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Integrating large-scale single-cell RNA sequencing in central nervous system disease using self-supervised contrastive learning.
The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-scale CNS scRNA-seq data still encounters challenges due to the complexity and heterogeneity among CNS cell types/subtypes. In this study, we introduce a self-supervised contrastive learning method, called scCM, for integrating large-scale CNS scRNA-seq data. scCM brings functionally related cells close together while simultaneously pushing apart dissimilar cells by comparing the variations of gene expression, effectively revealing the heterogeneous relationships within the CNS cell types/subtypes. The effectiveness of scCM is evaluated on 20 CNS datasets covering 4 species and 10 CNS diseases. Leveraging these strengths, we successfully integrate the collected human CNS datasets into a large-scale reference to annotate cell types and subtypes in neural tissues. Results demonstrate that scCM provides an accurate annotation, along with rich spatial information of cell state. In summary, scCM is a robust and promising method for integrating large-scale CNS scRNA-seq data, enabling researchers to gain insights into the cellular and molecular mechanisms underlying CNS functions and diseases.
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A cross-model single-cell atlas reveals conserved involvement of osteopontin in polycystic kidney disease.
Polycystic kidney disease (PKD) arises from mutations in cilia-associated genes, such as PKD1 and PKD2, expressed in renal epithelial cells, leading to progressive kidney dysfunction and end-stage kidney disease. Patients with PKD exhibit significant heterogeneity in disease progression, largely due to genetic and environmental modifiers. Like patients, mouse models of PKD also exhibit significant heterogeneity with regards to the gene mutated, age of disease onset, and rate of disease progression. To elucidate the cellular and molecular consequences of these variables, we constructed an integrated single-cell RNA sequencing (scRNA-seq) atlas across mouse models of PKD, mapping changes in cell type composition, gene expression, and intercellular signaling networks across the whole atlas and within individual models. Across models, scRNA-seq data revealed increased Spp1 (osteopontin) expression and signaling from PKD-enriched clusters. Global deletion of Spp1 in Pkd1RC/RC mice resulted in a modest reduction in cyst severity and improved kidney function. From these studies, we created a freely available, searchable website (https://bmblx.bmi.osumc.edu/scPKD/) that can be used to identify cross- and intra-model changes in gene expression, guiding researchers to new therapeutic targets for treating PKD.
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Analyzation of the Peripheral Blood Mononuclear Cells Atlas and Cell Communication of Rheumatoid Arthritis Patients Based on Single-Cell RNA-Seq.
BACKGROUND: Rheumatoid arthritis (RA) is a common chronic inflammatory autoimmune disease with a multifactorial etiology. Peripheral blood is the main channel of the immune system, and peripheral blood mononuclear cells (PBMCs) are the immune cells that initiate the autoimmune inflammatory process. However, there are few reports on the mechanisms of peripheral blood immunity in RA. METHODS: ScRNA-seq was performed on four RA samples and integrated with single-cell transcriptome data from four healthy control samples downloaded from publicly available databases for analysis. RESULTS: A total of 52,073 cells were used for descending clustering analysis to map RA peripheral blood immune cells at single-cell resolution. Redimensional clustering analysis of four major immune cells (T cells, monocytes, B cells, and natural killer cells) revealed that double-negative T (DNT) cells were significantly altered in abundance and function. And a number of genes (including SOCS3, cAMP-responsive element modulator (CREM), B2M, MTFP1, RSRP1, and YWHAB) were specifically downregulated in DNT cells. RA T cells, especially DNT cells, exhibit significant metabolic defects and dysfunction, mainly in the form of inhibition of oxidative phosphorylation, ATP synthesis, and major histocompatibility complex (MHC)-I-mediated antigen presentation. In addition, cellular communication networks were established, and it was evident that RA is significantly attenuated in the number and intensity of cellular communication. Monocytes and T cells play key roles in the process of the immune inflammatory response through CCL and MHC-related pathways. CONCLUSIONS: This study describes the landscape of the peripheral blood immune system and cell communication in RA, characterizes the abundance of PBMCs, gene expression profiles, and changes in signaling pathways in RA patients, and identifies several key cell subpopulations (DNT and classic monocytes) and specific genes (SOCS3, CREM, B2M, MTFP1, RSRP1, and YWHAB). Meanwhile, we propose that classic monocytes in peripheral blood may migrate to sites of inflammation in synovial tissue under the chemotaxis of the chemokines CCL3 and CCL3L1, differentiate into macrophages, secrete proinflammatory cytokines, and thus participate in the inflammatory response. These findings provide new insights for the future elucidation of the peripheral blood immune mechanisms of RA and the search for new clinical therapeutic targets.
