Virtual mutagenesis of the yeast cyclins genetic network reveals complex dynamics of transcriptional control networks
- PMID: 21541341
- PMCID: PMC3081828
- DOI: 10.1371/journal.pone.0018827
Virtual mutagenesis of the yeast cyclins genetic network reveals complex dynamics of transcriptional control networks
Abstract
Study of genetic networks has moved from qualitative description of interactions between regulators and regulated genes to the analysis of the interaction dynamics. This paper focuses on the analysis of dynamics of one particular network--the yeast cyclins network. Using a dedicated mathematical model of gene expression and a procedure for computation of the parameters of the model from experimental data, a complete numerical model of the dynamics of the cyclins genetic network was attained. The model allowed for performing virtual experiments on the network and observing their influence on the expression dynamics of the genes downstream in the regulatory cascade. Results show that when the network structure is more complicated, and the regulatory interactions are indirect, results of gene deletion are highly unpredictable. As a consequence of quantitative behavior of the genes and their connections within the network, causal relationship between a regulator and target gene may not be discovered by gene deletion. Without including the dynamics of the system into the network, its functional properties cannot be studied and interpreted correctly.
Conflict of interest statement
Figures






Similar articles
-
The transcriptional network activated by Cln3 cyclin at the G1-to-S transition of the yeast cell cycle.Genome Biol. 2010;11(6):R67. doi: 10.1186/gb-2010-11-6-r67. Epub 2010 Jun 23. Genome Biol. 2010. PMID: 20573214 Free PMC article.
-
Stochastic simulation for the inference of transcriptional control network of yeast cyclins genes.Nucleic Acids Res. 2012 Aug;40(15):7096-103. doi: 10.1093/nar/gks440. Epub 2012 May 15. Nucleic Acids Res. 2012. PMID: 22589416 Free PMC article.
-
Refining current knowledge on the yeast FLR1 regulatory network by combined experimental and computational approaches.Mol Biosyst. 2010 Dec;6(12):2471-81. doi: 10.1039/c004881j. Epub 2010 Oct 11. Mol Biosyst. 2010. PMID: 20938527
-
Exploring genetic interactions and networks with yeast.Nat Rev Genet. 2007 Jun;8(6):437-49. doi: 10.1038/nrg2085. Nat Rev Genet. 2007. PMID: 17510664 Review.
-
Transcriptional networks: reverse-engineering gene regulation on a global scale.Curr Opin Microbiol. 2004 Dec;7(6):638-46. doi: 10.1016/j.mib.2004.10.009. Curr Opin Microbiol. 2004. PMID: 15556037 Review.
References
-
- Kim MS, Kim JR, Cho KH. Dynamic network rewiring determines temporal regulatory functions in Drosophila melanogaster development processes. Bioessays. 2010;32:505–513. - PubMed
-
- Luscombe NM, Babu MM, Yu H, Snyder M, Teichmann SA, et al. Genomic analysis of regulatory network dynamics reveals large topological changes. Nature. 2004;431:308–312. - PubMed
-
- To CC, Vohradsky J. Measurement variation determines the gene network topology reconstructed from experimental data: a case study of the yeast cyclin network. FASEB J. 2010;24:3468–3478. - PubMed
-
- Akutsu T, Miyano S, Kuhara S. Algorithms for Identifying Boolean Networks and Related Biological Networks Based on Matrix Multiplication and Fingerprint Function. J Comput Biol. 2000;7:331–343. - PubMed
-
- Davidich M, Bornholdt S. The transition from differential equations to Boolean networks: a case study in simplifying a regulatory network model. J Theor Biol. 2008;255:269–277. - PubMed
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Molecular Biology Databases
Research Materials