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scNCL: transferring labels from scRNA-seq to scATAC-seq data with neighborhood contrastive regularization.
MOTIVATION: scATAC-seq has enabled chromatin accessibility landscape profiling at the single-cell level, providing opportunities for determining cell-type-specific regulation codes. However, high dimension, extreme sparsity, and large scale of scATAC-seq data have posed great challenges to cell-type identification. Thus, there has been a growing interest in leveraging the well-annotated scRNA-seq data to help annotate scATAC-seq data. However, substantial computational obstacles remain to transfer information from scRNA-seq to scATAC-seq, especially for their heterogeneous features. RESULTS: We propose a new transfer learning method, scNCL, which utilizes prior knowledge and contrastive learning to tackle the problem of heterogeneous features. Briefly, scNCL transforms scATAC-seq features into gene activity matrix based on prior knowledge. Since feature transformation can cause information loss, scNCL introduces neighborhood contrastive learning to preserve the neighborhood structure of scATAC-seq cells in raw feature space. To learn transferable latent features, scNCL uses a feature projection loss and an alignment loss to harmonize embeddings between scRNA-seq and scATAC-seq. Experiments on various datasets demonstrated that scNCL not only realizes accurate and robust label transfer for common types, but also achieves reliable detection of novel types. scNCL is also computationally efficient and scalable to million-scale datasets. Moreover, we prove scNCL can help refine cell-type annotations in existing scATAC-seq atlases. AVAILABILITY AND IMPLEMENTATION: The source code and data used in this paper can be found in https://github.com/CSUBioGroup/scNCL-release.
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Using In Silico Pseudobulk Differential Expression and Trajectory Analysis of Single Cell RNA Sequencing to Reveal Stem Cell State Transitions in Colonic Inflammation.
Colonic inflammation induces profound alterations in the intestinal mucosa that are evident at both macroscopic and microscopic levels, including disruption of epithelial barrier integrity, crypt fission, and immune cell infiltration. Recent advances in single-cell and spatial RNA sequencing have greatly expanded our understanding of the cellular diversity of the colonic mucosa, enabling pathological features to be directly linked to underlying cellular and molecular mechanisms. This chapter demonstrates the application of single-cell RNA sequencing (scRNA-seq) analysis techniques to interrogate stem cell dynamics in the context of inflammatory bowel disease. Using publicly available datasets, the chapter provides a step-by-step workflow implemented in Python, covering data access, loading, integration of multiple datasets, and initial preprocessing. Cells are mapped to large single-cell atlas references to infer cell identities, followed by a pseudobulk analysis strategy to assess inflammation-associated changes in cell phenotypes. Finally, trajectory inference approaches are applied to explore potential mechanisms governing the specification and modulation of key cell types during inflammation. Accompanied by an online resource containing fully annotated scripts, this chapter offers guided instruction in contemporary scRNA-seq analysis workflows. It is intended as an accessible introduction for researchers seeking to develop practical skills in single-cell data analysis that can be readily applied to their own biological questions.
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Single-cell transcriptomics of the Drosophila ring gland identifies the SoxN-Vvl complex as a key regulator of juvenile hormone biosynthesis.
Juvenile hormone (JH) is essential for maintaining juvenile status and promoting reproduction in insects, yet the transcriptional regulation of JH biosynthesis remains poorly understood. Previous transcriptomic studies of the Drosophila ring gland-which is composed of the corpus allatum (CA), prothoracic gland (PG), and corpora cardiaca (CC)-have treated the ring gland as a single tissue. As a result, these approaches lacked the resolution necessary to dissect JH biosynthesis and its regulation in a cell-type-specific manner. To overcome this limitation, we performed single-cell RNA sequencing (scRNA-seq) of 7,919 cells isolated from the larval ring glands. This analysis resolved distinct transcriptional profiles for the CA, PG, and CC, and enabled the identification of CA-specific transcription factors. Among them, SoxNeuro (SoxN), was found to be essential for JH biosynthesis and functionally important for both metamorphosis and reproduction. We further demonstrate that SoxN physically interacts with Ventral veins lacking (Vvl) to form a transcriptional complex that directly regulates Jhamt, a rate-limiting enzyme in JH biosynthesis, via a defined promoter region. Together, this work presents a single-cell transcriptomic atlas of the Drosophila ring gland and identifies the SoxN-Vvl complex as a critical regulator of JH biosynthesis, offering insight into the transcriptional control of insect endocrine function.
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Anti-tumor effects on tumor-infiltrating natural killer cells by localized ablative immunotherapy and immune checkpoint inhibitors: An integrated and comparative study using scRNAseq analysis.
