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A single-cell meta-analysis evidences transposable element dysregulation in sex-based differences in Parkinson's disease.
Transposable elements (TEs) (mobile genetic elements comprising ∼45% of the human genome) have recently emerged as potential contributors to Parkinson's disease (PD); however their role and sex-specific impact remain poorly understood. Here, we present the first integrative meta-analysis of TE expression across 4 substantia nigra single-nucleus RNA-seq datasets, comprising a total of 66 donors, generating a cell-type-resolved atlas of TE dysregulation in PD. We identified widespread TE activation across major brain cell types (i.e. neurons, astrocytes, oligodendrocytes and microglia), with marked upregulation of L1s in neurons and HERVs in oligodendrocytes. Sex-stratified analyses revealed distinct male- and female-biased TE signatures, indicating regulatory programs uniquely affected in each sex, including MIR elements in microglia and Alu subfamilies in neurons. Correlation and genomic proximity analyses also uncovered TE-gene associations linked to important PD pathways such as neuroinflammation or myelination. Collectively, our study positions TEs as potential sex-modulated contributors to PD pathology and also provides a public web resource (PATOSS) to explore PD-associated TE transcriptional deregulation.
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A single-cell resolution developmental atlas of hematopoietic stem and progenitor cell expansion in zebrafish.
During vertebrate embryogenesis, fetal hematopoietic stem and progenitor cells (HSPCs) exhibit expansion and differentiation properties in a supportive hematopoietic niche. To profile the developmental landscape of fetal HSPCs and their local niche, here, using single-cell RNA-sequencing, we deciphered a dynamic atlas covering 28,777 cells and 9 major cell types (23 clusters) of zebrafish caudal hematopoietic tissue (CHT). We characterized four heterogeneous HSPCs with distinct lineage priming and metabolic gene signatures. Furthermore, we investigated the regulatory mechanism of CHT niche components for HSPC development, with a focus on the transcription factors and ligand-receptor networks involved in HSPC expansion. Importantly, we identified an endothelial cell-specific G protein-coupled receptor 182, followed by in vivo and in vitro functional validation of its evolutionally conserved role in supporting HSPC expansion in zebrafish and mice. Finally, comparison between zebrafish CHT and human fetal liver highlighted the conservation and divergence across evolution. These findings enhance our understanding of the regulatory mechanism underlying hematopoietic niche for HSPC expansion in vivo and provide insights into improving protocols for HSPC expansion in vitro.
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Development and validation of prognostic and diagnostic model for pancreatic ductal adenocarcinoma based on scRNA-seq and bulk-seq datasets.
The 5-year overall survival (OS) of pancreatic ductal adenocarcinoma (PDAC) is only 10%, partly owing to the lack of reliable diagnostic and prognostic biomarkers. The raw gene-cell matrix for single-cell RNA-seq (scRNA-seq) analysis was downloaded from the GSA database. We drew cell atlas for PDAC and normal pancreatic tissues. The inferCNV analysis was used to distinguish tumor cells from normal ductal cells. We identified differential expression genes (DEGs) by comparing tumor cells and normal ductal cells. The common DEGs were used to conduct prognostic and diagnostic model using univariate and multivariate Cox or logistic regression analysis. Four genes, MET, KLK10, PSMB9 and ITGB6, were utilized to create risk score formula to predict OS and to establish diagnostic model for PDAC. Finally, we drew an easy-to-use nomogram to predict 2-year and 3-year OSs. In conclusion, we developed and validated the prognostic and diagnostic model for PDAC based on scRNA-seq and bulk-seq datasets.
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Projecting RNA measurements onto single cell atlases to extract cell type-specific expression profiles using scProjection.
Multi-modal single cell RNA assays capture RNA content as well as other data modalities, such as spatial cell position or the electrophysiological properties of cells. Compared to dedicated scRNA-seq assays however, they may unintentionally capture RNA from multiple adjacent cells, exhibit lower RNA sequencing depth compared to scRNA-seq, or lack genome-wide RNA measurements. We present scProjection, a method for mapping individual multi-modal RNA measurements to deeply sequenced scRNA-seq atlases to extract cell type-specific, single cell gene expression profiles. We demonstrate several use cases of scProjection, including identifying spatial motifs from spatial transcriptome assays, distinguishing RNA contributions from neighboring cells in both spatial and multi-modal single cell assays, and imputing expression measurements of un-measured genes from gene markers. scProjection therefore combines the advantages of both multi-modal and scRNA-seq assays to yield precise multi-modal measurements of single cells.
