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visium spatial gene expression profiles spatial transcriptome analysis  (10X Genomics)

 
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    Structured Review

    10X Genomics visium spatial gene expression profiles spatial transcriptome analysis
    Visium Spatial Gene Expression Profiles Spatial Transcriptome Analysis, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/spatial+transcriptome+analysis+visium/data+spatial+transcriptomic/pm39632980-245-3-12
    Average 86 stars, based on 1 article reviews
    visium spatial gene expression profiles spatial transcriptome analysis - by Bioz Stars, 2026-09
    86/100 stars

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    Related Articles

    Spatial Transcriptomics:

    Article Title: Single-cell multiomics gene regulatory landscape reveals impaired spermatogonial stem cells and macrophage-driven inflammaging during testicular aging.
    Article Snippet: 29 Testicular aging is a key driver of declining male reproductive health, but a comprehensive 30 understanding of its underlying epigenetic drivers is lacking.. To address this, we construct a 31 multiomics aging atlas by integrating single-cell RNA sequencing, single-cell assay for 32 transposase-accessible chromatin sequencing (scATAC-seq), and spatial transcriptomics of 33 young and aged mouse testes.. Our analysis reveals that altered chromatin accessibility 34 accompanies transcriptional dysregulation and identifies spermatogonial stem cells (SSCs) as 35 the most epigenetically vulnerable population.

    Sequencing:

    Article Title: Single-cell multiomics gene regulatory landscape reveals impaired spermatogonial stem cells and macrophage-driven inflammaging during testicular aging.
    Article Snippet: 29 Testicular aging is a key driver of declining male reproductive health, but a comprehensive 30 understanding of its underlying epigenetic drivers is lacking.. To address this, we construct a 31 multiomics aging atlas by integrating single-cell RNA sequencing, single-cell assay for 32 transposase-accessible chromatin sequencing (scATAC-seq), and spatial transcriptomics of 33 young and aged mouse testes.. Our analysis reveals that altered chromatin accessibility 34 accompanies transcriptional dysregulation and identifies spermatogonial stem cells (SSCs) as 35 the most epigenetically vulnerable population.

    Article Title: Spatial single-cell landscape of tumor-associated macrophages and their crosstalk with the tumor microenvironment.
    Article Snippet: .. To minimize batch effects caused by differences in sequencing platforms and methodologies, all single-cell and spatial transcriptomic data were obtained exclusively from the 10x Genomics and 10x Visium platforms. ..

    Gene Expression:

    Article Title: Single-cell multiomics gene regulatory landscape reveals impaired spermatogonial stem cells and macrophage-driven inflammaging during testicular aging.
    Article Snippet: 29 Testicular aging is a key driver of declining male reproductive health, but a comprehensive 30 understanding of its underlying epigenetic drivers is lacking.. To address this, we construct a 31 multiomics aging atlas by integrating single-cell RNA sequencing, single-cell assay for 32 transposase-accessible chromatin sequencing (scATAC-seq), and spatial transcriptomics of 33 young and aged mouse testes.. Our analysis reveals that altered chromatin accessibility 34 accompanies transcriptional dysregulation and identifies spermatogonial stem cells (SSCs) as 35 the most epigenetically vulnerable population.

    Single Cell:

    Article Title: Spatial single-cell landscape of tumor-associated macrophages and their crosstalk with the tumor microenvironment.
    Article Snippet: .. To minimize batch effects caused by differences in sequencing platforms and methodologies, all single-cell and spatial transcriptomic data were obtained exclusively from the 10x Genomics and 10x Visium platforms. ..

    Article Title: The Role of Tumor Necrosis Factor Signaling in Atherosclerosis and Stroke
    Article Snippet: .. To characterise TNF signaling within atherosclerotic plaques, we analysed two publicly available datasets: (i) an integrated single-cell RNA-sequencing (scRNA-seq) atlas of 259,116 cells from human carotid, coronary, and femoral plaques (73 donors), and (ii) Xenium (10x Genomics) spatial transcriptomic data comprising 120,164 cells from carotid endarterectomy specimens with pathologist-annotated subregions (12 donors). ..

