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A molecular cell atlas of mouse lemur, an emerging model primate.
Mouse lemurs are the smallest and fastest reproducing primates, as well as one of the most abundant, and they are emerging as a model organism for primate biology, behaviour, health and conservation. Although much has been learnt about their ecology and phylogeny in Madagascar and their physiology, little is known about their cellular and molecular biology. Here we used droplet-based and plate-based single-cell RNA sequencing to create Tabula Microcebus, a transcriptomic atlas of 226,000 cells from 27 mouse lemur organs opportunistically obtained from four donors clinically and histologically characterized. Using computational cell clustering, integration and expert cell annotation, we define and biologically organize more than 750 lemur molecular cell types and their full gene expression profiles. This includes cognates of most classical human cell types, including stem and progenitor cells, and differentiating cells along the developmental trajectories of spermatogenesis, haematopoiesis and other adult tissues. We also describe dozens of previously unidentified or sparsely characterized cell types. We globally compare expression profiles to define the molecular relationships of cell types across the body, and explore primate cell and gene expression evolution by comparing lemur transcriptomes to those of human, mouse and macaque. This reveals cell-type-specific patterns of primate specialization and many cell types and genes for which the mouse lemur provides a better human model than mouse1. The atlas provides a cellular and molecular foundation for studying this model primate and establishes a general approach for characterizing other emerging model organisms.
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A genome and single-nucleus cerebral cortex transcriptome atlas of the short-finned pilot whale Globicephala macrorhynchus.
Cetaceans (dolphins, whales, and porpoises) have large and anatomically sophisticated brains. To expand our understanding of the cellular makeup of cetacean brains and the similarities and divergence between the brains of cetaceans and terrestrial mammals, we report a short-finned pilot whale (Globicephala macrorhynchus) single-nucleus transcriptome atlas. To achieve this goal, we assembled a chromosome-scale reference genome spanning 2.25 Gb on 22 chromosomes and profiled the gene expression of five major anatomical cortical regions of the short-finned pilot whale by single-nucleus RNA-sequencing (snRNA-seq). We identified six major cell lineages in the cerebral cortex (excitatory neurons, inhibitory neurons, oligodendrocytes, oligodendrocyte precursor cells, astrocytes, and endothelial cells), eight molecularly distinct subclusters of excitatory neurons, and four subclusters of inhibitory neurons. Finally, a comparison of snRNA-seq data from the short-finned pilot whale, human, and rhesus macaque revealed a broadly conserved cellular makeup of brain cell types. Our study provides genomic resources and molecular insights into cetacean brain evolution.
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Cell landscape atlas for patients with chronic thromboembolic pulmonary hypertension after pulmonary endarterectomy constructed using single-cell RNA sequencing.
This study aimed to construct an atlas of the cell landscape and comprehensively characterize the cellular repertoire of the pulmonary endarterectomized tissues of patients with chronic thromboembolic pulmonary hypertension (CTEPH). Five pulmonary endarterectomized tissues were collected. 10× Genomics single-cell RNA sequencing was performed, followed by the identification of cluster marker genes and cell types. Gene Ontology (GO) enrichment analysis was conducted. Seventeen cell clusters were characterized, corresponding to 10,518 marker genes, and then classified into eight cell types, including fibroblast/smooth muscle cell, endothelial cell, T cell/NK cell, macrophage, mast cell, cysteine rich secretory protein LCCL domain containing 2 (CRISPLD2)+ cell, cancer stem cell, and undefined. The specific marker genes of fibroblast/smooth muscle cell, endothelial cell, T cell/NK cell, macrophage, mast cell, and cancer stem cell were significantly enriched for multiple functions associated with muscle cell migration, endothelial cell migration, T cell activation, neutrophil activation, erythrocyte homeostasis, and tissue remodeling, respectively. No functions were significantly enriched for the marker gene of CRISPLD2+ cell. Our study, for the first time, provides an atlas of the cell landscape of the pulmonary endarterectomized tissues of CTEPH patients at single-cell resolution, which may serve as a valuable resource for further elucidation of disease pathophysiology.
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Spatial gene expression at single-cell resolution from histology using deep learning with GHIST.
