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Exploring the Abnormal Characteristics of the Ovaries During the Estrus Period of Kazakh Horses Based on Single-Cell Transcriptome Technology.
The ovary is among the earliest organs to undergo age-related degeneration, limiting the reproductive potential of elite horses and constraining the growth of the equine industry. Follicular development during estrus is a key determinant of fertility, yet the molecular mechanisms underlying its decline, particularly at the level of specific ovarian cell types, remain poorly understood in equids. Here, we constructed a single-cell transcriptomic atlas to investigate ovarian changes in Kazakh horses. Using single-cell RNA sequencing (scRNA-seq), we profiled 112,861 cells from follicle-containing and follicle-absent ovaries, identifying nine distinct ovarian cell types and their subtypes, each with distinct gene expression signatures. Functional enrichment analyses revealed cell type-specific engagement in biological pathways, including ECM-receptor interaction, PI3K-Akt signaling, and oxytocin signaling. Gene expression patterns indicated tightly regulated processes of ovarian activation and cell differentiation. Notably, stromal cells exhibited high expression of ROBO2, LOC111770199, and TMTC2, while smooth muscle cells (SMCs) were marked by elevated levels of CCL5, KLRD1, and NKG7. Moreover, cell-cell interaction analyses revealed robust signaling interactions among SMCs, endothelial cells, neurons, and proliferating (cycling) cells. Together, these findings provide a comprehensive single-cell transcriptomic map of normal and abnormal ovarian states during estrus in Kazakh horses, offering novel insights into the cellular mechanisms of follicular development and identifying potential diagnostic biomarkers and therapeutic targets for ovarian quiescence in equids.
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Population-scale immune multiome atlas reveals regulatory disease mechanisms.
Most disease-associated genetic variants lie in non-coding regions1,2, yet mechanistic insights are limited by the lack of an empirical framework for characterizing the molecular consequences of regulatory variation. Single-cell molecular quantitative trait locus (QTL) mapping3,4 connects variants to gene regulation but lacks the power and simultaneous measurements to trace mechanisms from chromatin to expression5. Here we show that population-scale simultaneous profiling of chromatin accessibility and gene expression across immune cells reveals regulatory architectures connecting variants to disease. From paired single-nucleus assay for transposase-accessible chromatin-sequencing (snATAC-seq) and single-nucleus RNA-sequencing (snRNA-seq) analysis of 10 million peripheral blood mononuclear cells in 1,108 Finnish individuals6, we identify 51,083 cis-expression QTLs for 20,829 genes, 338,100 cis-chromatin accessibility QTLs for 210,584 peaks, 119,094 putative causal variants and 593,765 peak-gene links. Variants completing chromatin-to-expression cascades show twice the disease colocalization of chromatin-only effects, with massively parallel reporter assays7 validating 10,428 fine-mapped molecular QTLs. At evolutionarily constrained genes, we identify multilayered regulatory buffering, in which chromatin accessibility changes occur with normal effect sizes, but transmission to expression is attenuated through weaker, more numerous enhancer-gene links. This reconciles why disease variants preferentially target constrained genes despite apparent expression QTL depletion8-11. Analysis using a massively parallel reporter assay7 confirms that this buffering acts downstream of the regulatory element, with constraint operating at the chromatin-to-expression interface rather than on intrinsic cis-regulatory activity. Our atlas provides testable hypotheses for over half of immune disease associations, illustrated by cascades at autoimmune loci (TICAM1 and RHOH) and Finnish-enriched variants (TNRC18 and IL21R).
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The Cellular and Molecular Landscape of Synchronous Pediatric Sialoblastoma and Hepatoblastoma.
