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The Transcriptomic Signature of Donkey Ovarian Tissue Revealed by Cross-Species Comparative Analysis at Single-Cell Resolution.
Donkeys (Equus asinus) hold significant agricultural value in China, particularly for their hides and meat, which possess notable medicinal and dietary importance. However, their reproductive efficiency remains suboptimal compared with other livestock. Ovarian function is a key determinant of fertility, yet the molecular mechanisms underlying donkey ovarian biology remain largely unexplored. To address this gap, we performed single-cell RNA sequencing of donkey ovaries, generating a high-resolution transcriptomic atlas comprising 17,423 cells. Cross-species comparative analysis revealed a high degree of evolutionary conservation in core ovarian cell types, including endothelial, epithelial, immune, and smooth muscle cells, among vertebrates. In contrast, granulosa and theca cells exhibited distinct transcriptional profiles across species, reflecting lineage-specific adaptations. Notably, we identified key genes with donkey-specific expression patterns, including NR3C1 in endothelial cells, LIPE in granulosa cells, and DHRS9 in theca interna cells. Furthermore, an in vitro cumulus-oocyte complex model demonstrated the critical role of GATM in mammalian oocyte maturation. Collectively, these findings provide a comprehensive characterization of ovarian cell-type conservation and species-specific adaptations, offering key molecular insights into the mechanisms underlying cross-species differences in reproductive efficiency.
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Single-cell RNA-seq reveals the communications between extracellular matrix-related components and Schwann cells contributing to the earlobe keloid formation.
Keloid is a major type of skin fibrotic disease, with one prominent feature of extensive accumulation of extracellular matrix (ECM) components, and another feature of pain/itching, which is closely related to the peripheral nervous system (PNS). However, the molecular pathogenesis of these two prominent features still needs to be further explored. In the present study, we performed single-cell RNA sequencing (scRNA-seq) on clinical earlobe keloid samples and adjacent normal skin samples and constructed a keloid atlas of 31,379 cells. All cells were clustered into 13 major cell types using cell-type-specific markers. Among them, fibroblast, vascular endothelial cells, and smooth muscle cells were defined as the ECM-related populations according to their ECM-associated functions. Also, we found that Schwann cells (SCs) were the main neuron cells of PNS in the skin. Interestingly, the cell proportions of ECM-related populations, as well as SC were increased significantly in the earlobe keloid compared to the adjacent normal tissues, suggesting an important role of these cell types in the development of the earlobe keloid. Comprehensive cell-cell interaction analysis at the single-cell level revealed a strong interaction between SC and ECM-related subgroups which might be mediated by SEMA3C signaling pathways and MK/PTN gene family, which are found to be mainly involved in promoting cell proliferation and migration. Moreover, further exploration of the interactions of ECM-related populations and SC in different keloids, including earlobe keloid, back keloid, and chest keloid revealed an increasing amount of TGFβ-TGFβ receptor interactions in chest/back keloids as compared to earlobe keloid, which suggested the anatomic site-specific pathogenesis in different keloids. Altogether, these findings suggested the interactions between ECM-related populations and SC contributing to the earlobe keloid formation and helped us to better understand the pathogenesis of keloids.
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scBrainScope: cross-species multidimensional brain atlas.
As one of the most evolutionarily complex and functionally diverse organs, the brain is characterized by its intricate structure, developmental alterations, and cellular heterogeneity. Although extensive brain atlases exist, there remains an urgent need for an integration platform that brings together gene expression profiles and analysis tools to explore features across species, brain regions, developmental stages, and pathological conditions. Thus, we developed scBrainScope, a detailed and interactive transcriptomic atlas of the brain. Our platform brings together single cell sequencing data from 135 species, covering 433 brain regions, 198 developmental stages, and 100 neurological diseases. In addition, we compiled 737 bulk RNA sequencing datasets from 275 species, along with 1154 spatial datasets of brain, spinal cord, and embryonic tissues. scBrainScope comprises six atlas modules (AtlasScope, RegionScope, TissueScope, SpaceScope, PathoScope, and AgeScope) and three analytical modules (sPandora, ePandora, and cPandora). Together, these tools enable researchers to investigate cell identity, gene programs, and spatial organization at multiple scales and dimensions. scBrainScope is freely available at http://8.142.154.29/scBrainScope or http://www.brainscopes.org, offering an interactive, data-rich resource for neuroscience, evolutionary biology, and translational medicine.