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Preliminary Analysis of Aging-Related Genes in Intracerebral Hemorrhage by Integration of Bulk and Single-Cell RNA Sequencing Technology.
BACKGROUND: Aging is recognized as the key risk for intracerebral hemorrhage (ICH). The detailed mechanisms of aging in ICH warrant exploration. This study aimed to identify potential aging-related genes associated with ICH. METHODS: ICH-specific aging-related genes were determined by the intersection of differentially expressed genes (DEGs) between perihematomal tissues and corresponding contralateral parts of four patients with ICH (GSE24265) and 349 aging-related genes obtained from the Aging Atlas database. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) analyses were performed to identify the potential biological functions and pathways in which these ICH-specific aging-related genes may be involved. Then, PPI network was established to identify the hub genes of ICH-specific aging-related genes. Meanwhile, miRNA-mRNA and transcription factor (TF)-mRNA regulatory networks were constructed to further explore the ICH-specific aging-related genes regulation. The relationship between these hub genes and immune infiltration was also further explored. Additional single-cell RNA-seq analysis (scRNA-seq, GSE167593) was used to locate the hub genes in different cell types. Besides, expression levels of the hub genes were validated using clinical samples from our institute and another GEO dataset (GSE206971). RESULTS: This study identified 24 ICH-specific aging-related genes, including 22 up-regulated and 2 down-regulated genes. The results of GO and KEGG suggested that the ICH-specific aging-related genes mainly enriched in immunity and inflammation-related pathways, suggesting that aging may affect the ich pathogenesis by regulating inflammatory and immune-related pathways. CONCLUSION: Our study revealed 24 ICH-specific aging-related genes and their functions highly pertinent to ICH pathogenesis, providing new insights into the impact of aging on ICH.
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A 3D gene expression atlas of the floral meristem based on spatial reconstruction of single nucleus RNA sequencing data.
Cellular heterogeneity in growth and differentiation results in organ patterning. Single-cell transcriptomics allows characterization of gene expression heterogeneity in developing organs at unprecedented resolution. However, the original physical location of the cell is lost during this methodology. To recover the original location of cells in the developing organ is essential to link gene activity with cellular identity and function in plants. Here, we propose a method to reconstruct genome-wide gene expression patterns of individual cells in a 3D flower meristem by combining single-nuclei RNA-seq with microcopy-based 3D spatial reconstruction. By this, gene expression differences among meristematic domains giving rise to different tissue and organ types can be determined. As a proof of principle, the method is used to trace the initiation of vascular identity within the floral meristem. Our work demonstrates the power of spatially reconstructed single cell transcriptome atlases to understand plant morphogenesis. The floral meristem 3D gene expression atlas can be accessed at http://threed-flower-meristem.herokuapp.com .
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Single-cell transcriptomes of dissecting the intra-tumoral heterogeneity of breast cancer microenvironment.
OBJECTIVE: To investigate the mechanism by which heterogeneity in breast cancer developed and acted in single-cell transcriptomes. METHODS: The composition of breast cancer based on the single-cell transcriptomes of 54,055 high-quality cells from clinical specimens of 4 malignant and 4 non-malignant patients were investigated. RESULTS: We identified six common expression programs and six subtype-specific expression programs form malignant epithelial cells. The expression program of malignant epithelial cells exhibited activated EMT (Epithelial Mesenchymal Transition) in TME, which might indicate EMT intervention have a general therapeutic effect on various subtypes. Gene set enrichment analysis (GSEA) based on the top 50 highly NMF (non-negative matrix factorization) score genes in each program depicted the distinct function of each program in breast cancer progression. Moreover, we revealed the profound cellular heterogeneity of myeloid cell lineages in breast cancer. In macrophages, two mainly tumor associated macrophages (TAMs), TAM1 and TAM2, were also detected and the highly variable genes in TAM2 were strongly enriched in IFN-α and IFN-γ. The changes of lipid metabolism pathways in macrophages are closely related to the microenvironment of breast cancer. CONCLUSION: We constructed a comprehensive single-cell transcriptome atlas of 54,055 cells from 4 malignant and 4 nonmalignant patients, providing insights into the mechanisms underlying breast cancer progression and the development of potential therapeutic strategies in breast cancer.
