single-cell RNA-seq method is used to determine the transcriptomes of over 12,000 individual pancreatic cells from four human donors and two mouse strains. Cells could be divided into 15 clusters that matched previously characterized cell types: all endocrine cell types, including rare epsilon-cells; exocrine cell types; vascular cells; Schwann cells; quiescent and activated stellate cells; and four types of immune cells. Subpopulations of ductal cells with distinct expression profiles were detected and validated their existence with immuno-histochemistry stains. In human beta- cells, heterogeneity in the regulation of genes relating to functional maturation and levels of ER stress were detected. Finally , bulk gene expression samples using the single-cell data to detect disease-associated differential expression were deconvoluted. The dataset provides a resource for the discovery of novel cell type-specific transcription factors, signaling receptors, and medically relevant genes.
Content Source : https://www.ncbi.nlm.nih.gov/pubmed/27667365
Acknowledgements:
Data Source Credit :
https://hemberg-lab.github.io/scRNA.seq.datasets/human/pancreas/
Research Paper :
A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure.
https://www.ncbi.nlm.nih.gov/pubmed/27667365