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Single-Nucleus Transcriptomic Atlas Reveals Disease-Associated Cellular States in Human Glomerular Diseases.
INTRODUCTION: Glomerular diseases are a major cause of chronic kidney disease and kidney failure worldwide, yet the cellular mechanisms underlying their heterogeneity remain incompletely understood. Single-nucleus RNA sequencing (snRNA-seq) enables high-resolution characterization of transcriptional alterations across diverse kidney cell populations. METHODS: We performed snRNA-seq on snap-frozen kidney biopsy tissues obtained from treatment-naïve patients with minimal change disease (MCD), membranous nephropathy (MN), IgA nephropathy (IgAN), and diabetic kidney disease (DKD), together with control kidney samples. In total, 333,938 nuclei from 37 individuals were analyzed to define disease-associated transcriptional programs across kidney cell types. RESULTS: Upregulated transcripts formed disease-specific programs that were shared across multiple cell types, whereas downregulated transcripts were largely cell type-specific and conserved across diseases. We identified disease-associated cellular states, including a glomerular epithelial population exhibiting a hybrid transcriptional profile shared between podocytes and parietal epithelial cells (PECs); a podocyte subpopulation with endocytosis-related gene expression, correlated with proteinuria severity and treatment response; and expansion of periostin (POSTN)-expressing myofibroblasts, inversely associated with estimated glomerular filtration rate (eGFR) and spatially colocalized with podocyte injury. Each cellular state was independently recovered in external single-cell cohorts. CONCLUSION: Single-nucleus transcriptomic profiling of human kidney biopsy tissues reveals disease-specific and shared cellular programs across major glomerular diseases. This resource provides insight into the cellular mechanisms underlying glomerular injury and identifies disease-associated cell states that may contribute to disease progression.
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Migrasome-related long non-coding RNAs orchestrate immune microenvironment and serve as a novel prognostic model in clear cell renal cell carcinoma.
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) represents the most common histological subtype of kidney cancer and constitutes a major global health burden. Despite increasing recognition of the roles of migrasome-related long non-coding RNAs (MRLs) in tumor biology, their prognostic relevance in ccRCC remains largely undefined. Therefore, this study aimed to systematically identify MRLs associated with ccRCC prognosis and construct a robust prognostic model to improve risk stratification and guide potential therapeutic strategies. METHODS: To identify MRLs, we initially performed a correlation analysis integrating transcriptomic profiles with clinical parameters of ccRCC patients from The Cancer Genome Atlas (TCGA). Leveraging the expression matrix of MRLs, we subsequently employed the least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic signature. A comprehensive assessment was carried out to determine the model's predictive robustness. At single-cell resolution, we delineated the cellular composition of ccRCC, capturing transcriptional heterogeneity across distinct cell populations. Ultimately, long non-coding RNAs (lncRNAs) derived from the prognostic model were experimentally validated in clinical specimens through reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and the landscape of migrasome-related genes (MRGs) was further defined using single-cell RNA sequencing (scRNA-seq) data. RESULTS: A prognostic signature comprising five MRLs-EMX2OS, AC106897.1, AC087645.2, AC121338.2, and C5orf66-was established to stratify patient risk. The derived risk score was subsequently validated as an independent predictor of overall survival (OS) in ccRCC patients. A nomogram integrating this score exhibited strong predictive capability. Immune landscape analysis uncovered marked differences in functional immune features between high- and low-risk cohorts defined by the lncRNA-based model. Notably, the high-risk group displayed enrichment of immune-related processes, whereas the low-risk group demonstrated enhanced predicted responsiveness to a spectrum of therapeutic compounds. scRNA-seq identified 17 distinct cellular subpopulations and highlighted the involvement of tumor cell-intrinsic vascular endothelial growth factor (VEGF) signaling in modulating migrasome-associated molecular programs. CONCLUSIONS: This study emphasizes the prognostic utility of a signature comprising five MRLs for ccRCC, offering valuable insights for clinical risk stratification and therapeutic decision-making. Additionally, modulation of tumor cell migration and migrasome function via the VEGF signaling pathway offers a mechanistic basis for targeted intervention.
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KMT2D deficiency leads to cellular developmental disorders and enhancer dysregulation in neural-crest-containing brain organoids.
KMT2D, a H3K4me1 methyltransferase primarily regulating enhancers, is a leading cause of KABUKI syndrome. This multisystem disorder leads to craniofacial and cognitive abnormalities, possibly through neural crest and neuronal lineages. However, the impacted cell-of-origin and molecular mechanism of KMT2D during the development of KABUKI disease remains unknown. Here we have optimized a brain organoid model to investigate neural crest and neuronal differentiation. To pinpoint KMT2D's enhancer target, we developed a genome-wide cis-regulatory element explorer (GREE) based on single-cell multiomic integration. Single cell RNA-seq revealed that KMT2D-knockout (KO) and patient-derived organoids exhibited neural crest deformities and GABAergic overproduction. Mechanistically, GREE identified that KMT2D targets a roof-plate-like niche cell and activates the niche cell-specific WNT3A enhancer, providing the microenvironment for neural crest and neuronal development. Interestingly, KMT2D-mutated mice displayed decreased WNT3A expression in the diencephalon roof plate, indicating impaired niche cell function. Deleting the WNT3A enhancer in the organoids presented phenotypic similarities to KMT2D-depletion, emphasizing the WNT3A enhancer as the predominant target of KMT2D. Conversely, reactivating WNT signaling in KMT2D-KO rescued the lineage defects by restoring the microenvironment. Overall, our discovery of KMT2D's primary target provides insights for reconciling complex phenotypes of KABUKI syndrome and establishes a new paradigm for dissecting the mechanisms of genetic disorders from genotype to phenotype.
