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Xu, Y.

Publications and source records attributed to Xu, Y..

At least 37 records · Page 2Linked to original sources

Multi-omics fine-mapping uncovers a pleiotropic intestinal enhancer variant linking PMAIP1 regulation to pig growth and fatness

Genetic loci influencing multiple complex traits often remain difficult to interpret because the underlying functional variants, target genes and tissue contexts are unresolved. Here, we investigated the regulatory basis of a shared signal for average daily gain (ADG) and backfat thickness (BF) in Yorkshire pigs. By integrating GWAS in 7,972 pigs, targeted capture sequencing, LD-based fine-mapping, porcine epigenomic annotations, three-dimensional chromatin interaction maps and functional assays, we narrowed the shared SSC1 signal to a 1.59-Mb interval and functionally prioritized rs334769214 (T>G) as the leading candidate variant. The T>G substitution produced marked allele-specific differences in enhancer activity and nuclear-protein binding, while transcription-factor co-transfection assays identified FOXL1-responsive, allele-dependent regulatory activity. Chromatin interaction and CRISPRa analyses supported a regulatory connection between the rs334769214-containing enhancer and PMAIP1, and PMAIP1 overexpression promoted apoptosis in porcine intestinal epithelial cells. In the capture-sequenced subset, the G allele was associated with higher ADG and BF, consistent with a relative loss-of-activation model. Together, these findings delineate a candidate FOXL1-enhancer-PMAIP1 regulatory pathway and demonstrate how multi-omics fine-mapping can advance a shared quantitative-trait locus toward a testable molecular mechanism underlying variation in growth and fatness.

genetics↗

Pair-complete structural gating enables Pareto optimization of de novo cyclic peptides with preserved binding geometry and improved developability

Cyclic peptides can engage extended protein interfaces, but sequence changes that improve developability often disrupt the selected target-bound geometry. Existing property-guided design methods lack a principled way to preserve this geometry during local multiproperty optimization. Here we present RF-PepTune, which separates structural eligibility from property prioritization. Before any property score is queried, RF-PepTune evaluates single substitutions and all position-distinct pairs induced by admitted substitutions to build a parent-specific, pair-complete admission graph. Pareto Monte Carlo tree search then optimizes predicted permeability, solubility, non-fouling, and low-haemolysis scores exclusively within this graph, and selected sequences undergo full structural re-evaluation. In a matched three-arm comparison of 334 parents across MDM2, GABARAP, and MCL1, joint property-structure success rose from 10.2% without admission to 51.5% with single-substitution admission and 77.5% with pair-complete admission; pair-complete gating improved success by 26.0 percentage points over single-substitution gating (95% CI, 20.7-31.4). Property-positive but structure-failing endpoints fell from 88.3% to 9.3%. In a separate target-balanced set, all 90 prioritized outputs improved all four model-native scores while satisfying prespecified structural criteria. This work establishes pairwise structural gating as a general strategy for constrained multi-objective molecular optimization.

bioinformatics↗

Generation of a transgenic cephalopod

Coleoid cephalopods (cuttlefish, octopus, and squid) are marine mollusks with elaborate nervous systems that support a diverse repertoire of complex behaviors. These include the neural control of the color, pattern, and texture of the skin, facilitating both adaptive camouflage and innate patterning that may reflect internal state. The development of transgenic cephalopods expressing fluorescent proteins, optogenetic actuators, and reporters of neural activity would contribute a new and important technology to cephalopod biology. The generation of transgenic cephalopods, however, has remained a major challenge. Here, we report the development of stable transgenic dwarf cuttlefish (Ascarosepion bandense) expressing ubiquitous nuclear-localized mScarlet, a red fluorescent protein. We evaluated multiple strategies for transgenesis, and established cuttlefish lines using both CRISPR and the transposons Sleeping Beauty and Minos. The stable expression of transgenes enabled live imaging of cell dynamics during embryonic development. The Minos transposon emerged as the most efficient transgenesis strategy and is adaptable to promoters and transgenes of choice. These strategies now enable the generation of diverse genetic tools for mechanistic studies of cephalopod biology.

