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Found: 4 872
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Single-cell and spatial transcriptomics define 20E-driven developmental reprogramming in silkworm wing disc.
Insect wing development involves tissue patterning, cell fate transitions, and hormone signaling, yet its spatiotemporal logic remains unclear. The silkworm, with large wing discs and defined stages, provides an ideal model for high resolution analysis. Here, we construct a spatiotemporal single-cell atlas of the silkworm wing disc across 10 timepoints, identifying 12 major cell types and their developmental transitions. Wing morphogenesis (Wm) cells act as central progenitors, differentiating into epithelial and cuticle lineages under lineage-specific transcription factors. Time‑resolved snRNA‑seq reveals hierarchical transcriptional reprogramming, with Wm cells functioning as early signaling hubs. Functional modules and signaling pathways were activated in spatiotemporal controlled manner. 20‑hydroxyecdysone treatment rapidly accelerates fate transitions and gene expression, recapitulating natural development within hours. Integration of morphology, hormone levels, and gene expression supports a five-stage Gene Transition Model describing progressive fate resolution. This work reveals wing development in silkworm and provides insights into hormone-driven organogenesis and potential manipulation of insect development in agriculture.
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Single-cell transcriptomic profiling of halo nevi and normal nevi reveals CD8+ T cell activation in melanocytic autoimmunity.
Halo nevus is an autoimmune skin disorder characterized by autoreactive CD8+ T cells that target and destroy melanocytes, resulting in a depigmented perilesional halo. Yet the upstream triggers of this activation remain unclear. Here, we performed single-cell RNA sequencing (scRNA-seq) on halo nevi and normal nevi, identifying ten canonical skin cell types and five melanocyte subclusters. Integrated scRNA-seq and immunofluorescence staining revealed that halo nevi, unlike normal nevi, exhibit robust infiltration of activated, type II interferon-responsive CD8+ T cells. Among melanocyte subclusters, one subset (Cluster 3) showed pronounced upregulation of antigen-presenting molecules, interferon-stimulated genes, and chemokines. Comparative analyses further demonstrated that melanocytes in halo nevi increased oxidative phosphorylation, interferon-driven pathways, and antigen processing and presentation. Together, these data provide single-cell transcriptional atlas of halo nevi versus normal nevi, reveal melanocyte-intrinsic and immune-mediated mechanisms underlying autoimmune melanocyte destruction, and highlight pathogenic pathways shared with vitiligo that may inform the development of targeted therapies.
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DiSignAtlas: an atlas of human and mouse disease signatures based on bulk and single-cell transcriptomics.
Molecular signatures are usually sets of biomolecules that can serve as diagnostic, prognostic, predictive, or therapeutic markers for a specific disease. Omics data derived from various high-throughput molecular biology technologies offer global, unbiased and appropriately comparable data, which can be used to identify such molecular signatures. To address the need for comprehensive disease signatures, DiSignAtlas (http://www.inbirg.com/disignatlas/) was developed to provide transcriptomics-based signatures for a wide range of diseases. A total of 181 434 transcriptome profiles were manually curated from studies involving 1836 nonredundant disease types in humans and mice. Then, 10 306 comparison datasets comprising both disease and control samples, including 328 single-cell RNA sequencing datasets, were established. Furthermore, a total of 3 775 317 differentially expressed genes in humans and 1 723 674 in mice were identified as disease signatures by analysing transcriptome profiles using commonly used pipelines. In addition to providing multiple methods for the retrieval of disease signatures, DiSignAtlas provides downstream functional enrichment analysis, cell type analysis and signature correlation analysis between diseases or species when available. Moreover, multiple analytical and comparison tools for disease signatures are available. DiSignAtlas is expected to become a valuable resource for both bioscientists and bioinformaticians engaged in translational research.
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Improving atlas-scale single-cell annotation models with hierarchical cross-entropy loss.
Accurately annotating cell types is essential for extracting biological insight from single-cell RNA sequencing data. Although cell types are naturally organized into hierarchical ontologies, most computational models do not explicitly incorporate this structure into their training objectives. Here, we introduce a hierarchical cross-entropy loss that aligns model objectives with biological structure. Applied to architectures ranging from linear models to transformers, this simple modification improves out-of-distribution performance by 12-15% without added computational cost. Critically, we underscore the need to focus on new data generation that improves the connectivity among annotated cell types. Our work suggests that this is likely to yield more generalizable algorithms than would solely increasing model complexity.
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Single-cell transcriptome analysis reveals secretin as a hallmark of human enteroendocrine cell maturation.
