Epigenetic catalysis in an evolutionary context

Abstract

Recent work by Ciliberti et al. finds the spinglass model of regulatory gene networks adapted from neural network studies to have a single giant connected component in a metanetwork space of interaction matrices, permitting only gradual evolutionary transition, in conflict with empirical studies of development in sea urchin species that found evidence for punctuated equilibrium evolutionary transition. Shifting perspective from the highly parallel matrix space to the grammar/syntax of the time series of expressed phenotypes via a recently introduced cognitive paradigm permits import of other techniques from statistical physics to the study of gene expression, in particular application of Landau's spontaneous symmetry breaking arguments. This produces a straightforward multi-component model generating punctuated equilibrium in the evolution of development. Analogs to Bennett and Hacker's mereological fallacy and to Krebs' sufficiency failure that haunt neural network models of high order cognition also severely constrain the usefulness of spinglass models in the study of gene expression dynamics. Our methods, by contrast, permit incorporation of epigenetic effects in a highly natural manner, finding them analogous to a tunable enzyme catalyst in a process also subject to phase transition analogs.