A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure

By Maayan Baron, A. Veres, Samuel L. Wolock, Aubrey L. Faust, Renaud Gaujoux, A. Vetere, J. Ryu, B. Wagner, S. Shen-Orr, Allon M. Klein and 2 more. Cell Systems, 2016

1,337 citations recorded by the source corpus.

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.

Subfields: Genetics, Molecular Biology, Surgery

View Paper: https://www.semanticscholar.org/paper/25a15f29e54fad3b3451b13be3eed80e4888d486

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Citations in the corpus

Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq (2018, methodology): “We also analyzed a human pancreatic islet scRNA-Seq dataset where variability between four donors resulted in more substantial batch-effects to see how that would impact the behavior of cNMF (Baron et al., 2016).”
scDeepSort: a pre-trained cell-type annotation method for single-cell transcriptomics using deep learning with a weighted graph neural network (2021, methodology): “alpha, beta and delta cells) in the HCL pancreas dataset, another large human pancreas dataset (37) by Baron et al.”
A human cell atlas of fetal gene expression (2020, methodology): “” To test the applicability of Garnett trained models to future data, we applied the pancreas model to human adult pancreas scRNA-seq data from reference (100).”