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Found: 4 877
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A developmental single-cell atlas of the Drosophila visual system glia reveals cell type diversification and subcellular mRNA compartmentalization.
Glial cells are essential for proper nervous system development and function. To understand glial development and function, we comprehensively annotated the glial cells from two large single-cell mRNA-sequencing (scRNA-seq) atlases of the developing Drosophila visual system. This allowed us to identify all glial cell types from larval to adult stages and follow their developmental trajectories to understand how the diversity of glial types is generated during development. We show that whereas most glial types, such as chiasm glia, gradually change their transcriptome as they mature during development, neuropil glia that transcriptionally appear as a single-cell class in larvae, splits into ensheathing (EG) and astrocyte-like (ALG) glia types during pupal stages. We have experimentally validated these developmental trajectories and identified the genetic markers expressed through the differentiation between EG and ALG classes. Unexpectedly, our analysis of scRNA-seq datasets allowed us to discover that the transcriptome of glial cell bodies can be distinguished from that of their processes. We have identified that processes are enriched for distinct mRNAs that were validated in vivo. This work provides the most detailed transcriptomic analysis of optic lobe glia during development and helps explain the expansion of glial diversity observed in the adult visual system. We also present an innovative computational approach to identify mRNA species that are differentially localized to cell bodies or cellular processes.
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Integration of imaging-based and sequencing-based spatial omics mapping on the same tissue section via DBiTplus.
Spatially mapping the transcriptome and proteome in the same tissue section can profoundly advance our understanding of cellular heterogeneity and function. Here we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multimodal spatial omics approach combining sequencing-based spatial transcriptomics and multiplexed protein imaging on the same section, enabling both single-cell-resolution cell typing and transcriptome-wide interrogation of biological pathways. DBiTplus utilizes spatial barcoding and RNase H-mediated cDNA retrieval, preserving tissue architecture for multiplexed protein imaging. We developed computational pipelines to integrate these modalities, allowing imaging-guided deconvolution to generate single-cell-resolved spatial transcriptome atlases. We demonstrate DBiTplus across diverse samples including frozen mouse embryos, and formalin-fixed paraffin-embedded human lymph nodes and lymphoma tissues, highlighting its compatibility with challenging clinical specimens. DBiTplus uncovered mechanisms of lymphomagenesis, progression and transformation in human lymphomas. Thus, DBiTplus is a unified workflow for spatially resolved single-cell atlasing and unbiased exploration of biological mechanisms in a cell-by-cell manner at transcriptome scale.
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Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina.
Most genetic risk variants linked to ocular diseases are nonprotein coding and presumably contribute to disease through dysregulation of gene expression; however, understanding their mechanisms has been impeded by incomplete annotation of transcriptional regulatory elements across retinal cell types. To address this, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome, and three-dimensional (3D) chromatin architecture in human retina, macula, and retinal pigment epithelium/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 retinal cell types. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the advancements in deep-learning techniques, we developed sequence-based predictors to interpret noncoding risk variants of retinal diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases and provides a resource for studying the gene regulatory programs of the human retina and ocular diseases.
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Single-Cell and Spatial Transcriptomics Unveil Key Regulators Governing Cell Differentiation for Schistosoma japonicum Sexual Development.
Schistosomiasis remains a major global health challenge, primarily due to the large number of egg production by sexually mature parasites. However, the cellular basis and regulatory programs governing sexual development and egg production are poorly characterized. Here, we constructed a dynamic single-cell atlas of Schistosoma japonicum (S. japonicum) covering key development stages of sexual maturation and egg production, and integrated it for the first time with spatial transcriptomics to map tissue‑resolved cellular niches. Through bioinformatic analysis and experimental validation, we identified several critical cell populations and regulatory networks that drive parasite development and egg laying. By mapping de novo identified transcription factors (TFs) onto these atlases, we generated a comprehensive spatiotemporal expression profile of TFs and define the regulatory programs of several tissue-specific TFs including Zfp, Fbp3, and Lim. Integrated re‑clustering further revealed and validated key regulators of germline stem-cell differentiation in S. japonicum. Finally, comparative analyses with S. mansoni single-cell datasets revealed both conserved and species‑divergent cellular plasticity, providing unprecedented insights into their distinct biological traits. Collectively, our comprehensive study establishes a foundational resource for understanding schistosome biology, deciphers regulatory programs underlying cell differentiation and pathogenicity, and accelerates the identification of key molecules involved in sexual development against schistosomiasis.
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Integrative single-cell analysis reveals endothelial diversity in the vasa vasorum of human atherosclerosis.
