Background Digestion is facilitated by coordinated contractions of the intestinal muscularis externa, a bilayered smooth muscle structure that is composed of inner circular (ICM) and outer longitudinal (OLM) muscles. We performed transcriptome analysis of intestinal mesenchyme tissue at E14.5, when the ICM, but not the OLM is present, to investigate the transcriptional program of the ICM. Results We identified 3967 genes enriched in E14.5 intestinal mesenchyme. The gene expression profiles were clustered and annotated to known muscle genes, identifying a muscle- enriched subcluster. Using publically available in situ data, 127 genes were verified as expressed in ICM. Examination of the promoter and regulatory regions for these co-expressed genes revealed enrichment for cJUN transcription factor binding sites and cJUN protein was enriched in ICM. cJUN ChIP-seq, performed at E14.5, revealed that cJUN regulatory regions contain characteristics of muscle enhancers. Finally, we show that cJUN is a target of Hedgehog (Hh), a signaling pathway known to be important in smooth muscle development, and identify a cJUN genomic enhancer that is responsive to Hh. Conclusions This work provides the first transcriptional catalog for the developing ICM and suggests that cJUN regulates gene expression in the ICM downstream of Hh signaling.
BackgroundThe Hedgehog (Hh) signaling pathway, acting through three homologous transcription factors (GLI1, GLI2, GLI3) in vertebrates, plays multiple roles in embryonic organ development and adult tissue homeostasis. At the level of the genome, GLI factors bind to specific motifs in enhancers, some of which are hundreds of kilobases removed from the gene promoter. These enhancers integrate the Hh signal in a context-specific manner to control the spatiotemporal pattern of target gene expression. Importantly, a number of genes that encode Hh pathway molecules are themselves targets of Hh signaling, allowing pathway regulation by an intricate balance of feed-back activation and inhibition. However, surprisingly few of the critical enhancer elements that control these pathway target genes have been identified despite the fact that such elements are central determinants of Hh signaling activity. Recently, ChIP studies have been carried out in multiple tissue contexts using mouse models carrying FLAG-tagged GLI proteins (GLIFLAG). Using these datasets, we tested whether a meta-analysis of GLI binding sites, coupled with a machine learning approach, could reveal genomic features that could be used to empirically identify Hh-regulated enhancers linked to loci of the Hh signaling pathway.ResultsA meta-analysis of four existing GLIFLAG datasets revealed a library of GLI binding motifs that was substantially more restricted than the potential sites predicted by previous in vitro binding studies. A machine learning method (kmer-SVM) was then applied to these datasets and enriched k-mers were identified that, when applied to the mouse genome, predicted as many as 37,000 potential Hh enhancers. For functional analysis, we selected nine regions which were annotated to putative Hh pathway molecules and found that seven exhibited GLI-dependent activity, indicating that they are directly regulated by Hh signaling (78 % success rate).ConclusionsThe results suggest that Hh enhancer regions share common sequence features. The kmer-SVM machine learning approach identifies those features and can successfully predict functional Hh regulatory regions in genomic DNA surrounding Hh pathway molecules and likely, other Hh targets. Additionally, the library of enriched GLI binding motifs that we have identified may allow improved identification of functional GLI binding sites.Electronic supplementary materialThe online version of this article (doi:10.1186/s12861-016-0106-0) contains supplementary material, which is available to authorized users.
Genetic knockout studies in mice concluded that the differentiation of endocrine lineages in the pancreas and intestine requires the transcription factor neurogenin3 (NGN3). However, case reports of patients with NGN3 mutations show that most patients do not develop diabetes until later in childhood, suggesting that NGN3 may not be required for human beta cell differentiation in vivo. We have identified a patient with a previously undescribed NGN3 loss-of-function mutation and generated induced pluripotent stem cells from patient fibroblasts to analyze the role of NGN3 in human beta cell differentiation. We used established protocols to differentiate patient-specific iPSCs (PS-iPSCs) into pancreatic progenitor cells and beta-like cells in parallel with the H1 hESC line. The PS- iPSCs displayed significantly lower pancreatic progenitor cell differentiation with only 10.7% of the double positive PDX1+/NKX6.1+ cell population present, whereas the control H1s hESCs produce 60% double positive cells. After further differentiation into beta-like cells, H1 cells produced multiple endocrine cell types, while the PS-iPSC line was not able to make significant numbers of endocrine cells. To assess if the loss of NGN3 was the primary cause for the loss of pancreatic progenitor cells and beta-like cell differentiation, we used CRISPR-cas9 gene editing to correct the patient’s mutation in the PS-iPSCs (cPS-iPSCs). Correcting the patient’s mutation restored the PDX1+/NKX6.1+ cell population in the pancreatic progenitor stage. Beta-like cells differentiated from cPS- iPSCs were capable of glucose responsive insulin secretion at the end of the differentiation protocol. In conclusion, our data suggests that NGN3 may have a previously unidentified role important for the differentiation of pancreatic progenitor cells and that there may be a relationship between NKX6.1 and NGN3 that is critical for pancreatic development. Disclosure K. Millette: None. K.R. Vogt: None. A. Salas: None. P. Pitukcheewanont: None. J. Austin: None. M. Martin: None. S. Georgia: None.
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