Literature DB >> 17178139

Wagner's canalization model.

Emilia Huerta-Sanchez1, Rick Durrett.   

Abstract

Wagner (1996, Does evolutionary plasticity evolve? Evolution 50, 1008-1023.) and Siegal and Bergman, 2002 and Azevedo et al., 2006 have studied a simple model of the evolution of a network of N genes, in order to explain the observed phenomenon that systems evolve to be robust. These authors primarily considered the case N=10 and used simulations to reach their conclusions. Here we investigate this model in more detail, considering systems of different sizes with and without recombination, and with selection for convergence instead of to a specified limit. For the simpler evolutionary model lacking recombination, we analyze the system as a neutral network. This allows us to describe the equilibrium distribution networks within genotype space. Our results show that, given a sufficiently large population size, the qualitative observation that systems evolve to be robust, is itself robust, as it does not depend on the details of the model. In simple terms, robust systems have more viable offspring, so the evolution of robustness is merely selection for increased fecundity, an observation that is well known in the theory of neutral networks.

Mesh:

Year:  2006        PMID: 17178139     DOI: 10.1016/j.tpb.2006.10.006

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  11 in total

1.  Effects of recombination on complex regulatory circuits.

Authors:  Olivier C Martin; Andreas Wagner
Journal:  Genetics       Date:  2009-08-03       Impact factor: 4.562

Review 2.  Robustness and evolvability.

Authors:  Joanna Masel; Meredith V Trotter
Journal:  Trends Genet       Date:  2010-07-01       Impact factor: 11.639

3.  Modeling the evolution of complex genetic systems: the gene network family tree.

Authors:  Janna L Fierst; Patrick C Phillips
Journal:  J Exp Zool B Mol Dev Evol       Date:  2015-01       Impact factor: 2.656

Review 4.  Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.

Authors:  Alexander Spirov; David Holloway
Journal:  Methods       Date:  2013-05-30       Impact factor: 3.608

5.  Evolution of gene regulatory networks by fluctuating selection and intrinsic constraints.

Authors:  Masaki E Tsuda; Masakado Kawata
Journal:  PLoS Comput Biol       Date:  2010-08-05       Impact factor: 4.475

6.  Model transcriptional networks with continuously varying expression levels.

Authors:  Mauricio O Carneiro; Clifford H Taubes; Daniel L Hartl
Journal:  BMC Evol Biol       Date:  2011-12-19       Impact factor: 3.260

7.  Most networks in Wagner's model are cycling.

Authors:  Ricardo Pinho; Elhanan Borenstein; Marcus W Feldman
Journal:  PLoS One       Date:  2012-04-12       Impact factor: 3.240

8.  The underlying molecular and network level mechanisms in the evolution of robustness in gene regulatory networks.

Authors:  Mario Pujato; Thomas MacCarthy; Andras Fiser; Aviv Bergman
Journal:  PLoS Comput Biol       Date:  2013-01-03       Impact factor: 4.475

9.  In silico evolution of gene cooption in pattern-forming gene networks.

Authors:  Alexander V Spirov; Marat A Sabirov; David M Holloway
Journal:  ScientificWorldJournal       Date:  2012-12-25

10.  Survival of the sparsest: robust gene networks are parsimonious.

Authors:  Robert D Leclerc
Journal:  Mol Syst Biol       Date:  2008-08-05       Impact factor: 11.429

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