DiabetesGenomicsPeer-reviewed journal article
An integrated map of cell type-specific gene expression in pancreatic islets
Ruth M. ElgamaliD, Parul KudtarkariD, Rebecca L. MeltoniD, Hannah M MummeyiD, Paola Benaglio, Mei-Lin Okino, Kyle J. GaultoniD
Abstract
Pancreatic islets are comprised of multiple endocrine cell types that produce hormones required for glucose homeostasis, and islet dysfunction is a major factor in the development of type 1 and type 2 diabetes (T1D, T2D). Numerous studies have generated gene expression profiles in individual islet cell types using single cell assays. However, there is no canonical reference of gene expression in islet cell types in both health and disease that is also easily accessible for researchers to access, query, and use in bioinformatics pipelines. Here we present an integrated reference map of islet cell type-specific gene expression from 192,203 cells derived from single cell RNA-seq assays of 65 non-diabetic, T1D autoantibody positive (Aab+), T1D, and T2D donors from the Human Pancreas Analysis Program. We identified 10 endocrine and non-endocrine cell types as well as sub-populations of several cell types, and defined sets of marker genes for each cell type and sub-population. We tested for differential expression within each cell type in T1D Aab+, T1D, and T2D states, and identified 1,701 genes with significant changes in expression in any cell type. Most changes were observed in beta cells in T1D, and, by comparison, there were almost no genes with changes in T1D Aab+. To facilitate user interaction with this reference, we provide the data using several single cell visualization and reference mapping tools as well as open-access analytical pipelines used to create this reference. The results will serve as a valuable resource to investigators studying islet biology and diabetes.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 105
- FWCI
- 28.57
- Field percentile
- top 1%
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