Localized ablative immunotherapy (LAIT), a combination of photothermal therapy (PTT) and the immunostimulant glycated chitosan (GC), has demonstrated therapeutic efficacy in cancer treatment. However, its impact on the tumor microenvironment (TME), particularly on tumor-infiltrating natural killer (TINK) cells, remains to be fully elucidated. Using single-cell RNA sequencing (scRNAseq), we analyzed the transcriptional and functional modulations of TINK cells by LAIT in a mouse breast cancer model. Additionally, we investigated immune checkpoint inhibitor (ICI)-induced changes in NK cells across multiple cancer types and evaluated the clinical relevance of these transcriptional changes using The Cancer Genome Atlas (TCGA) database. ScRNAseq revealed five NK cell subtypes, with LAIT increasing the proportion of interferon-enriched NK cells and enhancing NK cell differentiation and cytotoxicity. Functional analyses demonstrated that LAIT upregulated activation, cytotoxic, and interferon pathway genes while downregulating immune-suppressive genes, effects largely driven by GC. Comparative analysis showed significant transcriptional overlap between ICI and LAIT, highlighting shared pathways in NK cell-mediated cytotoxicity and chemokine signaling. Prognostic models constructed from ICI- and LAIT-induced gene signatures effectively stratified breast cancer patients by survival risk, with LAIT-induced genes showing the highest predictive performance. Furthermore, higher NK cell proportions and the expression of key prognostic genes, such as PSME2, IGKC, and KLRB1, were associated with improved overall survival. LAIT and ICIs enhance NK cell-mediated antitumor responses via distinct yet complementary mechanisms, emphasizing their potential for synergistic use. These findings provide novel insights into NK cell modulation within the TME and support the development of combinatorial immunotherapy strategies.
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A single-cell transcriptomic atlas reveals the emergence of medusa-specific cell states in the scyphozoan Aurelia coerulea.
The life cycle of most medusozoan cnidarians is marked by the metagenesis from the asexually reproducing sessile polyp and the sexually reproducing motile medusa. At present, it is unknown to what extent this drastic morphological transformation is accompanied by molecular changes in the cell type composition. Here, we provide a single-cell transcriptome atlas of the cosmopolitan scyphozoan Aurelia coerulea focusing on changes in individual cell states during the transition from polyp to medusa. Notably, this transition is marked by an increase in cell type diversity, including an expansion of neural subtypes and the appearance of striated muscles. We find that two families of neuronal lineages are specified by homologous transcription factors in the sea anemone Nematostella vectensis and A. coerulea, suggesting an origin in the common ancestor of medusozoans and anthozoans about 500 Myr ago. Our analysis suggests that gene duplications might be drivers for the increase of cellular complexity during the evolution of cnidarian neuroglandular lineages and highlights the close relationship of neurons and muscles. One key medusozoan-specific cell type is the striated muscle in the subumbrella. Evaluating muscle types by fiber anatomy and gene expression validation of their individual molecular profiles made it possible for the first time to investigate transcriptome differences between smooth and striated muscles. Although smooth and striated muscles are phenotypically different, both have a similar regulation of the contractile complex, reminiscent to the regulation of smooth muscles in bilaterians. This contrasts with bilaterian striated muscles, where the regulation of muscle contraction involves Ca2+ binding troponins and their interaction with Tropomyosin. These data suggest that smooth muscle contraction regulation is ancestral and the use of troponins in striated muscles only evolved in bilaterians.
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Cross-species scRNA-seq reveals the cellular landscape of retina and early alterations in type 2 diabetes mice.
Single-cell RNA sequencing (scRNA-seq) analysis have provided an unprecedented resolution for the studies on diabetic retinopathy (DR). However, the early changes in the retina in diabetes remain unclear. A total of 8 human and mouse scRNA-seq datasets, containing 276,402 cells were analyzed individually to comprehensively delineate the retinal cell atlas. The neural retinas were isolated from the type 2 diabetes (T2D) and control mice, and scRNA-seq analysis was conducted to evaluate the early effects of diabetes on the retina. Bipolar cell (BC) heterogeneity were identified. We found some stable BCs across multiple datasets, and explored their biological functions. A new RBC subtype (Car8_RBC) in the mouse retina was validated using the multi-color immunohistochemistry. AC149090.1 was significantly upregulated in the rod cells, ON cone BCs (CBCs), OFF CBCs, and RBCs in T2D mice. Additionally, the interneurons, especially BCs, were the most vulnerable cells to diabetes by integrating scRNA-seq and genome-wide association studies (GWAS) analyses. In conclusion, this study delineated a cross-species retinal cell atlas and uncovered the early pathological alterations in the retina of T2D mice.
