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Series GSE85241 Query DataSets for GSE85241
Status Public on Oct 04, 2016
Title A single-cell transcriptome atlas of the human pancreas [CEL-seq2]
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary 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.
 
Contributor(s) Muraro MJ, Dharmadhikari G, de Koning E, van Oudenaarden A
Citation(s) 27693023
Submission date Aug 05, 2016
Last update date May 15, 2019
Contact name Mauro Muraro
E-mail(s) m.muraro@scdiscoveries.com
Organization name Single Cell Discoveries
Street address Uppsalalaan, 8
City Utrecht
State/province Utrecht
ZIP/Postal code 3584 CT
Country Netherlands
 
Platforms (1)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
Samples (32)
GSM2262792 Donor D28, live sorted cells, library 1
GSM2262793 Donor D28, live sorted cells, library 2
GSM2262794 Donor D28, live sorted cells, library 3
Relations
BioProject PRJNA337935
SRA SRP080991

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Supplementary file Size Download File type/resource
GSE85241_cel-seq_barcodes.csv.gz 424 b (ftp)(http) CSV
GSE85241_cellsystems_dataset_4donors_updated.csv.gz 16.2 Mb (ftp)(http) CSV
GSE85241_readme_demultiplexing_Cel-seq_data.pdf.gz 157.0 Kb (ftp)(http) PDF
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