The traditional nomenclature of enteroendocrine cells (EECs), established in 1977, applied the "one cell - one hormone" dogma, which distinguishes subpopulations based on the secretion of a specific hormone. These hormone-specific subpopulations included S cells for secretin (SCT), K cells for glucose-dependent insulinotropic polypeptide (GIP), N cells producing neurotensin (NTS), I cells producing cholecystokinin (CCK), D cells producing somatostatin (SST), and others. In the past 15 years, reinvestigations into murine and human organoid-derived EECs, however, strongly questioned this dogma and established that certain EECs coexpress multiple hormones. Using the Gut Cell Atlas, the largest available single-cell transcriptome dataset of human intestinal cells, this study consolidates that the original dogma is outdated not only for murine and human organoid-derived EECs, but also for primary human EECs, showing that the expression of certain hormones is not restricted to their designated cell type. Moreover, specific analyses into SCT-expressing cells reject the presence of any cell population that exhibits significantly elevated secretin expression compared to other cell populations, previously referred to as S cells. Instead, this investigation indicates that secretin production is realized jointly by other enteroendocrine subpopulations, validating corresponding observations in murine EECs also for human EECs. Furthermore, our findings corroborate that SCT expression peaks in mature EECs, in contrast, progenitor EECs exhibit markedly lower expression levels, supporting the hypothesis that SCT expression is a hallmark of EEC maturation.
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Single-cell analysis reveals a LAMB3-dependent immunosuppressive environment in gallbladder neck/cystic duct carcinoma.
BACKGROUND & AIMS: Gallbladder cancer (GBC) originating from the fundus/body (GBCF/B) and neck/cystic duct (GBCN/CD) exhibits distinct clinical outcomes. Location-associated heterogeneity is intricately linked to oncogenic properties and multicellular interactions within the tumor microenvironment (TME). METHODS: Single-cell transcriptomic analysis was performed on 569,736 cells derived from 38 GBCF/B and 17 GBCN/CD samples. Whole-exome sequencing (WES) was used to identify genomic alterations in malignant epithelial cells. Additionally, TCGA datasets, multiplex immunohistochemistry, scTCR-seq, spatial transcriptomics, and functional assays were integrated to investigate subtype-specific differences. RESULTS: The cellular atlas revealed distinct TME patterns. Hallmarked by TP53 mutations and robust antigen presentation, GBCF/B tumors were enriched with plasma cells (p = 0.009), CXCL13+ T cells (p = 0.046), CXCL9+ macrophages (p = 0.042), and proliferative immune cells (p = 0.015), constituting an immune-activated TME. Conversely, stem-like GBCN/CD tumor cells fostered an angiogenic, immunosuppressive milieu, enriched with endothelial cells (p = 0.02), SPP1+ macrophages (p = 0.006), MYH11+ vCAFs (p = 0.029), and GZMK+NR4A2+CD8+ T cells (p = 0.028). Notably, elevated LAMB3 in GBCN/CD tumor cells emerged as a central immune regulator, driving macrophage infiltration and T-cell dysfunction to establish an immunosuppressive niche. CONCLUSIONS: This study underscores the profoundly immunosuppressive microenvironment in gallbladder cancer originating from the neck/cystic duct (GBCN/CD), highlights the role of LAMB3+ tumor cells in immune modulation, and identifies LAMB3 as a potential therapeutic target for GBCN/CD. IMPACT AND IMPLICATIONS: By delineating distinct TME landscapes between GBC originating from the fundus/body (GBCF/B) and those from the neck/cystic duct (GBCN/CD), this study provides compelling evidence for site-specific precision therapeutic strategies. We demonstrate that GBCF/B tumors are highly enriched with established biomarkers predictive of immunotherapy responsiveness-including elevated tumor mutational burden, robust PD-L1 and interferon-γ signatures, and abundant CXCL13+ T cells, plasma cells, and CXCL9+ macrophages-indicating these patients are optimal candidates for immunotherapeutic interventions. Conversely, GBCN/CD tumors exhibit a profoundly immunosuppressive TME orchestrated by LAMB3+ tumor cells. Targeting LAMB3 therefore represents a promising approach to overcome immune resistance in patients with GBCN/CD.
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Single cell multi-omics atlases unlock cellular mysteries.
Understanding cell type-specific gene regulatory programs is crucial to decipher the regulation of important traits. Recent multiome studies by Zhang et al. and Wang et al. generated single cell-resolution atlases integrating gene expression and chromatin accessibility, uncovering regulatory networks and developmental transitions that provide novel insights into the regulation of agronomic traits.
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Cell-type specific early perception of nine phytohormones revealed by single-nucleus transcriptomics in Arabidopsis.
