, [64Cu]Cu-DOTA-A20-K16R allograft uptake was reduced by treatments that lowered v{beta}6 expression and CLAD severity. Finally, [64Cu]Cu-DOTA-A20-K16R autoradiographic analysis on human explanted lungs with CLAD showed elevated activity that correlated with v{beta}6 expression. Collectively, these findings demonstrate the potential utility of v{beta}6 molecular imaging to detect CLAD pathogenesis.

immunology↗

bioRxiv2025

Landscape Expansion Microscopy Reveals Interactions between Membrane and Phase-Separated Organelles

Landscape Expansion Microscopy (land-ExM) is a light microscopy technique that visualizes both lipid and protein ultrastructural context of cells. Achieving this level of detail requires both superresolution and a high signal-to-noise ratio. Although expansion microscopy (ExM) provides superresolution, obtaining high signal-to-noise images of both proteins and lipids remains challenging. Land-ExM overcomes this limitation by using self-retention trifunctional anchors to significantly enhance protein and lipid signals in expanded samples. This improvement enables the accurate visualization of diverse membrane organelles and phase separations, as well as the three-dimensional visualization of their contact sites. As a demonstration, we revealed triple-organellar contact sites among the stress granule, the nuclear tunnel, and the nucleolus. Overall, land-ExM offers a high-contrast superresolution platform that advances our understanding of how cells spatially coordinate interactions between membrane organelles and phase separations. eTOC SummaryZhuang et al. introduce land-ExM, a super-resolution approach that simultaneously maps protein and lipid ultrastructure in cells with high contrast. This method visualizes 3D interactions between membrane-bound organelles and phase-separated condensates, uncovering organelle contact sites such as stress granules at nuclear tunnels adjacent to nucleoli.

cell biology↗

bioRxiv2025

Acoustoluminescence in Transition Metal and Rare Earth Oxides Beyond 1800 nm for In Vivo Imaging

Acoustoluminescence (AL) is promising for molecular imaging in living tissue, but efficient acousto-optic conversion remains challenging due to the [~]108 times difference in quantum energy between phonons (1 MHz ultrasound) and photons (visible or near-infrared light). Here, we report AL in transition metal oxides (TMOs) and rare earth oxides (REOs) at wavelengths beyond 1800 nm in the short-wave infrared (SWIR) or near-infrared II (NIR-II, 1000-3000 nm) window, under ultrasound excitation at power densities 100-150-fold lower than those required for sonoluminescence in liquids. High-temperature N2/H2-mixed gas reduction was demonstrated as a safe and efficient method to regulate the AL spectra and brightness of TMOs and REOs. TMOs exhibited broadband NIR-II AL emission. Intrinsic emission peaks of rare earth ions and non-conventional luminescence were observed in the AL spectra of REOs under ultrasound excitation. NIR-II AL imaging enabled twice the penetration depth of fluorescence imaging. We developed a scanning focused ultrasound AL imaging system for in vivo tumor imaging through the intact hindlimb, achieving acoustic resolution and penetration depths exceeding one centimeter.

bioengineering↗

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

scE2TM improves single-cell embedding interpretability and reveals cellular perturbation signatures

Single-cell RNA sequencing technologies have revolutionized our understanding of cellular heterogeneity, yet computational methods often struggle to balance performance with biological interpretability. Embedded topic models have been widely used for interpretable single-cell embedding learning. However, these models suffer from the potential problem of interpretation collapse, where topics semantically collapse towards each other, resulting in redundant topics and incomplete capture of biological variation. Furthermore, the rise of single-cell foundation models creates opportunities to harness external biological knowledge for guiding model embeddings. Here, we present scE2TM, an external knowledge-guided embedded topic model that provides a high-quality cell embedding and interpretation for scRNA-seq analysis. Through embedding clustering regularization method, each topic is constrained to be the center of a separately aggregated gene cluster, enabling it to capture unique biological information. Across 20 scRNA-seq datasets, scE2TM achieves superior clustering performance compared with seven state-of-the-art methods. A comprehensive interpretability benchmark further shows that scE2TM-learned topics exhibit higher diversity and stronger consistency with underlying biological pathways. Modeling interferon-stimulated PBMCs, scE2TM simulates topic perturbations that drive control cells toward stimulated-like transcriptional states, faithfully mirroring experimental interferon responses. In melanoma, scE2TM identifies malignant-specific topics and extrapolates them to unseen patient data, revealing gene programs associated with patient survival.

