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SRP202046
Mus musculus
58 Downloadable Samples
NextSeq 500
Description
Data accompaning to van Gurp et al. Development 2019. single-cell sequencing of the developing mouse pancreas followed by Seurat analysis to discover genes important for alpha and beta cell differentiation. Overall design: Single-cells from mouse embryonic pancreas at E12.5, E13.5, E14.5, E15.5 and E18.5 were isolated and enriched for MIP-GFP and sorted into 384-well plates. Afterwards, SORT-seq was performed and single-cell transcriptomics profiles were obtained.
Publication Title
A transcriptomic roadmap to α- and β-cell differentiation in the embryonic pancreas.
Sample Metadata Fields
Subject
View Samples- Homo sapiens
- 32 Downloadable Samples
- NextSeq 500
Description
To understand organ function it is important to have an inventory of the cell types present in the tissue and of the corresponding markers that identify them. This is a particularly challenging task for human tissues like the pancreas, since reliable markers are limited. Transcriptome-wide studies are typically done on pooled islets of Langerhans, which obscures contributions from rare cell types and/or potential subpopulations. To overcome this challenge, we developed an automated single-cell sequencing platform to sequence the transcriptome of thousands of single pancreatic cells from deceased organ donors, allowing in silico purification of all main pancreatic cell types. We identify cell type-specific transcription factors, a subpopulation of REG3A-positive acinar cells, and cell surface markers that allow sorting of live alpha and beta cells with high purity. This resource will be useful for developing a deeper understanding of pancreatic biology and pathophysiology of diabetes mellitus. Overall design: Islets of Langerhans were extracted from human cadaveric pancreata and kept in culture until single-cell dispersion and FACS sorting. Single-cell transcriptomics was performed on live cells from this mixture using an automated version of CEL-seq2 on live, FACS sorted cells. The StemID 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.
Publication Title
A Single-Cell Transcriptome Atlas of the Human Pancreas.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 18 Downloadable Samples
- Illumina HiSeq 2500, NextSeq 500
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. Overall design: 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.
Publication Title
De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data.
Sample Metadata Fields
Specimen part, Subject
View Samples- Mus musculus
- 13 Downloadable Samples
- NextSeq 500, Illumina HiSeq 2500
Description
Paneth cells (PCs) are long-lived secretory cells that reside at the bottoms of small intestinal crypts. Besides serving as niche cells for the neighboring Lgr5-positive stem cells, PCs secrete granules containing a broad spectrum of antimicrobial proteins, including lysozymes and defensins1. Here, we have used single-cell RNA sequencing to explore PC differentiation. We found a maturation gradient from early secretory progenitors to mature PCs, capturing the full maturation path of PCs. Moreover, differential expression of a subset of defensin genes in lysozyme-high PCs, e.g. Defa20, reveals at least two distinct stages of maturation. Overall design: We traced Lgr5+ stem cells from Lgr5-CreERT2 C57Bl6/J mice bred to a Rosa26LSL-YFP reporter mice and sorted YFP+ cells 5 days, 3 weeks and 8 weeks after tamoxifen injection.
Publication Title
De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data.
Sample Metadata Fields
Specimen part, Cell line, Subject
View Samples- Populus tremula x populus alba
- 10 Downloadable Samples
Affymetrix Poplar Genome Array (poplar)
Description
Regeneration of transgenic cells remains a major obstacle to research and commercial deployment of transgenic plants for most species.
Publication Title
Genome scale transcriptome analysis of shoot organogenesis in Populus.
Sample Metadata Fields
Sex
View Samples- Homo sapiens
- 50 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
Expression profile of human donor lungs that have developed primary graft dysfunction (PGD) after lung transplantation and those that have not.
Publication Title
Expression profiling of human donor lungs to understand primary graft dysfunction after lung transplantation.
