Box 6.5Canalization and the Connectivity of Transcriptional Regulatory Networks

To explore the possibility that genetic canalization may be a by-product of other selective forces, … [we start with] the model of A. Wagner, who treats development as the interaction of a network of transcriptional regulatory genes, phenotype as the equilibrium state of this network, and fitness as a function of the distance between an individual's equilibrium state and the optimum state…. Evolution in the model [a generalized version of Wagner's] consists of three phases: mating, development, and selection. Mating and selection are modeled in accord with traditional population-genetic approaches…. [To handle development] one can represent a network of transcriptional regulators by a state vector containing the concentration of each gene product and a matrix, the entries of which represent the effects of each gene product on the expression of each gene. Entries may be either positive (activating) or negative (repressing) and may differ in magnitude. Zero elements in the matrix represent the absence of interaction between the given gene product and gene. The developmental process is then fully described by a set of nonlinear coupled difference equations…. Wagner draws an analogy between the rows of the interaction matrix and the enhancer regions of the genes in the network and further justifies the biological realism of this type of model by reference to data from actual genetic networks. An important assumption in the model, also justified by A. Wagner, is that functional genetic networks will reach a stable equilibrium gene-expression state, and that unstable networks reflect, in a sense, the failure of development. Thus, in his model and ours, development itself enforces a kind of selection, because we require that the network of regulatory interactions produce a stable equilibrium gene-expression state (its “phenotype”), whose distance to an optimum state can then be measured during the selection phase.

… We report here the results of numerical simulations of our model of an evolving developmental-genetic system. We demonstrate an important, perhaps primary, role for the developmental process itself in creating canalization, in that insensitivity to mutation evolves even when stabilizing selection is absent. We go on to demonstrate that the complexity of the network is a key factor in this evolutionary process, in that networks with a greater proportion of connections evolve greater insensitivity to mutation.

… One is led to wonder whether the evolution of canalization under no stabilizing selection on the gene-expression pattern is an artifact of the modeling framework or whether it represents a finding of real biological significance. We argue that the latter is true on a number of counts. To begin, we acknowledge that it is difficult to envision a scenario in nature in which the stability of a developmental module is required, but the phenotype produced by that module is not subject to selection. One situation in which this condition may hold is when a species colonizes a new territory with virtually unlimited resources, so selection is only for those that develop to reproduce. Furthermore, even if such a scenario does not pertain, the conceptual decomposition of stabilizing selection into selection for an optimum and selection for developmental stability is important. Thus, even in scenarios in which members of a population are subject to selection for an optimum, the evolution of canalization may proceed because of the underlying selection for stability of the developmental outcome. Our results suggest that this underlying selection can occur very fast. Because others have argued that the evolution of canalization under stabilizing selection may be slow, developmental stability may therefore be the dominant force in the evolution of canalization.

SOURCE: Reprinted by permission from M.L. Siegal and A. Bergman, “Waddington's Canalization Revisited: Developmental Stability and Evolution,” Proceedings of the National Academy of Sciences 99(16):10528-10532, 2002. Copyright 2002 National Academy of Sciences. (References and figures are omitted above and can be found in the original article.)

From: 6, A Computational and Engineering View of Biology

Cover of Catalyzing Inquiry at the Interface of Computing and Biology
Catalyzing Inquiry at the Interface of Computing and Biology.
National Research Council (US) Committee on Frontiers at the Interface of Computing and Biology; Wooley JC, Lin HS, editors.
Washington (DC): National Academies Press (US); 2005.
Copyright © 2005, National Academy of Sciences.

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