genetics↗

Integrated immunopeptidomics and transcriptomics reveal a cancer-restricted non-canonical HLA class I ligandome in medulloblastoma

Medulloblastoma is the leading type of malignant brain tumor in children. Despite recent advances in T cell-based immunotherapy, the low mutational burden of medulloblastoma poses a considerable challenge to the discovery of mutation-derived neoantigens. Previous studies of medulloblastoma have investigated tumor-associated antigens and neoantigens derived from aberrant splice junctions. The landscape of non-canonical HLA class I-bound peptides (ncHLAp) remains poorly defined. To broaden the repertoire of targetable antigens in medulloblastoma, we mapped the ncHLAp landscape across the four major molecular subgroups of medulloblastoma (Group 3, Group 4, WNT, and SHH) by integrating immunopeptidomic and transcriptomic analyses. Candidates were further filtered against normal-tissue immunopeptidomic and ribosome profiling datasets to identify cancer-restricted ncHLAp (CR ncHLAp). A total of 2,298 ncHLAp were identified across 21 human medulloblastoma samples, of which 598 were CR ncHLAp. These CR ncHLAp were primarily derived from non-canonical translational sources, including retained introns, out-of-frame open reading frames, and long non-coding RNAs. Some CR ncHLAp were shared across medulloblastoma samples and detected in other cancer types. More than 70% of the CR ncHLAp were predicted to bind at least one patient-matched HLA allotype, and approximately 87% were predicted to have immunogenic potential. Collectively, this study defines a previously undercharacterized component, CR ncHLAp, of the medulloblastoma HLA-I ligandome and suggests that CR ncHLAp may serve as promising candidate targets for T-cell-based immunotherapy in medulloblastoma.

cancer biology↗

Ultra-fast and scalable high-resolution full-length single-cell RNA sequencing using CHART-seq

Plate-based full-length single-cell RNA sequencing resolves transcript structure details but remains difficult to scale because each cell usually requires a separate library. Here we developed CHART-seq (Combinatorial Heteroduplex Assay via Recombinant Tn5), which uses orthogonally indexed Tn5 complexes to tagment RNA/cDNA heteroduplexes and permits early sample pooling. The workflow processed up to 96 cells per library, was compatible with 384-well expansion, and completed library preparation within 3 h at a reagent cost below US$1 per cell. At matched sequencing depth, CHART-seq detected more genes and annotated isoforms than Smart-seq2, Smart-seq3, Flash-seq and SHERRY2, while retaining broad genebody coverage and reproducible expression estimates. In the CHART-seq results of vascular smooth muscle cells, TGF-{beta}1 pretreatment before PDGF-BB exposure partly restored contractile features, suppressed a PDGF-associated inflammatory programme, and induced a distinct metabolic-matrix response with coordinated transcript-usage changes. These biological findings remain exploratory because independent biological replicates were unavailable. CHART-seq provides a rapid, scalable route to full-length single-cell transcript profiling with gene-programme and candidate isoform resolution.

genomics↗

MoTRUST: adaptive semantic protection for mosaic single-cell integration and molecular recovery

Single-cell multi-omics reveals complementary aspects of cellular identity, but heterogeneous assays produce incomplete modality combinations. Integrating these mosaic measurements while preserving biological structure and recovering missing molecular information remains challenging. We present MoTRUST, combining neural representations, adaptive semantic protection, molecular prediction and conditional residual diffusion. MoTRUST ranked first in overall integration across 30 tasks spanning six scenarios and surpassed the strongest evaluated controls on six of eleven development recovery endpoints. Conditional residual diffusion reduced aggregate marginal prediction scores by 4.4-5.1% across three ATAC-to-RNA data sources while preserving point predictions. Together, these capabilities enable accurate mosaic integration and molecular recovery for multimodal characterization of cellular heterogeneity.