Sialoblastoma (SBL) is an infrequent embryonal malignant tumor originating from the salivary gland, resembling primitive salivary gland anlage, whereas hepatoblastoma (HB) is the most common pediatric liver malignancy. The simultaneous occurrence of both tumors is extremely rare. Here we reported a case of a 6-month-old infant diagnosed with synchronous SBL and HB. The patient received neoadjuvant chemotherapy followed by surgical resection. Fresh tissues of both tumors were collected before and after chemotherapy, which were further profiled by whole exome sequencing (WES) and single-cell RNA sequencing (scRNA-seq). WES analysis revealed potential somatic driver mutation PIK3CA p.Glu454Lys for SBL and canonical mutation CTNNB1 p.Ser45Pro for HB. No shared somatic variants or common copy number alterations were found between SBL and HB primary tumor samples. Though scRNA-seq, single-cell atlases were constructed for both tumors. SBL may recapitulate a pre-acinar stage in the development of salivary gland, including basaloid, duct-like, myoepithelial-like, and cycling phenotypes. In the meantime, HB was composed of tumor cells resembling different stages of the liver, including hepatocyte-like, hepatic progenitor-like, and hepatoblast-like cells. After chemotherapy, both tumors were induced into a more mature phenotype. In terms of transcriptional signatures, SBL and HB showed enhanced expression of epithelial markers KRT8, KRT18, and essential embryo development genes SDC1, MDK, indicating the disruption of normal embryo epithelium development. Finally, heterozygous deleterious germline mutation BLM and FANCI were identified which could predispose the patient to higher cancer risk. It partially explained the reason for the co-occurrence of SBL and HB. Taken together, we provided valuable resources for deciphering cellular heterogeneity and adaptive change of tumor cells after chemotherapy for synchronous SBL and HB, providing insights into the mechanisms leading to synchronous pediatric tumors.
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Single-cell epigenomics in plants.
Single-cell technologies enable epigenomics characterization at single-cell resolution, offering novel insights into gene expression regulation and a wide range of biological processes, including cell fate determination, developmental differentiation, and environmental adaptation. In recent years, plant single-cell epigenomics has witnessed rapid progress, empowering the construction of cell type-specific chromatin accessibility atlases, the identification of candidate cis-regulatory elements (CREs), the inference of gene regulatory networks, and the elucidation of regulatory mechanisms underlying plant development, stress responses, species evolution, and complex agronomic traits. Nevertheless, single-cell methodologies for profiling histone modifications, DNA methylation, 3-dimensional genome organization, and spatial epigenomic states in plants are still in their infancy. In this review, we systematically elaborate the technological framework, bioinformatic workflows, key research advances, and existing challenges in the field of plant single-cell epigenomics and highlight future perspectives for its in-depth development.
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Single-nucleus transcriptional profiling reveals TCF7L2 as a key regulator in adipogenesis in goat skeletal muscle development.
Intramuscular adipogenesis plays an important role in muscle development, which determines the quality of goat meat. However, its underlying cellular and molecular mechanisms remain poorly understood. In this study, we provided detailed cellular atlases of goat longissimus dorsi during muscle development at single-nucleus resolution, and identified the subpopulations of fibroblasts/fibro-adipogenic progenitors (FAPs) and muscle satellite cell (MuSC), as well as the differentiation trajectory of FAPs subpopulations. Cellular ligand-receptor interaction analysis revealed enriched BMP and IGF pathways implicated in within-tissue crosstalk centered around FAPs. Through single-nucleus gene regulatory network analysis and in vitro interference verification, we found that TCF7L2 was a critical transcriptional factor (TF) in early adipogenesis in skeletal muscle. Overall, our work reveals the cellular intricacies and diversity of goat longissimus dorsi during muscle development, implementing insights into the critical roles of BMP, IGF pathways and TCF7L2 TF in intramuscular adipogenesis.
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A single-cell atlas of entorhinal cortex from individuals with Alzheimer's disease reveals cell-type-specific gene expression regulation.
There is currently little information available about how individual cell types contribute to Alzheimer's disease. Here we applied single-nucleus RNA sequencing to entorhinal cortex samples from control and Alzheimer's disease brains (n = 6 per group), yielding a total of 13,214 high-quality nuclei. We detail cell-type-specific gene expression patterns, unveiling how transcriptional changes in specific cell subpopulations are associated with Alzheimer's disease. We report that the Alzheimer's disease risk gene APOE is specifically repressed in Alzheimer's disease oligodendrocyte progenitor cells and astrocyte subpopulations and upregulated in an Alzheimer's disease-specific microglial subopulation. Integrating transcription factor regulatory modules with Alzheimer's disease risk loci revealed drivers of cell-type-specific state transitions towards Alzheimer's disease. For example, transcription factor EB, a master regulator of lysosomal function, regulates multiple disease genes in a specific Alzheimer's disease astrocyte subpopulation. These results provide insights into the coordinated control of Alzheimer's disease risk genes and their cell-type-specific contribution to disease susceptibility. These results are available at http://adsn.ddnetbio.com.
