Identification of transcripts with enriched expression in the developing and adult pancreas

Brad G Hoffman¹ , Bogard Zavaglia¹ , Joy Witzsche¹ , Teresa Ruiz de Algara¹ , Mike Beach¹ , Pamela A Hoodless²^,3 , Steven JM Jones³^,4 , Marco A Marra³^,4 and Cheryl D Helgason¹^,5

¹Department of Cancer Endocrinology, BC Cancer Research Center, West 10th Ave, Vancouver, BC, V5Z 1L3, Canada

²Terry Fox Laboratory, BC Cancer Research Center, West 10th Ave, Vancouver, BC, V5Z 1L3, Canada

³Department of Medical Genetics, Faculty of Medicine, University of British Columbia, University Boulevard, Vancouver, BC, V6T 1Z3, Canada

⁴Micheal Smith Genome Sciences Centre, BC Cancer Agency, West 7th Ave, Vancouver, BC, V5Z 4S6, Canada

⁵Department of Surgery, Faculty of Medicine, University of British Columbia, West 10th Avenue, Vancouver, BC, V5Z 4E3, Canada

author email corresponding author email

Genome Biology 2008, 9:R99doi:10.1186/gb-2008-9-6-r99


Published:	14 June 2008

Subject areas: Development, Cell biology, Genetics

Abstract

Background

Despite recent advances, the transcriptional hierarchy driving pancreas organogenesis remains largely unknown, in part due to the paucity of comprehensive analyses. To address this deficit we generated ten SAGE libraries from the developing murine pancreas spanning Theiler stages 17-26, making use of available Pdx1 enhanced green fluorescent protein (EGFP) and Neurog3 EGFP reporter strains, as well as tissue from adult islets and ducts.

Results

We used a specificity metric to identify 2,536 tags with pancreas-enriched expression compared to 195 other mouse SAGE libraries. We subsequently grouped co-expressed transcripts with differential expression during pancreas development using K-means clustering. We validated the clusters first using quantitative real time PCR and then by analyzing the Theiler stage 22 pancreas in situ hybridization staining patterns of over 600 of the identified genes using the GenePaint database. These were then categorized into one of the five expression domains within the developing pancreas. Based on these results we identified a cascade of transcriptional regulators expressed in the endocrine pancreas lineage and, from this, we developed a predictive regulatory network describing beta-cell development.

Conclusion

Taken together, this work provides evidence that the SAGE libraries generated here are a valuable resource for continuing to elucidate the molecular mechanisms regulating pancreas development. Furthermore, our studies provide a comprehensive analysis of pancreas development, and insights into the regulatory networks driving this process are revealed.