The increased use of spatially resolved transcriptomics provides new biological insights into disease mechanisms. However, the high cost and complexity of these methods are barriers to broader application. Consequently, methods have been created to predict spot-based gene expression from routinely collected histology images. Recent benchmarking showed that current methodologies have limited accuracy and spatial resolution, constraining translational capacity. Here, we introduce GHIST, a deep learning-based framework that predicts spatial gene expression at single-cell resolution by leveraging subcellular spatial transcriptomics and synergistic relationships between multiple layers of biological information. We validated GHIST using public datasets and The Cancer Genome Atlas data, demonstrating its flexibility across different spatial resolutions and superior performance. Our results underscore the utility of in silico generation of single-cell spatial gene expression measurements and the capacity to enrich existing datasets with a spatially resolved omics modality, paving the way for scalable multi-omics analysis and biomarker identification.
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Molecular identity of human limbal heterogeneity involved in corneal homeostasis and privilege.
PURPOSE: The corneal limbus maintains the homeostasis, immune and angiogenic privilege of cornea. This study aimed to depict the landscape of human limbal tissues by single-cell RNA sequencing (scRNA-seq). METHODS: Single cells of human limbus collected from donor corneas were subjected to 10x scRNA-seq, followed by clustering cell types through the t-distributed stochastic neighbor embedding (t-SNE) and unbiased computational informatic analysis. Immunofluorescent staining was performed using human corneas to validate the analysis results. RESULTS: 47,627 cells acquired from six human limbal tissues were collected and subjected to scRNA-seq. 14 distinct clusters were identified and 8 cell types were annotated with representative markers. In-depth dissection revealed three limbal epithelial cell subtypes and refined the X-Y-Z hypothesis of corneal epithelial maintenance. We further unveiled two cell states with higher stemness (TP63+ and CCL20+ cells), and two other differentiated cell states (GPHA2+ and KRT6B + cells) in homeostatic limbal stem/progenitor cells (LSPCs) that differ in transcriptional profiles. Cell-cell communication analysis revealed the central role of LSPCs and their bidirectional regulation with various niche cells. Moreover, comparative analysis between limbus and skin deciphered the pivotal contribution of limbal immune cells, vascular and lymphatic endothelial cells to corneal immune and angiogenic privilege. CONCLUSIONS: The human limbus atlas provided valuable resources and foundations for understanding corneal biology, disease and potential interventions.
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Single-cell RNA Sequencing Discovered Subtypes Associated with Angiogenesis and Propranolol Treatment in Infantile Hemangioma.
Infantile hemangioma (IH), a benign vascular tumor of infancy, is characterized by rapid postnatal growth and subsequent spontaneous resolution. Although propranolol, initially developed for cardiovascular disorders, is the primary treatment for IH, its precise molecular mechanisms remain incompletely elucidated. This study employed single-cell RNA sequencing (scRNA-seq) to generate a comprehensive cellular atlas comprising eight tissues from three IH infants, sampled both before and after propranolol treatment, alongside two normal infant skin samples, yielding 103,082 cells. Concurrently, tumor-normal tissue paired whole-genome sequencing (WGS) was conducted on samples from 13 IH infants. To provide a comprehensive genomic landscape, we also characterized germline and somatic variations. scRNA-seq analysis identified two distinct propranolol-targeted IH-specific cell subtypes: APLN + hemangioma endothelial cells (HemECs), associated with angiogenesis, and CENPF + hemangioma pericytes (Hem-Pericytes), associated with IH proliferation. WGS revealed that the majority of mutations resided in intronic regions, somatic copy number alterations changed weakly, and that most somatic mutations were clonal. Functional validation demonstrated that propranolol treatment suppressed APLN transcription. Overall, this integrative study delineated two distinct IH-specific cell subtypes, with detailed characterization of germline/somatic mutations, copy number variations, and clonal evolution in IH.
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Comprehensive Transcriptome Annotation of Thousands of HIV-1 Genomes.
Alternative splicing in HIV-1 has been a central focus of decades of research, uncovering key mechanisms of viral gene regulation, immune evasion, and therapeutic response - yet, no reference resource has existed to support transcriptome-wide analysis, limiting adoption of modern computational methods. We present HIV Atlas (https://ccb.jhu.edu/HIV_Atlas), the first reference-quality annotation of HIV-1 and SIV transcriptional diversity. We manually curated transcriptomes for HIV-1HXB2 and SIVmac239 and developed Vira, an automated annotation-transfer method specifically designed to address unique challenges of viral genome biology, to generate high-quality annotations for 2,077 complete HIV-1 genomes. Using the resources presented in our work, we evaluated conservation of splice sites, revealing near-perfect preservation of major donors and acceptors. Furthermore, using several public datasets, we demonstrate how HIV Atlas enhances methodology, improves the quality and novelty of results, and opens novel avenues for research, supporting more accurate and comprehensive analyses of bulk, single-cell, and spatial RNA-seq in HIV-1 studies.
