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Series GSE81076 Query DataSets for GSE81076
Status Public on Jun 24, 2016
Title A single-cell transcriptome atlas of the human pancreas
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary 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.
Contributor(s) Muraro MJ, Dharmadhikari G, Grün D, de Koning E, van Oudenaarden A
Citation(s) 27345837
Submission date May 03, 2016
Last update date May 15, 2019
Contact name Mauro Muraro
Organization name Single Cell Discoveries
Street address Uppsalalaan, 8
City Utrecht
State/province Utrecht
ZIP/Postal code 3584 CT
Country Netherlands
Platforms (2)
GPL16791 Illumina HiSeq 2500 (Homo sapiens)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
Samples (18)
GSM2142253 Donor number 10, CD63+ sorted cells
GSM2142254 Donor number 10, live sorted cells, library 1
GSM2142255 Donor number 10, live sorted cells, library 2
BioProject PRJNA320424
SRA SRP074299

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Supplementary file Size Download File type/resource
GSE81076_D2_3_7_10_17.txt.gz 5.3 Mb (ftp)(http) TXT
GSE81076_cel-seq_barcodes.csv.gz 424 b (ftp)(http) CSV
GSE81076_readme_demultiplexing_Cel-seq_data.rtf 57.1 Kb (ftp)(http) RTF
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