bioinformatics↗

From single-sequence structure prediction to protein fitness landscape through a composable, epistasis-aware mutation atlas

Mapping the multi-mutant fitness landscape is vital to protein engineering, but is challenging due to the vast combinatorial sequence space awaiting exploration. A central difficulty lies in the accurate and efficient modeling of non-additive epistatic effects among individual mutations, which partially arise from the physical inter-residue interactions prescribed by the protein structure. Existing fitness predictors usually perform well on single mutants but become less powerful for higher-order mutants, due to the lack of explicitly considering the relationship between sequence, structure and function of the target protein. Here, we present an end-to-end framework named Cerebra-Epistasis, which couples a single-sequence structure predictor that explicitly endows the structure awareness beyond the conventional sequence-fitness mapping with a downstream fitness prediction network that deliberately models the non-linear epistatic effects beyond the traditional additive terms. When evaluated across diverse assays, Cerebra-Epistasis outperforms the other state-of-the-art baselines in multi-mutant fitness prediction, with enhanced advantage over increasing mutation orders. Moreover, our special design on the epistasis modeling allows reliable extrapolation from low-order mutant data to unseen higher-order combinations, enabling one-shot inference of the overall mutation atlas from the starting sequence, a benefit that supposedly introduces three orders of magnitude acceleration in the landscape-scale prediction.

bioinformatics↗

NSD2 deficiency disrupts the epigenetic landscape of cochlear hair cells to enhance ECM expression and to perturb cochlear hair cell function

Mammalian cochlear hair cells (HC) are crucial for hearing, and histone modifications may play an important role in HC maturation and functions. However, whether and how NSD2, a histone H3 lysine 36 (H3K36) dimethyltransferase, affects cochlear HC maturation remains unclear. Here, we established an HC-specific Nsd2 knockout mouse model and discovered that the loss of NSD2 results in severe structural defects in stereociliary bundles and profound hearing impairment. Integrated multi-omics profiling revealed that NSD2 deficiency leads to a decreased expression of H3K36me2, which in turn alters genome-wide chromatin accessibility and gene expression. Mechanistically, NSD2 deficiency triggers the aberrant upregulation of extracellular matrix (ECM) genes at the transcriptional level, causing excessive collagen accumulation and compromising tissue structure. Crucially, ECM intervention can mitigate NSD2-deficiency mediated hearing damage. Our study reveals an epigenetic mechanism by which NSD2 regulates cochlear HC maturation through inhibition of chromatin remodeling-induced ECM accumulation, and provides a potential new therapeutic direction for hearing impairment.

cell biology↗

Spatiotemporal atlas resolves the mesenchymal-epithelial stem cell axis governing human hair follicle aging and pathology

How adult stem cell populations coordinate tissue regeneration across physiological and pathological states remains unclear. Hair follicles contain epithelial and mesenchymal stem cells that codetermine hair regeneration. Here, we integrate a multimodal spatiotemporal atlas with functional validation to define the mesenchymal-epithelial stem cell dynamics governing human hair follicle homeostasis, aging, and androgenetic alopecia. Aging is characterized by passive depletion of hDSC-derived regenerative cues, whereas AGA involves a shift of hDSC toward an inhibitory signaling hub that promotes HFSC dysfunction. We further pinpoint hDSC-secreted PTN as a key regenerative factor that promotes hair growth and counteracts androgen-induced growth suppression. This study provides a holistic framework of adult stem cell crosstalk across physiological and pathological states, offering a mechanistic roadmap to reinstate tissue regeneration.

