Biology subjects

Yang, C.

Publications and source records attributed to Yang, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Kintsugi maps nucleus-poor RNA compartments in subcellular spatial transcriptomics

Subcellular spatial transcriptomics captures where RNA is in tissue, but a single location holds too few molecules of any one gene to estimate composition alone. Every current method fixes in advance where to borrow -- a smoothing scale, a cell outline or a factor model -- and the fixed choice shapes what is visible. Kintsugi removes the fixed choice and lets held-out molecules decide, gene by gene, how much to borrow from spatial neighbours and from other genes at the same location. On a lung section measured by both Xenium and Visium HD, the data-chosen allocation placed an epithelial programme where the Xenium molecules were, ahead of smoothing, cell segmentation and a factor model; the result replicated across tissues and against protein. Across a 45-core pulmonary fibrosis cohort, separating composition from captured amount shows that a fibroblastic focus is not a place with more RNA but a place with different RNA: 2.8-fold higher in activated-fibroblast composition while segmented nuclear density is at most 1.08-fold higher.

bioinformatics↗

bioRxiv2026

RevPert: ranking candidate drivers of transcriptomic state transitions via gallery-native reverse perturbation

Cellular state transitions underlie adaptation, ageing and disease, yet prioritizing catalogued genetic perturbations whose expression signatures match an observed transcriptomic shift remains difficult. Most models predict phenotype from a nominated intervention, whereas genetic inverse benchmarks are largely restricted to within-screen identity recovery. Here we introduce RevPert, a gallery-native reverse perturbation model that ranks a fixed genetic catalog for a query contrast {Delta}Y* = YB - YA by combining signed Pearson connectivity with a learned residual. Across Replogle Essential Perturb-seq (four lines) and LINCS-KO screens (ten lines), RevPert recovered held-out interventions at leading performance relative to matched baselines. Applied to public drug-resistance contrasts in HCC and CML, dual-arm ranking placed pre-specified disease anchors far higher on the expected arms than ranking the same signatures by differential-expression magnitude alone (Essential residual model for HCC; a transductive GWPS residual for CML). RevPert therefore couples within-screen reverse ranking to a screen-external signed-geometry check; the latter calibrates literature anchors and is not claimed as held-out recovery.

bioinformatics↗

bioRxiv2026

A retinal adrenergic module tunes mammalian visual evolution

How conserved neural circuits are modified during mammalian evolution remains poorly understood. Here we combine cross-species single-cell transcriptomics, in situ validation, retinal physiology, and conditional genetics to identify a superorder-associated adrenergic module in the mammalian retina. We find that ADRB1, which encodes the {beta}1-adrenergic receptor, is uniquely expressed in rod bipolar cells of sampled Euarchontoglires, but is absent from homologous cells in sampled Laurasiatheria and Marsupialia. In mice, {beta}1-adrenergic receptor localizes to rod bipolar cell terminals and boosts transmission to AII amacrine cells through Gs-adenylyl cyclase-cAMP-PKA signaling pathway. This modulation enhances synchronous release, accelerates downstream ganglion cell output, and increases scotopic electroretinographic responses, while rod-bipolar-cell-specific Adrb1 deletion abolishes norepinephrine-induced enhancement without disrupting baseline vision. In the diurnal tree shrew, a Euarchontoglires species with a cone-dominated retina, ADRB1 is instead redeployed from rod bipolar cells to cone photoreceptors. These findings reveal an evolutionarily mobile neuromodulatory module that tunes retinal computation according to visual ecology.

evolutionary biology↗

bioRxiv2026

PanSVmerger: a flexible pipeline for merging multiallelic structural variants in pangenome graphs

