Mouse Pancreatic Endocrine Cell Transcriptome Defined in the Embryonic Ngn3-Null Mouse

OBJECTIVE—To document the transcriptome of the pancreatic islet during the early and late development of the mouse pancreas and highlight the qualitative and quantitative features of gene expression that contribute to the specification, growth, and differentiation of the major endocrine cell types. A further objective was to identify endocrine cell biomarkers, targets of diabetic autoimmunity, and regulatory pathways underlying islet responses to physiological and pathological stimuli. RESEARCH DESIGN AND METHODS—mRNA expression profiling was performed by microarray analysis of e12.5–18.5 embryonic pancreas from neurogenin 3 (Ngn3)-null mice, a background that abrogates endocrine pancreatic differentiation. The intersection of this data with mRNA expression in isolated adult pancreatic islets and pancreatic endocrine tumor cell lines was determined to compile lists of genes that are specifically expressed in endocrine cells. RESULTS—The data provided insight into the transcriptional and morphogenetic factors that may play major roles in patterning and differentiation of the endocrine lineage before and during the secondary transition of endocrine development, as well as genes that control the glucose responsiveness of the β-cells and candidate diabetes autoantigens, such as insulin, IA-2 and Slc30a8 (ZnT8). The results are presented as downloadable gene lists, available at https://www.cbil.upenn.edu/RADQuerier/php/displayStudy.php?study_id=1330, stratified by predictive scores of relative cell-type specificity. CONCLUSIONS—The deposited data provide a rich resource that can be used to address diverse questions related to islet developmental and cell biology and the pathogenesis of type 1 and 2 diabetes.

T he major endocrine and exocrine cell types of the pancreas share a common embryological origin from the foregut endoderm and possess common phenotypic characteristics related to the regulated secretion of polypeptides (1). Microarraybased gene expression analysis of the genes that are related by ontology and common pathways of metabolism and signaling (2)(3)(4) in the tissue is hampered by difficulty of separating endocrine from exocrine tissue at early embryological ages except by laborious procedures based on cell sorting that may distort the expression profiles. An alternative approach adopted here is to compare gene expression in fetal pancreas from E12.5-18.5 from wildtype and neurogenin 3 (Ngn3) knockout (Ϫ/Ϫ) mice: animals in which the ductal and exocrine programs proceed normally but islet endocrine cells fail to develop (5). Ngn3 is expressed transiently around E14.5 in a small population of endocrine progenitor cells (6), and Ngn3 Ϫ/Ϫ mice fail to express key islet transcription factors Isl1, Pax4, Pax6, and NeuroD1 (5). Nevertheless, pancreatic exocrine cell lineage is correctly specified through the expression of Ptf1a and Prox1, and only minor changes in acinar cellular polarity and zymogen granule accumulation occur (5).
Data expression profiles from pancreata of Ngn3 Ϫ/Ϫ versus wild-type animals were compared with normal adult mouse pancreatic islets and islet-derived tumor cell lines (7) to provide information on endocrine cell-type specificity of genes that are downregulated in Ngn3 Ϫ/Ϫ animals. The example of Slc30a8 (ZnT8), a gene that has been associated with type 2 diabetes (8) and that encodes a type 1 diabetes autoantigen (9) is highlighted.
Data were analyzed with GeneSpring 7.2 (Silicon Genetics, Redwood City, CA) and GC Robust Multi-array Average (GC RMA) used for normalization. ANOVA was applied to cell line data, and P values were corrected by Benjamini and Hochberg's procedure. P Ͻ 0.05 were considered significant. NetAffx (Affymetrix, Santa Clara, CA; http://www.affymetrix.com/analysis/ index.affx) was used to extract a common probe set between MOE430 2.0 and MGU74Av2 platforms. Gene classification was performed with FatiGO (http:// fatigo.bioinfo.cipf.es).
Quantitative RT-PCR (qRT-PCR) was performed on cDNA (5 ng) derived from total RNA by iScript cDNA synthesis kits (Bio-Rad Laboratories, Hercules, CA). Assays used FAM dye-labeled Taqman MGB probes and an ABI 7000 PCR instrument (Applied Biosystems, Foster City, CA) and were normalized to glyceraldehyde-3-phosphate dehydrogenase. Triplicate cycle threshold values were normalized to samples.