cell biology↗

FFPE-CUTAC: A Single Assay, Multiple Layers

Background: Archival biobanks of formalin-fixed paraffin-embedded (FFPE) specimens represent a vast and underused resource for retrospective molecular studies linked to clinical follow-up. However, fixation-induced chemical modification and nucleic acid fragmentation limit scalable genomic and transcriptomic profiling. FFPE-CUTAC (Cleavage Under Targeted Accessible Chromatin) is an RNA polymerase II-targeted DNA assay specifically designed to profile regulatory activity in FFPE tissue. Here, we assess its archival robustness, information content, compatibility with RNA-seq, and ability to recover copy-number alterations. Results: In meningioma and breast cancer cohorts, we benchmarked FFPE-CUTAC against matched fresh-frozen RNA-seq, FFPE RNA-seq and FFPE whole-genome sequencing. For FFPE specimens spanning up to 25 years, FFPE-CUTAC showed no systematic collection-year-associated decline in library yield or signal-quality metrics. In contrast, FFPE RNA-seq is more affected by the FFPE tissue degradation and specimen age on read composition, gene-body coverage, and gene detection. By measuring RNA polymerase II occupancy on chromatin rather than mature RNA abundance, FFPE-CUTAC is less constrained by transcript half-life, polyadenylation or transcript-capture design. FFPE-CUTAC extends beyond gene regions to non-coding regulatory elements, while the shared gene-level signals supported its integration with existing RNA-seq cohorts for large-scale, long-term clinical association study. FFPE-CUTAC libraries also retain DNA dosage information and can be used to recover chromosome-arm gain, loss and intact states with 96% concordance to matched whole-genome sequencing. Conclusions: By converting routinely preserved pathology sections into integrated regulatory and copy-number profiles, FFPE-CUTAC provides a practical foundation for constructing clinically annotated disease maps to support molecular stratification, prognostic modeling and treatment-association studies.

cancer biology↗

Multiomics Reveals IGF-1 c.258A > G Reduces Triacylglycerol Containing Medium-Chain Fatty Acid in Milk

Fatty acid composition of milk triacylglycerol (TAG) is important for neonatal growth. We previously identified a synonymous mutation widely distributed in human populations, IGF-1 c.258A > G, which decreased milk TAG content in gene-edited mice. So far, the acyl chain composition of affected TAGs, underlying molecular mechanism, and cross-species conservation remain unclear. Here, integrated transcriptomic and metabolomic analyses of mouse mammary glands revealed that this mutation downregulates IGF-1 expression and elevates lipoprotein lipase (LPL) activity, and potential associations between IGF-1 and peroxisome proliferator-activated receptor {gamma} (PPARG), fatty acid synthase (FASN) and lipin 1 (LPIN1). Association analysis in 295 Bama pigs carrying this gene polymorphism showed reduced milk lipid content in sows; further, correspondingly lower litter weight was significantly associated with the genotype. Integrated metabolomic profiling of mouse mammary glands and porcine milk demonstrated insufficient production of lauric and myristic acids. Accordingly, supplementing these two fatty acids restored TAG content. Mechanistically, IGF-1 promotes triacylglycerol-containing medium-chain fatty acid (MCFA-TAG) synthesis by activating the PPARG-FASN/LPIN1 axis, whereas increased LPL activity indirectly suppresses this axis through long-chain fatty acid accumulation. Together, our results reveal the molecular mechanism whereby this mutation affects milk lipid synthesis, providing insights into the regulation of MCFA-TAG synthesis.

molecular biology↗

Vulnerability of triple negative breast cancer to daraxonrasib pan-RAS(on) inhibition

Triple-Negative Breast Cancer (TNBC) is a clinical subtype where aberrant expression of receptor tyrosine kinases (RTKs) leads to the activation of the RAS-RAF-MEK-ERK pathway contributing to tumor progression. Therapies targeting components of the RAF-MEK-ERK pathway in TNBC have been disappointing due to rapid onset of adaptive reprogramming of the RTK landscape leading to pathway reactivation. To overcome the dynamic heterogeneity of RTK expression and their convergence in activating RAS, treatment with the pan-RAS(on) inhibitor daraxonrasib (RMC-6236), which inhibits RAS-GTP regulation of RAF kinases, inhibited proliferation independent of TNBC kinotype or oncogenic RAS mutation in three of four TNBC cell lines in vitro and two patient-derived TNBC xenografts in mice. Daraxonrasib in combination with the MEK inhibitor trametinib prevented reactivation of the RAF-MEK-ERK pathway observed with each inhibitor alone and further enhanced inhibition of tumor growth in TNBC cell lines and xenografts. Inhibiting pan-RAS(on) RAS-GTP, with daraxonrasib, alone or in combination with a MEK inhibitor, provides a new strategy for the treatment of TNBC that inhibits RTK activation of the RAS-RAF-MEK-ERK pathway and tumor proliferation.

