PERSPECTIVE - COMPLEX ADAPTATIONS AND THE EVOLUTION OF EVOLVABILITY

The problem of complex adaptations is studied in two largely disconnec ted research traditions: evolutionary biology and evolutionary compute r science. This paper summarizes the results from both areas and compa res their implications. In evolutionary computer science it was found that the Darwinian process of mutation, recombination and selection is not universally effective in improving complex systems like computer programs or chip designs. For adaptation to occur, these systems must possess ''evolvability,'' i.e., the ability of random variations to so metimes produce improvement. It was found that evolvability critically depends on the way genetic; variation maps onto phenotypic variation, an issue known as the representation problem. The genotype-phenotype map determines the variability of characters, which is the propensity to vary. Variability needs to be distinguished from variations, which are the actually realized differences between individuals. The genotyp e-phenotype map is the common theme underlying such varied biological phenomena as genetic canalization, developmental constraints, biologic al versatility, developmental dissociability, and morphological integr ation. For evolutionary biology the representation problem has importa nt implications: how is it that extant species acquired a genotype-phe notype map which allows improvement by mutation and selection? Is the genotype phenotype map able to change in evolution? What are the selec tive forces, if any, that shape the genotype-phenotype map? We propose that the genotype-phenotype map can evolve by two main routes: epista tic mutations, or the creation of new genes. A common result for organ ismic design is modularity. By modularity we mean a genotype-phenotype map in which there are few pleiotropic effects among characters servi ng different functions, with pleiotropic effects falling mainly among characters that are part of a single functional complex. Such a design is expected to improve evolvability by limiting the interference betw een the adaptation of different functions. Several population genetic models are reviewed that are intended to explain the evolutionary orig in of a modular design. While our current knowledge is insufficient to assess the plausibility of these models, they form the beginning of a framework for understanding the evolution of the genotype-phenotype m ap.