SummaryPangenome graphs capture extensive genetic diversity but introduce analytical challenges due to the redundant representation of structural variations (SVs). While existing tools effectively address cross-sample redundancy or cross-locus redundancy, none specifically target the intra-locus allelic redundancy inherent to pangenome graphs. Here, we present PanSVmerger, an open-source tool designed to consolidate redundant multiallelic SVs within individual loci using three complementary clustering strategies: adaptive k-mer-based Jaccard distance, global alignment distance via VSEARCH, and length distribution. Validation on HPRC pangenome data demonstrates that PanSVmerger effectively reduces multiallelic complexity (e.g., AC [≥] 3 loci from 62.4% to 4.7% using Strategy A) with a modest trade-off: Recall decreased from 97.13% to 93.58%, while precision improved from 94.95% to 96.56%, yielding an overall F1-score of 95.05%. These results demonstrate that PanSVmerger effectively consolidates redundant allele representations with only a minimal loss of sensitivity, making it well-suited for downstream applications that require clean, non-redundant variants. Availability and implementationPanSVmerger is implemented in Python 3.8+ and freely available under the MIT license at GitHub: https://github.com/tingting100/PanSVmerger. The software requires vcflib, bcftools, and optionally VSEARCH. Comprehensive documentation and tutorials are provided.

bioinformatics↗

bioRxiv2026

Blood-Mediated Opto-Acoustic Stimulation of Brain Cortex at Sub-millimeter Precision

Direct modulation of neural activity with high spatiotemporal precision is a cornerstone in experimental neuroscience. Here, we present a blood-mediated optoacoustic stimulation (BOAS) approach that utilizes blood as an endogenous transducer for brain stimulation. By delivering 532-nm nanosecond pulsed laser to the cortex, we demonstrate that the absorption of hemoglobin generates sufficient acoustic pressure to trigger neuronal activity. By integrating BOAS with calcium imaging in GCaMP6f-expressing mice, localized neuronal responses were observed. Quantitative analysis reveals that BOAS produces responses comparable to natural visual stimulation and is significantly more efficient than the photothermal stimulation. Furthermore, we show that the response is dose-dependent. At high energy doses, BOAS induces cortical spreading depression. Histological evaluation confirmed that the brain maintains tissue integrity even under these stimulation parameters. Together, this work establishes a versatile method for precise brain stimulation as an alternative method for stimulating neuron at cortex.

bioengineering↗

bioRxiv2026

The S1B-Targeting PEDV Neutralizing Antibody C62 Prematurely Activates S-trimer and Mimics Receptor Function

Porcine epidemic diarrhea virus (PEDV) causes devastating enteric disease in piglets, yet the mechanistic basis of antibody-mediated neutralization remains poorly understood. Here, we determined the structure of PEDV HNXX-strain spike domain B (S1B) simultaneously bound by C62, a neutralizing porcine monoclonal antibody against PEDV G2 strains, and N34, a non-neutralizing porcine PEDV antibody. The structure reveals that C62 targets a conserved, cryptic epitope that is accessible only when S1B adopts an "up" conformation. Functionally, we showed that C62 has substantially stronger activity than N34 in triggering S-trimer disassembly and inducing the formation of proteinase K-resistant, post-fusion-like S2 structures. Despite the weaker triggering activity of N34, both C62 and N34 can function as artificial receptors. Notably, although the C62 epitope is conserved across both G1 and G2 strains, C62 exhibits G2-strain-biased neutralizing activity. We further showed that differences in cell-surface membrane fusion activity among PEDV spikes correlate with distinct viral entry pathways and are jointly determined by the S1A and S1B sequences. Together, our findings identify a strain-specific vulnerable site on the PEDV S-trimer and provide insight into how cell-surface membrane fusion activity may influence viral entry pathway selection and antibody neutralization efficacy.

microbiology↗

bioRxiv2026

Discovery of a taxusin-mediated route to baccatin III enables its complete biosynthesis in engineered microbes

Taxol (paclitaxel) is a frontline anticancer drug widely applied for the treatment of breast, ovarian and lung cancers. Currently, its supply mainly relies on the semi-synthesis using baccatin III from Taxus plants. Heterologous biosynthesis of baccatin III in microorganisms offers a promising solution to alleviate global Taxol supply shortage, but remains challenging due to pathway complexity. Here, we report a novel taxusin-mediated biosynthetic pathway for baccatin III production via the identification of C13 deacetylase, elucidation of the exact sequence underlying C1 hydroxylation, and stepwise enzymatic functional validation. Through protein engineering of the promiscuous C1 and C5 hydroxylases, coupled with the distribution of pathway modules in Saccharomyces cerevisiae and Escherichia coli, we achieved the de novo biosynthesis of baccatin III. Collectively, our findings remodel the current biosynthetic framework governing the formation of Taxol precursors and highlight the great potential of microbial cell factories for the production of complex plant-derived therapeutic compounds. Highlights* Discovery of C13 deacetylase reveals a novel biosynthetic route to baccatin III via taxusin * Stepwise verification of the complete biosynthetic route to baccatin III through taxusin and baccatin VI * Single-site mutation reversed the product selectivity of T1OH and converted T5OH into a specific taxoid C5 hydroxylase * Complete biosynthesis of baccatin III in engineered microbes

