The problem of complex adaptations is studied in two largely disconnected research traditions: evolutionary biology and evolutionary computer science. This paper summarizes the results from both areas and compares 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 sometimes 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 variation, which are the actually realized differences between individuals. The genotype-phenotype map is the ...

The current implementation of the Neo-Darwinian model of evolution typically assumes that the set of possible phenotypes is organized into a highly symmetric and regular space equipped with a notion of distance, for example, a Euclidean vector space. Recent computational work on a biophysical genotype-phenotype model based on the folding of RNA sequences into secondary structures suggests a rather different picture. If phenotypes are organized according to genetic accessibility, the resulting space lacks a metric and is formalized by an unfamiliar structure, known as a pretopology. Patterns of phenotypic evolution -- such as punctuation, irreversibility, modularity -- result naturally from the properties of this space. The classical framework, however, addresses these patterns by exclusively invoking natural selection on suitably imposed fitness landscapes. We propose to extend the explanatory level for phenotypic evolution from fitness considerations alone to include the topological st...

The distinction between continuous and discontinuous transitions is a longstanding problem in the theory of evolution. Continuity being a topological property, we present a formalism that treats the space of phenotypes as a (finite) topological space, with a topology that is derived from the probabilities with which of one phenotype is accessible from another through changes at the genotypic level. The shape space of RNA secondary structures is used to illustrate this approach. We show that evolutionary trajectories are continuous if and only if they follow connected paths in phenotype space.

Nest building was measured in “active ” (housed with access to running wheels) and “sedentary” (without wheel access) mice (Mus domesticus) from four replicate lines selected for 10 generations for high voluntary wheel-running behavior, and from four randombred control lines. Based on previous studies of mice bidirectionally selected for thermoregulatory nest building, it was hypothesized that nest building would show a negative correlated response to selection on wheelrunning. Such a response could constrain the evolution of high voluntary activity because nesting has also been shown to be positively genetically correlated with successful production of weaned pups. With wheel access, selected mice of both sexes built significantly smaller nests than did control mice. Without wheel access, selected females also built significantly smaller nests than did control females, but only when body mass was excluded from the statistical model, suggesting that body mass mediated this correlated response to selection. Total distance run and mean running speed on wheels was significantly higher in selected mice than in controls, but no differences in amount of time spent running were measured, indicating a complex cause of the response of nesting to selection for voluntary wheel running. KEY WORDS: Artificial selection; evolutionary constraint; correlated response; genetic correlation; nesting behavior; wheel-running behavior.

In this paper Lewontin's notion of "quasi-independence" of characters is formalized as the assumption that a region of the phenotype space can be represented by a product space of orthogonal factors. In this picture each character corresponds to a factor of a region of the phenotype space. We consider any region of the phenotype space that has a given factorization as a "type", i.e., as a set of phenotypes that share the same set of phenotypic characters. Using the notion of local factorizations we develop a theory of character identity based on the continuity of common factors among di#erent regions of the phenotype space. We also consider the topological constraints on evolutionary transitions among regions with di#erent regional factorizations, i.e., for the evolution of new types or body plans. It is shown that direct transition between di#erent "types" is only possible if the transitional forms have all the characters that the ancestral and the derived types have and are thus compatible with the factorization of both types. Transitional forms thus have to go over a "complexity hump" where they have more quasi-independent characters than either the ancestral as well as the derived type. The only logical, but biologically unlikely, alternative is a "hopeful monster" that transforms in a single step from the ancestral type to the derived type. Topological considerations also suggest a new factor that may contribute to the evolutionary stability of "types." It is shown that if the type is decomposable into factors which are vertex irregular (i.e. have states that are more or less preferred in a random walk), the region of phenotypes representing the type contains islands of strongly preferred states. In other words types have a statistical tendency of retaining evolu...

Central notions in evolutionary biology are intrinsically topological. This claim is maybe most obvious for the discontinuities associated with punctuated equilibria. Recently, a mathematical framework has been developed that derives the concepts of phenotypic characters and homology from the topological structure of the phenotype space. This structure in turn is determined by the genetic operators and their interplay with the properties of the genotype-phenotype map.

SYNOPSIS. Phenotypes manifest a balance between the inherited tendency to remain the same (phenotypic stability) and the tendency to change in response to current environmental conditions (adaptation). This paper explores the role of functional integration and functional trade-offs in generating phenotypic stability by limiting the responses of individual characters to environmental selection. Evolutionarily stable configurations (ESCs) are systems of functionally interacting characters within which characters are ‘‘judged’ ’ by their contribution to systemlevel functionality. This ‘‘internal’ ’ component of selection differs from traditional ‘‘external’ ’ selection in that it travels with the organism wherever it goes and is maintained across a wide range of environments. External selection, in contrast, is by definition environment-dependent. The temporal and geographic constancy of internal selection therefore acts to maintain phenotypic stability even as environments change. Functional trade-offs occur when one character participates in more than one function, but can only be optimized for one. Participation of certain (‘‘keystone’’) characters in a trade-off potentially causes stabilization of an entire system owing to a cascade of functional dependencies on that character. Phylogenetic character analysis is an essential part of elucidating these processes, but patterns cannot be used as prima facie evidence of particular processes.

Fundamental properties like robustness and evolvability are present in many dynamic systems. In biological systems, for instance, it seems that both properties are in continuous tension. However, this tension provokes throughout evolution the persistence of mutations and the existence of future evolutionary potential for changes. The special characteristics of biological systems, tell us that its distinctive properties could have been developed in pre-biotic era. In other words, the basic properties of life would have been better comprehended if we had realized that they arisen much earlier than previously thought. Hence, it is needed to be aware that it would come when we would hardly be able to find a molecule remotely resembling DNA, RNA, or even proteins. Nevertheless, it seems that a grand evolution must have happened between the phases of protocellular and bacterial evolutionary history. The design of this chapter is focus in proposing a working hypothesis, which addresses the problem of the emergence and self-maintenance of protocellular organization; and also the kind of evolutionary mechanism before life arose. Some results concluded from recent researches indicate that the development of interconnected molecular processes from scratch is possible, which would evolve from random initial conditions. At this point, it is shown that the most primary or basic properties of biological systems found in evolution are connected with new observations, and theoretical and practical implications. This happened due to how prebiotic protocells adapted and survived on that remote era. Moreover, the special self-organizing 1 2 Information and Computation dynamics of biological systems suggests that its distinctive faculties could have been developed in prebiotic era much earlier than hitherto thought.

Response of Sod-2 enzyme activity to selection for high voluntary wheel running