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A single-nucleus transcriptomic atlas of the adult Aedes aegypti mosquito.
The female Aedes aegypti mosquito's remarkable ability to hunt humans and transmit pathogens relies on her unique biology. Here, we present the Aedes aegypti Mosquito Cell Atlas, a comprehensive single-nucleus RNA sequencing dataset of more than 367,000 nuclei from 19 dissected tissues of adult female and male Aedes aegypti, providing cellular-level resolution of mosquito biology. We identify novel cell types and expand our understanding of sensory neuron organization of chemoreceptors to all sensory tissues. Our analysis uncovers male-specific cells and sexually dimorphic gene expression in the antenna and brain. In female mosquitoes, we find that glial cells in the brain, rather than neurons, undergo the most extensive transcriptional changes following blood feeding. Our findings provide insights into the cellular basis of mosquito behavior and sexual dimorphism. The Aedes aegypti Mosquito Cell Atlas resource enables systematic investigation of cell type-specific expression across all mosquito tissues.
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Integrated single-cell transcriptomics and epigenomics reveals strong germinal center-associated etiology of autoimmune risk loci.
The germinal center (GC) response is critical for both effective adaptive immunity and establishing peripheral tolerance by limiting autoreactive B cells. Dysfunction in these processes can lead to defective immune responses to infection or contribute to autoimmune disease. To understand the gene regulatory principles underlying the GC response, we generated a single-cell transcriptomic and epigenomic atlas of the human tonsil, a widely studied and representative lymphoid tissue. We characterize diverse immune cell subsets and build a trajectory of dynamic gene expression and transcription factor activity during B cell activation, GC formation, and plasma cell differentiation. We subsequently leverage cell type–specific transcriptomic and epigenomic maps to interpret potential regulatory impact of genetic variants implicated in autoimmunity, revealing that many exhibit their greatest regulatory potential in GC-associated cellular populations. These included gene loci linked with known roles in GC biology (IL21, IL21R, IL4R, and BCL6) and transcription factors regulating B cell differentiation (POU2AF1 and HHEX). Together, these analyses provide a powerful new cell type–resolved resource for the interpretation of cellular and genetic causes underpinning autoimmune disease.
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BCL9 regulates CD226 and CD96 checkpoints in CD8+ T cells to improve PD-1 response in cancer.
To date, the overall response rate of PD-1 blockade remains unsatisfactory, partially due to limited understanding of tumor immune microenvironment (TIME). B-cell lymphoma 9 (BCL9), a key transcription co-activator of the Wnt pathway, is highly expressed in cancers. By genetic depletion and pharmacological inhibition of BCL9 in tumors, we found that BCL9 suppression reduced tumor growth, promoted CD8+ T cell tumor infiltration, and enhanced response to anti-PD-1 treatment in mouse colon cancer models. To determine the underlying mechanism of BCL9's role in TIME regulation, single-cell RNA-seq was applied to reveal cellular landscape and transcription differences in the tumor immune microenvironment upon BCL9 inhibition. CD155-CD226 and CD155-CD96 checkpoints play key roles in cancer cell/CD8+ T cell interaction. BCL9 suppression induces phosphorylation of VAV1 in CD8+ T cells and increases GLI1 and PATCH expression to promote CD155 expression in cancer cells. In The Cancer Genome Atlas database analysis, we found that BCL9 expression is positively associated with CD155 and negatively associated with CD226 expression. BCL9 is also linked to adenomatous polyposis coli (APC) mutation involved in patient survival following anti-PD-1 treatment. This study points to cellular diversity within the tumor immune microenvironment affected by BCL9 inhibition and provides new insights into the role of BCL9 in regulating CD226 and CD96 checkpoints.
