Spatially resolved multiomics of human cardiac niches - Multiome ATAC
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ABSTRACT:
PROVIDER: PRJEB61895 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Spatially resolved multiomics of human cardiac niches - Multiome GEX
| PRJEB61891 | ENA
Project description:Using Multiome and previously published sc/snRNA-seq data, we studied eight anatomical regions of the human heart including left and right ventricular free walls (LV and RV), left and right atria (LA and RA), left ventricular apex (AX), interventricular septum (SP), sino-atrial node (SAN) and atrioventricular node (AVN). For the first time, we profile the cells of the human cardiac conduction system, revealing their distinctive repertoire of ion channels, G-protein coupled receptors and cell-cell interactions. We map the identified cells to spatial transcriptomic data to discover cellular niches within the eight regions of the heart.
2023-06-13 | E-MTAB-12916 | biostudies-arrayexpress
Project description:Using Multiome and previously published sc/snRNA-seq data, we studied eight anatomical regions of the human heart including left and right ventricular free walls (LV and RV), left and right atria (LA and RA), left ventricular apex (AX), interventricular septum (SP), sino-atrial node (SAN) and atrioventricular node (AVN). For the first time, we profile the cells of the human cardiac conduction system, revealing their distinctive repertoire of ion channels, G-protein coupled receptors and cell-cell interactions. We map the identified cells to spatial transcriptomic data to discover cellular niches within the eight regions of the heart.
2023-06-13 | E-MTAB-12919 | biostudies-arrayexpress
Project description:Spatially resolved multiomics of human cardiac niches - Visium
| PRJEB62497 | ENA
Project description:Using Multiome and previously published sc/snRNA-seq data, we studied eight anatomical regions of the human heart including left and right ventricular free walls (LV and RV), left and right atria (LA and RA), left ventricular apex (AX), interventricular septum (SP), sino-atrial node (SAN) and atrioventricular node (AVN). For the first time, we profile the cells of the human cardiac conduction system, revealing their distinctive repertoire of ion channels, G-protein coupled receptors and cell-cell interactions. We map the identified cells to spatial transcriptomic data to discover cellular niches within the eight regions of the heart.
2023-06-01 | E-MTAB-12975 | biostudies-arrayexpress
Project description:These samples are part of a study to provide a spatially resolved single-cell multiomics map of human trophoblast differentiation in early pregnancy. Here we profiled human implantation sites, decidual and placental samples from 6-9 PCW by 10x multiome snRNA-seq/snATAC-seq.
2023-02-09 | E-MTAB-12595 | biostudies-arrayexpress
Project description:The function of a cell is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here we combine single-cell and spatial transcriptomics data to discover cellular niches within eight regions of the human heart. We map cells to microanatomical locations and integrate knowledge-based and unsupervised structural annotations. We also profile the cells of the human cardiac conduction system1. The results revealed their distinctive repertoire of ion channels, G-protein-coupled receptors (GPCRs) and regulatory networks, and implicated FOXP2 in the pacemaker phenotype. We show that the sinoatrial node is compartmentalized, with a core of pacemaker cells, fibroblasts and glial cells supporting glutamatergic signalling. Using a custom CellPhoneDB.org module, we identify trans-synaptic pacemaker cell interactions with glia. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug-target interactions to provide mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches that may contribute to infection defence. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be applied to other tissues and organs.
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Project description:Understanding the spatial distribution of T cells is pivotal to decrypting immune dysfunction in cancer. Current spatially resolved transcriptomics fall short in directly annotating T cell receptors (TCRs), limiting the comprehension of anti-cancer immunity. We introduce a novel technology, Spatially Resolved T Cell Receptor Sequencing (SPTCR-seq), integrating target enrichment and long-read sequencing for highly sensitive TCR sequencing. This approach yields an on-target rate of ~85%, and via a bespoke computational pipeline, it provides meticulous spatial mapping, error correction, and UMI refinement. SPTCR-seq outperforms PCR-based methods, offering superior reconstruction of the complete TCR architecture, inclusive of V, D, J regions and the vital complementarity-determining region 3 (CDR3). Applying SPTCR-seq, we reveal local T cell diversity, clonal expansion, and transcriptional evolution across spatially distinct niches in glioblastoma, identifying critical involvement of NK and B cells in spatial T cell adaptation. SPTCR-seq, by bridging spatially resolved omics and TCR sequencing, stands as a robust tool for exploring T cell dysfunction in cancers and beyond.
2023-07-25 | GSE238071 | GEO
Project description:This study presents a single cell and spatially resolved transcriptomics analysis of human breast cancers. We develop a single cell method of intrinsic subtype classification (scSubtype) to reveal recurrent neoplastic cell heterogeneity. Immunophenotyping using CITE-Seq provides high-resolution immune profiles, including novel PD-L1/PD-L2+ macrophage populations associated with clinical outcome. Mesenchymal cells displayed diverse functions and cell surface protein expression through differentiation within 3 major lineages. Stromal-immune niches were spatially organized in tumors, offering insights into anti-tumor immune regulation. Using single cell signatures, we deconvoluted large breast cancer cohorts to stratify them into nine clusters, termed ‘ecotypes’, with unique cellular compositions and clinical outcomes. This study provides a comprehensive transcriptional atlas of the cellular architecture of breast cancer.
2021-06-24 | GSE176078 | GEO
Project description:The recent development of spatial omics enables single-cell profiling of the transcriptome and the 3D organization of the genome in a spatially resolved manner. A spatial epigenomics method would expand the repertoire of spatial omics tools and accelerate our understanding of the spatial regulation of cellular processes and tissue functions. Here, we developed an imaging approach for spatially resolved profiling of epigenetic modifications in single cells
2022-12-16 | GSE191069 | GEO