Navigating the Depths and Avoiding the Shallows of Pancreatic Islet Cell Transcriptomes.

Islet gene expression has been widely studied to better understand the transcriptional features that define a healthy ß-cell. Transcriptomes of FACS-purified α-, ß-, and δ-cells using bulk RNA-sequencing have facilitated our understanding of the complex network of cross talk between islet cells and its effects on ß-cell function. However, these approaches were by design not intended to resolve heterogeneity between individual cells. Several recent studies used single-cell RNA sequencing (scRNA-Seq) to report considerable heterogeneity within mouse and human ß-cells. In this Perspective, we assess how this newfound ability to assess gene expression at single-cell resolution has enhanced our understanding of ß-cell heterogeneity. We conduct a comprehensive assessment of several single human ß-cell transcriptome data sets and ask if the heterogeneity reported by these studies showed overlap and concurred with previously known examples of ß-cell heterogeneity. We also illustrate the impact of the inevitable limitations of working at or below the limit of detection of gene expression at single cell resolution and their consequences for the quality of single-islet cell transcriptome data. Finally, we offer some guidance on when to opt for scRNA-Seq and when bulk sequencing approaches may be better suited.