Biology subjects

Yang, Z.

Publications and source records attributed to Yang, Z..

At least 199 records · Page 11Linked to original sources

bioRxiv2025

Dynamic early recruitment of GAK-Hsc70 regulates coated pit maturation

Clathrin-mediated endocytosis (CME) is the process by which clathrin assembles on the plasma membrane to form clathrin-coated pits (CCPs), which then invaginate, accumulate cargo and are released by fission from the membrane to form clathrin-coated vesicles (CCVs). A transition of nascent CCPs from flat-to-curved has been observed by various methods. However, what drives this transition remains unknown and controversial. GAK and its chaperone protein, Hsc70, are well-known to mediate clathrin release from CCVs and several studies have observed a late burst of GAK recruitment as CCVs form. Other studies have proposed that early recruitment of GAK-Hsc70 could function to provide the necessary energy source to remodel nascent flat clathrin lattices, replacing hexagons with pentagons and enabling a gain of curvature and invagination of the growing CCP; however, direct functional evidence is lacking. Here we show that GAK knockdown inhibits CCP formation and invagination. Furthermore, mutations in the J domain of GAK that abolish Hsc70 recruitment to and activation at CCPs, lead to the accumulation of GAK at CCPs, hinder CCP stabilization and invagination and result in a striking increase in the proportion of short-lived, abortive CCPs. These findings support the hypothesis that GAK-Hsc70 promotes the turnover and remodeling of nascent clathrin assemblies required for curvature development during CME. Significance StatementGAK and its chaperone protein, Hsc70, are known to be recruited to clathrin-coated vesicles (CCVs) to mediate clathrin uncoating. Previous studies have proposed that early recruitment of GAK-Hsc70 to CCPs could function to remodel nascent flat clathrin lattices, replacing hexagons with pentagons and enabling a gain of curvature of the assembling polymeric coat. However, there are conflicting views, and direct functional evidence is lacking. Here we show that GAK knockdown inhibits CCP formation and invagination. A detailed domain-specific mutational analysis of GAK pinpointed the importance of J domain-Hsc70 interactions in regulating crucial early steps of CME including CCP stabilization and invagination. These findings support a hypothesis that GAK-Hsc70 promotes turnover of clathrin at nascent CCPs required for curvature development.

cell biology↗

bioRxiv2025

RAPID: Reliable and efficient Automatic generation of submission rePortIng checklists with large language moDels