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Aging-Associated Alterations in Mammary Epithelia and Stroma Revealed by Single-Cell RNA Sequencing.
Aging is closely associated with increased susceptibility to breast cancer, yet there have been limited systematic studies of aging-induced alterations in the mammary gland. Here, we leverage high-throughput single-cell RNA sequencing to generate a detailed transcriptomic atlas of young and aged murine mammary tissues. By analyzing epithelial, stromal, and immune cells, we identify age-dependent alterations in cell proportions and gene expression, providing evidence that suggests alveolar maturation and physiological decline. The analysis also uncovers potential pro-tumorigenic mechanisms coupled to the age-associated loss of tumor suppressor function and change in microenvironment. In addition, we identify a rare, age-dependent luminal population co-expressing hormone-sensing and secretory-alveolar lineage markers, as well as two macrophage populations expressing distinct gene signatures, underscoring the complex heterogeneity of the mammary epithelia and stroma. Collectively, this rich single-cell atlas reveals the effects of aging on mammary physiology and can serve as a useful resource for understanding aging-associated cancer risk.
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scMCA: A Tool to Define Mouse Cell Types Based on Single-Cell Digital Expression.
For decades, people have been trying to define cell type with the combination of expressed genes. The choice of the limited number of genes for the classification limits the precision of this system. Here, we build a "single-cell Mouse Cell Atlas (scMCA) analysis" pipeline based on scRNA-seq datasets covering all mouse cell types. We build the scMCA reference and then use the tool "scMCA" to match single-cell digital expression to its closest cell type.
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Construction and validation of a β-hydroxybutyrylation-related molecular model for predicting prognosis of papillary thyroid carcinoma.
BACKGROUND: Papillary thyroid carcinoma (PTC) usually has a favorable prognosis, yet a subset of patients develops persistent, recurrent, or biologically aggressive disease. The clinical relevance of lysine β-hydroxybutyrylation (Kbhb)-related transcriptional programs in PTC remains unclear. Accordingly, this study aimed to characterize Kbhb-related molecular heterogeneity in PTC, construct a prognostic signature, and explore its association with the tumor microenvironment (TME). METHODS: Transcriptomic and clinical data from PTC samples within The Cancer Genome Atlas Thyroid Carcinoma (TCGA-THCA) cohort were analyzed to identify Kbhb-related differentially expressed genes (DEGs), define molecular subtypes, construct a prognostic signature, and characterize tumor microenvironmental features. Single-cell RNA-sequencing data from PTC were further used to explore the cellular distribution of representative genes. RESULTS: We identified 51 Kbhb-related DEGs in PTC and defined two Kbhb molecular subtypes. The Kbhb_C2 subtype showed shorter progression-free interval (PFI) and a more immune- and stroma-enriched microenvironment. A six-gene prognostic signature comprising TARID, CDSN, PIMREG, KLRC1, SYT13, and NPR3 was then established. High-risk patients had significantly worse PFI in the full, training, and testing cohorts, with 1-, 3-, and 5-year areas under the curve (AUCs) of 0.715, 0.793, and 0.771, respectively, in the full cohort. High-risk tumors also exhibited higher stromal, immune, and ESTIMATE scores, altered immune infiltration, and increased expression of multiple immune checkpoint molecules. Single-cell analysis confirmed distinct cell-type-specific expression patterns of representative genes. CONCLUSIONS: Kbhb-related transcriptional programs define clinically relevant molecular heterogeneity in PTC and are closely associated with prognosis and TME remodeling. The identified six-gene signature provides a biologically interpretable framework for risk stratification in PTC.