Ontology highlight
ABSTRACT:
PROVIDER: PRJNA487961 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq
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Project description:Highly multiplexed single-cell quantitative PCR
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Project description:Epithelial-mesenchymal plasticity contributes to a variety of biological processes, including tumour progression. A variety of epithelial-mesenchymal transition (EMT) responses have been reported and no common, EMT-defining gene expression program has been identified. Here, we have performed a comparative analysis of the EMT response, leveraging highly multiplexed single-cell RNA sequencing (scRNA-seq) to measure expression profiles of 103,999 cells from 960 samples, comprising 12 EMT time course experiments and independent kinase inhibitor screens for each.
2020-03-24 | GSE147405 | GEO
Project description:Spatially resolved, highly multiplexed RNA profiling in single cells
| PRJNA280631 | ENA
Project description:Characterization of the single-cell transcriptional landscape by highly multiplex RNA-Seq
| PRJNA126555 | ENA
Project description:Plasmacytoid dendritic cells [pDCs] represent a rare innate immune subset uniquely endowed with the capacity to produce substantial amounts of type-I interferons [IFN-I]. This function of pDCs is critical for effective antiviral defenses and has been implicated in autoimmunity. While IFN-I and select cytokines have been recognized as pDC secreted products, a comprehensive agnostic profiling of the pDC secretome in response to a physiologic stimulus has not been reported. We applied LC-MS/MS to catalogue the repertoire of proteins secreted by pDCs in response to challenge with live influenza H1N1. Additionally, using single-cell RNA-seq [scRNA-seq], we perform multidimensional analyses of pDC transcriptional diversification following stimulation. Our data reveal an abundance of protein species released by pDCs in addition to IFN-I, and evidence highly specialized roles within the pDC population ranging from dedicated cytokine super-producers to cells with APC-like functions. Moreover, dynamic expression of transcription factors and surface markers characterize activated pDC fates.
2021-11-12 | MSV000088375 | MassIVE
Project description:Highly-multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific markers is challenging. To overcome this obstacle, we have developed an approach for enriching mIHC images with single-cell RNA-seq data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements. Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA) performs transcriptome-guided annotation of highly-multiplexed cytometry datasets. It increases the level of detail in histological analyses by enabling annotation of subtle cell populations, spatial patterns of transcription, and interactions between cell types. More generally, it enables the systematic annotation of cell populations in cytometry data. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published highly-multiplexed cytometry and mIHC data.
2021-03-23 | GSE160766 | GEO
Project description:Background: We reasoned that unraveling the dynamic changes in accessibility of genomic regulatory elements and gene expression at single-cell resolution will inform the basic mechanisms of nephrogenesis. Methods: We performed single-cell ATAC-seq and RNA-seq both individually (Singleomes; Six2GFP cells) and jointly in the same cells (Multiomes; kidneys) to generate integrated chromatin and transcriptional maps in mouse embryonic and neonatal nephron progenitor cells (NPCs). Results: We demonstrate that singleomes and multiomes are comparable in assigning most cell states, identification of new cell type markers, and defining the transcription factors driving cell identity. However, multiomes are more precise in defining the progenitor population. Multiomes identified a “pioneer” bHLH/Fox motif signature in NPCs. Moreover, we identified a subset of Fox factors exhibiting high chromatin activity in podocytes. One of these Fox factors, Foxp1, is important for nephrogenesis. Key nephrogenic factors are distinguished by strong correlation between linked gene-regulatory elements and gene expression. Conclusion: Mapping the regulatory landscape at single-cell resolution informs the regulatory hierarchy of nephrogenesis. Paired single-cell epigenomes and transcriptomes of nephron progenitors should provide a foundation to understand prenatal programming, regeneration following injury, and ex vivo nephrogenesis.
2022-04-01 | GSE199928 | GEO
Project description:<p>Follicular lymphoma (FL) is a generally incurable B-cell malignancy which has the potential to transform into highly aggressive lymphomas. Genomic studies indicate it is often a small subpopulation rather than the dominant population in the FL that gives rise to the more aggressive subtype. To resolve the underlying transcriptional networks of follicular B-cell lymphomas at single molecule and cell resolution, we leveraged droplet-based barcoding technology for highly parallel single cell RNA-Seq. We analyzed the transcriptomes from tens of thousands of cells derived from five primary FL tumors. Simultaneously, we conducted multi-dimensional flow cell sorting to validate our characterizing of cellular lineages and critical expressed proteins. For each tumor, we identified multiple cellular subpopulations, matching known hematopoietic lineages. Comparison of gene expression by matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC class II genes. By leveraging the single-cell resolution on large numbers of cells per patient, we were able to examine tumor-resident T cells. We identified pairs of immune checkpoint molecules that were co-expressed, providing a potentially useful strategy for selection of patient-tailored combination immunotherapies. In summary, massively parallel measurement of single-cell expression in thousands of tumor cells and tumor-resident lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.</p>
| phs001378 | dbGaP
Project description:Defining the Transcriptional Landscape during Cytomegalovirus Latency with Single-Cell RNA Sequencing
| PRJNA394123 | ENA