ImportanceMedical reporting guidelines are significant in improving the transparency, quality, and integrity of medical research, particularly in randomized clinical trials; adherence to these guidelines supports research interpretability and has direct implications for downstream applications, such as patient treatment. However, with over 600 distinct reporting guidelines, manual assessments are often time-consuming and labor-intensive. ObjectiveTo evaluate an automated reporting checklist generation tool using large language models and retrieval augmentation generation technology, called RAPID. Design, Setting, and ParticipantsThis study used large language models to design a retrieval augmentation generation architecture and collected published journal articles as training and validation sets to optimize prompts within the framework and comprehensively evaluate the performance of the framework. Medical reporting experiments were collected from 50 randomized controlled trials without the intervention of AI tools and 41 randomized controlled trials with the intervention of AI tools. Main Outcomes and MeasuresFor effective evaluation of the performance of this tool, a classification accuracy metric (Reported/Not Reported) defined as the number of correct judgments divided by all judgments and a content consistent score metric defined as the number of contents retrieved by the tool that are the same as those retrieved by researchers divided by the total number of judgments were calculated. ResultsThe RAPID tool uses the widely used Word document and Portable Document Format as an input file. Fifty published journal articles without the intervention of AI tools and 41 published journal articles with the intervention of AI tools were collected as CONSORT and CONSORT-AI datasets. All of the CONSORT reporting items (37) were included in the tool. RAPID achieved a high average accuracy rate of 92.11% and a content consistency score of 81.14% on the CONSORT dataset. Of the CONSORT-AI reporting items, 11 items related to the intervention of AI tools were included in the tool. RAPID achieved an average accuracy of 83.81% with a content consistency score of 72.51% on the CONSORT-AI dataset. For these two reporting guidelines, a training set of 5 articles was selected from each dataset to refine the prompts used in the tools for CONSORT and CONSORT-AI reporting checklist. The validation set of the remaining articles was used to assess the performance of the RAPID. The RAPID tool used the Word document and Portable Document Format of the articles as input files. A RAPID graphical user interface was built using JavaScript and Vue. Conclusions and RelevanceThe RAPID tool is designed to assist in the reporting of various types of trials. RAPID has strong scalability, which can be easily adapted to different medical reporting guidelines without transfer learning on a large dataset. RAPID may effectively save time and improve working efficiency for different user groups, for example, 1) simplifying the submission process and improving report quality by verifying manuscript completeness for medical authors; 2) facilitating evaluation of report quality for medical researchers; 3) expediting manuscript distribution for medical editors; and 4) identifying reporting deficiencies and providing deeper insights for review comments for reviewers. Key PointsO_ST_ABSQuestionC_ST_ABSCan large language model tools automatically generate medical reporting checklists for manuscripts of different types of clinic trials? FindingsAn automated reporting checklist generation tool using large language models and retrieval augmentation generation technology, RAPID, was developed. RAPID was fully evaluated on all items across two separate datasets related to the Consolidated Standards of Reporting Trials (CONSORT) and CONSORT-AI reporting guidelines. In the first dataset corresponding to CONSORT, RAPID achieved an average accuracy of 92.11%, while in the second dataset associated with CONSORT - AI, it reached an average accuracy of 83.81%. Additionally, RAPID is highly scalable. It can be easily and smoothly adapted to different medical reporting guidelines without transfer learning on a large dataset. MeaningRAPID can effectively save time and improve working efficiency for different user groups such as medical authors, researchers, editors, and reviewers.

bioinformatics↗

bioRxiv2025

Pneumo-Typer: a high-throughput capsule genotype visualization tool with integrated serotype and sequence type prediction for Streptococcus pneumoniae

BackgroundStreptococcus pneumoniae persists as a leading global pathogen, with current capsule-based vaccines like PCV13 offering limited coverage against its extensive serotype diversity (>100 serotypes). This restricted coverage drives the emergence of non-vaccine serotypes. Moreover, vaccine efficacy is further compromised by immune evasion caused by capsule genotype (CapT) variations within vaccine-covered serotypes, while existing genome-based tools lack robust analytical capabilities for CapT. ResultsWe developed Pneumo-Typer, a CapT visualization tool enabling rapid identification of CapT variations in S. pneumoniae. Application to 17,407 publicly available genomes from the NCBI database revealed widespread CapT variations across vaccine-covered serotypes, providing critical insights for optimizing vaccine formulations. In addition, Pneumo-Typer integrates high-accuracy serotype prediction (98.44% accuracy across 93 serotypes) and multilocus sequence typing (ST), facilitating comprehensive genomic surveillance. Besides, CapT and ST information can assist in serotype determination. Pneumo-Typer enables integrated analysis of serotype-CapT-ST relationships, demonstrating that while most serotypes associate with multiple STs and CapTs, ST and CapT lineages evolve independently. Strikingly, multi-serotype serogroups exhibited pronounced CapT diversity, suggesting evolutionary processes driving serogroup expansion through CapT plasticity. ConclusionsIn summary, Pneumo-Typer is an integrated platform for genomic surveillance of pneumococcal populations. By resolving previously underexplored serotype-CapT-ST linkages, the tool provides a framework for next-generation vaccine design, emphasizing the need for vaccine formulations that address both serotype replacement and CapT-driven immune evasion.

