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

TitleTime series gene expression profiling and temporal regulatory pathway analysis of BMP6 induced osteoblast differentiation and mineralization.
Publication TypeJournal Article
Year of Publication2011
AuthorsLuo W, Friedman MS, Hankenson KD, Woolf PJ
JournalBMC Syst Biol
Volume5
Pagination82
Date Published2011 May 23
ISSN1752-0509
KeywordsAlgorithms, Bone Morphogenetic Protein 6, Cell Differentiation, Computational Biology, Gene Expression Profiling, Gene Expression Regulation, Humans, Models, Biological, Models, Genetic, Models, Statistical, Oligonucleotide Array Sequence Analysis, Osteoblasts, Receptors, Notch, Signal Transduction, Systems Biology, Time Factors
Abstract

<p><b>BACKGROUND: </b>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.</p><p><b>RESULTS: </b>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.</p><p><b>CONCLUSION: </b>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.</p>

DOI10.1186/1752-0509-5-82
Alternate JournalBMC Syst Biol
PubMed ID21605425
PubMed Central IDPMC3126716
Grant ListR01 AR049682 / AR / NIAMS NIH HHS / United States
R01 AR054714 / AR / NIAMS NIH HHS / United States
R01 DE017471 / DE / NIDCR NIH HHS / United States
U54-DA-021519 / DA / NIDA NIH HHS / United States