bioinformatics↗

bioRxiv2025

AlterNet: Alternative splicing-aware gene regulatory networkinference

Gene regulatory networks (GRNs) help decode biological systems by identifying how genes interact and regulate cellular processes. However, conventional GRN inference methods operate at the gene-level, overlooking transcript-level variability introduced by alternative splicing (AS). In this work, we present AlterNet, the first GRN inference and annotation pipeline which considers isoform of transcription factors as distinct regulators in a GRN. AlterNet builds on the GRNBoost2 inference algorithm, and includes a transcript plausibility and annotation workflow. We applied AlterNet to expression data from heart tissue, including samples from donors with normal heart function and from patients with different types of cardiomyopathy. The resulting isoform-level GRNs uncovered highly relevant regulatory interactions not detectable at the gene-level. Overall, AlterNet infers transcript-level regulatory network which enable the discovery of novel, biologically relevant regulatory interactions that remain hidden in gene-level GRNs. The source code of AlterNet is available on GitHub https://github.com/bionetslab/AlterNet, and can be installed as a Python package.

bioinformatics↗

bioRxiv2025

Sexually dimorphic role of estrogen receptor α in preserving right ventricular endothelial integrity

Right ventricular (RV) function and adaptation to afterload increase determine survival in pulmonary hypertension (PH). RV adaptation in PH is sexually dimorphic and more preserved in females, mediated by protective estrogen receptor (ER) signaling in cardiomyocytes. However, the effects of ER on RV endothelial cells (RVECs), a critical mediator of RV homeostasis and adaptation, are unknown. We hypothesized that ER exerts sexually dimorphic pro-angiogenic effects on RVECs in vitro and promotes RV vascularization in vivo. Compared to cells isolated from wild-type animals, RVECs from male and female rats with an ER loss-of-function mutation (ERMut) showed reduced ability to form pseudo-vascular networks and migrate. RVECs from female ERMut rats demonstrated increased apoptosis. In a PH model induced by monocrotaline (MCT), female ERMut rats exhibited increased RV hypertrophy and reduced RV capillary density before (10 days) and at the time of established PH (28 days). Capillary rarefaction was associated with increased RVEC apoptosis, and, as identified by single-nucleus RNA-sequencing, by a net loss of the endocardial RVEC sub-population. Differentially expressed gene analysis and pathway analysis identified that capillary and endocardial RVECs from female MCT-PH ERMut rats demonstrated decreased expression of migration pathways and increased expression of apoptosis pathways. These findings reveal a sex-specific endothelial-intrinsic role of ER that is essential for angiogenesis in the RV under both homeostatic and pathological conditions. This effect appears to stem from the enhanced survival and migration capacity of capillary and endocardial RVEC. Collectively, our results identify ER as a potential target for developing sex-specific RV-directed therapies in PH. Translational perspectiveEffects of ER on vascular function in RV failure induced by PH are poorly understood. We unveiled a novel sexually dimorphic role of ER in regulating RV vascularization and RVEC function. Single nucleus RNA-Sequencing in female wild-type and ER loss-of-function rats with PH identified 5 unique RVEC sub-populations under transcriptional control of ER. Our findings provide insights into previously undescribed pro-angiogenic, pro-migratory and anti-apoptotic roles of ER in female RVs and RVECs. Promoting RVEC migration or inhibiting RVEC apoptosis to enhance RV angiogenesis may be viable pathways to maintain RV function in PH patients of either sex. These findings offer novel opportunities and potential therapeutic avenues for preventing or treating RV failure.

