Abstract
Here, we present a detailed method for generating a dynamic transcriptional regulatory network from large-scale chromatin immunoprecipitation data, and functional analysis of participating factors through the identification and characterization of significantly overrepresented multi-input motifs in the network. This is done by visualizing interactive data using a network analysis tool, such as Cytoscape, clustering DNA targets of the transcription factors based on their network topologies, and statistically analyzing each cluster based on its size and properties of its members. These analyses yield testable predictions about the conditional and cooperative functions of the factors. This is a versatile approach that allows the visualization of network architecture on a genome-wide level and is applicable to understanding combinatorial control mechanisms of DNA-binding regulators that conditionally cooperate in a wide variety of biological models.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsSpringer Nature is developing a new tool to find and evaluate Protocols. Learn more
References
Shen-Orr SS, Milo R, Mangan S, Alon U. 2002. Network motifs in the transcriptional regulation network of Escherichia coli. Nat Genet 31: 64–8
Luscombe NM, Babu MM, Yu H, Snyder M, Teichmann SA, Gerstein M. 2004. Genomic analysis of regulatory network dynamics reveals large topological changes. Nature 431: 308–12
Smith JJ, Ramsey SA, Marelli M, Marzolf B, Hwang D, Saleem RA, Rachubinski RA, Aitchison JD. 2007. Transcriptional responses to fatty acid are coordinated by combinatorial control. Mol Syst Biol 3: 115
Ren B, Robert F, Wyrick JJ, Aparicio O, Jennings EG, Simon I, Zeitlinger J, Schreiber J, Hannett N, Kanin E, Volkert TL, Wilson CJ, Bell SP, Young RA. 2000. Genome-wide location and function of DNA binding proteins. Science 290: 2306–9
Nagalakshmi U, Wang Z, Waern K, Shou C, Raha D, Gerstein M, Snyder M. 2008. The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320: 1344–9
Park PJ. 2009. ChIP-seq: advantages and challenges of a maturing technology. Nat Rev Genet 10: 669–80
Gurvitz A, Rottensteiner H. 2006. The biochemistry of oleate induction: transcriptional upregulation and peroxisome proliferation. Biochim Biophys Acta 1763: 1392–402
Koerkamp MG, Rep M, Bussemaker HJ, Hardy GP, Mul A, Piekarska K, Szigyarto CA, De Mattos JM, Tabak HF. 2002. Dissection of transient oxidative stress response in Saccharomyces cerevisiae by using DNA microarrays. Mol Biol Cell 13: 2783–94
Smith JJ, Marelli M, Christmas RH, Vizeacoumar FJ, Dilworth DJ, Ideker T, Galitski T, Dimitrov K, Rachubinski RA, Aitchison JD. 2002. Transcriptome profiling to identify genes involved in peroxisome assembly and function. J Cell Biol 158: 259–71
Harbison CT, Gordon DB, Lee TI, Rinaldi NJ, Macisaac KD, Danford TW, Hannett NM, Tagne JB, Reynolds DB, Yoo J, Jennings EG, Zeitlinger J, Pokholok DK, Kellis M, Rolfe PA, Takusagawa KT, Lander ES, Gifford DK, Fraenkel E, Young RA. 2004. Transcriptional regulatory code of a eukaryotic genome. Nature 431: 99–104
Xu Z, Wei W, Gagneur J, Perocchi F, Clauder-Munster S, Camblong J, Guffanti E, Stutz F, Huber W, Steinmetz LM. 2009. Bidirectional promoters generate pervasive transcription in yeast. Nature 457: 1033–7
R Development Core Team. 2010. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. 2003. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res 13: 2498–504
Smith JJ, Miller LR, Kreisberg R, Vazquez L, Wan Y Aitchison JD. 2011. Environment-responsive transcription factors bind subtelomeric elements and regulate gene silencing. Mol Syst Biol 7: 455
MacIsaac KD, Wang T, Gordon DB, Gifford DK, Stormo GD, Fraenkel E. 2006. An improved map of conserved regulatory sites for Saccharomyces cerevisiae. BMC Bioinformatics 7: 113
Acknowledgments
This work was funded by grants NIH/NIGMS R01 GM075152, NIH P50 GM076547, and NIH U54 RR022220. We also thank the Luxembourg Centre for Systems Biomedicine and the University of Luxembourg for support.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Smith, J.J., Saleem, R.A., Aitchison, J.D. (2011). Statistical Analysis of Dynamic Transcriptional Regulatory Network Structure. In: Cagney, G., Emili, A. (eds) Network Biology. Methods in Molecular Biology, vol 781. Humana Press. https://doi.org/10.1007/978-1-61779-276-2_16
Download citation
DOI: https://doi.org/10.1007/978-1-61779-276-2_16
Published:
Publisher Name: Humana Press
Print ISBN: 978-1-61779-275-5
Online ISBN: 978-1-61779-276-2
eBook Packages: Springer Protocols