cancer biology↗

PAXIP1-PAGR1 directs cohesin recruitment during break-induced telomere repair

Cohesin is a conserved multiprotein complex (SMC1, SMC3, RAD21, and either STAG1 or STAG2) that organizes three-dimensional genome architecture and regulates chromosome segregation, gene expression, and DNA damage repair (1-4). Following double-strand breaks (DSBs), cohesin is recruited to sites of DNA damage - a process considered essential for efficient homologous recombination (5-15). Yet how DSB signaling elicits cohesin recruitment and subsequent cohesion establishment remains poorly understood. Here we show that telomere replication stress activates de novo STAG2-cohesin loading, thereby promoting break-induced telomeric DNA repair. We demonstrate that this DNA break-elicited cohesin recruitment is strictly controlled by the BRCT domain-containing DNA damage recognition factor PAXIP1 and its functional partner PAGR1. Cryo-electron microscopy structure reveals that PAGR1, together with PAXIP1, physically binds to a composite interface formed by the STAG2-RAD21 cohesin subcomplex. Complementary mutational and biochemical analyses define the molecular basis of this interaction and establish its essential role in break-induced cohesion establishment. Furthermore, we show that PAXIP1-PAGR1-enacted STAG2-cohesin recruitment complements with the PML body-associated pathway in orchestrating break-induced alternative lengthening of telomeres (ALT). Concurrent depletion of PML together with PAXIP1, PAGR1 or STAG2 disrupts ALT-mediated telomere maintenance, leading to end-to-end chromosomal fusion and mitotic cell death. Collectively, these findings uncover a distinctive molecular mechanism through which DSB signaling directs de novo cohesion establishment, and highlight its critical importance in break-induced telomere repair.

molecular biology↗

PlantRegMoD: An integrative and AI-driven multi-omics database for plant regeneration research

Plant regeneration underpins plant developmental plasticity, tissue culture, genetic transformation and crop improvement. Although numerous related omics datasets have been generated, specialized multi-omics databases for this field are still scarce. Here, we constructed PlantRegMoD, an AI-powered integrated database dedicated to plant regeneration. This platform hosts 20.54 TB standardized multi-omics data from 147 projects across 32 plant species and 2,593 samples. We established a unified hierarchical classification system covering five major categories and nine regeneration models, and curated 236 regeneration genes as well as their 28,190 homologs across 58 representative plant species. It contains extensive transcriptomic resources across all regeneration models, together with 196,423 single cells and over 8.81 million epigenetic peaks to dissect cellular heterogeneity and multi-layered epigenetic regulation. Equipped with nine online omics-related tools and a RAG-based intelligent Q&A system, PlantRegMoD greatly reduces bioinformatic barriers and serves as a robust resource for mechanistic, functional and evolutionary studies of plant regeneration.

plant biology↗

Sex-dimorphic immune trajectories across the canine lifespan and early-life signatures of geroprotective interventions

Canine models are invaluable for translational geroscience, but widespread gonadectomy in companion dogs obscures natural sex-specific aging trajectories. Here, we characterize the age-associated hematologic and serum cytokine profiles of 80 intact laboratory Beagles spanning 1 to 11 years. Contrary to classical linear models of immunosenescence and inflammaging, we reveal that canine immune aging is highly dynamic and sexually dimorphic. While absolute leukocyte counts declined continuously, cytokine remodeling was sex-specific: intact males exhibited extensive age-dependent inflammatory restructuring, whereas females demonstrated restricted fluctuations. To establish baseline geroprotective signatures, we evaluated 24 young beagles following a 90-day intervention with rapamycin, canagliflozin, or dietary restriction. Rapamycin induced robust immune modulation, while canagliflozin prompted early, sex-biased weight loss and narrower cytokine responses. Together, our findings demonstrate that canine immune aging involves complex, sexually dimorphic remodeling. By utilizing an intact cohort to isolate natural dimorphic trajectories, we provide a crucial foundation for developing precision, sex-optimized geroprotectors.