cell biology↗

bioRxiv2025

Binary vector origin predictably determines Agrobacterium-mediated transformation outcome across eukaryotic kingdom

Agrobacterium-mediated transformation (AMT) is the primary means of genetic engineering in plants and many fungi, but the factors that control transformation outcomes--efficiency, transgene insertion number, and transgene integrity--remain poorly characterized. Although transformation outcomes dictate an events potential utility in both industrial and academic contexts, AMT remains largely unoptimized for these metrics. Here, we systematically analyze the impact of the transgene-harboring binary vector on transformation outcomes across plant and fungal species. Through a comparison of different plasmid origin of replication (ORI) families and engineered copy number variants, our results reveal that the ORI family--not plasmid copy number--dictates T-DNA insertion number, backbone inclusion, and transformation efficiency, while plasmid copy number tuning alters efficiency without changing ORI family-specific signatures. Independent of plasmid copy number across kingdoms, the most widely used pVS1 ORI-based vectors (e.g. pCambia) result in significantly more insertions per transformant and high levels of transgene silencing compared to the less-utilized pSa ORI family, which enriches for more uniform single insertion events. Furthermore, we demonstrate that ORI-dependent transformation outcomes in yeast predictably reflect those in Arabidopsis. Together, these results lay the foundation for future binary vector design aimed at achieving more predictable, controllable, and optimized transformation outcomes across diverse eukaryotic hosts.

plant biology↗

bioRxiv2025

Distinctive Functionality of Semantic Hubs: Evidence from Semantic Dementia

Semantic cognition relies on a distributed network with multiple candidate hub regions that bind multimodal conceptual information. While the anterior temporal lobe (ATL) is widely regarded as a core semantic hub, the roles of other candidate regions--such as the fusiform gyrus (FFG) and posterior middle temporal gyrus (pMTG)--remain debated, particularly regarding verbal and non-verbal semantic processing within the same sensory modality. This study examined 33 patients with semantic dementia and 20 healthy controls using a comprehensive behavioral battery (word and picture versions of the Pyramid and Palm Trees Test and a word-picture verification task) combined with multimodal neuroimaging, including voxel-based morphometry, diffusion-weighted imaging, and resting-state fMRI. Partial correlation and commonality analyses revealed that (1) the left ATL selectively underpins abstract verbal semantic processing, (2) the left FFG contributes to general semantic processing across verbal and non-verbal stimuli, (3) and the left pMTG plays a critical role in integrating verbal and non-verbal semantic information. White matter tracts linking the left ATL and FFG to the right ATL significantly predicted semantic integration performance, underscoring the importance of inter-hemispheric structural connectivity. Functional measures in contralateral regions, including amplitude of low-frequency fluctuation (ALFF) in the right FFG and degree centrality (DC) in the right pMTG, also predicted integration outcomes, suggesting compensatory network reorganization. These findings highlight functional specialization among semantic hubs and underscore the importance of multimodal, cross-hemispheric approaches for understanding the neural architecture of semantic representation.

neuroscience↗

bioRxiv2025

DEEPReditor-CMG: A deep-learning-based predictive RNA editor for crop mitochondria genomes

