Bulletin of the American Physical Society
2007 APS March Meeting
Volume 52, Number 1
Monday–Friday, March 5–9, 2007; Denver, Colorado
Session X6: Networks in Genetic Regulation |
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Sponsoring Units: GSNP DBP Chair: Erzsebet Ravasz, Los Alamos National Laboratory Room: Colorado Convention Center 207 |
Friday, March 9, 2007 8:00AM - 8:36AM |
X6.00001: Check Point as Fixed point: Analysis of a Yeast Cell-Cycle Model Invited Speaker: The cell cycle regulation in the budding yeast \textit{Saccharomyces cerevisiae} is one of the best studied biological systems. Many major players and their interactions have been identified by decades of work in genetics and biochemistry as well as by the more recent effort in high throughput genomics and proteomics. On the other hand, current information about the network is mostly qualitative---while there is a circuit diagram (although it may not be complete) of who regulates whom, there is little quantitative information (e.g. the kinetic constants) about the regulation. Here we construct a model of yeast cell-cycle regulation from the known circuit diagram using ordinary differential equations and focus our attention on the global dynamic property and structural stability of the system. We found that certain qualitative conclusions about the system's behavior are very robust to parameter choices. In particular, each checkpoint can be a global attractor---when a checkpoint is on \textit{all} cell states evolve to the stationary state corresponding to the checkpoint arrest. Furthermore, there is a unique globally attracting trajectory for this dynamic system, which corresponds to the biological pathway of the cell cycle regulation. Substantial changes of certain parameters, especially when several parameters are changed simultaneously, can result in qualitative changes in the system's behavior. Typically, these not-so-robust parameters are associated with transitions between different cell-cycle phases and the corresponding abnormal behavior is often related to the arrest or bypass of a checkpoint. Our results reveal a robust picture of the yeast cell cycle regulation and the mechanisms under which the robustness can be compromised. [Preview Abstract] |
Friday, March 9, 2007 8:36AM - 9:12AM |
X6.00002: Boolean modeling of cellular regulatory networks Invited Speaker: Interaction between gene products forms the basis of essential processes like signal transduction, cell metabolism or embryonic development. Recent experimental advances helped uncover the structure of many cellular networks, creating a surge of interest in the dynamical description of gene regulation. Traditionally genetic and protein interactions are modeled by differential equations based on reaction kinetics, but these studies are greatly hampered by the sparsity of known kinetic detail. As an alternative, qualitative models assuming a small set of discrete states for gene products, or combinations of discrete and continuous dynamics, are gaining acceptance. Many results also suggest that the interaction topology plays a determining role in the dynamics of regulatory networks and there is significant robustness to changes in kinetic parameters. This presentation will focus on a Boolean model of the signal transduction network regulating drought response in plants. We integrate qualitative and indirect relationships into the simplest network consistent with all experimental observations, and express the regulation of network nodes as logical functions. Our model captures the regulation of more than forty identified network components, and accords well with previous experimental results at both the pathway and whole cell physiological level. We identify the dynamical repertoire of the network by varying process durations and initial conditions and by simulating gene disruptions, and find a remarkable robustness against a significant fraction of possible perturbations. Although qualitative, the model provides a ranking of disruptions and perturbations in the order of their severity. We experimentally test, and validate, the most surprising prediction. The success of this model illuminates the emergent (network-level) functional robustness of cellular regulatory networks. [Preview Abstract] |
Friday, March 9, 2007 9:12AM - 9:48AM |
X6.00003: Symmetry and the Self-Organized Evolution of Canalization in Boolean Networks Invited Speaker: Canalization of genetic regulatory networks have been argued to be favored by evolutionary processes due to the stability that it can confer to phenotype expression. Using an N-K Boolean network model of a genetic regulatory network, we explore whether a significant amount of canalization can arise in purely random networks in the absence of evolutionary pressures. We use a mapping of the Boolean functions in the Kauffman N-K model for genetic regulatory networks onto a k-dimensional Ising hypercube to show that the functions can be divided into different classes strictly due to geometrical constraints. The classes can be counted and their properties determined using results from group theory and isomer chemistry. We demonstrate that partially canalized functions completely dominate all possible Boolean functions, particularly for higher K. This indicates that partial canalization is extremely common, even in randomly chosen networks, and has implications for how much information can be obtained in experiments on native state genetic regulatory networks. Furthermore, we demonstrate that a highly canalized state evolves spontaneously from a competition between the nodes. Network finite-size effects are found to be important to that evolutionary process. [Preview Abstract] |
Friday, March 9, 2007 9:48AM - 10:24AM |
X6.00004: Quantitative aspects of gene regulation by small RNAs Invited Speaker: Small, non-coding RNAs (sRNAs) play an important role as genetic regulators in both prokaryotes and eukaryotes. Many sRNAs act through base-pairing interaction with target messenger RNAs (mRNAs) to regulate transcription, translation, and mRNA stability. sRNAs represent a novel form of genetic regulation distinct from more thoroughly studied protein regulators. This talk addresses quantitative aspectsof sRNA-mediated genetic regulation, focusing on noise, tunability, and feedback. In particular, we compare and contrast sRNA and protein regulators in an attempt to understand the compartive advantages of each form of regulation. [Preview Abstract] |
Friday, March 9, 2007 10:24AM - 11:00AM |
X6.00005: Gene regulatory networks: what is still missing? Invited Speaker: Gene regulatory networks have evolved to respond to a changing environment, serving the survival of the biological population. The topology of these networks has been investigated with the hope of gaining insight into their function or identifying the factors shaping their evolution. Recent studies have shown that gene regulatory networks have different in-degree and out-degree distribution, contain network motifs and are organized in a hierarchical set of layers. However, important pieces of information are still needed before the topological features of these networks can be correctly determined and their response to environmental changes can be modeled at increasingly large scale. [Preview Abstract] |
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