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Criticality Is an Emergent Property of Genetic Networks that Exhibit Evolvability

Overview of attention for article published in PLoS Computational Biology, September 2012
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Title
Criticality Is an Emergent Property of Genetic Networks that Exhibit Evolvability
Published in
PLoS Computational Biology, September 2012
DOI 10.1371/journal.pcbi.1002669
Pubmed ID
Authors

Christian Torres-Sosa, Sui Huang, Maximino Aldana

Abstract

Accumulating experimental evidence suggests that the gene regulatory networks of living organisms operate in the critical phase, namely, at the transition between ordered and chaotic dynamics. Such critical dynamics of the network permits the coexistence of robustness and flexibility which are necessary to ensure homeostatic stability (of a given phenotype) while allowing for switching between multiple phenotypes (network states) as occurs in development and in response to environmental change. However, the mechanisms through which genetic networks evolve such critical behavior have remained elusive. Here we present an evolutionary model in which criticality naturally emerges from the need to balance between the two essential components of evolvability: phenotype conservation and phenotype innovation under mutations. We simulated the Darwinian evolution of random Boolean networks that mutate gene regulatory interactions and grow by gene duplication. The mutating networks were subjected to selection for networks that both (i) preserve all the already acquired phenotypes (dynamical attractor states) and (ii) generate new ones. Our results show that this interplay between extending the phenotypic landscape (innovation) while conserving the existing phenotypes (conservation) suffices to cause the evolution of all the networks in a population towards criticality. Furthermore, the networks produced by this evolutionary process exhibit structures with hubs (global regulators) similar to the observed topology of real gene regulatory networks. Thus, dynamical criticality and certain elementary topological properties of gene regulatory networks can emerge as a byproduct of the evolvability of the phenotypic landscape.

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Geographical breakdown

Country Count As %
United States 13 7%
Mexico 2 1%
Netherlands 1 <1%
Italy 1 <1%
Australia 1 <1%
Norway 1 <1%
Colombia 1 <1%
Iran, Islamic Republic of 1 <1%
Canada 1 <1%
Other 5 3%
Unknown 169 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 59 30%
Student > Ph. D. Student 30 15%
Student > Master 21 11%
Professor 18 9%
Student > Bachelor 16 8%
Other 36 18%
Unknown 16 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 75 38%
Physics and Astronomy 29 15%
Biochemistry, Genetics and Molecular Biology 17 9%
Computer Science 10 5%
Neuroscience 10 5%
Other 32 16%
Unknown 23 12%