    In Situ:

    Article Title: SARS-CoV-2 infection and vaccination elicit distinct pharyngeal mucosal B cell responses in children.
    Article Snippet: .. Spatial transcriptomic profiling with Xenium In Situ platform Slides were prepared following the manufacturer’s instructions and workflow for FFPE tissue samples (CG000578 Rev A; 10x Genomics). .. A 5-μm section from the tissue block containing the same paired tonsil and adenoid samples (one from INF donor and one from VAC donor) used for immunofluorescence were carefully attached to the sample area on a Xenium slide (Histoserv, MD).

    Article Title: An antioxidant therapy elicits distinct transcriptome responses in 22q11-deleted upper layer cortical projection neurons.
    Article Snippet: .. To assess L 2/3 PN transcriptional responses that underlie NAC’s therapeutic effects in vivo, we first established that spatial transcriptomic RNA quantification in situ (10X Genomics Xenium) securely identifies L 2/3 PNs and their neighbors, thus ensuring that transcriptional states can be assessed in intact cortices of early post-natal WT, LgDel, LgDel + NAC and WT + NAC L 2/3 mice. ..

    Article Title: Won't you be my neighbor? Control of the immune response by stromal and immune cell microenvironments within the lymph node.
    Article Snippet: Efficacious immune responses require the coordinated encounter of rare antigen-specific adaptive lymphocytes with their cognate innate antigen-presenting cells (APCs) in space and time.. This spatiotemporal problem of immunity is solved by secondary lymphoid organs, such as lymph nodes (LNs), which coordinate adaptive immune responses by recruiting APCs and lymphocytes into close juxtaposition with tissue antigens drained from the periphery.. A central tenet to the overall function of the LN is the spatial organization of leukocytes into discrete microenvironments orchestrated by the mesenchymal and endothelial cells, collectively termed LN stromal cells (LNSCs).

    Formalin-fixed Paraffin-Embedded:

    Article Title: SARS-CoV-2 infection and vaccination elicit distinct pharyngeal mucosal B cell responses in children.
    Article Snippet: .. Spatial transcriptomic profiling with Xenium In Situ platform Slides were prepared following the manufacturer’s instructions and workflow for FFPE tissue samples (CG000578 Rev A; 10x Genomics). .. A 5-μm section from the tissue block containing the same paired tonsil and adenoid samples (one from INF donor and one from VAC donor) used for immunofluorescence were carefully attached to the sample area on a Xenium slide (Histoserv, MD).

    In Vivo:

    Article Title: An antioxidant therapy elicits distinct transcriptome responses in 22q11-deleted upper layer cortical projection neurons.
    Article Snippet: .. To assess L 2/3 PN transcriptional responses that underlie NAC’s therapeutic effects in vivo, we first established that spatial transcriptomic RNA quantification in situ (10X Genomics Xenium) securely identifies L 2/3 PNs and their neighbors, thus ensuring that transcriptional states can be assessed in intact cortices of early post-natal WT, LgDel, LgDel + NAC and WT + NAC L 2/3 mice. ..

    RNA sequencing:

    Article Title: The Role of Tumor Necrosis Factor Signaling in Atherosclerosis and Stroke
    Article Snippet: .. To characterise TNF signaling within atherosclerotic plaques, we analysed two publicly available datasets: (i) an integrated single-cell RNA-sequencing (scRNA-seq) atlas of 259,116 cells from human carotid, coronary, and femoral plaques (73 donors), and (ii) Xenium (10x Genomics) spatial transcriptomic data comprising 120,164 cells from carotid endarterectomy specimens with pathologist-annotated subregions (12 donors). ..



