Transcriptomes of the major human pancreatic cell types

Abstract

Aims/hypothesis We sought to determine the mRNA transcriptome of all major human pancreatic endocrine and exocrine cell subtypes, including human alpha, beta, duct and acinar cells. In addition, we identified the cell type-specific distribution of transcription factors, signalling ligands and their receptors. Methods Islet samples from healthy human donors were enzymatically dispersed to single cells and labelled with cell type-specific surface-reactive antibodies. Live endocrine and exocrine cell subpopulations were isolated by FACS and gene expression analyses were performed using microarray analysis and quantitative RT-PCR. Computational tools were used to evaluate receptor–ligand representation in these populations. Results Analysis of the transcriptomes of alpha, beta, large duct, small duct and acinar cells revealed previously unrecognised gene expression patterns in these cell types, including transcriptional regulators HOPX and HDAC9 in the human beta cell population. The abundance of some regulatory proteins was different from that reported in mouse tissue. For example, v-maf musculoaponeurotic fibrosarcoma oncogene homologue B (avian) (MAFB) was detected at equal levels in adult human alpha and beta cells, but is absent from adult mouse beta cells. Analysis of ligand–receptor interactions suggested that EPH receptor–ephrin communication between exocrine and endocrine cells contributes to pancreatic function. Conclusions/interpretation This is the first comprehensive analysis of the transcriptomes of human exocrine and endocrine pancreatic cell types—including beta cells—and provides a useful resource for diabetes research. In addition, paracrine signalling pathways within the pancreas are shown. These results will help guide efforts to specify human beta cell fate by embryonic stem cell or induced pluripotent stem cell differentiation or genetic reprogramming.

Cell-type, allelic, and genetic signatures in the human pancreatic beta cell transcriptome

“…This approach successfully filters out highly expressed genes in contaminating cell types (e.g., SST, GCG from somatostatin, and glucagon cells contaminating the beta cell population), otherwise mistaken as key players in the expression signature of beta cells. In addition to known beta-cell-specific transcripts (INS, IGF2, PDX1) we highlight further targets, some featured already in a microarray analysis of sorted islet cells (Dorrell et al 2011b), e.g., RGS16, negative regulator of G-protein signaling, involved in endocrine pancreas development and re-expressed in adult cells in response to GLP-1 (Villasenor et al 2010); ADCYAP1, pituitary adenylate cyclase activating polypeptide 1, involved in insulin secretion and beta cell regeneration/proliferation (Sakurai et al 2011); HADH, hydroxyacyl-CoA dehydrogenase, negative regulator of insulin secretion (Hardy et al 2007) associated with Alzheimer's (Nicolls et al 2003), which is in turn associated with diabetes. Many other genes however have not been described before in the context of beta cells, including: NPTX2, neuronal pentraxin 2, found in neuronal cells and gliomas but also shown to be frequently downregulated in pancreatic cancers (Zhang et al 2012); TSPAN1, tetraspanin 1, which can associate with alpha6.beta1 integrin and promote FAK phosphorylation (Huang et al 2008) shown by us to be involved in insulin secretion (Rondas et al 2011); GPM6A, neuronal membrane glycoprotein of unknown function but identified as a beta cell marker in sorted mouse islet cells (Dorrell et al 2011a); BMP5, bone morphogenic protein 5, implicated in pancreas and fetal beta cell development ( Jiang et al 2002); and P2RY1, purinergic receptor through which ADP and ATP modulate insulin secretion (Fernandez-Alvarez et al 2001).…”

End Sequence Analysis Toolkit (ESAT) expands the extractable information from single-cell RNA-seq data

“…This system is ideal for two reasons. First, all previous descriptions of islet composition have relied on known markers of cells (Pechhold et al 2009;Dorrell et al 2011;Hrvatin et al 2014;Blodgett et al 2015) or sequenced a relatively small number of cells (70) . inDrop allows the profiling of thousands of cells, and hence, rare cell populations of even <1% are likely to be well represented.…”

Genetic Drivers of Pancreatic Islet Function

“…The greenyellow module consists of 387 transcripts, including Gcg, Irx1,Irx2,Arx,Mafb,Ttr, Gria3 and Sstr2. These transcripts have been previously associated with selective expression in α-cells (DORRELL et al 2011;ACKERMANN et al 2016;DIGRUCCIO et al 2016;XIN et al 2016;LAWLOR et al 2017). The yellowgreen module contains 109 transcripts, including many that have been linked to selective expression in δ-cells; Sst, Hhex, Rbp4 and Ghsr (DORRELL et al 2011;ACKERMANN et al 2016;DIGRUCCIO et al 2016;XIN et al 2016;LAWLOR et al 2017).…”