Plant development and stress responses are coordinated through phytohormone-mediated gene networks, yet resolving their spatiotemporal crosstalk remains challenging. Here, we generate a single-nucleus transcriptomic atlas of Arabidopsis seedlings, capturing early (0.5 h, 3 h) responses to 9 hormones across ~500,000 nuclei, including auxin, cytokinin, ABA, gibberellin, strigolactone, brassinosteroid, ethylene, JA, and SA. Within this window, most hormones showed rapid and cell-type-specific responses, whereas JA, SA, ABA showed more sustained and convergent responses by 3 h. Co-directional transcriptomic overlap was strongest at 0.5 h, while the JA-, SA-, and ABA-related responses showed the highest overlap at 3 h. Pathway-level analysis indicated asymmetric relationships among JA, SA, and ABA across biosynthetic and catabolic layers. Spatially, transcriptomic response overlap separated shoots from other tissues, with guard cells as shoot-side outliers showing weak JA-SA-ABA overlap. We further identified an SA-induced guard-cell-specific MYB60-centered module linked to ABA-associated stomatal regulators, suggesting a circuit that may fine-tune stomatal dynamics. Together, this atlas provides a high-resolution view of phytohormone response dynamics and interactions.
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Single-cell transcriptomics and multimodal molecular profiling revealed the oncogenesis and tumor microenvironment of cardiac myxoma.
This study investigates the distinct cellular composition of cardiac myxoma (CM), the pathways underlying its origin, and the mechanisms driving the development of diverse tumor morphologies. A comprehensive single-cell RNA sequencing (scRNA-seq) analysis was performed on five CM tissue samples and five normal atrial septum samples, encompassing the construction of a CM cell atlas, cell differentiation trajectory reconstruction, cell-cell interaction prediction, identification of cluster-specific transcription factor regulons, and assessment of tumor cell heterogeneity. Validation of scRNA-seq results was conducted through hematoxylin-eosin staining, multiplex immunofluorescence, cellular experiments, and a public database. This study profiled a total of 86,741 cells and identified 13 distinct cell sub-populations based on gene expression. Mesenchymal cells predominated in CM tissues, with high expression of calretinin. Findings from scRNA-seq analysis demonstrated that cardiac endothelial cells undergo endothelial-to-mesenchymal transition (EndoMT), giving rise to mesenchymal-like CM cells. Moreover, hematoxylin-eosin staining and multiplex immunofluorescence revealed variations in the subtypes and functions of tumor-associated fibroblasts and mural cells across different CM morphologies (lobulated and villous). This study demonstrated that CM cells exhibit mesenchymal-like characteristics and their origin is linked to the EndoMT of cardiac endothelial cells. The subtypes of tumor-associated fibroblasts and mural cells contribute to the morphological diversity of CM.
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Multi-Omics and Single-Cell Dissection Reveals EXT1 as a Glycosylation-Linked Therapeutic Target in Cancer.
Background: Glycosylation and inflammation are pivotal in tumor progression, yet the specific glycosyltransferases bridging these processes remain poorly defined. This study investigated Exostosin-1 (EXT1), a key enzyme in heparan sulfate (HS) biosynthesis, as a mechanistic bridge connecting inflammation, stromal remodeling, and immune evasion-driven cancers. Methods: We used a multi-omics approach including Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression on The Cancer Genome Atlas (TCGA) pan-cancer cohorts, transcriptomics, survival, single-cell RNA sequencing (scRNA-seq), DNA methylation profiling, pathway enrichment analysis (MetaCore), molecular docking, and immunohistochemistry (IHC) on pancreatic adenocarcinoma (PAAD) and lung adenocarcinoma (LUAD) tissue microarrays. Results: EXT1 was identified as one of only two genes overlapping inflammation- and glycosylation-related gene sets, strongly associated with poor overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) across cancers, particularly in PAAD and LUAD. Pan-cancer profiling revealed broad EXT1 upregulation. ScRNA-seq localizedEXT1to stromal cells (pancreatic stellate cells, fibroblasts) and epithelial cells co-expressed with immune checkpoint markers. EXT1 promoter hypomethylation correlated with high expression and poor survival. Enrichment analysis of EXT1-correlated genes highlighted activation of critical pro-tumorigenic pathways, including transforming growth factor-β (TGF-β), lysophosphatidic acid (LPA), epidermal growth factor receptor-phosphoinositide 3-kinase-AKT-mitogen-activated protein kinase (EGFR-PI3K-AKT-MAPK), integrin-focal adhesion kinase-Rho GTPase (integrin-FAK-Rho), and epithelial-mesenchymal transition (EMT) pathways. IHC validated stage-dependent EXT1 overexpression in both PAAD and LUAD. Conclusion: This multi-omics study identifies EXT1 as a novel link between glycosylation and inflammation. It functions as a driver of stromal activation, immune checkpoint engagement, and tumor progression. EXT1 represents a clinically relevant biomarker and a promising therapeutic target in inflammation-driven cancers like PAAD and LUAD.