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The Inheritance of Process: A Dynamical Systems Approach
Author(s) -
Jaeger Johannes,
Irons David,
Monk Nick
Publication year - 2012
Publication title -
journal of experimental zoology part b: molecular and developmental evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.823
H-Index - 63
eISSN - 1552-5015
pISSN - 1552-5007
DOI - 10.1002/jez.b.22468
Subject(s) - evolvability , macroevolution , inheritance (genetic algorithm) , evolutionary dynamics , process (computing) , heredity , conceptual framework , evolutionary biology , selection (genetic algorithm) , dynamical systems theory , punctuated equilibrium , biology , computer science , artificial intelligence , genetics , population , epistemology , phylogenetics , sociology , philosophy , demography , physics , quantum mechanics , gene , operating system
A central unresolved problem of evolutionary biology concerns the way in which evolution at the genotypic level relates to the evolution of phenotypes. This genotype–phenotype map involves developmental and physiological processes, which are complex and not well understood. These processes co‐determine the rate and direction of adaptive change by shaping the distribution of phenotypic variability on which selection can act. In this study, we argue—expanding on earlier ideas by Goodwin, Oster, and Alberch—that an explicit treatment of this map in terms of dynamical systems theory can provide an integrated understanding of evolution and development. We describe a conceptual framework, which demonstrates how development determines the probability of possible phenotypic transitions—and hence the evolvability of a biological system. We use a simple conceptual model to illustrate how the regulatory dynamics of the genotype–phenotype map can be passed on from generation to generation, and how heredity itself can be treated as a dynamic process. Our model yields explanations for punctuated evolutionary dynamics, the difference between micro‐ and macroevolution, and for the role of the environment in major phenotypic transitions. We propose a quantitative research program in evolutionary developmental systems biology—combining experimental methods with mathematical modeling—which aims at elaborating our conceptual framework by applying it to a wide range of evolving developmental systems. This requires a large and sustained effort, which we believe is justified by the significant potential benefits of an extended evolutionary theory that uses dynamic molecular genetic data to reintegrate development and evolution. J. Exp. Zool. (Mol. Dev. Evol.) 9999B:591–612, 2012. © 2012 Wiley Periodicals, Inc.