bioinformatics↗

bioRxiv2025

Dietary cysteine enhances intestinal stemness via CD8+ T cell-derived IL-22

A critical question in physiology is understanding how tissues adapt and alter their cellular composition in response to dietary cues. The mammalian small intestine, a vital digestive organ that absorbs nutrients, is maintained by rapidly renewing Lgr5+ intestinal stem cells (ISCs) at the intestinal crypt base. While Lgr5+ ISCs drive intestinal adaptation by altering self-renewal and differentiation divisions in response to diverse diets such as high-fat diets and fasting regimens, little is known about how micronutrients, particularly amino acids, instruct Lgr5+ ISC fate decisions to control intestinal homeostasis and repair after injury. Here, we demonstrate that cysteine, an essential amino acid, enhances the ability of Lgr5+ ISCs to repair intestinal injury. Mechanistically, the effects of cysteine on ISC-driven repair are mediated by elevated IL-22 from intraepithelial CD8{beta}+ T cells. These findings highlight how coupled cysteine metabolism between ISCs and CD8+ T cells augments intestinal stemness, providing a dietary approach that exploits ISC and immune cell crosstalk for ameliorating intestinal damage.

cell biology↗

bioRxiv2025

Unraveling the mechanism of 1-deoxynojirimycin (DNJ) accumulation: the role of SWEET3 in mulberry chloroplasts

Transporters are crucial for the accumulation and secretion of plant metabolic products. 1-Deoxynojirimycin (DNJ), a natural compound widely distributed in nature and known for its medicinal properties, has production limitations in microorganisms and herbaceous plants. Mulberry leaves, being easy to harvest and growing rapidly, are the main source of DNJ. However, the current production from mulberry is insufficient to meet the demand. Improving DNJ content in mulberry and thereby reducing production costs is a significant challenge. We first used a green fluorescent tag to visualize the localization of DNJ and found that DNJ highly accumulates in the chloroplasts of mulberry leaves but not in callus tissue. The sugar transporter gene SWEET3, which is highly expressed in mulberry leaves but not in callus, was shown to have DNJ transport capability. Molecular docking analysis revealed that the acidic amino acid residues E68 and D126 in the SWEET3 protein are potential binding sites for DNJ, and both neutral and basic mutations at these sites significantly reduced the ability to DNJ-transporting ability of SWEET3. Furthermore, transient overexpression or RNA interference of SWEET3 in mulberry leaves significantly increased or decreased DNJ content, respectively. Similarly, stable overexpression of the SWEET3 in mulberry hairy roots led to an enhancement in DNJ content within the roots. Our results demonstrated that SWEET3 is essential for DNJ accumulation in mulberry. The study represents a breakthrough in increasing DNJ yield in mulberry through the key role of transporters and identify specific molecular targets required for developing mulberry germplasm with increased DNJ levels.

plant biology↗

bioRxiv2025

Organisation of axial regions of isolated mitotic chromosomes visualised by cryo correlative light and electron tomography

The formation of mitotic chromosomes is essential for the accurate segregation of genetic material during cell division. Increasing evidence suggests that chromosome formation involves the reorganization of DNA into loops anchored within chromosomal axial regions, whose structural organization remains insufficiently characterized. Taking advantage of DT40 cells, an avian cell model characterized by the presence of a range of chromosome sizes from 3.2-197 Mb, we have established a preparation of entire close-to-native native mitotic chromosomes for cryogenic correlative light and electron microscopy (cryo-CLEM). The size of the smallest chromosomes allows imaging of their axial regions without further thinning. Cryo-electron tomography of the chromosome axial regions reveals the presence of heterogeneous non-histone macromolecular densities (NHMDs), approximately 30-45 nm in size, interspersed within chromatin/DNA regions. We propose that NHMDs may contain condensins and contribute to chromosome architecture. In addition to NHMDs, we identified dense clusters of particles, similar in size, near the chromosome surface, likely associated with ribosomal components. To quantitatively differentiate NHMDs from these surface clusters, we developed an analytical approach based on particle interspacing and spatial distribution within the chromosome volume. By establishing a cryo-CLEM workflow for whole, near-native mitotic chromosomes, our study provides a foundation for investigating their ultrastructural architecture.

