Evolvability

  • The capacity to generate selectable phenotypic variation has been treated largely from the perspective of evolutionary genetics and molecular cell biology, both of which emphasize different types of genetic explanatory approaches (Wagner and Zhang 2011; Kirschner and Gerhart 1998; Gerhart and Kirschner 2007). However, a growing literature has emerged surrounding generic explanations of evolvability that appeal to abstract network properties, such as robustness (Draghi et al. 2010; Kitano 2004; Wagner 2005), sparseness (Friedlander et al. 2013), and criticality (Torres-Sosa et al. 2012). Additionally, mathematically formulated mechanical models of developmental processes have been used to explain evolutionary patterns such as convergence (Chirat et al. 2013).
  • Some have urged that selection cannot maintain the complex organization that we find in living systems, and that traits behave according to self-organizational dynamics and must be generic to survive (Kauffman 1993). Others argue that a population genetic perspective is essential and prevents facile appeals to natural selection when trying to explain complexity (Fernández and Lynch 2011; Lynch 2007). Still others try to combine a ubiquitous generic robustness at multiple levels and specific genetic properties to account for evolvability (Wagner 2005, 2011).
  • At least three factors act as obstacles to progress in explanatory integration: (1) a polarization of generic and genetic approaches to evolvability; (2) a tendency to concentrate on one or a small subset of genetic or generic properties as more important in understanding evolvability; and, (3) the lack of comparison between models to expose conflicting assumptions within and between genetic and generic approaches.
  • This workshop addresses research questions such as: What aspects of evolvability are explained genetically? Generically? What are the best examples of each type of explanation in isolation? Are there examples of integrated explanations involving genetic and generic approaches? If so, what are their characteristics? Are they successful? What empirical, theoretical, and conceptual barriers exist to integrating genetic and generic explanations of evolvability? What conflicting assumptions exist among different explanatory models?
  • A complete reading list and schedule of discussion from the workshop will be made available shortly after the workshop next May.

Suggested Readings

Floral morphogenesis: stochastic explorations of a gene network epigenetic landscape

Álvarez-Buylla, E.R., Á. Chaos, M. Aldana, M. Benítez, Y. Cortes-Poza, C. Espinosa-Soto, D.A. Hartasánchez, R.B. Lotto, D. Malkin, G.J. Escalera Santos, and P. Padilla-Longoria. 2008. Floral morphogenesis: stochastic explorations of a gene network epigenetic landscape. PLoS ONE 3(11):e3626.

Systems biology approaches to development beyond bioinformatics: nonlinear mechanistic models using plant systems

Álvarez-Buylla, E.R., J. Dávila-Velderrain, and J.C. Martínez-García. 2016. Systems biology approaches to development beyond bioinformatics: nonlinear mechanistic models using plant systems. BioScience 66:371–383.

Flower development as an interplay between dynamical physical fields and genetic networks

Barrio, R.Á., A. Hernández-Machado, C. Varea, J.R. Romero-Arias, and E.R. Álvarez-Buylla. 2010. Flower development as an interplay between dynamical physical fields and genetic networks. PLoS ONE 5(10): e13523.

Predicting patterns of long-term adaptation and extinction with population genetics

Bertram, J., K. Gomez, and J. Masel. 2017. Predicting patterns of long-term adaptation and extinction with population genetics. Evolution 71:204–214.

Evolution and evolvability: celebrating Darwin 200

Brookfield, J.F.Y. 2009. Evolution and evolvability: celebrating Darwin 200. Biology Letters 5:44–46.