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


CONCLUSIONS
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.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Kim
Junil
J
Department of Bio and Brain Engineering and KI for the BioCentury, Korea Advanced Institute of Science and Technology, 335 Gwahangno, Yuseong-gu, Daejeon, 305-701, Korea.
Kim
Tae-Geon
TG
Jung
Sung Hoon
SH
Kim
Jeong-Rae
JR
Park
Taesung
T
Heslop-Harrison
Pat
P
Cho
Kwang-Hyun
KH
D002454:Cell Differentiation / Q000502:physiology*; D003198:Computer Simulation; D019143:Evolution, Molecular; D005246:Feedback / Q000502:physiology; D018507:Gene Expression Regulation, Developmental / Q000502:physiology*; D008957:Models, Genetic; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
D020543:Proteome