cell biology↗

bioRxiv2025

Mouse Cortical Cellular Diversification Through Lineage Progression of Radial Glia

Cortical radial glia (RGs) sequentially generate pyramidal neurons (PyNs) and glia. In this study, we investigated the cell intrinsic programs underlying cortical cellular diversification using time-series scRNA-seq and snATAC-seq on purified mouse cortical progenitors across embryonic and postnatal stages. Our data revealed that RGs transition from early to late over time, sequentially producing intermediate neuronal progenitors (INPs) and intermediate glial progenitors (IGPs). While INPs expand exclusively to generate PyNs, IGPs progress from young to old, sequentially producing cortical astrocytes, oligodendrocytes, and olfactory bulb interneurons. We constructed comprehensive molecular maps that reflect cell lineage progression. In particularly, we found that chromatin accessibility drives cortical cellular diversification by restricting broadly expressed transcription factors to specific stages and cell types. Developmental changes in chromatin accessibility confine Lhx2-induced neurogenesis to early-stage RGs, leading to the loss of neurogenic competence and the acquisition of gliogenic competence as corticogenesis progresses.

neuroscience↗

bioRxiv2025

Rhamnose-mediated modulation of hair follicle growth: insights from chemical genomics

Pursuing compounds capable of stimulating hair follicle growth or regeneration presents a significant challenge in dermatological research. Dermal papilla (DP) cells, which serve as a dynamic niche for hair follicle stem cells, are often used to identify hair growth-promoting agents as a screening model. Here, we integrated human scalp single-cell RNA sequencing data with human DP cells (hDPCs) gene expression profiles to develop a gene panel for assessing hair follicle inductive potential, then applied a high-throughput sequencing-based high-throughput screening (HTS2) method to quantify the gene expressions of hDPCs perturbed by over 2000 small molecules. Notably, rhamnose was identified as a compound that restored the expression of hair-inducing genes in hDPCs. More importantly, the topical application of rhamnose accelerated hair follicle regeneration by promoting hair cycle into the anagen phase. Transcriptome and central carbon metabolism analyses revealed that rhamnose induced glucose metabolism remodeling favoring glycolysis in mice. A similar phenotype was also observed in rhamnose-treated hDPCs, as demonstrated by glycolysis and mitochondrial stress tests. The present study introduces a novel methodology for evaluating hair-inducing agents and provides valuable insights into the cellular and molecular mechanisms underlying the hair growth-promoting effects of rhamnose. These findings highlight the potential for the therapeutic application of rhamnose in the treatment of alopecia.

pharmacology and toxicology↗

bioRxiv2025

Achievement-Based Differences in Cognitive-Emotional Interplay During Classroom Learning: A Multimodal Analysis with Experience Sampling Method

BackgroundThe relationship between cognition and emotion during learning is crucial for educational theories and has been under debate for a long time, from the ancient philosophy to current scientific analyses. However, the relationship may not be uniform and may vary across diverse individual groups. AimsTherefore, this study aims to explore whether the relationship between cognition and emotion varies across different student groups. Furthermore, it examines whether neurophysiological evidence can provide insights into such group differences. SampleThe study involved 22 high school students (11 high-performing and 11 low-performing) over 13 math lessons. Surveys were administered three times during each lesson, yielding a multilevel dataset with 777 samples. MethodsThe experience sampling method was employed to gather data on cognitive and emotional states periodically, as well as their regulations. Simultaneously, multimodal neurophysiological data, including electroencephalograph (EEG), electrodermal activity (EDA), and photoplethysmography (PPG), were collected during classroom learning to analyze the relationship further. ResultsCognitive state, cognitive regulation, emotional state, and emotional regulation were highly correlated overall. In high-performing students, the association was higher than that in low-performing students, especially at the level of within-subject repeated-measures. Multimodal data revealed the common neurophysiological basis of the correlated variation between cognition and emotion, and highlighted different neurophysiological patterns between high and low achievers. ConclusionsThe joint evidence from the experience sampling survey and neurophysiological measures reveals that the cognitive-emotional relationship differs by academic achievement levels, with high achievers revealing a more consistent variation between cognition and emotion. Such co-variation shares a common neurophysiological pattern with features associated with high student-teacher interaction and high concentration, further explaining the group differences.

