Tissue Type(s): Pancreas 

Contributed by: Rickard Sandberg, Department of Cell and Molecular Biology (CMB), Karolinska Institutet, Integrated Cardio Metabolic Center (ICMC), Karolinska Institutet, Ludwig Institute for Cancer Research

Manuscript: Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells (https://www.biorxiv.org/content/10.1101/2020.04.19.049254v1)

Description: This study allows one to visualize and query genes as well as explore cell types, technical batches, and cell metrics associated with the manuscript. If published, this version of the data set is focused on the manuscript and is a subset of what may be made available by the original manuscript.

Original Publication: Segerstolpe, Åsa, et al. "Single-cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes." Cell metabolism 24.4 (2016): 593-607.

Full dataset: Raw data (Fastq files) for single-cell and whole-islet RNA-seq were submitted to ArrayExpress (EBI) using accession numbers ArrayExpress: E-MTAB-5061 and E-MTAB-5060, respectively. Relevant processed data is shared here in the downloads tab.

Abstract: Hormone-secreting cells within pancreatic islets of Langerhans play important roles in metabolic homeostasis and disease. However, their transcriptional characterization is still incomplete. Here, we sequenced the transcriptomes of thousands of human islet cells from healthy and type 2 diabetic donors. We could define specific genetic programs for each individual endocrine and exocrine cell type, even for rare δ, γ, ε, and stellate cells, and revealed subpopulations of α, β, and acinar cells. Intriguingly, δ cells expressed several important receptors, indicating an unrecognized importance of these cells in integrating paracrine and systemic metabolic signals. Genes previously associated with obesity or diabetes were found to correlate with BMI. Finally, comparing healthy and T2D transcriptomes in a cell-type resolved manner uncovered candidates for future functional studies. Altogether, our analyses demonstrate the utility of the generated single-cell gene expression resource.