18-fold) were readily detectable in wild-type but not
Ngn3 Ϫ/Ϫ animals with 40 cycles of PCR (data not shown). Of the transcripts that were downregulated Ͼfourfold, 46 mapped to transcripts highly expressed in adult islets (raw value Ͼ2,000 including ZnT8) and 28 to transcripts moderately expressed (500 -2,000) ( Table 2).
Comparison of ␣TC1.6and ␤TC3-cell transcripts identified 1,554 transcripts that were Ͼ2-fold enriched in ␤TC3 versus ␣TC1.6 and 403 that were Ͼ10-fold enriched (supplementary Table 5). Conversely, 1,202 transcripts were Ͼ2-fold enriched in ␣TC1.6versus ␤TC3-cell lines and 212 Ͼ10-fold (supplementary Table 6). Of the genes downregulated Ͼfivefold in the Ngn3 Ϫ/Ϫ mice, 74 were enriched in ␣TC-cells and 108 in ␤TC-cell lines (supplementary Tables  7 and 8). Another 1,396 transcripts were expressed in both ␣TCand ␤TC-cell lines and 774 not detected. qRT-PCR analyses of islets and cell lines (Fig. 1A-F) showed that insulin transcripts were enriched in adult islets versus ␤TCand not expressed in ␣TCor mPAC-cell lines (Fig.  1D). By microarray analysis, insulin expression in islets and ␤-cell lines did not differ since signals were saturated (Ͼ25,000 arbitrary units). Glucagon transcript levels by qRTPCR were higher in islets than in ␣TC-cells and present at a low level in ␤TC3and MIN6-cells but absent in mPAC-cells (Fig. 1E). By microarray analysis, the glucagon signals saturated in islets and ␣TC-cells but otherwise showed the same trend of expression. ZnT8 transcript levels by qRTPCR were 4-to 5-fold higher in ␤-cell lines than in ␣TC1.6-cells and 50-to 100-fold higher than in ductal cells (Fig. 1F). Microarray analysis showed ZnT8 expression in islets and ␣and ␤-cell lines but not in ductal cells.
Immunohistochemical localization of ZnT8 in wild-type adult pancreas showed its expression in the majority of islet cells and absence in acinar and ductal tissue. It was principally colocalized with insulin and also found in a subpopulation of somatostatin-positive cells. Expression in ␣-cells was not detectable (Fig. 2). E18.5 Ngn3 Ϫ/Ϫ pancreas tissue did not show any ZnT8, insulin, glucagon, or somatostatin expression (data not shown).

DISCUSSION
The loss of expression of genes in the pancreas of Ngn3 Ϫ/Ϫ mice provides a model to define the transcriptome of the endocrine pancreas and offers insight into the transcriptional and morphogenetic factors responsible for the patterning and differentiation of the endocrine lineage. Genes responsive to paracrine signaling from endocrine cells adjacent to exocrine or ductal cells might also have been revealed, although there was little evidence of this. As previously observed (5), expression of the pancreatic islet hormones (insulin, glucagon, somatostatin, pancreatic polypeptide, and ghrelin) were markedly diminished alongside genes known to be expressed in islets but not in acinar tissue (IAPP, ChgrA, ChgrB, Npy, Pyy, PCSK1, PCSK2, and IGRP/G6pc2). Several candidate transcriptional regulators of islet cell lineage development were likewise absent (NeuroD, MafB, Insm1, Myt1, Pax6, and Isl1).
At E12.5, there are a few endocrine cells that are immunoreactive to glucagon and occasional insulin and glucagon double-positive cells. During this phase, Robo1 (Dutt1 protein, orthologous to the Drosophila roundabout) and an expressed sequence tag 9430047L24Rik encoding Unc5c homolog are the two most endocrineenriched transcripts. Robo1 encodes a molecule of the neural-cell adhesion molecule family that interacts with the extracellular ligand Slit (13-15) that has been implicated in migration of axons, myoblasts, and leukocytes in vertebrates and in lung development (16).
At the time of the secondary transition, Ngn3 Ϫ/Ϫ -downregulated transcripts are likely to reflect specific transcripts of the immediate precursors of endocrine cells and thus overlap with profiles derived from fluorescenceactivated cell sorter-sorted Ngn3-enhanced green fluorescent protein ϩ cells (supplementary Tables 9 and 10 The above microarray datasets can be downloaded from an open access Web site: http://www.cbil.upenn.edu/RAD/ php/displayStudy.php?study_idϭ1330. While the current study focuses on embryological development of the pancreas, these datasets can potentially be analyzed in other ways to provide an understanding of islet function in health and disease. Given the current interest in identifying biomarkers that could be used to isolate ␤-cells and their precursors or to image islet mass, it was of interest to review how effective the selection criteria used here to ascertain ␤-cell specificity would be in identifying a ␤-cell marker of lower abundance. The example is the insulin granule zinc transporter ZnT8 (Slc30a8), a type 1A diabetes autoantigen (9) and a gene associated with type 2 diabetes susceptibility (8). ZnT8 transcripts were decreased 18-fold in Ngn3 Ϫ/Ϫ mice pancreas at E18.5 (Table  2), in ␤TC3and MIN6-cells, and to a lesser extent in ␣TC-cells ( Fig. 1A and F) but not in a mouse pancreatic ductal cell line (mPAC). Immunofluorescence microscopy showed colocalization with insulin and with a minor islet cell population that coincides with the ␦-cell. A lower level of expression in the ␣-cell was indicated by qRTPCR and other studies (22) but could not be confirmed by immunohistochemistry. A similar strategy could apply the current datasets for the discovery of novel regulatory processes involved in islet metabolism, stimulus secretion coupling, gene transcription, and intracellular and intracellular signaling.