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Identification of fatty acids synthesis and metabolism-related gene signature and prediction of prognostic model in hepatocellular carcinoma.
BACKGROUND: Fatty acids synthesis and metabolism (FASM)-driven lipid mobilization is essential for energy production during nutrient shortages. However, the molecular characteristics, physiological function and clinical prognosis value of FASM-associated gene signatures in hepatocellular carcinoma (HCC) remain elusive. METHODS: The Gene Expression Omnibus database (GEO), the Cancer Genome Atlas (TCGA), and International Cancer Genome Consortium (ICGC) database were utilized to acquire transcriptome data and clinical information of HCC patients. The ConsensusClusterPlus was employed for unsupervised clustering. Subsequently, immune cell infiltration, stemness index and therapeutic response among distinct clusters were decoded. The tumor immune dysfunction and exclusion (TIDE) algorithm was utilized to anticipate the response of patients towards immunotherapy, and the genomics of drug sensitivity in cancer (GDSC) tool was employed to predict their response to antineoplastic medications. Least absolute shrinkage and selection operator (LASSO) regression analysis and protein-protein interaction (PPI) network were employed to construct prognostic model and identity hub gene. Single cell RNA sequencing (scRNA-seq) and CellChat were used to analyze cellular interactions. The hub gene of FASM effect on promoting tumor progression was confirmed through a series of functional experiments. RESULTS: Twenty-six FASM-related genes showed differential expression in HCC. Based on these FASM-related differential genes, two molecular subtypes were established, including Cluster1 and Cluster2 subtype. Compared with cluster2, Cluster1 subtype exhibited a worse prognosis, higher risk, higher immunosuppressive cells infiltrations, higher immune escape, higher cancer stemness and enhanced treatment-resistant. PPI network identified Acetyl-CoA carboxylase1 (ACACA) as central gene of FASM and predicted a poor prognosis. A strong interaction between cancer stem cells (CSCs) with high expression of ACACA and macrophages through CD74 molecule (CD74) and integrin subunit beta 1 (ITGB1) signaling was identified. Finally, increased ACACA expression was observed in HCC cells and patients, whereas depleted ACACA inhibited the stemness straits and drug resistance of HCC cells. CONCLUSIONS: This study provides a resource for understanding FASM heterogeneity in HCC. Evaluating the FASM patterns can help predict the prognosis and provide new insights into treatment response in HCC patients.
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Single-Cell RNA-Seq Reveals Lineage and X Chromosome Dynamics in Human Preimplantation Embryos.
Mouse studies have been instrumental in forming our current understanding of early cell-lineage decisions; however, similar insights into the early human development are severely limited. Here, we present a comprehensive transcriptional map of human embryo development, including the sequenced transcriptomes of 1,529 individual cells from 88 human preimplantation embryos. These data show that cells undergo an intermediate state of co-expression of lineage-specific genes, followed by a concurrent establishment of the trophectoderm, epiblast, and primitive endoderm lineages, which coincide with blastocyst formation. Female cells of all three lineages achieve dosage compensation of X chromosome RNA levels prior to implantation. However, in contrast to the mouse, XIST is transcribed from both alleles throughout the progression of this expression dampening, and X chromosome genes maintain biallelic expression while dosage compensation proceeds. We envision broad utility of this transcriptional atlas in future studies on human development as well as in stem cell research.
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A Novel 14-Gene Panel Associated With Efferocytosis for Predicting Pancreatic Cancer Prognosis Through Bulk and Single-Cell Databases.