neuroscience↗

bioRxiv2025

Constitutive expression of cardiomyocyte Klf9 precipitates metabolic dysfunction and spontaneous heart failure.

Metabolic adaptations and flexibility during development and disease play an essential in cardiomyocyte function and survival. We recently reported Glucocorticoid receptor (GR)-Kruppel-like factor 9 (Klf9) axis in mediating metabolic adaptations in cardiomyocytes stimulated with Dexamethasone. Klf9 expression decreases in hypertrophic and failing hearts, suggesting its importance in cardiac homeostasis and its potential contribution to dysfunction under pressure overload. Genome wide Klf9 occupancy in adult hearts revealed 2,242 genes directly associated with Klf9, with enrichment in metabolic pathways, autophagy, ubiquitin-mediated proteolysis, and cellular senescence. We generated and characterized a conditional cardiac specific Klf9 knock-In (Klf9KI) mice, which developed progressive cardiac hypertrophy, cardiac dysfunction and cardiac failure by 8wks of age, with mortality by 12-14wks. RNA-seq analysis at 1wk, 4wks, and 8wks showed stage-specific transcriptional changes. At 1 week, 64.81% of differentially expressed genes were downregulated, aligning with Klf9s predicted role as a transcriptional repressor. At 4wks and 8wks, more genes were upregulated, suggesting more of secondary targets in response to cardiac phenotype. KEGG pathway analysis showed dysregulation in lipid, carbohydrate and glutathione metabolism, transcriptional regulation, apoptosis, and innate immunity. Untargeted Metabolomics at 4wks identified significant alterations in tissue metabolite levels, particularly in pathways involving fatty acid metabolism, amino acids, and glucose, correlating with transcriptome data. Mitochondrial function assays revealed progressive dysregulation. At 2 weeks, complex I activity was significantly reduced, while complex II and IV activities were partially preserved. By 4 weeks, all measured respiratory complexes showed significant declines, consistent with decline in mitochondrial function. These mitochondrial deficits preceded overt cardiac dysfunction and likely contributed to the development of hypertrophy and failure. In conclusion, constitutive Klf9 overexpression disrupts transcriptional and metabolic homeostasis, driving progressive hypertrophy, cardiac dysfunction, and failure.

cell biology↗

bioRxiv2025

Plakophilin-2 Coordinates Energy Metabolism and Contractility in Cardiomyocytes, Revealing Its Roles beyond Desmosomes

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a familial cardiac disease associated with ventricular arrhythmias and an increased risk of sudden cardiac death. Mutations in the desmosome gene Plakophilin-2, PKP2, lead to reduction in PKP2 protein and collapse of desmosomes that is known to compromise contractility and electrical stability of cardiomyocytes. Our previous studies demonstrated the efficacy of adeno-associated virus 9 (AAV9)-mediated restoration of PKP2 expression in a cardiac specific knock-out mouse model of Pkp2 and revealed profound changes in mRNA signatures of metabolic enzymes that were reversed by the gene replacement approach. In this study, we used PKP2-deficient mouse hearts and human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to identify changes in steady-state metabolite levels associated with impaired lipid homeostasis, glycolysis, and glucose oxidation. These metabolic phenotypes align with human ARVC metabolic data and reflect an intrinsic impairment of cellular energy metabolism. Here we showed for the first time that these intracellular metabolic defects were associated specifically with poor contractility of cardiomyocytes. AAV9:PKP2 restored contractility, improved electrophysiological properties and Ca2+ transients. In contrast, we observed that treating PKP2-deficient cardiomyocytes pharmacologically with small molecule metabolic enhancers improved contractility but not electrophysiological properties and Ca2+ transients, suggesting differential sensitivity of structure-mediated functions in response to metabolic perturbance. Our study modeled and revealed a direct intracellular connection between compromised PKP2 function and metabolic impairment. We proposed that an increased risk of decoupling energy-responsive contractility from less energy-responsive electrical activities can be a new arrhythmogenic mechanism, potentially responsible for exercise-triggered cardiac adversity in ARVC disease development and progression.

