Homo sapiens
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: S-EPMC7033132E-GEOD-73727S-EPMC6602355
PROVIDER: PRJNA297774 | ENA |
REPOSITORIES: ENA
Dataset's files
primary
| Action | DRS | |||
|---|---|---|---|---|
| SRR2558120.fastq.gz | Fastqsanger.gz | |||
| SRR2558130.fastq.gz | Fastqsanger.gz | |||
| SRR2558140.fastq.gz | Fastqsanger.gz | |||
| SRR2558150.fastq.gz | Fastqsanger.gz | |||
| SRR2558160.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 72 |
Publications
Single-cell transcriptomes reveal characteristic features of human pancreatic islet cell types.
Li Jin J Klughammer Johanna J Farlik Matthias M Penz Thomas T Spittler Andreas A Barbieux Charlotte C Berishvili Ekaterine E Bock Christoph C Kubicek Stefan S
EMBO reports 20151221 2
Pancreatic islets of Langerhans contain several specialized endocrine cell types, which are commonly identified by the expression of single marker genes. However, the established marker genes cannot capture the complete spectrum of cellular heterogeneity in human pancreatic islets, and existing bulk transcriptome datasets provide averages across several cell populations. To dissect the cellular composition of the human pancreatic islet and to establish transcriptomes for all major cell types, we ...[more]
Similar Datasets
Project description:Human pluripotent stem cells (PSCs), including human embryonic stem cells and induced pluripotent stem cells, are promising cell sources in regenerating pancreatic islets through in vitro directed differentiation. Recent progress in this research field has made it possible to generate glucose-responsive pancreatic islet cells from PSCs. Single-cell RNA sequencing techniques have been applied to analyze PSC-derived endocrine beta-cells, which are then compared with human islets. This has led to the identification of novel signaling pathways and molecules involved in lineage commitment during pancreatic differentiation and maturation processes. Single-cell transcriptomics are also used to construct a detailed map of in vivo endocrine differentiation of developing mouse embryos to study pancreatic islet development. Mimicking those occurring in vivo, it was reported that differentiating PSCs can generate similar islet cell structures, while metabolomics analysis highlighted key components involved in PSC-derived pancreatic islet cell function, providing information for the improvement of in vitro pancreatic maturation procedures. In addition, cell transplantation into diabetic animal models, together with the cell delivery system, is studied to ensure the therapeutic potentials of PSC-derived pancreatic islet cells. Combined with gene-editing technology, the engineered mutation-corrected PSC lines originated from diabetes patients could be differentiated into functional pancreatic islet cells, suggesting possible autologous cell therapy in the future. These PSC-derived pancreatic islet cells are a potential tool for studies of disease modeling and drug testing. Herein, we outlined the directed differentiation procedures of PSC-derived pancreatic islet cells, novel findings through transcriptome and metabolome studies, and recent progress in disease modeling.
| S-EPMC7784351 | BioStudies
Project description:Pancreatic islets of Langerhans contain several specialized endocrine cell types, which are commonly identified by the expression of single marker genes. However, the established marker genes cannot capture the complete spectrum of cellular heterogeneity in human pancreatic islets, and existing bulk transcriptome datasets provide averages across several cell populations. To dissect the cellular composition of the human pancreatic islet and to establish transcriptomes for all major cell types, we performed single-cell RNA sequencing on 70 cells sorted from human primary tissue. We used this dataset to validate previously described marker genes at the single-cell level and to identify specifically expressed transcription factors for all islet cell subtypes. All data are available for browsing and download, thus establishing a useful resource of single-cell expression profiles for endocrine cells in human pancreatic islets.
| S-EPMC4784001 | BioStudies
Project description:The maintenance of pancreatic islet architecture is crucial for proper β-cell function. We previously reported that disruption of human islet integrity could result in altered β-cell identity. Here we combine β-cell lineage tracing and single-cell transcriptomics to investigate the mechanisms underlying this process in primary human islet cells. Using drug-induced ER stress and cytoskeleton modification models, we demonstrate that altering the islet structure triggers an unfolding protein response that causes the downregulation of β-cell maturity genes. Collectively, our findings illustrate the close relationship between endoplasmic reticulum homeostasis and β-cell phenotype, and strengthen the concept of altered β-cell identity as a mechanism underlying the loss of functional β-cell mass.
| S-EPMC8700697 | BioStudies
Project description:To understand organ (dys)function it is important to have a complete inventory of its cell types and the corresponding markers that unambiguously identify these cell types. This is a challenging task, in particular in human tissues, because unique cell-type markers are typically unavailable, necessitating the analysis of complex cell type mixtures. Transcriptome-wide studies on pancreatic tissue are typically done on pooled islet material. To overcome this challenge we sequenced the transcriptome of thousands of single pancreatic cells from deceased organ donors with and without type 2 diabetes (T2D) allowing in silico purification of the different cell types. We identified the major pancreatic cell types resulting in the identification of many new cell-type specific and T2D-specific markers. Additionally we observed several subpopulations within the canonical pancreatic cell types, which we validated in situ. This resource will be useful for developing a deeper understanding of pancreatic biology and diabetes mellitus. Human cadaveric pancreata were used to extract islets of Langerhans, which were kept in culture until single-cell dispersion and FACS sorting. Single-cell transcriptomics was performed on live cells from this mixture using CEL-seq or on cells stained for CD63, CD13, TGFBR3 or CD24 and CD44. The RaceID algorithm was used to identify clusters of cells corresponding to the major pancreatic cell types and to mine for novel cell type-specific genes as well as subpopulations within the known pancreatic cell types.
