TY - JOUR
T1 - Potential unsatisfiability of cyclic constraints on stochastic biological networks biases selection towards hierarchical architectures
AU - Smith, Cameron
AU - Pechuan, Ximo
AU - Puzio, Raymond S.
AU - Biro, Daniel
AU - Bergman, Aviv
N1 - Publisher Copyright:
© 2015 The Author(s) Published by the Royal Society. All rights reserved.
PY - 2015/7/6
Y1 - 2015/7/6
N2 - Constraints placed upon the phenotypes of organisms result from their interactions with the environment. Over evolutionary time scales, these constraints feed back onto smaller molecular subnetworks comprising the organism. The evolution of biological networks is studied by considering a network of a fewnodes embedded in a larger context. Taking into account this fact that any network under study is actually embedded in a larger context, we define network architecture, not on the basis of physical interactions alone, but rather as a specification of the manner in which constraints are placed upon the states of its nodes. We show that such network architectures possessing cycles in their topology, in contrast to those that do not, may be subjected to unsatisfiable constraints. This may be a significant factor leading to selection biased against those network architectures where such inconsistent constraints are more likely to arise. We proceed to quantify the likelihood of inconsistency arising as a function of network architecture finding that, in the absence of sampling bias over the space of possible constraints and for a given network size, networks with a larger number of cycles are more likely to have unsatisfiable constraints placed upon them. Our results identify a constraint that, at least in isolation, would contribute to a bias in the evolutionary process towards more hierarchical -modular versus completely connected network architectures. Together, these results highlight the context dependence of the functionality of biological networks.
AB - Constraints placed upon the phenotypes of organisms result from their interactions with the environment. Over evolutionary time scales, these constraints feed back onto smaller molecular subnetworks comprising the organism. The evolution of biological networks is studied by considering a network of a fewnodes embedded in a larger context. Taking into account this fact that any network under study is actually embedded in a larger context, we define network architecture, not on the basis of physical interactions alone, but rather as a specification of the manner in which constraints are placed upon the states of its nodes. We show that such network architectures possessing cycles in their topology, in contrast to those that do not, may be subjected to unsatisfiable constraints. This may be a significant factor leading to selection biased against those network architectures where such inconsistent constraints are more likely to arise. We proceed to quantify the likelihood of inconsistency arising as a function of network architecture finding that, in the absence of sampling bias over the space of possible constraints and for a given network size, networks with a larger number of cycles are more likely to have unsatisfiable constraints placed upon them. Our results identify a constraint that, at least in isolation, would contribute to a bias in the evolutionary process towards more hierarchical -modular versus completely connected network architectures. Together, these results highlight the context dependence of the functionality of biological networks.
KW - Biological networks
KW - Evolution
KW - Genotype-phenotype map
KW - Systems biology
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U2 - 10.1098/rsif.2015.0179
DO - 10.1098/rsif.2015.0179
M3 - Article
C2 - 26040595
AN - SCOPUS:84936754943
SN - 1742-5689
VL - 12
JO - Journal of the Royal Society Interface
JF - Journal of the Royal Society Interface
IS - 108
M1 - 0179
ER -