synthetic biology↗

bioRxiv2026

Beyond Generic Signal Peptides: ApexSP Enables Cargo-Specific Secretion Design

Recombinant proteins are widely used in biopharmaceuticals, industrial manufacturing, and molecular diagnostics; however, efficient secretion remains a major bottleneck limiting their large scale production. As core elements controlling protein entry into secretion pathways, signal peptides do not function solely based on their own sequences, but rather depend on coordinated compatibility among cargo protein properties, secretion pathways, and host backgrounds. Current signal peptide engineering mainly relies on a limited number of commonly used signal peptides, empirical selection, and individual experimental screening, making it difficult to design efficient secretion elements tailored to specific expression systems. Here, we present ApexSP, a signal peptide design framework for secretion engineering tailored to individual cargo proteins. ApexSP is built upon a large scale, high quality signal peptide knowledge base and integrates a discrete diffusion generative model constrained by evolutionary information, a multitask biological filter incorporating topology information, and a signal peptide and mature protein compatibility ranking model to enable integrated design of signal peptides for specific expression systems. ApexSP achieved high accuracy in multiple attribute prediction tasks, including pathway classification and cleavage site prediction, reaching or exceeding the performance of existing signal peptide prediction tools. Moreover, the cargo protein aware ranking module improved the enrichment of candidates with high secretion performance. Experimental validation across multiple eukaryotic and prokaryotic expression systems demonstrated that screening only 10 candidate sequences generated by ApexSP yielded multiple designed signal peptides outperforming reference signal peptides, with the best performing design in the ApGA expressed Pichia pastoris system achieving a 1.71 fold increase in secretion performance compared with the factor signal peptide. Overall, ApexSP advances signal peptide research from sequence prediction toward secretion element design, demonstrating that a single round of designed signal peptides can achieve high secretion performance suitable for further engineering optimization.

synthetic biology↗

bioRxiv2026

Hidden genetic diversity in 320 nearly-complete East Asian genome assemblies

East Asian populations, representing over 20% of the global population, remain critically underrepresented in human genomic studies, limiting our understanding of population-stratified genetic variation and its implications for health and disease. Here we present the first phase of the Asian Pan-Genome project (APG), comprising 320 nearly complete, fully phased haploid genome assemblies from 160 East Asian individuals. These assemblies achieve unprecedented quality, with an average contig N50 of 144.3 megabase pairs and an average quality value of 64.5. Leveraging these superior assemblies, we reveal previously uncharacterized diversity in human repeatome, including population-stratified patterns in centromere satellites and rDNA arrays. Compared to existing global human genome assemblies, the newly generated genomes supplement 152 million base pairs of novel sequences, 355 gene gains, 18,300 structural variation loci and 26 large euchromatic inversions missing from current human pangenomes. We perform population stratification analyses of structural variations, and further resolve the structural haplotypes of complex genomic regions such as Major Histocompatibility Complex and Survival Motor Neuron loci across global pangenomes, exemplifying tandem-duplicate and inversion-rich complex locus architectures in the human genome, respectively. This resource provides a critical foundation for human genetic studies, especially for East Asian populations, promoting more accurate variant discovery, reducing bias, and ultimately advancing the equity and efficacy of genomic medicine.

genomics↗

bioRxiv2026

ERK signaling integrates multiple mechanisms to drive cortical evolutionary expansion