physiology↗

DiffGSP: reversing mRNA diffusion to unlock high-fidelity spatial transcriptomics

Spatial transcriptomics enables gene expression profiling within intact tissues while preserving spatial context, providing unprecedented insights into cellular organization and function. However, mRNA diffusion during tissue processing can cause transcripts originating from adjacent cells to be captured at a given spot. This spatial misalignment challenges a fundamental premise of spatial transcriptomics that measured gene expression faithfully corresponds to its spatial origin, thereby compromising spatial fidelity and potentially biasing biological interpretation. Here, we present DiffGSP, a physics-informed framework that integrates Fick's law with graph signal processing to explicitly model diffusion-induced distortions and recover the underlying spatial gene expression landscape. Comprehensive benchmarking across diverse datasets and evaluation metrics demonstrates the consistent ability of DiffGSP to restore spatial gene expression patterns. By computationally reversing diffusion-induced distortions, DiffGSP enables the discovery of fine anatomical structures in the mouse brain, spatially organized gene modules in the kidney, intratumoral heterogeneity in colorectal cancer, and tertiary lymphoid structures in lung adenocarcinoma. Built on a physically interpretable framework and broadly applicable to sequencing-based spatial transcriptomics technologies, DiffGSP improves the fidelity of spatial gene expression reconstruction and enables more reliable biological interpretation.

bioinformatics↗

Molecular Editing in Protein Degradation: From a Dual NSD2/GSPT1 Degrader to an NSD2-Selective PROTAC and a GSPT1-Selective Molecular Glue

Both NSD2 and GSPT1 represent compelling targets for anti-cancer drug discovery. Herein, we carried out single-atom modification of LLC0424, an NSD2 degrader with GSPT1 neosubstrate engagement, to yield two structurally analogous molecules with divergent modes of action: 424-ND, an NSD2-selective degrader, and 424-GD, a GSPT1-selective degrader. 424-ND drove selective NSD2 degradation and suppressed androgen receptor (AR) signaling in prostate cancer cells. 424-GD induced selective degradation of GSPT1 and upregulated the integrated stress response markers ATF4 and ATF3. Biolayer interferometry revealed distinct ternary complex cooperativity profiles in the presence of NSD2 or GSPT1, which directly correlate with the observed biased degradation activity. Molecular dynamics and metadynamics simulations showed that the compounds adopt distinct low-energy conformational ensembles with different spatial orientations, likely underlying their divergent cooperativity and selectivity. These findings demonstrate that minimal structural alteration permits precision control over degrader target selectivity, while furnishing selective chemical probes for NSD2 and GSPT1.

cancer biology↗

MutCleaner: Cleaning and Standardizing Biological Mutation Datasets for Variant Effect Prediction

Summary: Protein mutation datasets are widely used in variant effect prediction and protein engineering, but datasets from different sources often lack consistent conventions for mutation representation, sequence representation, data organization, and experimental labels, making these resources difficult to integrate directly and limiting their use in downstream analyses and modeling. MutCleaner is an extensible Python framework that cleans, validates, and standardizes protein- and codon-level mutation datasets through composable cleaning pipelines, unified sequence and mutation data structures, and dataset-specific cleaners. It provides standardized resources covering 16 protein and codon mutation datasets with more than 12.14 million mutation records. Availability and implementation: MutCleaner is an open-source Python package released under the Apache License 2.0. The source code is available on https://github.com/xulab-research/MutCleaner, the package is distributed through https://pypi.org/project/mutcleaner/, and the documentation is available https://xulab-research.github.io/MutCleaner/.

bioinformatics↗