A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure
Although the function of the mammalian pancreas hinges on complex interactions of distinct cell types, gene expression profiles have primarily been described with bulk mixtures. Here we implemented a droplet-based, single-cell RNA-seq method to determine the transcriptomes of over 12,000 individual...
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Published in | Cell systems Vol. 3; no. 4; pp. 346 - 360.e4 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
26.10.2016
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Subjects | |
Online Access | Get full text |
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Summary: | Although the function of the mammalian pancreas hinges on complex interactions of distinct cell types, gene expression profiles have primarily been described with bulk mixtures. Here we implemented a droplet-based, single-cell RNA-seq method 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. We detected subpopulations of ductal cells with distinct expression profiles and validated their existence with immuno-histochemistry stains. Moreover, among human beta- cells, we detected heterogeneity in the regulation of genes relating to functional maturation and levels of ER stress. Finally, we deconvolved bulk gene expression samples using the single-cell data to detect disease-associated differential expression. Our dataset provides a resource for the discovery of novel cell type-specific transcription factors, signaling receptors, and medically relevant genes.
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•We report over 12,000 individual pancreatic cell transcriptomes in human and mouse•We detect novel expression of TFs, signaling receptors, and medically relevant genes•We identify subpopulations and heterogeneity within pancreatic cell types•We deconvolve bulk gene expression samples using the single-cell data
Single-cell transcriptomics of over 12,000 cells from four human donors and two mouse strains was determined using inDrop. Cells were divided into 15 clusters that matched previously characterized cell types. Detailed analysis of each population separately revealed subpopulations within the ductal population, modes of activation of stellate cells, and heterogeneity in the stress among beta cells. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Lead Contact Present address: Institute for Computational Medicine, New York University School of Medicine, New York, NY 10016, USA Co-first author |
ISSN: | 2405-4712 2405-4720 |
DOI: | 10.1016/j.cels.2016.08.011 |