Showing papers on "Evolvability published in 2004"

Evolvability is a selectable trait

Abstract: Concomitant with the evolution of biological diversity must have been the evolution of mechanisms that facilitate evolution, because of the essentially infinite complexity of protein sequence space. We describe how evolvability can be an object of Darwinian selection, emphasizing the collective nature of the process. We quantify our theory with computer simulations of protein evolution. These simulations demonstrate that rapid or dramatic environmental change leads to selection for greater evolvability. The selective pressure for large-scale genetic moves such as DNA exchange becomes increasingly strong as the environmental conditions become more uncertain. Our results demonstrate that evolvability is a selectable trait and allow for the explanation of a large body of experimental results.

Bounded Rationality and the Search for Organizational Architecture: An Evolutionary Perspective on the Design of Organizations and Their Evolvability

Abstract: We employ a computational model of organizational adaptation to answer three research questions: (1) How does the architecture or structure of complexity affect the feasibility and usefulness of bo...

Rupert Riedl and the Re-Synthesis of Evolutionary and Developmental Biology: Body Plans and Evolvability

Abstract: This paper reviews the scientific career of Rupert Riedl and his contributions to evolutionary biology. Rupert Riedl, a native of Vienna, Austria, began his career as a marine biologist who made important contributions to the systematics and anatomy of major invertebrate groups, as well as to marine ecology. When he assumed a professorship at the University of North Carolina in 1968, the predominant thinking in evolutionary biology focused on population genetics, to the virtual exclusion of most of the rest of biology. In this atmosphere Riedl developed his ''systems theory" of evolution, which emphasizes the role of functional and developmental integration in limiting and enabling adaptive evolution by natural selection. The main objective of this theory is to account for the observed patterns of morphological evolution, such as the conservation of body plans. In contrast to other ''alternative'' theories of evolution, Riedl never denied the importance of natural selection as the driving force of evolution, but thought it necessary to contextualize natural selection with the organismal boundary conditions of adaptation. In Riedl's view development is the most important factor besides natural selection in shaping the pattern and processes of morphological evolution. J. Exp. Zool. (Mol. Dev. Evol.) 302B: 92-102, 2004. r 2004 Wiley-Liss, Inc.

Constraints on evolution and postcopulatory sexual selection: trade-offs among ejaculate characteristics.

Abstract: Ejaculates function as an integrated unit to ensure male fertility and paternity, can have a complex structure, and can experience multiple episodes of selection. Current studies on the evolution of ejaculates typically focus on phenotypic variation in sperm number, size, or related traits such as testes size as adaptations to postcopulatory male-male competition. However, the evolution of the integrated nature of ejaculate structure and function depends on genetic variation in and covariation between the component parts. Here we report a quantitative genetic study of the components of the ejaculate of the cockroach Nauphoeta cinerea, including those we know to experience postcopulatory sexual selection, in the context of functional integration of ejaculate characters. We use the patterns of genetic variation and covariation to infer how the integration of the functions of the ejaculate constrain and shape its evolution. Ejaculate components were highly variable, showed significant additive genetic variance, and moderate to high evolvability. The level of genetic variation in these characters, despite strong directional or truncating selection, may reflect the integration of multiple episodes of selection that occur in N. cinerea. There were few significant phenotypic correlations, but all the genetic correlations among ejaculate characters were significantly different from zero. The patterns of genetic variation and covariation suggest that there are important trade-offs among individual traits of the ejaculate and that evolution of ejaculate characteristics will not proceed unconstrained. Fully describing the genetic relationships among traits that perform as an integrated unit helps us understand how functional relationships constrain or facilitate the evolution of the complex structure that is the ejaculate.

Pleiotropy and the Genomic Location of Sexually Selected Genes

Abstract: Sexual selection drives the evolution of traits involved in the competition for mates. Although considerable research has focused on the evolution of sexually selected traits, their underlying genetic architecture is poorly resolved. Here I address the pleiotropic effects and genomic locations of sexually selected genes. These two important characteristics can impose considerable constraints on evolvability and may influence our understanding of the process of sexual selection. Theoretical models are inconsistent regarding the genomic location of sexually selected genes. Models that do not incorporate pleiotropic effects often predict sex linkage. Conversely, sex linkage is not explicitly predicted by the condition-dependent model (which considers pleiotropic effects). Evidence largely based on reciprocal crosses supports the notion of sex linkage. However, although they infer genetic contribution, reciprocal crosses cannot identify the genes or their pleiotropic effects. By surveying the genome of Drosophila melanogaster, I provide evidence for the genomic location and pleiotropic effects of 63 putatively sexually selected genes. Interestingly, most are pleiotropic (73%), and they are not preferentially sex linked. Their pleiotropic effects include fertility, development, life span, and viability, which may contribute to condition and/or fitness. My findings may also provide evidence for the capture of genetic variation in condition via the pleiotropic effects of sexually selected genes.