| E-GEOD-81076 | BioStudies
Project description:Pancreatic islets consist of several cell types, including alpha, beta, delta, epsilon, and PP cells. Due to cellular heterogeneity, it is challenging to interpret whole-islet transcriptome data. Single-cell transcriptomics offers a powerful method for investigating gene expression at the single-cell level and identifying cellular heterogeneity and subpopulations. Here, we describe a protocol for mouse pancreatic islet isolation, culturing, and dissociation into a single-cell suspension. This protocol yields highly viable cells for successful library preparation and single-cell RNA sequencing. For complete details on the use and execution of this protocol, please refer to Lee et al. (2020).
| S-EPMC7757316 | BioStudies
Project description:<h4>Background</h4>Human pancreatic islets are a central focus of research in metabolic studies. Transcriptomics is frequently used to interrogate alterations in cultured human islet cells using single-cell RNA-sequencing (scRNA-seq). We introduce single-nucleus RNA-sequencing (snRNA-seq) as an alternative approach for investigating transplanted human islets.<h4>Methods</h4>The Nuclei EZ protocol was used to obtain nuclear preparations from fresh and frozen human islet cells. Such preparations were first used to generate snRNA-seq datasets and compared to scRNA-seq output obtained from cells from the same donor. Finally, we employed snRNA-seq to obtain the transcriptomic profile of archived human islets engrafted in immunodeficient animals.<h4>Results</h4>We observed virtually complete concordance in identifying cell types and gene proportions as well as a strong association of global and islet cell type gene signatures between scRNA-seq and snRNA-seq applied to fresh and frozen cultured or transplanted human islet samples.<h4>Conclusions</h4>We propose snRNA-seq as a reliable strategy to probe transcriptomic profiles of freshly harvested or frozen sources of transplanted human islet cells especially when scRNA-seq is not ideal.
| S-EPMC8356387 | BioStudies
Project description:Improved stem cell-derived pancreatic islet (SC-islet) differentiation protocols robustly generate insulin-secreting β cells from patient induced pluripotent stem cells (iPSCs). These advances are enabling <i>in vitro</i> disease modeling studies and the development of an autologous diabetes cell replacement therapy. SC-islet technology elucidates key features of human pancreas development and diabetes disease progression through the generation of pancreatic progenitors, endocrine progenitors, and β cells derived from diabetic and nondiabetic iPSCs. Combining disease modeling with gene editing and next-generation sequencing reveals the impact of diabetes-causing mutations and diabetic phenotypes on multiple islet cell types. In addition, the supply of SC-islets, containing β and other islet cell types, is unlimited, presenting an opportunity for personalized medicine and overcoming several disadvantages posed by donor islets. This review highlights relevant studies involving iPSC-β cells and progenitors, encompassing new conclusions involving cells from patients with diabetes and the therapeutic potential of iPSC-β cells.
| S-EPMC8080107 | BioStudies
Project description:Blood glucose levels are tightly controlled by the coordinated action of at least four cell types constituting pancreatic islets. Changes in the proportion and/or function of these cells are associated with genetic and molecular pathophysiology of monogenic, type 1, and type 2 (T2D) diabetes. Cellular heterogeneity impedes precise understanding of the molecular components of each islet cell type that govern islet (dys)function, particularly the less abundant delta and gamma/pancreatic polypeptide (PP) cells. Here, we report single-cell transcriptomes for 638 cells from nondiabetic (ND) and T2D human islet samples. Analyses of ND single-cell transcriptomes identified distinct alpha, beta, delta, and PP/gamma cell-type signatures. Genes linked to rare and common forms of islet dysfunction and diabetes were expressed in the delta and PP/gamma cell types. Moreover, this study revealed that delta cells specifically express receptors that receive and coordinate systemic cues from the leptin, ghrelin, and dopamine signaling pathways implicating them as integrators of central and peripheral metabolic signals into the pancreatic islet. Finally, single-cell transcriptome profiling revealed genes differentially regulated between T2D and ND alpha, beta, and delta cells that were undetectable in paired whole islet analyses. This study thus identifies fundamental cell-type-specific features of pancreatic islet (dys)function and provides a critical resource for comprehensive understanding of islet biology and diabetes pathogenesis.
| S-EPMC5287227 | BioStudies
Project description:This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of alpha-cells (5%), beta-cells (92%), delta-cells (1%) and PP-cells (2%). We identified cell-type specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability (23%), low sequencing quality (13%) or contamination resulting in the detection of more than one islet hormone (64%). Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system. Single-cell RNA sequencing of mouse C57BL/6 pancreatic islet cells
| E-GEOD-77980 | BioStudies
Project description:This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells, allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of ?-cells (5%), ?-cells (92%), ?-cells (1%), and pancreatic polypeptide cells (2%). We identified cell-type-specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability, low sequencing quality, or contamination resulting in the detection of more than one islet hormone. Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system.
| S-EPMC4812709 | BioStudies