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Open Access Research article

Time series gene expression profiling and temporal regulatory pathway analysis of BMP6 induced osteoblast differentiation and mineralization

Weijun Luo12, Michael S Friedman3, Kurt D Hankenson4* and Peter J Woolf156*

Author Affiliations

1 Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA

2 Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA

3 Thermogenesis Corporation, Rancho Cordova, CA 95742, USA

4 Department of Animal Biology, University of Pennsylvania, Philadelphia, PA 19104, USA

5 Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA

6 Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA

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BMC Systems Biology 2011, 5:82  doi:10.1186/1752-0509-5-82

Published: 23 May 2011

Abstract

Background

BMP6 mediated osteoblast differentiation plays a key role in skeletal development and bone disease. Unfortunately, the signaling pathways regulated by BMP6 are largely uncharacterized due to both a lack of data and the complexity of the response.

Results

To better characterize the signaling pathways responsive to BMP6, we conducted a time series microarray study to track BMP6 induced osteoblast differentiation and mineralization. These temporal data were analyzed using a customized gene set analysis approach to identify temporally coherent sets of genes that act downstream of BMP6. Our analysis identified BMP6 regulation of previously reported pathways, such as the TGF-beta pathway. We also identified previously unknown connections between BMP6 and pathways such as Notch signaling and the MYB and BAF57 regulatory modules. In addition, we identify a super-network of pathways that are sequentially activated following BMP6 induction.

Conclusion

In this work, we carried out a microarray-based temporal regulatory pathway analysis of BMP6 induced osteoblast differentiation and mineralization using GAGE method. This novel temporal analysis is more informative and powerful than the classical static pathway analysis in that: (1) it captures the interconnections between signaling pathways or functional modules and demonstrates the even higher level organization of molecular biological systems; (2) it describes the temporal perturbation patterns of each pathway or module and their dynamic roles in osteoblast differentiation. The same set of experimental and computational strategies employed in our work could be useful for studying other complex biological processes.