BACKGROUND: Efferocytosis (ER) plays a crucial role in the programmed clearance of dead cells, a process that is mediated by phagocytic immune cells. However, further exploration is needed to determine the full extent of its impact on the progression of pancreatic ductal adenocarcinoma (PDAC), particularly through interactions among tumor cells, stromal cells, and immune cells within the tumor microenvironment (TME). METHODOLOGY AND RESULTS: In this study, we comprehensively analyzed the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, as well as additional databases from multiple bioinformatics websites, utilizing 167 ER features derived from the integration of single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic data. A set of 14 ER-associated prognostic signatures, referred to as the "14-gene panel" genes, was identified based on overall survival (OS)/disease-free survival (DFS) data, Pearson correlation coefficients, and multivariate Cox regression analyses. The model pathways enriched by the four-gene combination represented by "LEAF" and the 14-gene combination represented by the "14-gene panel" presented a high degree of similarity, including among the adhesion, mitotic, G2/M checkpoint, and epithelial‒mesenchymal transition (EMT) signaling pathways. Least absolute shrinkage and selection operator (LASSO) regression was subsequently employed to construct an ER risk scoring system using deep learning, based on the following formula: LGALS3, EMP1, ASPH, and FNDC3B, collectively termed the "LEAF" panel. Additionally, random survival forest (RSF) algorithms facilitated the identification of a key panel of genes, designated "LEAP" genes, including LGALS3, EREG, ASPH, and PLS3; three of which genes (ASPH, LGALS3, and EREG) were identified as key factors influencing the behaviors of PDAC tumors, tumor-associated stroma, and macrophages. Finally, we utilized experimental methods, including Boyden chamber analyses, immunohistochemical staining, and cell cycle analyses, to demonstrate that interference with ASPH suppresses the malignant properties of tumors, including proliferation and migration. Multiplex immunofluorescence staining was employed to identify EREG as highly relevant to the M2 macrophage subpopulation. CONCLUSION: Our findings underscore the importance of considering a novel prognostic signature comprising 14 ER genes in the context of the TME when investigating the biology of PDAC. Future studies may explore how modulating these interactions could lead to novel therapeutic opportunities.
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SEC61G promotes colorectal cancer progression by regulating cytosolic Ca2+ concentration.
BACKGROUND: Intracellular calcium (Ca2+) signaling regulates key cancer processes. Research findings suggest that the SEC61 complex, involved in protein translocation, contributes to calcium leakage from the endoplasmic reticulum. However, the mechanism by which SEC61 Translocon Subunit Gamma (SEC61G), a component of this complex, influences colorectal cancer (CRC) progression remains unclear. METHODS: Bioinformatics analysis was performed using The Cancer Genome Atlas data sets to identify candidate genes on chromosome 7p, examine their association with DNA copy number amplification. In addition, SEC61G expression in CRC cells and tissues was validated using reverse-transcription quantitative polymerase chain reaction and immunohistochemistry. Moreover, in vitro and in vivo experiments were performed to investigate the effects of SEC61G overexpression and knockdown on CRC cell proliferation. Furthermore, publicly available single-cell RNA sequencing (scRNA-seq) and spatial transcriptome sequencing (ST-seq) data were used to validate the role of SEC61G in CRC. RESULTS: SEC61G was significantly upregulated in CRC tissues and was correlated with poor prognosis in patients with CRC. SEC61G overexpression enhanced cell proliferation and activated the EGFR pathway, promoting cell cycle progression from the G1 to S phase. In addition, SEC61G overexpression increased cytosolic Ca2+ levels, which activated EGFR signaling via calmodulin. Moreover, analyses of scRNA-seq and ST-seq data confirmed that SEC61G expression was higher in tumor epithelial cells and that it was co-expressed with EGFR pathway-related genes. CONCLUSIONS: SEC61G promotes CRC progression by regulating cytosolic Ca2+ concentration, EGFR activation, and cell cycle progression, highlighting its potential as a prognostic biomarker and therapeutic target in CRC.