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An atlas of cartilage in the distal radius generated via single-cell RNA sequencing reveals cell‒cell interaction patterns similar to those of the ankle.
Among the skeletal structures of the wrist joint, an articular disc exists between the cartilage of the distal ulna and carpus, whereas the cartilage of the distal radius almost directly contacts the carpus. In this study, articular cartilage tissues from the distal radius were obtained from donors, and scRNA-seq was conducted. This study provides deep insight into the articular cartilage of the distal radius. Five cartilage tissue samples from the distal radius were obtained from 5 donors, and scRNA-seq was conducted. To verify the distribution of each cell type, the samples were subjected to immunohistochemistry. Ultimately, 51,826 cells were analysed, and 11 cell types were annotated, including FC-A, FC-B, MirCs, SpCs, preHTCs, HTC-A, HTC-B, HomCs, ProCs, ImmCs, and RegCs. Cell‒cell interactions and specific TFs for chondrocyte subsets were identified, which indicate that ATF1, IRF3, KDM5B, and SMARCC2 are specific for SpCs, and ETS2, MXI1, CEBPB, and EGR1 were obviously expressed across cell types and samples. The FN1, COMP and CD99 pathways and cell‒cell interaction patterns of the distal radius may be similar to those of the ankle.
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A spatiotemporal lifecycle atlas decodes spatial coordination in rice.
How gene expression programs are coordinated across space and time to build a complete plant remains poorly understood. Here, we combine high-resolution spatial transcriptomics, single-nucleus RNA sequencing, and a gap-free reference genome to build a 3D spatiotemporal atlas of rice, spanning 10 organs and 61 stages from seed to seed. Our datasets profile 851,725 nuclei and 347,640 spatial bins, defining 119 cell types and 133 subtypes across the rice lifecycle. Through multimodal integration, we reconstruct an inferred developmental trajectory graph that links cell states from the proembryo to mature organs and identifies trajectory-associated regulators. We further implicate the pleiotropic regulator OsARF1 in distinct spatial gene programs across developmental contexts. We also uncover widespread axis-associated transcriptional asymmetry, including dorsoventral endosperm programs that partition starch and protein accumulation. Collectively, this high-resolution atlas provides a spatiotemporal framework for understanding rice development and guiding future crop improvement.
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Modeling the Genetic Regulation of Cancer Metabolism: Interplay between Glycolysis and Oxidative Phosphorylation.
Abnormal metabolism is a hallmark of cancer, yet its regulation remains poorly understood. Cancer cells were considered to utilize primarily glycolysis for ATP production, referred to as the Warburg effect. However, recent evidence suggests that oxidative phosphorylation (OXPHOS) plays a crucial role during cancer progression. Here we utilized a systems biology approach to decipher the regulatory principle of glycolysis and OXPHOS. Integrating information from literature, we constructed a regulatory network of genes and metabolites, from which we extracted a core circuit containing HIF-1, AMPK, and ROS. Our circuit analysis showed that while normal cells have an oxidative state and a glycolytic state, cancer cells can access a hybrid state with both metabolic modes coexisting. This was due to higher ROS production and/or oncogene activation, such as RAS, MYC, and c-SRC. Guided by the model, we developed two signatures consisting of AMPK and HIF-1 downstream genes, respectively, to quantify the activity of glycolysis and OXPHOS. By applying the AMPK and HIF-1 signatures to The Cancer Genome Atlas patient transcriptomics data of multiple cancer types and single-cell RNA-seq data of lung adenocarcinoma, we confirmed an anticorrelation between AMPK and HIF-1 activities and the association of metabolic states with oncogenes. We propose that the hybrid phenotype contributes to metabolic plasticity, allowing cancer cells to adapt to various microenvironments. Using model simulations, our theoretical framework of metabolism can serve as a platform to decode cancer metabolic plasticity and design cancer therapies targeting metabolism. Cancer Res; 77(7); 1564-74. ©2017 AACR.