Research article

Characterization of the proneural gene regulatory network during mouse telencephalon development

Julia M Gohlke^{* 1} , Olivier Armant^{* 2,4} , Frederick M Parham¹ , Marjolein V Smith³ , Celine Zimmer² , Diogo S Castro² , Laurent Nguyen² , Joel S Parker³ , Gerard Gradwohl⁴ , Christopher J Portier¹ and François Guillemot²

¹Environmental Systems Biology Group, Laboratory of Molecular Toxicology, National Institute of Environmental Health Sciences, RTP, NC 27709, USA

²Division of Molecular Neurobiology, National Institute for Medical Research, The Ridgeway, Mill Hill, London, UK

³Constella Health Sciences, Durham, NC 27713, USA

⁴INSERM U682, Avenue Molière, 67200 Strasbourg, France

author email corresponding author email* Contributed equally

BMC Biology 2008, 6:15doi:10.1186/1741-7007-6-15

Published:	31 March 2008

Abstract

Background

The proneural proteins Mash1 and Ngn2 are key cell autonomous regulators of neurogenesis in the mammalian central nervous system, yet little is known about the molecular pathways regulated by these transcription factors.

Results

Here we identify the downstream effectors of proneural genes in the telencephalon using a genomic approach to analyze the transcriptome of mice that are either lacking or overexpressing proneural genes. Novel targets of Ngn2 and/or Mash1 were identified, such as members of the Notch and Wnt pathways, and proteins involved in adhesion and signal transduction. Next, we searched the non-coding sequence surrounding the predicted proneural downstream effector genes for evolutionarily conserved transcription factor binding sites associated with newly defined consensus binding sites for Ngn2 and Mash1. This allowed us to identify potential novel co-factors and co-regulators for proneural proteins, including Creb, Tcf/Lef, Pou-domain containing transcription factors, Sox9, and Mef2a. Finally, a gene regulatory network was delineated using a novel Bayesian-based algorithm that can incorporate information from diverse datasets.

Conclusion

Together, these data shed light on the molecular pathways regulated by proneural genes and demonstrate that the integration of experimentation with bioinformatics can guide both hypothesis testing and hypothesis generation.