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Supervised classification enables rapid annotation of cell atlases.
Single-cell molecular profiling technologies are gaining rapid traction, but the manual process by which resulting cell types are typically annotated is labor intensive and rate-limiting. We describe Garnett, a tool for rapidly annotating cell types in single-cell transcriptional profiling and single-cell chromatin accessibility datasets, based on an interpretable, hierarchical markup language of cell type-specific genes. Garnett successfully classifies cell types in tissue and whole organism datasets, as well as across species.
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Continuous lifelong learning for modeling of gene regulation from single cell multiome data by leveraging atlas-scale external data.
Accurate context-specific Gene Regulatory Networks (GRNs) inference from genomics data is a crucial task in computational biology. However, existing methods face limitations, such as reliance on gene expression data alone, lower resolution from bulk data, and data scarcity for specific cellular systems. Despite recent technological advancements, including single-cell sequencing and the integration of ATAC-seq and RNA-seq data, learning such complex mechanisms from limited independent data points still presents a daunting challenge, impeding GRN inference accuracy. To overcome this challenge, we present LINGER (LIfelong neural Network for GEne Regulation), a novel deep learning-based method to infer GRNs from single-cell multiome data with paired gene expression and chromatin accessibility data from the same cell. LINGER incorporates both 1) atlas-scale external bulk data across diverse cellular contexts and 2) the knowledge of transcription factor (TF) motif matching to cis-regulatory elements as a manifold regularization to address the challenge of limited data and extensive parameter space in GRN inference. Our results demonstrate that LINGER achieves 2-3 fold higher accuracy over existing methods. LINGER reveals a complex regulatory landscape of genome-wide association studies, enabling enhanced interpretation of disease-associated variants and genes. Additionally, following the GRN inference from a reference sc-multiome data, LINGER allows for the estimation of TF activity solely from bulk or single-cell gene expression data, leveraging the abundance of available gene expression data to identify driver regulators from case-control studies. Overall, LINGER provides a comprehensive tool for robust gene regulation inference from genomics data, empowering deeper insights into cellular mechanisms.
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Single Cell RNA-Sequencing Reveals a Murine Gallbladder Cell Transcriptome Atlas During the Process of Cholesterol Gallstone Formation.
Gallstone disease is a worldwide common disease. However, the knowledge concerning the gallbladder in the pathogenesis of cholesterol gallstone formation remains limited. In this study, using single-cell RNA sequencing (scRNA-seq) to obtain the transcriptome of gallbladder cells, we showed cellular heterogeneity and transcriptomic dynamics in murine gallbladder cells during the process of lithogenesis. Our results indicated gallbladder walls were subjected to remodeling during the process of lithogenesis. The major molecular events that happened included proliferation of epithelial cells, infiltration of immune-cells, activation of angiogenesis, and extracellular matrix modulation. Furthermore, we observed partial reversal of gallbladder cell transcriptomes by ursodeoxycholic acid treatment. This work thus provides novel and integral knowledges on the cellular changes during lithogenesis, which is of great significance to the understanding of pathogenesis and treatment of cholesterol gallstone.
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Cell atlas of the immune microenvironment in gastrointestinal cancers: Dendritic cells and beyond.
Gastrointestinal (GI) cancers occur in the alimentary tract and accessory organs. They exert a global burden with high morbidity and mortality. Inside the tumor microenvironment, dendritic cells (DCs) are the most efficient antigen-presenting cells and are necessary for adaptive immune responses such as T and B-cell maturation. However, the subsets of DCs revealed before were mostly based on flow cytometry and bulk sequencing. With the development of single-cell RNA sequencing (scRNA-seq), the tumor and microenvironment heterogeneity of GI cancer has been illustrated. In this review, we summarize the classification and development trajectory of dendritic cells at the single-cell level in GI cancer. Additionally, we focused on the interaction of DCs with T cells and their effect on the response to immunotherapy. Specifically, we focused on the newly identified tumor-infiltrating dendritic cells and discuss their potential function in antitumor immunity.