cell biology↗

bioRxiv2025

Intracellular tension relaxation engineered through D-enantiomeric hydrogel maneuvers neurogenesis and immunomodulation to facilitate spinal cord repair

Microenvironmental mechanics regulate morphogenesis and post-injury inflammation, however, the fragile mechanical strength and oxidative physiological environment hinder precise and consistent mechanical management after spinal cord injury (SCI). Here, we engineered self-assembling hydrogels of enantiomeric peptides with neural tissue- matching mechanical properties to persistently manipulate mechanosensing and mechanotransduction through stereo conformational recognition and consequent protein affinity difference. While hindering proliferation and morphogenesis in non-neural cells, D-hydrogel-induced intracellular tension relaxation triggered neurogenesis and ECM remolding in astrocytes, while simultaneously suppressing pro-inflammation and promoting pro-regeneration in microglia, which together enable neuroprotection from degeneration and enhance functional recovery in severe SCI rat models. These effects are mediated through neurogenic morphology changes resulting from cytoskeletal tension relaxation, leading to the opening of mechanosensitive ion channels in the cellular membrane, chromatin unfolding, and YAP nuclear translocation. This exclusive D- hydrogel-dependent neurogenesis, triggered by intracellular tension relaxation, revealed a neural-specific response to mechanical cues and provided a targeted tissue repair strategy for nerve injury. TeaserIntracellular tension relaxion activates morphogenesis specifically in neural cells through reversing neurogenic cellular morphology.

neuroscience↗

bioRxiv2025

MAIT cell deficiency exacerbates neuroinflammation in P301S human tau transgenic mice

The role of immune cells in neurodegeneration remains incompletely understood. Our recent study revealed the presence of mucosal-associated invariant T (MAIT) cells in the meninges, where they express antioxidant molecules to maintain meningeal barrier integrity. Accumulation of misfolded tau proteins are a hallmark of neurodegenerative diseases. The role of MAIT cells in tau-related neuroinflammation and neurodegeneration, however, remains unclear. Here we report that the meninges of P301 mutant human tau transgenic mice had increased numbers of MAIT cells, which retained their expression of antioxidant molecules. Mr1-/-P301S mice that lacked MAIT cells exhibited increased tau pathology and hippocampus atrophy compared to control Mr1+/+ P301S mice. Adoptive transfer of MAIT cells reduced tau pathology and hippocampus atrophy in Mr1-/- P301S mice. Meningeal barrier integrity was compromised in Mr/-/-P301S mice, but not in control Mr1+/+ P301S mice. A distinctive microglia subset with proinflammatory gene expression profile (M-inflammatory) was enriched in the hippocampus of Mr1-/- P301S mice. The transcriptomes of the remaining microglia in these mice also shifted towards a proinflammatory state, with increased expression of inflammatory cytokines, chemokines, and genes related with ribosome biogenesis and immune responses to toxic substances. The transfer of MAIT cells restored meningeal barrier integrity and suppressed microglial inflammation in the Mr1-/- P301S mice. Together, our data indicate an important role for MAIT cells in regulating tau-pathology-related neuroinflammation and neurodegeneration.

immunology↗

bioRxiv2025

Using green space virtual reality to prevent stress-induced working memory impairment