A critical first step in human evolutionary divergence from chimpanzees and other primates is the production of greatly increased numbers of cortical pyramidal neurons during development and over evolutionary time. This expansion underpins the enlarged human cerebral cortex and, consequently, higher-order cognition and consciousness. However, the cellular and molecular mechanisms driving this progressive increase in cortical neuron number remain incompletely understood. Here we show that elevated ERK signaling in human cortical radial glia (RGs), relative to mouse RGs, arises from evolutionary changes in the developmental expression of existing shared genes. Using the Emx1-Cre line to overexpress MEK1DD, a constitutively active mutant of rat MAP2K1, we found that enhanced ERK signaling in mouse cortical RGs upregulates cAMP-PKA signaling, along with promoting self-renewal, expanding the RG pool, and accelerating cell cycle progression. Conversely, overexpression of PKA signaling in mouse cortical RGs via in utero electroporation of constitutively active PRKACA mutants (L206R or W196G) reduces ERK activity, prolongs the cell cycle, suppresses SHH-SMO and YAP/TAZ pathway activity, and blocks ependymal gliogenesis. Together, our results demonstrate that ERK and PKA signaling in cortical RGs engage a dynamic balance of synergistic and antagonistic interactions. This interplay couples evolutionarily enhanced ERK and PKA activities to increased cortical RG numbers, prolonged cell cycle progression, and an extended neurogenic period, which collectively culminate in a marked increase in neuronal production. We conclude that heightened ERK pathway activity in cortical RGs serves as a central driver of progressive neocortical expansion across mammalian evolution. Significance StatementThe human brains extraordinary cognitive abilities stem from a dramatic increase in cortical neuron numbers during evolution. This study reveals that enhanced ERK signaling in human cortical radial glia neural stem cells, relative to other primates, is a key driver of this expansion. By manipulating this pathway in mice, we demonstrate that ERK coordinates multiple mechanisms--including self-renewal, cell cycle acceleration, and a dynamic interplay with PKA signaling--to boost neuronal output. These findings identify a core molecular axis underlying mammalian cortical evolution and provide a framework for understanding how the human cortex acquired its unique size and, consequently, its remarkable complexity.

developmental biology↗

bioRxiv2026

Spaceland: Histology-Guided Reconstruction of High-Resolution Whole-Organ 3D Molecular Atlases from Sparse Spatial Transcriptomics

Reconstructing whole organs in three-dimensional molecular detail is a key step toward building virtual organs for modeling tissue organization, disease progression and drug perturbation responses. However, high-resolution whole-organ spatial transcriptomic profiling remains impractical, forcing a trade-off between reconstruction fidelity and sampling density. Here, we introduce Spaceland, a morphology-guided framework that reconstructs continuous, high-resolution 3D molecular landscapes from sparsely sampled spatial transcriptomic sections and serial H&E histology. Spaceland formulates this task as learning continuous gene-expression fields within a morphology-informed histological space. It constructs a dense 3D morphological scaffold by optical-flow interpolation of foundation model-derived H&E representations and decodes sparse spot-level transcriptomic measurements onto an 8 m histology-aligned grid. Across mouse olfactory bulb, mouse hemibrain and spatiotemporal planarian regeneration, Spaceland generalized across platforms, tissue scales and biological contexts. In mouse benchmarks, Spaceland bridged 400 m molecular gaps, resolved sub-spot organization, outperformed ST-based interpolation and 2D H&E-based prediction methods, and remained robust with 160-320 m H&E intervals. In planarian regeneration, it enabled time-resolved whole-organism analysis from only four Visium sections per stage, revealing dynamic neoblast-neural spatial remodeling. Together, Spaceland shifts 3D molecular atlas construction from exhaustive experimental sampling toward data-driven virtual tissue and organ modeling, providing a scalable route to whole-organ molecular reconstruction.