C-to-U RNA editing is a pervasive phenomenon in crop mitochondria, playing a pivotal role in the processing of functional proteins encoded by mitochondrial genes and serving as a crucial regulatory mechanism for nuclear control over mitochondrial gene expression. However, identifying editing sites across the mitochondrial genome with high precision remains a formidable challenge. To address this challenge and uncover the potential regulatory patterns of C-to-U RNA editing, this study compiled a comprehensive dataset of mitochondrial genome sequences from 13 crops, including Arabidopsis thaliana, Lactuca sativa var. Capitata, Oryza sativa Japonica, and Zea mays, among others, annotated with editing sites from NCBI. Utilizing TensorFlow 2.0, we constructed a rigorous hyperparameter optimization framework, which facilitated the development of the DEEPReditor-CMG model, demonstrating superior predictive capabilities. Based on the DEEPReditor-CMG model and three interspecies relationship indices, we discovered that species with closer phylogenetic relationships exhibit more similar C-to-U RNA editing mechanisms, providing valuable insights into the evolutionary conservation of RNA editing mechanisms. We further developed executable programs for predicting C-to-U RNA editing sites in crop mitochondrial genomes, leveraging the conserved nature of the crop RNA editing machinery to maximize prediction reliability and uncover new editing sites with great potential. This research not only deepens our understanding of C-to-U RNA editing and post-transcriptional regulatory mechanisms in crop mitochondria but also paves a novel avenue for investigating RNA editing mechanisms. Experimental data, computational code, and applications are publicly accessible at https://github.com/Qinsidong/DEEPReditor-CMG. HighlightsHigh-precision prediction model for C-to-U RNA editing in crops--DEEPReditor-CMG Three interspecies relationship indices describing C to U RNA editing Prediction tools based on the conservation of crop RNA editing mechanisms Open-sourced experimental data, computational code, and applications

bioinformatics↗

bioRxiv2025

The Liver is an Inflammatory Mediator of Pulmonary Arterial Hypertension

The livers contribution to pulmonary arterial hypertension (PAH) pathogenesis remains unclear. We hypothesized that the liver promotes inflammatory injury to the pulmonary endothelium. PAH patients without liver disease with pulmonary artery endothelial cell (PAEC) biopsies were included. Liver serologies and imaging were analyzed by unsupervised classification and regression tree (CART) to identify subclinical liver dysfunction clusters. Two machine-learning models predicted cluster assignment and informed differential expression. PAEC transcriptomes were compared to liver and lung data from monocrotaline and Sugen-Hypoxia rats. Liver fibrosis was assessed in rat and human PAH livers. Among 25 PAH patients (76% female, median age 61 [30 - 84] years), CART identified clusters distinguished by Model for End-Stage Liver Disease Sodium (MELD-Na) [≥]12, predicting higher pulmonary vascular resistance ({beta}=0.5 Wood units per point increase in MELD-Na, 95% CI 0.2-0.8, p=0.005) after adjustment for right atrial pressure. Subjects with MELD-Na [≥]12 had decreased 6-minute walk distance (353 [120 - 576] m vs. 411[300 - 600] m, p=0.03), with upregulation of apelin, beta-catenin, and immune signaling. Rat lung ECs demonstrated survival and hepatic growth-factor signaling, while rat livers showed immune activation. Rat (20.8 vs 16.6 % area stained, p=0.09) and human PAH livers revealed fibrosis despite absent right ventricular failure, supporting a pathogenic lung-liver axis in PAH.

cell biology↗

bioRxiv2025

A universal law of thermodynamics-kinetics coupling shapes enzyme allocation and glycolytic efficiency across species

Efficient use of limited cellular resources is fundamental to metabolism. Although flux optimization is widely recognized as a central objective of metabolic networks, how flux efficiency influences the allocation of the metabolic proteome remains unclear and lacks direct validation. Here, we derive a simple analytical relationship linking the equilibrium constant and the catalytic-abundance quotient of reactions within a pathway that defines the condition for maximal efficiency. We refer to this principle as the law of thermodynamics-kinetics coupling. By integrating reaction thermodynamics, enzyme kinetics, transcriptomic, and proteomic data, we show that glycolytic enzyme allocation consistently obeys this law across evolutionarily distant species. Moreover, the drive to optimize glycolytic efficiency is strengthened under oncogenic signaling and limited cellular budget for glycolytic enzymes. These findings establish a universal principle governing enzyme allocation in metabolic pathways and reveal key determinants of efficiency optimality in glycolysis. Significance statementCurrent models of metabolic optimality either rely on coarse-grained proteome allocation or constraint-based simulations, largely neglecting the fundamental constraints imposed by enzyme kinetics and thermodynamics on pathway efficiency. Here, we derive and validate a universal law of thermodynamics-kinetics coupling that robustly governs the allocation of glycolytic enzymes across species under optimal efficiency. This study has three major advances: it reveals universal economic principles of metabolism with simple, generalized mathematical form, uncovers determinants underlying the heterogeneity of metabolic efficiency optimization, and provides a practical blueprint for efficiency optimization of engineered pathways.

