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Bioinformatics Advance Access originally published online on May 8, 2008
Bioinformatics 2008 24(13):1516-1522; doi:10.1093/bioinformatics/btn229
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Evolutionary design principles of modules that control cellular differentiation: consequences for hysteresis and multistationarity

Junil Kim 1, Tae-Geon Kim 2, Sung Hoon Jung 2, Jeong-Rae Kim 1, Taesung Park 3, Pat Heslop-Harrison 4 and Kwang-Hyun Cho 1,*

1Department of Bio and Brain Engineering and KI for the BioCentury, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon, 305-701, 2Department of Information and Communication Engineering, Hansung University, Seoul, 136-792, 3Department of Statistics, Seoul National University, Gwanak-gu, Seoul, 151-747, Korea and 4Department of Biology, University of Leicester, Leicester LE1 7RH, UK

*To whom correspondence should be addressed.


  Abstract

Motivation: Gene regulatory networks (GRNs) govern cellular differentiation processes and enable construction of multicellular organisms from single cells. Although such networks are complex, there must be evolutionary design principles that shape the network to its present form, gaining complexity from simple modules.

Results: To isolate particular design principles, we have computationally evolved random regulatory networks with a preference to result either in hysteresis (switching threshold depending on current state), or in multistationarity (having multiple steady states), two commonly observed dynamical features of GRNs related to differentiation processes. We have analyzed the resulting evolved networks and compared their structures and characteristics with real GRNs reported from experiments.

Conclusion: We found that the artificially evolved networks have particular topologies and it was notable that these topologies share important features and similarities with the real GRNs, particularly in contrasting properties of positive and negative feedback loops. We conclude that the structures of real GRNs are consistent with selection to favor one or other of the dynamical features of multistationarity or hysteresis.

Contact: ckh{at}kaist.ac.kr

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Trey Ideker

Received on January 12, 2008; revised on April 15, 2008; accepted on May 7, 2008

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