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A pan-cancer single-cell atlas uncovers the role of sex hormones and chromosomes in sex-divergent reprogramming of the tumor microenvironment.
BACKGROUND: Sex bias is pervasive in tumors; however, how sex chromosomes and hormone-responsive signaling shape the tumor microenvironment (TME) remains insufficiently characterized. Considering the critical impact of the TME on tumor progression and response to immunotherapy, a pan-cancer investigation of sex-specific and cancer-context-dependent TME features is warranted. METHOD: Based on stringent inclusion criteria, we constructed a high-resolution pan-cancer single-cell sequencing atlas by integrating 31 publicly available single-cell RNA-seq datasets, comprising a total of 1,831,436 cells by integrating 468 samples from eight types of non-sex-specific solid tumors (282 males and 186 females). After correcting for batch effects, we identified major and minor cellular subsets. Multiple computational approaches were applied to investigate sex-associated differences in cellular composition, gene expression, pathway activity, malignant cell states and intercellular communication. RESULTS: We systematically compared sex-specific TME features across eight common solid malignancies. Male-biased CD8+ T cell exhaustion emerged as a recurrent but non-uniform feature, with its magnitude varying across cancer types and being modified by tissue-specific contexts. This pattern was associated with androgen-response signature scores and expression-based loss of the Y chromosome (LOY) scores. M2-like macrophage polarization showed a more cancer-type-dependent pattern; although female-biased enrichment was observed in selected malignancies, it did not represent a uniform pan-cancer feature. Expression-based X chromosome inactivation (XCI)/XCI escape-related programs, estrogen-response signature scores and stromal components, including fibroblasts and endothelial cells, were associated with macrophage and immune-regulatory states in specific tumor contexts. Tumor cells of male origin displayed higher genomic instability and more aggressive phenotypes, with androgen-response signatures and LOY contributing to the development of a male biased malignant state. Furthermore, expression-based LOY scores in malignant cells were associated with CD8+ T cell exhaustion based on transcriptomic proxies. CONCLUSION: Our study uncovers extensive but heterogeneous sex-specific differences in the TME across multiple cancer types. We propose a regulatory framework linking sex chromosomes, hormone-responsive signaling and TME interactions, which is consistent with recurrent male-biased CD8⁺ T cell exhaustion and context-dependent M2-like macrophage polarization. Importantly, the magnitude and, in some cancers, the direction of these sex-biased features are modified by tissue-specific contexts. These findings underscore the need to include sex chromosome and hormone status as essential biological variables in studies of the tumor microenvironment and the design of immunotherapies.
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A gene regulatory network-aware graph learning method for cell identity annotation in single-cell RNA-seq data.
Cell identity annotation for single-cell transcriptome data is a crucial process for constructing cell atlases, unraveling pathogenesis, and inspiring therapeutic approaches. Currently, the efficacy of existing methodologies is contingent upon specific data sets. Nevertheless, such data are often sourced from various batches, sequencing technologies, tissues, and even species. Notably, the gene regulatory relationship remains unaffected by the aforementioned factors, highlighting the extensive gene interactions within organisms. Therefore, we propose scHGR, an automated annotation tool designed to leverage gene regulatory relationships in constructing gene-mediated cell communication graphs for single-cell transcriptome data. This strategy helps reduce noise from diverse data sources while establishing distant cellular connections, yielding valuable biological insights. Experiments involving 22 scenarios demonstrate that scHGR precisely and consistently annotates cell identities, benchmarked against state-of-the-art methods. Crucially, scHGR uncovers novel subtypes within peripheral blood mononuclear cells, specifically from CD4+ T cells and cytotoxic T cells. Furthermore, by characterizing a cell atlas comprising 56 cell types for COVID-19 patients, scHGR identifies vital factors like IL1 and calcium ions, offering insights for targeted therapeutic interventions.