Microvessels within atherosclerotic plaques are crucially involved in disease progression. Here, we generated a transcriptomic atlas of human atherosclerosis at single-cell resolution, encompassing 17,367 vascular endothelial cells (VECs) from five scRNA-seq studies, and verified key morphological characteristics using histology. SULF1+ arterial endothelial cells (ArtECs) represented the primary subcluster undergoing endothelial-to-mesenchymal transition (EndMT). Capillary-like endothelial cells (CapECs) were identified as primary mediators of angiogenesis, and a trajectory model illustrated the transition between tip and stalk cells, with subclusters of ArtECs and CapECs predominantly expressing CXCL12, thereby driving the CXCL12/CXCR4 signaling axis. The largest plaque EC cluster, exhibiting the most heterogeneity, was found among post-capillary venule endothelial cells (VenECs), particularly ACKR1highNR2F2low VenECs, which displayed distinct inflammatory transcriptional signatures characterized by adhesion molecules and chemokines. Overall, this atlas of atherosclerosis underscores endothelial heterogeneity and identifies SULF1+ ArtECs and VenECs as potential therapeutic targets for EndMT and leukocyte recruitment, respectively.
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Single-cell sequencing profiling of intratumoral heterogeneity and immunosuppressive microenvironment in primary thyroid cancer and lymph node metastases.
Metastasis is a major determinant of treatment failure and mortality in thyroid cancer, yet the interplay between malignant evolution and the immune microenvironment remains poorly characterized. Immunotherapy offers promise, but its efficacy requires a deeper understanding of tumor-associated immune infiltration and checkpoint regulation. In this study, we constructed a high-resolution transcriptomic atlas of the thyroid cancer ecosystem by analyzing 55,005 single cells from paired primary tumors and lymph node metastases. By integrating chromosomal copy number variation (CNV) inference with consensus nonnegative matrix factorization (cNMF), we deciphered the intrinsic heterogeneity of malignant epithelial cells, revealing distinct transcriptional programs and developmental trajectories driving the metastatic cascade. The metastatic niche exhibited significant reprogramming of the immunosuppressive landscape, characterized by the enrichment of FOXP3⁺ regulatory T (Treg) cells, LAMP3⁺ dendritic cells (DCs), and CCL18⁺ M2-like macrophages. Notably, while canonical checkpoints PD-1 and PD-L1/2 showed minimal expression, ligand-receptor interaction analysis identified the LAG3-LGALS3 axes as dominant immune evasion pathways mediating the crosstalk between CD8⁺ T cells and the tumor stroma. In conclusion, this study comprehensively maps the coevolution of malignant thyrocyte plasticity and the immunosuppressive metastatic niche. By uncovering the specific role of LAMP3⁺ DCs and identifying LAG3/TIGIT as critical alternative checkpoints, our findings challenge the utility of conventional PD-1 blockade in this context and provide a robust molecular rationale for developing next-generation immunotherapeutic strategies tailored to thyroid cancer. Although limited by a modest sample size, these findings provide a foundation for further investigation of the metastatic immune landscape in thyroid cancer.
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Single-nucleus RNA sequencing uncovers cell type-specific alterations in OSA-related liver injury.
Chronic intermittent hypoxia (CIH), a hallmark feature of obstructive sleep apnea (OSA), is strongly implicated in the development of hepatic injury. However, the cellular mechanisms underlying CIH-induced liver dysfunction remain poorly understood. This study aimed to systematically characterize hepatic cellular responses to CIH at single-nucleus resolution. A rodent model of CIH was established and subjected to histological and transcriptomic analyses. Single-nucleus RNA sequencing (snRNA-seq) was performed to delineate transcriptional alterations across liver cell populations. Differentially expressed genes (DEGs) and pathway enrichment analyses were conducted to identify key biological processes and signaling networks affected by CIH exposure. CIH exposure resulted in marked hepatic injury characterized by spotty necrosis and prominent infiltration of inflammatory cells. SnRNA-seq identified ten major liver cell types with stable composition but revealed extensive transcriptional reprogramming across multiple hepatic subpopulations. CIH suppressed PPAR signaling and fatty acid metabolism in hepatocytes and hepatic stellate cells and activated AMPK and PI3K-Akt pathways related to stress response and fibrogenic processes. Mononuclear phagocytes showed upregulation of NF-κB signaling and complement/coagulation cascades. Endothelial cells exhibited changes in genes associated with cytoskeletal organization and tight junctions. T cell subpopulations displayed altered expression of genes involved in metabolic regulation and endoplasmic reticulum stress. This study provides the first single-nucleus transcriptomic atlas of the liver under CIH, revealing cell type-specific molecular remodeling across hepatocytes, stromal, and immune cells. These findings elucidate the complex cellular interplay associated with CIH-induced hepatic injury and offer novel insights into potential therapeutic targets for OSA-related liver dysfunction.