Sample Metadata Fields
No sample metadata fields
View Samples- Oryza sativa
- 78 Downloadable Samples
- Affymetrix Rice Genome Array (rice)
Description
Rice (Oryza sativa, ssp. Japonica, cv. Nipponbare 1) plants were grown in a Conviron PGR 15 growth chamber using precise control of temperature, light, and humidity.<br></br>Diurnal (driven) conditions included 12L:12D light cycles and 31C/20C thermocycles in three different combinations. These were: photocycles (LDHH), 12 hrs. light (L)/12 hrs. dark (D) at a constant temperature (31C; HH); photo/thermocycles (LDHC): 12 hrs. light (L) /12 hrs. dark (D) with a high day temperature (31C) and a low night temperature (20C); and thermocycles (LLHC): continuous light (LL) with 12 hrs. high/12 hrs. low temperature (31C, day; 20C, night). Light intensity and relative humidity were 1000 micromol m-2s-2 and 60%, respectively.<br></br>Three-month-old rice plants were entrained for at least one week under the respective condition prior to initiation of each experiment. Leaves and stems from individual rice plants were collected every four hours for 48 hrs in driven (diurnal) conditions followed by a two day freerun spacer under continuous light/temperature followed by two additional days of sampling under the same continuous free run condition.<br></br>
Publication Title
Global profiling of rice and poplar transcriptomes highlights key conserved circadian-controlled pathways and cis-regulatory modules.
Sample Metadata Fields
Age, Specimen part, Time
View Samples- Oryza sativa
- 37 Downloadable Samples
- Affymetrix Rice Genome Array (rice)
Description
Rice (Oryza sativa, spp. Indica, cv. 93-11) plants were grown in a Conviron PGR 15 growth chamber using precise control of temperature, light, and humidity.<br></br>Diurnal (driven) conditions included 12L:12D light cycles and 31C/20C thermocycles in three different combinations. These were: photocycles (LDHH), 12 hrs. light (L)/12 hrs. dark (D) at a constant temperature (31C; HH); photo/thermocycles (LDHC): 12 hrs. light (L) /12 hrs. dark (D) with a high day temperature (31C) and a low night temperature (20C); and thermocycles (LLHC): continuous light (LL) with 12 hrs. high/12 hrs. low temperature (31C, day; 20C, night). Light intensity and relative humidity were 1000 micromol m-2s-2 and 60%, respectively.<br></br>Three-month-old rice plants were entrained for at least one week under the respective condition prior to initiation of each experiment. Leaves and stems from individual rice plants were collected every four hours for 48 hrs in driven (diurnal) conditions followed by a two day freerun spacer under continuous light/temperature followed by two additional days of sampling under the same continuous free run condition.
Publication Title
Global profiling of rice and poplar transcriptomes highlights key conserved circadian-controlled pathways and cis-regulatory modules.
Sample Metadata Fields
Age, Specimen part, Time
View Samples- Mus musculus
- 4 Downloadable Samples
- Illumina HiSeq 2000
Description
Expression profiling of resting B cells to classify active and silent genes based on expression levels Overall design: 4 biological replicates of mRNA extracted from freshly purified mouse CD43 negative resting B cells
Publication Title
The aurora B kinase and the polycomb protein ring1B combine to regulate active promoters in quiescent lymphocytes.
Sample Metadata Fields
Specimen part, Cell line, Subject
View Samples- Mus musculus
- 12 Downloadable Samples
- Illumina HiSeq 4000
Description
Purpose:We have the first-reported set of glial-specific transcripts utilizing the Ribotag model. We use this model to explore glial changes in DNBS-induced inflammation and neurokinin-2 receptor (NK2R) antagonism. Methods: Actively translated mRNA profiles of the distal colon myeneteric plexi of Rpl22(+/-)Sox10(+/-) male and female mice 8-10 weeks old were obtained utilizing the HA-tagged ribosomal immunoprecipitation and downstream RNA extraction. Samples meeting RNA quality standards by 18S and 28S rRNA peaks by 2100 Bioanalyzer and RNA 6000 Nano LabChip Kit (Agilent) were deep sequenced with the Illumina HiSeq 4000. Results: We mapped approximately 30-50 millions reads per sample to the mouse genome (v88) and identified approximately 100K ribosome-associated transcripts, with Tuxedo workflow, in distal colon glial cells with DNBS-induced inflammation and NK2R antagonism and their respective controls. Of these transcripts, changes in biological processes associated with inflammation and other important enteric nervous system communications between samples have been identified. Conclusions: Our study demonstrates the first use of the Ribotag model to provide glial cell-specific actively-translated mRNA changes in DNBS-induced inflammation with and without functional NK2R signalling. Overall design: Distal colon glial mRNA samples from Ribotag Rpl22(+/-)Sox10(+/-) mice administered either saline or DNBS and DMSO vehicle or NK2R antagonism.
Publication Title
Communication Between Enteric Neurons, Glia, and Nociceptors Underlies the Effects of Tachykinins on Neuroinflammation.
Sample Metadata Fields
Sex, Specimen part, Cell line, Subject
View Samples