Exposure to green space is associated with both physical and mental health benefits, including the potential to buffer acute stress responses, positioning it as a promising non-pharmacological approach to protect cognitive functions against stress. However, urban residents often face significant barriers in accessing green spaces, which are not equitably distributed. Virtual Reality (VR) technology offers a potential solution by simulating green space that could be made accessible to a broader demographic. Here, we explored whether VR-stimulated green space could dampen biological stress responses (i.e., heart rate and cortical response) and prevent stress-induced working memory (WM) impairment. Healthy young participants underwent acute stress induction followed by 15 minutes of VR-based green space (N=36) or control empty space (N=30) intervention. Although we observed the expected stress-induced increase in heart rates and elevated cortisol levels under stress, VR green space exposure failed to temper cortisol responses compared to the control VR space. Further, VR green space exposure did not bring benefits to protect working memory performance under stress across three WM tasks. Applying a Bayesian analysis approach throughout enabled us to find substantial evidence for the absence of an effect of VR-based green space exposure on biological markers of acute stress responses and working memory performance. Our findings suggest that VR-generated green space may not effectively replicate the stress-buffering effects of actual green space exposure. We discussed the implications of our findings regarding the potential and limitations of using VR or green space exposure to buffer stress responses.

neuroscience↗

bioRxiv2024

CLCNet: a contrastive learning and chromosome-aware network for genomic prediction in plants

Genomic selection (GS) leverages genome-wide markers and phenotypes to predict breeding values, with its effectiveness largely dependent on the accuracy of genomic prediction (GP) models. However, GP methods often struggle to capture inter-individual variability and are limited by the curse of dimensionality, where the number of SNPs far exceeds the sample size. To address these challenges, we present CLCNet (Contrastive Learning and Chromosome-aware Network), a novel deep learning framework that integrates contrastive learning and chromosome-aware feature modeling. CLCNet comprises two key components: (i) a contrastive learning module that enhances the models ability to capture fine-grained, genotype-dependent phenotypic differences among individuals, and (ii) a chromosome-aware module that captures structured feature selection at both chromosome and genome levels, thereby distilling the most informative SNPs. We evaluated CLCNet across four crop species, covering ten agronomically important traits, and compared it with a diverse set of classical linear, machine learning, and deep learning models. CLCNet achieved superior prediction performance, with statistically significant improvements in Pearson correlation coefficient (PCC), ranging from 0.34% to 12.19% over baseline, together with reduced mean squared error (MSE). Performance gains were more pronounced for traits with moderate linkage disequilibrium (LD; r2 = 0.21-0.36) and high heritability (h2 > 0.66), such as those in maize, rapeseed, and soybean. For cotton traits characterized by high LD (r2 = 0.74) and lower heritability (h2 < 0.50), CLCNet maintained robust performance without degradation. Overall, these results demonstrate that CLCNet is an effective framework for improving genomic prediction accuracy and holds strong potential for practical applications in plant breeding. Short abstractCLCNet is a novel deep learning framework for genomic prediction that integrates contrastive learning with chromosome-aware feature selection. By jointly modeling inter-individual genotype-phenotype variation and chromosomal genomic structure, CLCNet improves prediction accuracy under high-dimensional, low-sample-size conditions. Across four crop species and ten agronomic traits, CLCNet consistently outperformed classical statistical, machine learning, and existing deep learning models. The framework also identified biologically relevant SNPs and candidate genes, demonstrating its potential for practical applications in genomic selection and computational plant breeding. Key pointsO_LIWe propose CLCNet, a multi-task deep learning framework that integrates contrastive learning with chromosome-aware feature selection for genomic prediction, under high-dimensional, low-sample-size conditions. C_LIO_LIThe chromosome-aware module explicitly exploits genomic structural information to select representative and informative SNPs across chromosomes. C_LIO_LIContrastive learning improves model robustness by stabilizing representation learning and reducing the influence of random effects across samples. C_LIO_LIBy complementing GWAS analyses, CLCNet provides additional insights into genotype-phenotype relationships with potential relevance for gene discovery. C_LI Biographical NoteJiangwei Huang is a PhD candidate at the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences. His research focuses on genomic prediction, deep learning, and computational plant breeding. Zhihan Yang is a PhD candidate at the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences. Her research interests include genomic prediction and bioinformatics. Rongcheng Han is an associate professor at the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences. His research focuses on bioinformatics and plant phenomics. Yuqiang Jiang is a professor at the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences. His research interests include plant genomics, plant phenomics and genetic improvement. Organization descriptionThe Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, is a leading research institute focusing on genetics, genomics, molecular breeding, bioinformatics, and systems biology in plants and animals.