bioinformatics↗

bioRxiv2026

Scalable single-cell isoform profiling with sequencing-by-expansion

Single-cell RNA sequencing has transformed our understanding of cellular systems, yet the reliance on short-read sequencing restricts analysis to gene-level quantification and obscures the immense biological diversity generated by alternative splicing. While long-read sequencing technologies can capture full-length RNA and resolve transcript isoforms, current platforms remain constrained by throughput and high per-base costs, rendering them impractical for modern million-cell applications. To address this critical limitation, we developed and optimized sequencing-by-expansion (SBX) chemistry for high-throughput single-cell RNA isoform profiling. Integrated within the AXELIOS 1 sequencing platform, SBX employs a unique biochemical conversion process that transforms complementary DNA into expanded surrogate high signal-to-noise polymers called Xpandomers which are sequenced via translocation through a dense nanopore array yielding over 9.5 billion reads in a two-hour run. To leverage this unique data type for long-read single-cell RNA isoform sequencing, we developed the Consensus UMI Deduplication using Longest Length (CUDLL) algorithm, which computationally consolidates variable-length raw SBX reads into single, high-fidelity consensus reads, elevating sequence accuracy to 99.83% and maximizing per transcript read length. We demonstrate that this consensus approach successfully captures the vast isoform diversity of single-cell libraries and enables the accurate measure of differential isoform expression across distinct cell types in peripheral blood mononuclear cells. Furthermore, SBX coupled with CUDLL efficiently resolves T-cell and B-cell receptor clonotypes directly from whole-transcriptome libraries without the need for VDJ-specific target enrichment. Ultimately, this work establishes SBX and the AXELIOS 1 as a transformative platform for high-scale single-cell isoform sequencing.

genetics↗

bioRxiv2026

Gut microbiome derived folate metabolite suppresses colorectal cancer progression

The gut microbiota influences colorectal cancer (CRC) progression, primarily through the secretion of small molecule metabolites. While numerous microbial products are known to drive CRC, endogenous protective mechanisms remain largely uncharacterized. Utilizing a folate metabolomics platform, we demonstrate that the healthy gut microbiota produces folinic acid (FA), a known chemotherapeutic adjuvant also known as leucovorin. This microbially derived folinic acid is progressively depleted in mouse models of colitis-associated CRC and in human clinical metagenomic cohorts with advancing disease severity. Mechanistically, folinic acid acts as a signaling molecule that directly binds and inhibits the intracellular protease calpain-2. This interaction stabilizes epithelial E-cadherin protein expression and suppresses CRC epithelial-to-mesenchymal transition driving metastasis. Genetically manipulating gut microbial production of FA is sufficient to modulate CRC in vivo, even in the presence of chronic inflammation. This study reframes folinic acid from a chemotherapeutic enhancer to an endogenous microbial metabolite that actively suppresses CRC progression.

cancer biology↗

bioRxiv2026

Engineering the bacterial cellulose-forming surface as a programmable protein recruitment interface

Synthetic biology has advanced microorganisms to be programmed as production hosts, but its application to bacteria that inherently assemble extracellular materials remains limited. Komagataeibacter spp., natively synthesizes cellulose at the bacterial cell surface, creating a material-forming interface that has not been used as a programmable recruitment platform. Here we establish cell-surface display in Komagataeibacter intermedius and show that this interface can recruit defined proteins, making functionalization part of cellulose formation. By engineering LppOmpA, we displayed a fluorescent protein and genetically encoded capture modules (SpyTag and SilkTag) to selectively capture catcher-fused protein cargos onto K. intermedius cell surface. Recruitment of silk-derived structural protein before cellulose production generated silk-associated fibrous structures within the pellicles, with retained cargo signal after washing. The resulting biocomposite showed reorganized fibre-network morphology, increased surface hydrophobicity, mesoscale ordering, and improved wet-state compressive strength. Wild-type cells exposed to same conditions did not reproduce these changes, demonstrating that material properties arise from surface-directed recruitment rather than protein exposure alone. This work demonstrates the material-forming bacterial surface as a programmable engineering interface for organizing extracellular proteins, providing a general strategy for engineering living materials.

bioengineering↗

bioRxiv2026

Characterizing dynamic tissue architectures by identifying cell-type-specific spatiotemporal gene programs with stGP

Cellular gene programs unfold over biological time within spatially organized tissues. The same cell type can activate distinct programs in different spatial domains or multicellular niches. Spatiotemporal transcriptomics enables in situ measurement of these processes; however, the interplay between temporal progression and spatial organization complicates the identification of whether a gene program is influenced by temporal changes, spatial structure, or both. To overcome this challenge, we present spatiotemporal Gene Programs (stGP), a statistical framework for identifying interpretable cell-type-specific gene programs across multi-sample spatiotemporal transcriptomic studies. stGP preserves the molecular identity of each program through shared gene loadings, and decomposes individual cell activity into a temporal component that captures gene program responses over biological time, and a spatial component that characterizes variations within tissue sections. We quantify their relative contributions by estimating their variance components. Through comprehensive simulations and analyses of three spatiotemporal transcriptomic datasets across different tissues and technologies, stGP reveals spatiotemporal gene programs that distinguish preserved tissue architecture from dynamic remodeling. Our framework delineates age-associated cellular responses and uncovers localized program deployment within anatomical regions, aging hotspots, and multicellular niches. Our results establish stGP as an effective and robust framework for dissecting dynamic tissue architecture, providing insights into how cell-type-specific gene programs are coordinated across biological time and spatial microenvironments.

bioinformatics↗

bioRxiv2026

Unearthing a fungal giant: Dianjunaceae fam. nov., a novel Paleocene lineage of Xylariales harbouring Dianjunus rex gen. et sp. nov.