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The Single-Cell Atlas Revolution: Integrating Lineage, Space, and Evolution to Decode Animal Biology.
The advent of single-cell RNA sequencing (scRNA-seq) has fundamentally transformed biological research, converting our understanding of cellular diversity from a purely conceptual idea into a quantifiable, applicable, and observable reality. Early efforts successfully created catalogs of cell types across diverse tissues and species, delivering an effective inventory of the components that make up complex animal systems. Yet the field now stands at a crossroads; rather than bringing clarity, the ever-growing number of cellular atlases threatens to flood and overwhelm it. In this review, we argue that the next evolution of scRNA-seq must integrate three essential pillars: temporal dynamics, spatial information, and evolutionary conservation. We have entered the era of predictive biology, moving beyond simple inventories to build dynamic, multispecies, spatially resolved comparative meta-atlases. This new approach seeks not only to understand the fundamental processes of development, physiology, and disease but also to predict cellular behaviors and their evolutionary trajectories, ultimately achieving a mechanistic understanding of life's complexity.
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Construction of T-Cell-Related Prognostic Risk Models and Prediction of Tumor Immune Microenvironment Regulation in Pancreatic Adenocarcinoma via Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq.
Pancreatic adenocarcinoma (PAAD) is a fatal malignant tumor of the digestive system, and immunotherapy has currently emerged as a key therapeutic approach for treating PAAD, with its efficacy closely linked to T-cell subsets and the tumor immune microenvironment. However, reliable predictive markers to guide clinical immunotherapy for PAAD are not available. We analyzed the single-cell RNA sequencing (scRNA-seq) data focused on PAAD from the GeneExpressionOmnibus (GEO) database. Then, the information from the Cancer Genome Atlas (TCGA) database was integrated to develop and validate a prognostic risk model derived from T-cell marker genes. Subsequently, the correlation between these risk models and the effectiveness of immunotherapy was explored. Analysis of scRNA-seq data uncovered six T-cell subtypes and 1837 T-cell differentially expressed genes (DEGs). Combining these data with the TCGA dataset, we constructed a T-cell prognostic risk model containing 16 DEGs, which can effectively predict patient survival and immunotherapy outcomes. We have found that patients in the low-risk group had better prognostic outcomes, increased immune cell infiltration, and signs of immune activation compared to those in the high-risk group. Additionally, analysis of tumor mutation burden showed higher mutation rates in patients with PAAD in the high-risk group. Risk scores with immune checkpoint gene expression and drug sensitivity analysis provide patients with multiple therapeutic targets and drug options. Our study constructed a prognostic risk model for PAAD patients based on T-cell marker genes, providing valuable insights into predicting patient prognosis and the effectiveness of immunotherapy.
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A single-cell transcriptomic atlas of the pigtail macaque placenta in late gestation.
BACKGROUND: The placenta is a complex organ with multiple immune and non-immune cell types that promote fetal tolerance and facilitate the transfer of nutrients and oxygen. The nonhuman primate (NHP) is a key experimental model for studying human pregnancy complications, in part due to similarities in placental structure, which makes it essential to understand how single-cell populations compare across the human and NHP maternal-fetal interface. We constructed a single-cell RNA-Seq (scRNA-Seq) atlas of the placenta from the pigtail macaque (Macaca nemestrina) in the third trimester, comprising three different tissues at the maternal-fetal interface: the chorionic villi (placental disc), chorioamniotic membranes, and the maternal decidua. Each tissue was separately dissociated into single cells and processed through the 10X Genomics and Seurat pipeline, followed by aggregation, unsupervised clustering, and cluster annotation. Next, we determined the maternal-fetal origins of cell populations and analyzed single-cell RNA trajectory, Gene Ontology enrichment, and cell-cell communication. RESULTS: Single-cell populations in the pigtail macaque were strikingly similar in their identity and frequency to those found in the human placenta, including cells from trophoblast, stromal cell, immune, and macrophage lineages. An advantage of our approach was the deep sequencing of three tissues at the maternal-fetal interface, which yielded a rich diversity of common and rare single-cell populations. CONCLUSIONS: Single-cell populations from the third-trimester pigtail macaque placenta are highly concordant with those from the human placenta. This scRNA-Seq atlas provides a powerful resource for understanding experimental perturbations on the NHP placenta.