Single-cell RNAseq of human pancreatic islets from control and type 2 diabetes donors
Perturbed secretion of insulin and other pancreatic hormones is the main cause of type 2 diabetes (T2D). The pancreatic islets harbor five cell types that are potentially altered differently by T2D. Whole-islet transcriptomics and single-cell RNA-sequencing (scRNAseq) studies have revealed differentially expressed genes but unfortunately without reaching consensus. We propose that, rather than analyzing expression of individual genes or structural changes in networks of genes, building and analyzing networks of differentially synchronized genes on single-cell level gives unprecedented insights to disease. To this end, we developed a differential gene synchronization network analysis (dGSNA) algorithm and used it to analyze a high-quality pancreatic islet scRNAseq dataset from T2D and non-T2D individuals. dGSNA on beta cells revealed T2D-induced changes in twelve networks of genes, representing both canonical and less studied biological processes in the context of T2D. Analysis of these networks suggested that in T2D, beta cell energy metabolism, cell growth, differentiation and proteolysis programs are perturbed, whereas exocytosis, insulin translation and the unfolded protein response programs instead are enhanced.  To validate our method, we showed that ten out of eleven selected node genes regulated insulin mRNA levels and/or secretion in INS-1 832/13 cells. Further, knockout mouse models for two of these genes (Tmem176a/b and Cebpg) exhibited reduced beta cell mass and perturbed insulin secretion. The dGSNA algorithm thus predicts central disease processes in T2D, which was replicated in an independent data set, revealing targetable cellular functions. We conclude that analysis of networks of differentially synchronized genes provides insight into the pathophysiology of T2D. This approach is likely generally applicable to other diseases where scRNAseq data can be obtained. Overall design: The single-cell transcriptome data (6 control and 5 type 2 diabetes human donors) was generated at the Eukaryotic Single-cell Genomics facility at Science for Life Laboratory in Stockholm, Sweden.