systems biology↗

bioRxiv2025

Combinatorial factorizable libraries outperform enumerated and random libraries for antibody discovery

The effective use of high-throughput functional assays to discover novel biological therapeutics requires a diverse library of desirable candidates. Here we design candidate antibody libraries using factorizable neural networks (FNNs) that permit the economic synthesis of factorizable libraries that are depleted of non-specific binders. We experimentally evaluated an FNN designed antibody CDR-H3 factorizable library that is designed to contain binders to peptide-MHC (pMHC) complexes with depletion of library sequences that exhibit non-specific pMHC binding. The factorizable library comprises 104 prefixes that were randomly combined with 104 suffixes. We find that it contains more viable candidates than designed libraries with the same DNA synthesis budget on our pMHC binding task. FNNs make it possible to efficiently computationally design combinatorial libraries, a task that is not possible with conventional methods.

immunology↗

bioRxiv2025

Hypoimmunogenic human motor neurons induced from iPSCs in vivo substantially ameliorate ALS disease in large animal models

Stem cell-based therapy holds great potential for substituting degenerated motor neurons (MNs) in amyotrophic lateral sclerosis (ALS). Missing protocols for advanced differentiation of transplanted cells into MNs, immune rejection, and the lack of suitable ALS models for preclinical trials have slowed the development of effective therapies. Here, we employed multiplex genetic-editing to generate a novel human pluripotent stem cell line containing doxycycline (Dox)-inducible MNs-specific transcription factors and comprehensively modified immunomodulatory genes. We transplanted these cells into the spinal cord of ALS large animal models (SOD1G93A pigs and TIA1P362L rabbits), which faithfully recapitulate pathologies and symptoms observed in ALS patients. The transplanted cells could efficiently differentiate into functional MNs upon Dox treatment in vivo, distribute throughout the spinal cord and motor cortex via extensive migration, survive long-term without the need for immunosuppression. Notably, these MNs integrated into host neural circuits, as evidenced by their long projection of peripheral axons to target muscle and reformation of neuromuscular junctions. As result, pathologies and motor deficits were substantially ameliorated in both animal models. One Sentence SummaryHypoimmunogenic human motor neurons induced from iPSCs in vivo reform neuromuscular junctions and ameliorate ALS disease in pig and rabbit models.

neuroscience↗

bioRxiv2025

Methionine γ-lyase Traps Cofactor Pyridoxal-5'-phosphate through Specific Serine-Mediated Affinity

Pyridoxal-5'-phosphate (PLP), the ubiquitous and ancient cofactor, plays important roles in enzymatic elimination, transamination and other reactions. The catalytic efficiency of PLP-dependent enzymes is significantly higher than that of free PLP. The recruitment of PLP from the environment by the enzymes, particularly through interactions outside the active site, is the key step determining the occurrence of PLP-mediated catalysis. However, the precise mechanism by which enzymes recruit PLP remains elusive. Methionine {gamma}-lyase (MGL), a PLP-dependent enzyme, catalyzes the degradation of L-methionine, thereby suppressing cancer cell proliferation through serum or dietary methionine depletion. Here, we report the crystal structure of yMGL, which belongs to a newly identified subgroup of cystathionine {gamma}-lyases, in complex with L-methionine and PLP. Through truncating the C-terminal domain of yMGL both in vitro and in vivo, we demonstrated that this domain, outside the canonical PLP-binding domain, is essential for the specific interaction between yMGL and PLP, as well as for efficient L-methionine catabolism. A conserved Ser in the C-terminal domain, positioned at the active-site entrance of MGLs, confers specificity for PLP. These findings elucidate a previously uncharacterized mechanism of PLP recruitment by MGLs and promote rational design of MGLs with tailored cofactor selectivity and catalytic performance.