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Single-cell transcriptomics reveals diversity and conservation of chicken lymphocytes.
The domestic chicken (Gallus gallus) is a critical model for immunology and a major agricultural species, yet a comprehensive single-cell census of its immune architecture is lacking. Here, we constructed a high-resolution single-cell transcriptome atlas of three primary immune organs (thymus, bursa of Fabricius, and spleen) from chickens. Our analysis identified 24 distinct immune and stromal cell types, mapping their organ-specific distributions: B cells were predominantly localized to the bursa of Fabricius, while T cell subsets were enriched in the thymus. We delineated developmental trajectories and identified key transcription factors governing lineage commitment, including TCF12 for CD4⁺CD8⁺ T cells and SOX13 for T helper 2 cells. Further analysis revealed potential sexually dimorphic immune maturation, where B cells exhibited sex-biased gene expression primarily in early differentiation stages, whereas T cell differences were most pronounced during proliferation. Cross-species comparison demonstrated remarkable conservation of core immunoregulatory circuits, with transcription factors like MEF2C, LEF1, and GATA3 playing conserved roles in avian and mammalian immunity. This resource provides a foundational framework for understanding avian immune defense, advancing poultry disease-resistant breeding, and offers evolutionary insights into vertebrate immunology.
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Upregulation of interferon-γ activation in patients with anti-interferon-γ autoantibodies immunodeficiency syndrome: insights from single-cell analysis.
BACKGROUND: Anti-interferon-γ autoantibodies (AIGAs) immunodeficiency syndrome is an emerging adult-onset immunodeficiency causing opportunistic infections. However, its comprehensive immune landscape remains elusive. This study presents the first single-cell RNA sequencing (scRNA-seq) analysis of AIGAs immunodeficiency syndrome, aiming to delineate its pathogenic mechanisms. METHODS: We performed scRNA-seq on peripheral blood mononuclear cells (PBMCs) from 8 AIGAs immunodeficiency syndrome patients (4 infective, 4 stable phase) and 3 healthy controls. Findings were validated by flow cytometry in an expanded cohort (15 patients vs. 10 controls). RESULTS: Single-cell RNA sequencing of PBMCs from patients with AIGAs immunodeficiency syndrome identified a comprehensive immune subset profile, including effector memory CD4+ T cells, naive CD4+ T cells, regulatory T cells, GNLY+ CD8+ Tem, GZMK+ CD8+ Tem, naive CD8+ T cells, naive B cells, memory B cells, plasma cells, ISG+ atypical B cells, monocytes, and NKT cells. ScRNA-seq analysis revealed a significantly higher proportion of Th1 cells (16.62% vs. 6.94% in controls) and ISG+ B cells (2.95% vs. 0.53%), alongside a lower proportion of plasma cells (9.30% vs. 17.79%) and memory B cells (9.54% vs. 27.35%). Flow cytometry consistently confirmed the increase in Th1 cells (21.84% [14.87-27.57] vs. 11.96% [7.19-15.74]) and decreases in marginal zone B cells (2.87% [1.71-4.45] vs. 8.60% [6.77-15.65]), memory B cells (13.85% [5.72-20.23] vs. 22.96% [16.39-33.83]), and class-switched B cells (6.11% [2.39-9.10] vs. 10.18% [5.35-15.77]). Transcriptome analysis demonstrated upregulated expression of interferon-response and HLA genes (e.g., HLA-DQB1, HLA-DQA1, HLA-DRB1), whereas IRF1 was downregulated across all subsets; functional enrichment analyses further highlighted significant activation in IFN signaling and B cell activation pathways. CellChat and pseudotime analyses indicated that CD4+ Tem and CD14+ monocytes drive sustained Th1 inflammation and monocyte hyperactivation through enhanced pro-inflammatory and antigen-presenting interactions, with T-cell differentiation skewed toward terminal effectors and B-cell development disrupted by ISG+ B cell emergence, premature plasma cell formation, and IGLC3-biased class switching, collectively delineating the interferon-mediated immunopathology of AIGAs immunodeficiency syndrome. CONCLUSIONS: In summary, this first single-cell atlas maps AIGAs immunodeficiency syndrome as a Th1-skewed, IFN-γ-driven disorder sustained by CD4+ Tem-CD14+ monocyte crosstalk. It combines T-cell activation, expanded Th1 and ISG+ B cells, and loss of memory/plasma B cells to drive autoantibody generation. Skewed T- and B-cell trajectories and polygenic up-regulation of interferon/HLA genes provide a clear mechanistic rationale for targeted therapy.