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Single-Cell RNA Sequencing in Porcine Biology and Production.
Single-cell RNA sequencing (scRNA-seq) has emerged as a transformative technology for resolving cellular heterogeneity and deciphering gene regulatory networks in complex tissues. Despite challenges such as incomplete genome annotation, technical variability across platforms, and limitations in robust cell-type annotation, scRNA-seq has substantially advanced our understanding of the developmental processes, physiological regulation, and disease responses in pigs, an economically and biomedically important species, thereby providing insights into traits of agricultural and translational relevance. By profiling transcriptomes at the single-cell resolution, scRNA-seq enables the identification of rare cell populations, dynamic cellular states, and lineage trajectories that are critical for reproduction, growth, immunity, and metabolic homeostasis. Recent porcine scRNA-seq studies have generated high-resolution cellular atlases spanning embryos, reproductive organs, immune tissues, skeletal muscle, and the gastrointestinal tract, revealing cell-type-specific regulatory mechanisms associated with reproductive performance, muscle accretion, adipogenesis, immune competence, and intestinal functionality. This review summarizes the fundamental principles and analytical strategies of scRNA-seq, highlights its major applications in porcine biology and production, and discusses current challenges as well as future perspectives for integrating single-cell technologies into livestock science.
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A single-cell transcriptomic atlas reveals the immune panorama of neonatal sepsis.
Neonatal sepsis remains a leading cause of infant mortality, yet mechanisms driving concurrent hyperinflammation and immunosuppression remain unclear. Here, we perform single-cell RNA sequencing on 26 blood samples from 18 neonates, spanning acute sepsis, convalescence, and healthy controls. We identify 57 cell subtypes, revealing acute lymphoid depletion and myeloid expansion. S100A8+ myeloid-derived suppressor cell-like (MDSC-like) cells represent a putative cytokine-storm source, potentially amplified by a feedforward S100-TLR4-MYD88 circuit. Innate-like lymphocytes fail to expand, succumbing to apoptosis and exhaustion despite heightened cytotoxicity. CD4+ T cells display mitochondrial dysfunction, while regulatory T cells acquire a hyper-suppressive phenotype via the LGALS9-HAVCR2 axis. CD8+ T cells undergo interferon-driven, innate-like reprogramming before lapsing into exhaustion, and B cells shift toward stress-adaptive, tolerogenic states. Together, our atlas defines a dual pathology in which MDSC-like cell-driven cytokine storm coexists with multi-lineage immunoparalysis, nominating the S100-TLR4 axis and mitochondrial dysregulation as potential therapeutic targets.
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Single-cell RNA sequencing identifies long non-coding RNAs enriched in psoriatic epidermal subsets.
BACKGROUND: Psoriasis is a chronic inflammatory skin disease characterised by disrupted crosstalk between keratinocytes and immune cells, resulting in epidermal dysfunction. Long non-coding RNAs (lncRNAs) regulate gene expression in a cell- or tissue-specific manner, yet their role in psoriatic epidermal dysfunction remains poorly understood. OBJECTIVES: To generate a single-cell atlas of lncRNA expression in healthy and psoriatic epidermis and identify cell state-specific lncRNAs associated with disease. METHODS: Data from Smart-seq2 single-cell RNA sequencing of sorted CD45⁺ and CD45⁻ epidermal cells from healthy controls and lesional/non-lesional psoriatic skin were analysed. Selected lncRNAs were validated by RT-qPCR, single-molecule in situ hybridisation (RNAscope), and immunofluorescence. The regulation of LINC01137 was studied in IL-17A-treated primary keratinocytes and 3D epidermal models, and its function assessed using siRNA-mediated knockdown in keratinocytes. RESULTS: We identified 1412 epidermal lncRNAs with robust expression across distinct keratinocyte and immune cell states. LncRNAs exhibited strong cell type-specific expression in both keratinocytes and immune cells, moreover, several lncRNAs showed selective expression in psoriasis-associated cell states. LINC01137 was enriched in activated keratinocytes, induced by IL-17A and correlated with TGF-β pathway activity; its knockdown in primary keratinocytes attenuated TGF-β-induced SERPINE1/PAI-1 expression. LINC00892 was enriched in lesional Th1, Th17 and proliferating CD8+ T cells and showed increased expression as well as co-localisation with the T cell marker CD3 in psoriasis epidermis. CONCLUSIONS: This study identifies the single-cell non-coding transcriptomic landscape of the psoriatic epidermis and highlights distinct lncRNA signatures in keratinocytes and immune cells, suggesting their involvement in pathogenic processes in psoriasis.