biochemistry↗

bioRxiv2025

KLF5 controls subtype-independent highly interactive enhancers in pancreatic cancer to regulate cell survival

Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal cancer with a 5-year survival rate of 13%. Despite recent molecular stratification of tumors into distinct classical and basal-like cell states, most tumors are heterogeneous contain of both subtypes. Therefore, therapeutic approaches targeting one subtype may not be suitable for PDAC therapy. Here, we integrated chromatin accessibility (ATAC-seq), genome-wide occupancy (ChIP-seq) for epigenetic status (H3K27ac) and H3K4me3-anchored chromatin topology (HiChIP) to uncover subtype-independent highly interactive enhancers that interact with essential genes in PDAC. Motif analysis revealed these common enhancers were bound by KLF5 with subsequent depletion leading to decreased cell viability via induction of apoptosis. To elucidate the transcriptional and epigenetic mechanisms by which KLF5 functions in PDAC, we employed rapid depletion of KLF5 with dTAG technology and profiled the effects on the open and active chromatin landscape and transcription with nascent RNA and mRNA-seq over time. Enhancer inactivation via KRAB domain Zim3-dCas9 fusion protein confirmed KLF5-bound enhancers regulate target genes, including the anti-apoptotic gene BCL2L1. Multiplex immunofluorescence confirmed co-staining of KLF5 and Bcl-xL in patient samples and overexpression of Bcl-xL rescued the induction of apoptosis after KLF5 depletion. Taken together, this study provides new insights into common mechanisms to target highly heterogeneous PDAC tumors. TeaserKLF5 controls subtype-independent highly interactive enhancers to regulate cell viability in pancreatic cancer.

cancer biology↗

bioRxiv2025

In vivo Calcium Imaging in the Near-Infrared II Window

Non-invasive deep-tissue calcium imaging of live mammals with high sensitivity and resolution is challenging owing to light scattering experienced by traditional calcium ion (Ca2+) indicators with excitation and emission wavelengths within 400-750 nm. Here, we report near-infrared II (NIR-II) calcium imaging beyond 1000 nm by exploring a natural protein derived from a bacterium (Thermochromatium tepidum) living in a calcium carbonate-rich environment. This highly photostable fluorescent protein enables NIR-II imaging of intracellular Ca2+ responses to stimulant drugs in cultured mammalian cells with sensitivity comparable to that of visible Ca2+ indicators. We achieve in vivo NIR-II imaging of Ca2+ transients in response to two different tumor treatment strategies in intact tumors with high sensitivity, resolution, and contrast, opening the possibility of non-invasive deep-tissue calcium imaging for assessing treatment efficacy longitudinally. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/661443v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@149504eorg.highwire.dtl.DTLVardef@37722borg.highwire.dtl.DTLVardef@2878a7org.highwire.dtl.DTLVardef@1091d0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

JASMINE: A powerful representation learning method for enhanced analysis of incomplete multi-omics data

Integrative analysis of multi-omics data provides a more comprehensive and nuanced view of a subjects biological state. However, high-dimensionality and ubiquitous modality missingness present significant analytical challenges. Existing methods for incomplete multi-omics data are scarce, do not fully leverage both modality-specific and shared information, and produce task-biased representations. We propose JASMINE, a self-supervised representation learning method for incomplete multi-omics data that preserves both modality-specific and joint information and enhances sample similarity structure. JASMINE produces embeddings that achieve superior performance across multiple tasks for two different incomplete multi-omics datasets while requiring only a single round of training per dataset.

bioinformatics↗