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    10X Genomics visium spatial transcriptomics analysis
    ( A ) Samples of nuclei were derived from three whole dissociated hearts to generate distinct single-cell RNA-seq datasets at 8.6 post-conceptional weeks (pcw, confirmed XX genotype), 9.0 pcw (XY) and 10.7 pcw (XY). Samples of spatial transcriptomic analysis were derived from two whole dissociated hearts to collect cryosections and generate <t>Visium</t> datasets at 8.4 pcw (XY, 2 sections) and 9.7 pcw (XX, 4 sections). ( B ) Integrated UMAP representation of 49,227 profiled nuclei coloured by cell type. ( C ) UMAP representation of profiled nuclei as in (B) but separated by sample. Arrows indicate cluster 12 (SMC) in each, but that all cell types are present at each sample. ( D ) UMAP plots per sample indicating that all cell classes are also represented in each sample. ( E ) Dot plot of top marker genes for each Class (y axis: cardiomyocytes (I), endocardiovascular cells (II), stroma (III), epicardium (IV), blood (V) and neural crest progeny (VI). The size of the dot represents the percent of nuclei with transcripts at non-zero levels, and color intensity represents average log-normalized expression of the gene where relative abundance of typical markers is indicative of cell class. ( F ) UMAP feature plots of representative gene expression in Classes I to VI for MYH7 (cardiomyocytes), PECAM1 (endothelial and endocardial cells), EBF2 (stroma), TBX18 (epicardium), SPP1 (immune cells) and NRXN1 (neural crest). ( G ) Heatmap showing selected genes expressed in the nine cardiomyocyte clusters of Class I compared with the minority populations of lymphatic endothelium, Schwann cell precursors and neuroendocrine cells. Each column displays gene expression of an individual cell and genes are listed in the rows.
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    10X Genomics visium spatial transcriptome analysis
    ( A ) Samples of nuclei were derived from three whole dissociated hearts to generate distinct single-cell RNA-seq datasets at 8.6 post-conceptional weeks (pcw, confirmed XX genotype), 9.0 pcw (XY) and 10.7 pcw (XY). Samples of spatial transcriptomic analysis were derived from two whole dissociated hearts to collect cryosections and generate <t>Visium</t> datasets at 8.4 pcw (XY, 2 sections) and 9.7 pcw (XX, 4 sections). ( B ) Integrated UMAP representation of 49,227 profiled nuclei coloured by cell type. ( C ) UMAP representation of profiled nuclei as in (B) but separated by sample. Arrows indicate cluster 12 (SMC) in each, but that all cell types are present at each sample. ( D ) UMAP plots per sample indicating that all cell classes are also represented in each sample. ( E ) Dot plot of top marker genes for each Class (y axis: cardiomyocytes (I), endocardiovascular cells (II), stroma (III), epicardium (IV), blood (V) and neural crest progeny (VI). The size of the dot represents the percent of nuclei with transcripts at non-zero levels, and color intensity represents average log-normalized expression of the gene where relative abundance of typical markers is indicative of cell class. ( F ) UMAP feature plots of representative gene expression in Classes I to VI for MYH7 (cardiomyocytes), PECAM1 (endothelial and endocardial cells), EBF2 (stroma), TBX18 (epicardium), SPP1 (immune cells) and NRXN1 (neural crest). ( G ) Heatmap showing selected genes expressed in the nine cardiomyocyte clusters of Class I compared with the minority populations of lymphatic endothelium, Schwann cell precursors and neuroendocrine cells. Each column displays gene expression of an individual cell and genes are listed in the rows.
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    Image Search Results


    ( A ) Samples of nuclei were derived from three whole dissociated hearts to generate distinct single-cell RNA-seq datasets at 8.6 post-conceptional weeks (pcw, confirmed XX genotype), 9.0 pcw (XY) and 10.7 pcw (XY). Samples of spatial transcriptomic analysis were derived from two whole dissociated hearts to collect cryosections and generate Visium datasets at 8.4 pcw (XY, 2 sections) and 9.7 pcw (XX, 4 sections). ( B ) Integrated UMAP representation of 49,227 profiled nuclei coloured by cell type. ( C ) UMAP representation of profiled nuclei as in (B) but separated by sample. Arrows indicate cluster 12 (SMC) in each, but that all cell types are present at each sample. ( D ) UMAP plots per sample indicating that all cell classes are also represented in each sample. ( E ) Dot plot of top marker genes for each Class (y axis: cardiomyocytes (I), endocardiovascular cells (II), stroma (III), epicardium (IV), blood (V) and neural crest progeny (VI). The size of the dot represents the percent of nuclei with transcripts at non-zero levels, and color intensity represents average log-normalized expression of the gene where relative abundance of typical markers is indicative of cell class. ( F ) UMAP feature plots of representative gene expression in Classes I to VI for MYH7 (cardiomyocytes), PECAM1 (endothelial and endocardial cells), EBF2 (stroma), TBX18 (epicardium), SPP1 (immune cells) and NRXN1 (neural crest). ( G ) Heatmap showing selected genes expressed in the nine cardiomyocyte clusters of Class I compared with the minority populations of lymphatic endothelium, Schwann cell precursors and neuroendocrine cells. Each column displays gene expression of an individual cell and genes are listed in the rows.