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A single-cell atlas of the human airways from patients with allergic rhinitis comorbid with asthma.
BACKGROUND: Single-cell RNA profiling has already been applied to normal airway samples, but no data set includes brushings collected from patients with allergic rhinitis combined with asthma (ARcoAS) at distinct and well-identified microanatomical regions in the airways. OBJECTIVE: To investigate cell population distributions and transcriptional changes along the upper and lower airways of patients with ARcoAS by using single-cell RNA profiling. METHODS: Nasal and bronchial brush cells from patients with ARcoAS and healthy volunteers were collected for single-cell RNA sequencing analysis. The cellular clusters, differential gene analysis, cellular pathway enrichment, mimetic temporal analysis, and cellular communication were analyzed between the nasal and bronchial airways. RESULTS: A similar alteration in the cell profiles of the upper and lower airways was observed under chronic inflammatory conditions. A total of 3613 (57%) shared up-regulated genes, and 5410 (66%) shared down-regulated genes were identified between the upper and lower airways of ARcoAS. Impaired structure of ciliated cells and epithelial barrier was observed in diseased nasal and bronchial airways. The intercellular communication analysis revealed a decreased number and strength of intercellular interactions between epithelial cells and immune cells in the ARcoAS group. We found that the GZMA-PARD3 pathway disrupts the airway epithelial barrier in vitro. CONCLUSION: Our findings suggest that compromised ciliated cells and aberrant proliferation of basal cells may drive eosinophilic inflammation in response to type 2 inflammation in patients with ARcoAS. Robust characterization of a single-cell cohort in allergic airways establishes a valuable resource for future investigations and provides potential targets for tailored treatment.
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Single-Cell Annotation and Localization via Integrating Spatial Transcriptomics Maps the Mouse Ocular Atlas and RAO Dynamics.
Retinal artery occlusion (RAO), a blinding emergency, demands clarification of cellular spatiotemporal dynamics for targeted therapies. Single-cell RNA-seq is powerful but lacks spatial context, whereas spatial transcriptomics struggles with cell segmentation errors and low transcript capture efficiency. To overcome these, we developed the ASCAL (Automated Single-Cell Annotation and Localization) pipeline, integrating complementary spatial transcriptomics techniques: single-nucleus-resolution SeekSpace for cell annotation reference and uniform-coverage Stereo-seq for localization of annotated cells. This strategy enables automated annotation and localization of large-scale scRNA-seq datasets with minimal spatial sections. Leveraging ASCAL, we constructed a mouse whole-eye single-cell spatial atlas precisely mapping cell types across the ciliary body and retina. Moreover, we revealed pronounced spatial immune activation specifically enriched in the ganglion cell layer (GCL) in the RAO model, further validated by immunofluorescence staining. We also uncovered a selective depletion of active Rods. Importantly, RNAscope assays independently validated both the peripheral localization of this active Rod subcluster and its pronounced loss following RAO. Overall, this study provides a comprehensive spatial cell atlas of the whole eye and offers novel spatial-resolution insights into the pathological mechanisms of RAO, serving as a valuable resource for deciphering the physiological and pathological landscapes of the eye at single-cell resolution.