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Plos Biology : Topology and Robustness in the Drosophila Segment Polarity Network, Volume 2

By Lander, Arthur

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Book Id: WPLBN0003923094
Format Type: PDF eBook :
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Reproduction Date: 2015

Title: Plos Biology : Topology and Robustness in the Drosophila Segment Polarity Network, Volume 2  
Author: Lander, Arthur
Volume: Volume 2
Language: English
Subject: Journals, Science, Biology
Collections: Periodicals: Journal and Magazine Collection (Contemporary), PLoS Biology
Publication Date:
Publisher: Plos


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Lander, A. (n.d.). Plos Biology : Topology and Robustness in the Drosophila Segment Polarity Network, Volume 2. Retrieved from

Description : A complex hierarchy of genetic interactions converts a single-celled Drosophila melanogaster egg into a multicellular embryo with 14 segments. Previously, von Dassow et al. reported that a mathematical model of the genetic interactions that defined the polarity of segments (the segment polarity network) was robust (von Dassow et al. 2000). As quantitative information about the system was unavailable, parameters were sampled randomly. A surprisingly large fraction of these parameter sets allowed the model to maintain and elaborate on the segment polarity pattern. This robustness is due to the positive feedback of gene products on their own expression, which induces individual cells in a model segment to adopt different stable expression states (bistability) corresponding to different cell types in the segment polarity pattern. A positive feedback loop will only yield multiple stable states when the parameters that describe it satisfy a particular inequality. By testing which random parameter sets satisfy these inequalities, I show that bistability is necessary to form the segment polarity pattern and serves as a strong predictor of which parameter sets will succeed in forming the pattern. Although the original model was robust to parameter variation, it could not reproduce the observed effects of cell division on the pattern of gene expression. I present a modified version that incorporates recent experimental evidence and does successfully mimic the consequences of cell division. The behavior of this modified model can also be understood in terms of bistability in positive feedback of gene expression. I discuss how this topological property of networks provides robust pattern formation and how large changes in parameters can change the specific pattern produced by a network.


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