    Journal: bioRxiv

    Article Title: Multi-modal refinement of the human heart atlas during the first gestational trimester

    doi: 10.1101/2024.11.21.624698

    Figure Lengend Snippet: ( A ) Samples of nuclei were derived from three whole dissociated hearts to generate distinct single-cell RNA-seq datasets at 8.6 post-conceptional weeks (pcw, confirmed XX genotype), 9.0 pcw (XY) and 10.7 pcw (XY). Samples of spatial transcriptomic analysis were derived from two whole dissociated hearts to collect cryosections and generate Visium datasets at 8.4 pcw (XY, 2 sections) and 9.7 pcw (XX, 4 sections). ( B ) Integrated UMAP representation of 49,227 profiled nuclei coloured by cell type. ( C ) UMAP representation of profiled nuclei as in (B) but separated by sample. Arrows indicate cluster 12 (SMC) in each, but that all cell types are present at each sample. ( D ) UMAP plots per sample indicating that all cell classes are also represented in each sample. ( E ) Dot plot of top marker genes for each Class (y axis: cardiomyocytes (I), endocardiovascular cells (II), stroma (III), epicardium (IV), blood (V) and neural crest progeny (VI). The size of the dot represents the percent of nuclei with transcripts at non-zero levels, and color intensity represents average log-normalized expression of the gene where relative abundance of typical markers is indicative of cell class. ( F ) UMAP feature plots of representative gene expression in Classes I to VI for MYH7 (cardiomyocytes), PECAM1 (endothelial and endocardial cells), EBF2 (stroma), TBX18 (epicardium), SPP1 (immune cells) and NRXN1 (neural crest). ( G ) Heatmap showing selected genes expressed in the nine cardiomyocyte clusters of Class I compared with the minority populations of lymphatic endothelium, Schwann cell precursors and neuroendocrine cells. Each column displays gene expression of an individual cell and genes are listed in the rows.

    Article Snippet: As transcriptomics of single nuclei is high-resolution but sparse, and removes informative positional information from samples, we also undertook 10x Genomics Visium spatial transcriptomics analysis on two sections from a male heart collected at 8.4 pcw and four sections from a female one at 9.7 pcw ( , Figs. S4-9).

    Techniques: Derivative Assay, RNA Sequencing Assay, Marker, Expressing

    ( A ) Seurat UMAP (Uniform Manifold Approximation and Projection) plot of integrated spatial transcriptomic data from two 8.4 postconceptional week (pcw) heart sections and four 9.7 pcw heart sections. Each dot represents a spot covered by a histological section on the Visium spatial capture slides. 14 clusters of the developing heart corresponding to cardiac cell types are listed. ( B ) Visualization of clustering on each heart section after integration of spatial transcriptomic data. Cluster annotations and colors match those of the UMAP in A. ( C ) Spatial plots showing gene expression on heart sections, with highest expression in red and lower expression in blue. RV, right ventricle; LV, left ventricle; RA, right atrium; LA, left atrium; Ao, aorta.

    Journal: bioRxiv

    Article Title: Multi-modal refinement of the human heart atlas during the first gestational trimester

    doi: 10.1101/2024.11.21.624698

    Figure Lengend Snippet: ( A ) Seurat UMAP (Uniform Manifold Approximation and Projection) plot of integrated spatial transcriptomic data from two 8.4 postconceptional week (pcw) heart sections and four 9.7 pcw heart sections. Each dot represents a spot covered by a histological section on the Visium spatial capture slides. 14 clusters of the developing heart corresponding to cardiac cell types are listed. ( B ) Visualization of clustering on each heart section after integration of spatial transcriptomic data. Cluster annotations and colors match those of the UMAP in A. ( C ) Spatial plots showing gene expression on heart sections, with highest expression in red and lower expression in blue. RV, right ventricle; LV, left ventricle; RA, right atrium; LA, left atrium; Ao, aorta.

    Article Snippet: As transcriptomics of single nuclei is high-resolution but sparse, and removes informative positional information from samples, we also undertook 10x Genomics Visium spatial transcriptomics analysis on two sections from a male heart collected at 8.4 pcw and four sections from a female one at 9.7 pcw ( , Figs. S4-9).

    Techniques: Expressing