genomics↗

bioRxiv2024

Bovine Formative Embryonic Stem Cell Plasticity in Embryonic and Extraembryonic Differentiation

Bovine embryonic stem cells (bESCs) can greatly enhance understanding of bovine embryonic development and applications for disease-resistance, biomedical and zoonotic pre-clinical models. However, formative bESCs with distinct morphology and complete differentiation capacity are still unreported. We document here the generation of bESCs which are pluripotent both in vitro and in vivo, and efficiently converted into neural progenitor cells (NPCs) and primordial germ cell-like cells (PGCLCs) by direct differentiation. These cells exhibited distinct metabolic features from human and mouse ESCs and early embryos. Formative bESCs contributed to a wide range of cell types within embryonic and extraembryonic tissues after aggregating with mouse and bovine embryos. The establishment of bovine formative ESCs with dual developmental plasticity represents a milestone for agricultural biotechnology and decoding the underlying mechanism of bona fide bovine pluripotency. Summary statementGenerating bovine ESCs would greatly enhance understanding of bovine embryonic development and bioengineering of cattle for disease-resistance, biomedical and zoonotic pre-clinical models.

developmental biology↗

bioRxiv2024

Multiomic foundation model predicts epigenetic regulation by zero-shot

Deciphering cell type-specific perturbation effects on genes and cellular states demands considerable experimental resources. To overcome this challenge, we propose Perturbation Transformer (PertFormer), a foundation model to uncover functional and regulatory mechanisms through interpretable in silico perturbation process. PertFormer comprises 3 billion parameters pretrained on both bulk and single-cell datasets covering 9 types of multiomics (55 billion bp bulk multiomics and the largest-to-date 1.5 billion paired multiomic samples from 1 million single cells), capturing regulation of 300 kb around every genic region. PertFormer enables zero-shot prediction of functional perturbations and cell fate dynamics, outperforming existing methods by 20.9%-480.2%. PertFormer identifies novel tumor treatment targets, validated experimentally. The generalization capabilities of PertFormer have the potential to accelerate the discovery of biological and clinical targets.

genomics↗

bioRxiv2024

HMG-DTI: a drug-target interaction prediction framework combining Hierarchical Molecular Graphs and improved Convolutional Block Attention Module

Drug-target interactions (DTIs) are fundamental to understanding the therapeutic mechanisms of drugs, yet accurately predicting these interactions remains a significant challenge in drug discovery. Current computational approaches often fail to capture essential molecular motifs and spatial information of proteins, limiting their effectiveness, particularly when encountering proteins or compounds absent in the training datasets. To address these limitations, we propose mHMG-DTI, a novel framework that leverages an improved Convolutional Block Attention Module (iCBAM) for enhanced protein feature extraction and modified Hierarchical Molecular Graphs (mHMGs) for comprehensive molecular encoding. This hierarchical approach not only captures detailed local structures and broader connectivity patterns but also incorporates guiding knowledge to improve feature representation. Across a total of 16 experimental evaluations on four benchmark datasets spanning both classification and regression tasks, mHMG-DTI surpasses existing baseline models in 11 cases. These results highlight the potential of mHMG-DTI to enhance DTI prediction accuracy, thereby accelerating the drug discovery process and providing valuable insights into drug resistance and side effect mechanisms. Contactzeruiyang2-c@my.cityu.edu.hk

bioinformatics↗