Information propagation within the Genetic Network of Saccharomyces cerevisiae
- Equal contributors
1 Laboratory of Biosystem Dynamics, Computational Systems Biology Research Group, Tampere University of Technology, Tampere, Finland
2 Banting and Best Department of Medical Research University of Toronto, 160 College St. Room 1302. Toronto, ON, M5 S 3E1 Canada
3 Institute for Systems Biology, 1441N 34th St, Seattle, WA, 98103-8904, USA
4 Institute for Biocomplexity and Informatics, University of Calgary, Alberta T2N 1N4, Canada
5 Department of Biological Sciences, University of Calgary, Alberta T2N 1N4, Canada
BMC Systems Biology 2010, 4:143 doi:10.1186/1752-0509-4-143Published: 26 October 2010
A gene network's capacity to process information, so as to bind past events to future actions, depends on its structure and logic. From previous and new microarray measurements in Saccharomyces cerevisiae following gene deletions and overexpressions, we identify a core gene regulatory network (GRN) of functional interactions between 328 genes and the transfer functions of each gene. Inferred connections are verified by gene enrichment.
We find that this core network has a generalized clustering coefficient that is much higher than chance. The inferred Boolean transfer functions have a mean p-bias of 0.41, and thus similar amounts of activation and repression interactions. However, the distribution of p-biases differs significantly from what is expected by chance that, along with the high mean connectivity, is found to cause the core GRN of S. cerevisiae's to have an overall sensitivity similar to critical Boolean networks. In agreement, we find that the amount of information propagated between nodes in finite time series is much higher in the inferred core GRN of S. cerevisiae than what is expected by chance.
We suggest that S. cerevisiae is likely to have evolved a core GRN with enhanced information propagation among its genes.