During mycological surveys in Yunnan Province, China, specimens of a fungus producing massive, upright stromata up to 50 cm high and individually 2.2 Kg in weight were sampled. Through an integrative taxonomic approach combining detailed morphology, multilocus phylogeny (ITS, LSU, RPB2, TUB2), and phylogenomic analyses, this fungus is proposed as the new species Dianjunus rex gen. et sp. nov., the type of the new family Dianjunaceae (Xylariales). Phylogenetic analyses robustly place Dianjunaceae as a distinct sister clade to Graphostromataceae. Divergence time estimation dates the origin of this family to the early Paleocene ([~]65 Mya), coinciding with the post-K-Pg extinction period, when an estimated 75% of all plant and animal species went extinct, and a significant ecological reorganization of life on earth happened. The stromata of D. rex represent the largest fructifications documented within the Ascomycota, significantly expanding the known morphological range of the Xylariales. The study provides a comprehensive description, including a nodulisporium-like anamorph with periconiella-like branching patterns, and discusses the taxons phylogenetic placement, and distinctive morphology. This discovery highlights the unexplored fungal diversity in East Asian forests.

microbiology↗

bioRxiv2026

A Selective Multivalent NET-Associated Chromatin Neutralizer Resolves Infection-Associated Inflammation in Severe Sepsis

Targeting the overwhelming inflammation driven by neutrophil extracellular traps (NETs) during infection provides an opportunity to manage severe sepsis. This potential needs to be realized by exploring selective NET-neutralization materials, which remains a challenge. Herein, we report a multivalent macromolecular strategy that targets NET-associated DNA-histone chromatin complexes while preserving antibacterial activity of aminoglycoside. We identify 8-arm PEG-conjugated netilmicin (8-arm Netil) as a lead NETs-neutralizer from a library of multivalent aminoglycoside-displayed materials. When compared with 2- and 4-arm counterparts, 8-arm Netil exhibits potent antibacterial activity and high-affinity binding to DNA-histone chromatin complexes through stable multivalent noncovalent interactions, thereby suppressing NET-induced TLR4/TLR9 activation and macrophage inflammatory responses. In severe septic mice, intravenously administered 8-arm Netil preferentially accumulates in inflamed tissues, leading to improved survival protection, owing to the reduction of bacterial dissemination, NET accumulation, systemic cytokine production, and multiple-organ injury. These findings establish NET-associated DNA-histone chromatin complexes as actionable extracellular targets and demonstrate multivalent chromatin targeting as a rational material design strategy for selective NET neutralization and inflammation control in severe sepsis.

bioengineering↗

bioRxiv2026

Bamsnap-LRS: an automated batch visualization tool for long-read sequencing alignments

SummaryLong-read sequencing (LRS) has become essential for genome assembly, structural variations (SVs) detection, haplotype phasing and transcript isoform characterization. However, these applications often require manual inspection of read alignment for validation. Existing visualization tools are either interactive genome browsers that are difficult to scale to large datasets or batch-oriented tools that are not optimized for the unique alignment patterns of long-read data. We developed Bamsnap-LRS, an automated command-line tool for high-throughput LRS alignment visualization. It supports long-read-specific features, phased SNP inspection, and publication-ready batch figure generation within a unified framework for genomic, transcriptomic, and haplotype-aware analyses. Availability and ImplementationAll codes and examples are freely available at https://github.com/comery/Bamsnap-LRS. ContactChentao Yang (yangchentao@genomics.cn) and Yang Zhou (zhouyang@genomics.cn). Supplementary informationSupplementary Table 1 and Supplementary Figures 1-8 are available at xxx online.

bioinformatics↗