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The cell type composition of the adult mouse brain revealed by single cell and spatial genomics.
The function of the mammalian brain relies upon the specification and spatial positioning of diversely specialized cell types. Yet, the molecular identities of the cell types, and their positions within individual anatomical structures, remain incompletely known. To construct a comprehensive atlas of cell types in each brain structure, we paired high-throughput single-nucleus RNA-seq with Slide-seq-a recently developed spatial transcriptomics method with near-cellular resolution-across the entire mouse brain. Integration of these datasets revealed the cell type composition of each neuroanatomical structure. Cell type diversity was found to be remarkably high in the midbrain, hindbrain, and hypothalamus, with most clusters requiring a combination of at least three discrete gene expression markers to uniquely define them. Using these data, we developed a framework for genetically accessing each cell type, comprehensively characterized neuropeptide and neurotransmitter signaling, elucidated region-specific specializations in activity-regulated gene expression, and ascertained the heritability enrichment of neurological and psychiatric phenotypes. These data, available as an online resource (BrainCellData.org) should find diverse applications across neuroscience, including the construction of new genetic tools, and the prioritization of specific cell types and circuits in the study of brain diseases.
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Overview of Gene Expression Dynamics during Human Oogenesis/Folliculogenesis.
The oocyte transcriptome follows a tightly controlled dynamic that leads the oocyte to grow and mature. This succession of distinct transcriptional states determines embryonic development prior to embryonic genome activation. However, these oocyte maternal mRNA regulatory events have yet to be decoded in humans. We reanalyzed human single-oocyte RNA-seq datasets previously published in the literature to decrypt the transcriptomic reshuffles ensuring that the oocyte is fully competent. We applied trajectory analysis (pseudotime) and a meta-analysis and uncovered the fundamental transcriptomic requirements of the oocyte at any moment of oogenesis until reaching the metaphase II stage (MII). We identified a bunch of genes showing significant variation in expression from primordial-to-antral follicle oocyte development and characterized their temporal regulation and their biological relevance. We also revealed the selective regulation of specific transcripts during the germinal vesicle-to-MII transition. Transcripts associated with energy production and mitochondrial functions were extensively downregulated, while those associated with cytoplasmic translation, histone modification, meiotic processes, and RNA processes were conserved. From the genes identified in this study, some appeared as sensitive to environmental factors such as maternal age, polycystic ovary syndrome, cryoconservation, and in vitro maturation. In the future, the atlas of transcriptomic changes described in this study will enable more precise identification of the transcripts responsible for follicular growth and oocyte maturation failures.
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HISSTA: a human in situ single-cell transcriptome atlas.
MOTIVATION: Spatial transcriptomics holds great promise for revolutionizing biology and medicine by providing gene expression profiles with spatial information. Until recently, spatial resolution has been limited, but advances in high-throughput in situ imaging technologies now offer new opportunities by covering thousands of genes at a single-cell or even subcellular resolution, necessitating databases dedicated to comprehensive coverage and analysis with user-friendly intefaces. RESULTS: We introduce the HISSTA database, which facilitates the archival and analysis of in situ transcriptome data at single-cell resolution from various human tissues. We have collected and annotated spatial transcriptome data generated by MERFISH, CosMx SMI, and Xenium techniques, encompassing 112 samples and 28 million cells across 16 tissue types from 63 studies. To decipher spatial contexts, we have implemented advanced tools for cell type annotation, spatial colocalization, spatial cellular communication, and niche analyses. Notably, all datasets and annotations are interactively accessible through Vitessce, allowing users to focus on regions of interest and examine gene expression in detail. HISSTA is a unique database designed to manage the rapidly growing dataset of in situ transcriptomes at single-cell resolution. Given its comprehensive data content and advanced analysis tools with interactive visualizations, HISSTA is poised to significantly impact cancer diagnosis, precision medicine, and digital pathology. AVAILABILITY AND IMPLEMENTATION: HISSTA is freely accessible at https://kbds.re.kr/hissta/. The source code is available at https://doi.org/10.5281/zenodo.14904523.
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Mapping the Tissue Architecture and Endothelial-PEC Network in HAML Using Single-Cell and Spatial Transcriptomics.