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Single-cell transcriptomics reveals the hemocyte atlas and molecular mechanisms underlying the growth-immunity trade-off in Litopenaeus vannamei.
Individual growth heterogeneity in Litopenaeus vannamei severely constrains aquaculture uniformity and yield, yet the systemic cellular regulatory mechanisms underlying this phenomenon remain elusive. Here, we combined scRNA-seq and weighted gene co-expression network analysis (WGCNA) to systematically compare hemocyte profiles between fast-growing (FG) and slow-growing (SG) groups, to elucidate the cellular and molecular basis of the "growth-immunity trade-off." We identified six major hemocyte clusters and reconstructed a continuous differentiation trajectory spanning from progenitor-like cells (Cluster 5/0) through a high-metabolic biosynthetic transition state (Cluster 1/3) to mature immune effectors (Cluster 2/4). Pseudotime analysis indicated divergent hemocyte distribution patterns between the two groups: FG hemocytes were predominantly enriched near the trajectory origin (Cluster 5), a population characterized by high expression of tissue development-related genes. In contrast, cells from the SG group were shifted toward the intermediate and terminal stages, showing specific enrichment in the energy-demanding "biosynthetic" subpopulation (Cluster 3). Differential expression analysis showed that Cluster 3 cells in the SG group significantly upregulated mitochondrial complex I subunit (Ndufs3), oxidative phosphorylation, the TCA cycle, and ribosome pathways, exhibiting typical characteristics of high immuno-metabolism. WGCNA further uncovered the upstream regulatory networks driving this trade-off: the FG group systematically activated the dark-orange module (centered on IRS1 and CCND1), which synergistically maintains progenitor reserves via mTOR and insulin signaling. Conversely, the SG group showed higher activity of the turquoise module, characterized by aminoacyl-tRNA biosynthesis and the expression of the antimicrobial peptide Crustin in progenitor-like cells, suggesting a stress-associated immune activation state. These findings suggest that slow growth may be associated with a transcriptomic shift from progenitor-like states toward energetically demanding immune-related states, providing a cellular hypothesis for the growth-immunity trade-off in L. vannamei. These findings provide a novel cellular perspective on crustacean growth traits and identify key molecular targets for breeding superior strains that balance disease resistance and growth.
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Integrated profiling of RUNX3 in intratumoral NK cells activity through bulk and single-cell transcriptomic analysis.
BACKGROUND: Natural killer (NK) cells are core components of innate antitumor immunity, the dysfunction of NK cells in the tumor microenvironment is a major obstacle to the antitumor efficacy. Runt-related transcription factor 3 (RUNX3) acts as a critical tumor suppressor and regulates immune cell function, while its biological role in NK cells remains largely unexplored. Herein, we investigated the interaction between RUNX3 and NK cells in tumor microenvironment. METHODS: The Cancer Genome Atlas (TCGA) database was utilized to determine the genetic alteration of RUNX3 in pan-cancer. TIMER and GEPIA website were used to evaluate the correlation between RUNX3 and immune cell infiltration. Single-cell RNA sequencing (scRNA-seq) analysis was applied to characterize RUNX3 expression and pseudotime trajectory in NK cells. In vitro experiments were further performed to validate RUNX3's role in regulating NK cell functions. RESULTS: RUNX3 was significantly downregulated in lung adenocarcinoma and hepatocellular carcinoma tissues. Clinical analyses have demonstrated that defective RUNX3 expression was correlated with adverse prognosis. Immune infiltration analyses revealed that RUNX3 was positively associated with immune cell infiltration, particularly NK cells and CD8+ T cells. scRNA-seq indicated RUNX3 enrichment in intratumoral NK cells, and differential genes of RUNX3 were enriched in the MAPK signaling pathway. Pseudotime trajectory analysis indicated RUNX3 participated in NK cell differentiation. Moreover, RUNX3 overexpression enhanced NK cell viability, chemotactic capacity, cytotoxicity against tumor cells, and secretion of pro-inflammatory cytokines and granzyme B, while upregulating NK cell activation receptors. CONCLUSION: Our findings identify RUNX3 as a key regulator of NK cell-mediated antitumor immunity in LUAD and LIHC, providing a novel molecular target for enhancing innate immune surveillance and developing targeted immunotherapies for the aggressive malignancies.