Hepatic angiomyolipoma (HAML) is a rare variant of perivascular epithelioid cell neoplasms (PEComas). Unlike its more common renal angiomyolipoma (RAML), the unique spatial microenvironment of HAML and its specific progression mechanisms remain poorly characterized. Here, we integrated single-nucleus RNA-sequencing and spatial transcriptomics from three sporadic HAML cases. We mapped functionally heterogeneous PEComas subpopulations and their localized tissue niches. Transcriptomic alignment and spatial colocalization demonstrated a high similarity between endothelial cells and a subset of PEComas, supporting a potential transition trajectory. Furthermore, spatial intercellular communication analysis identified an endothelial-derived PDGFD-PDGFRB axis. We propose that this paracrine signaling engages downstream Ras cascades to sustain localized autophagic flux in adjacent PEComas, potentially acting as a compensatory survival mechanism parallel to intrinsic TSC-mTOR defects. While definitive in vivo functional fate-mapping and perturbation studies are requisite, this multi-omics atlas provides a novel spatial framework for HAML pathogenesis and highlights the endothelial-PEComa signaling network as a potential therapeutic vulnerability.
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Gene expression variations and allele-specific expression of two rice and their hybrid in caryopses at single-nucleus resolution.
Seeds are an indispensable part of the flowering plant life cycle and a critical determinant of agricultural production. Distinct differences in the anatomy and morphology of seeds separate monocots and dicots. Although some progress has been made with respect to understanding seed development in Arabidopsis, the transcriptomic features of monocotyledon seeds at the cellular level are much less understood. Since most important cereal crops, such as rice, maize, and wheat, are monocots, it is essential to study transcriptional differentiation and heterogeneity during seed development at a finer scale. Here, we present single-nucleus RNA sequencing (snRNA-seq) results of over three thousand nuclei from caryopses of the rice cultivars Nipponbare and 9311 and their intersubspecies F1 hybrid. A transcriptomics atlas that covers most of the cell types present during the early developmental stage of rice caryopses was successfully constructed. Additionally, novel specific marker genes were identified for each nuclear cluster in the rice caryopsis. Moreover, with a focus on rice endosperm, the differentiation trajectory of endosperm subclusters was reconstructed to reveal the developmental process. Allele-specific expression (ASE) profiling in endosperm revealed 345 genes with ASE (ASEGs). Further pairwise comparisons of the differentially expressed genes (DEGs) in each endosperm cluster among the three rice samples demonstrated transcriptional divergence. Our research reveals differentiation in rice caryopsis from the single-nucleus perspective and provides valuable resources to facilitate clarification of the molecular mechanism underlying caryopsis development in rice and other monocots.
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Identification and validation of a pyroptosis-related prognostic model for colorectal cancer based on bulk and single-cell RNA sequencing data.
BACKGROUND: Pyroptosis impacts the development of malignant tumors, yet its role in colorectal cancer (CRC) prognosis remains uncertain. AIM: To assess the prognostic significance of pyroptosis-related genes and their association with CRC immune infiltration. METHODS: Gene expression data were obtained from The Cancer Genome Atlas (TCGA) and single-cell RNA sequencing dataset GSE178341 from the Gene Expression Omnibus (GEO). Pyroptosis-related gene expression in cell clusters was analyzed, and enrichment analysis was conducted. A pyroptosis-related risk model was developed using the LASSO regression algorithm, with prediction accuracy assessed through K-M and receiver operating characteristic analyses. A nomogram predicting survival was created, and the correlation between the risk model and immune infiltration was analyzed using CIBERSORTx calculations. Finally, the differential expression of the 8 prognostic genes between CRC and normal samples was verified by analyzing TCGA-COADREAD data from the UCSC database. RESULTS: An effective pyroptosis-related risk model was constructed using 8 genes-CHMP2B, SDHB, BST2, UBE2D2, GJA1, AIM2, PDCD6IP, and SEZ6L2 (P < 0.05). Seven of these genes exhibited differential expression between CRC and normal samples based on TCGA database analysis (P < 0.05). Patients with higher risk scores demonstrated increased death risk and reduced overall survival (P < 0.05). Significant differences in immune infiltration were observed between low- and high-risk groups, correlating with pyroptosis-related gene expression. CONCLUSION: We developed a pyroptosis-related prognostic model for CRC, affirming its correlation with immune infiltration. This model may prove useful for CRC prognostic evaluation.
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Integration mapping of cardiac fibroblast single-cell transcriptomes elucidates cellular principles of fibrosis in diverse pathologies.
Single-cell technology has allowed researchers to probe tissue complexity and dynamics at unprecedented depth in health and disease. However, the generation of high-dimensionality single-cell atlases and virtual three-dimensional tissues requires integrated reference maps that harmonize disparate experimental designs, analytical pipelines, and taxonomies. Here, we present a comprehensive single-cell transcriptome integration map of cardiac fibrosis, which underpins pathophysiology in most cardiovascular diseases. Our findings reveal similarity between cardiac fibroblast (CF) identities and dynamics in ischemic versus pressure overload models of cardiomyopathy. We also describe timelines for commitment of activated CFs to proliferation and myofibrogenesis, profibrotic and antifibrotic polarization of myofibroblasts and matrifibrocytes, and CF conservation across mouse and human healthy and diseased hearts. These insights have the potential to inform knowledge-based therapies.