Evolution of a subsumption architecture neurocontroller

Abstract: An approach to robotics called layered evolution and merging features from the subsumption architecture into evolutionary robotics is presented, and its advantages are discussed. This approach is used to construct a layered controller for a simulated robot that learns which light source to approach in an environment with obstacles. The evolvability and performance of layered evolution on this task is compared to (standard) monolithic evolution, incremental and modularised evolution. To corroborate the hypothesis that a layered controller performs at least as well as an integrated one, the evolved layers are merged back into a single network. On the grounds of the test results, it is argued that layered evolution provides a superior approach for many tasks, and it is suggested that this approach may be the key to scaling up evolutionary robotics.

Fractal Proteins

Abstract: The fractal protein is a new concept intended to improve evolvability, scalability, exploitability and provide a rich medium for evolutionary computation. Here the idea of fractal proteins and fractal proteins with concentration levels are introduced, and a series of experiments showing how evolution can design and exploit them within gene regulatory networks is described.

Clarifying biotic homogenization.

Abstract: nouns – ‘hierarchy’, ‘connec- tivity’, ‘evolvability’, ‘complexity’ to name four – are becoming increasingly popular as evolutionary developmental biology tries to find its theoretical feet. With Gerhard Schlosser, an amphibian developmental biologist, Gunter Wagner has brought together a stellar team of contributors to discuss the abstract noun du jour, ‘modularity.’ In Modularity in Development and Evolution, we can read contributions from 42 authors, many of them distinguished, about topics as diverse as basic helix– loop–helix transcription factors, data-mining genome- wide expression data, vertebrate limbs, nematode vulvas and Wolbachia symbionts. Unsurprisingly, all authors agree that modularity is very important to development. The question is: what do they mean? The answer is: many different things. The editors make a brave attempt to keep matters under control by defining modules as structures or processes composed of tightly integrated parts, whilst being relatively autonomous from their surroundings. For developmental geneticists, modules are thereforegroups ofproteins that worktogether tospecify cells [e.g. the Notch–Delta–Su(H), pathway]. For a quan- titative geneticist, modules can be seen in the distribution of the pleiotropic effects of quantitative trait loci, which control various morphological traits. Developmental neurobiolo- gists point to embryologically and functionally distinct units of the central nervous system, whereas a nematode geneticist points to cells. Bioinformaticists see modules in ‘synexpression groups’ – clusters of co-ordinately regulated genes visible from expression profiling studies; dynamic systems modelers see them as networks of genes necessary and sufficient for carrying out a particular function; a complexity theorist sees them in basins of attraction in random boolean networks. And this is only a partial list. The sheer ubiquity of modular things, whatever those happen to be, suggests that modules matter to development. Having said that, one has the feeling that many contributors are cherry-picking the data. They are looking for, and finding, modules whilst ignoring non-modules. The problem seems to be that the modularity of things is, as the editors point out, a matter of degree. However, there is no formal theory of modularity and, in the absence of that, no consensus about how to measure it. The result is that we are invariably given the history of a case rather than a sense of its distribution. This is a natural history of modules. What about their evolution? As with more mundane attributes that organisms might have, say, parental care or wings, evolutionary biologists want to know several things about them. Why do modules exist? Are they the result of natural selection? Or can mutation and drift explain their presence? If selection, what kind of selection? We also want know how they evolve. If a module is found in Caenor- habditis elegans, is it also found in another nematode species? A fruit-fly? Humans? Are modules more con- served than non-modules? Has modularity – like complex- ity – increased over the course of evolution? These are important but difficult questions, and the contributors give a diversity of answers. Taking the last set of questions first, (how do modules evolve), it seems that sophisticated comparative studies of the evolution of modules are some way off. This is not a criticism: such studies need lots of data, which hardly exist outside of a few model organisms – but they will surely come. Why do modules exist? Some contributors seem to view modularity asanemergentpropertyofgeneticnetworks.Otherssuggest that developmental modularity evolves for its variational properties – it enables organisms to be more resistant to environmentalormutationalperturbations.Thesplithereis analogous to the Wright–Fisher dispute over dominance. Others again, suggest that modules permit evolvability (i.e. the production of heritable, selectable, phenotypic variation). This is a clade-selection argument – with all the weaknesses of such arguments. Many contributors hedge their bets by citing some or all of the above without considering the matter too deeply. But more careful discussions can be found in at least two papers. Force, Cresko and Pickett argue that ‘genotypic modularity’ – the use of genes in particular places and times independently of other genes – can increase simply as a consequence of Corresponding author: Armand M. Leroi (a.leroi@ic.ac.uk). Update TRENDS in Ecology and Evolution Vol.19 No.6 June 2004 284 www.sciencedirect.com

Towards more biological mutation operators in gene regulation studies

Abstract: Genetic regulation is often viewed as a complex system whose properties emerge from the interaction of regulatory genes. One major paradigm for studying the complex dynamics of gene regulation uses directed graphs to explore structure, behaviour and evolvability. Mutation operators used in such studies typically involve the insertion and deletion of nodes, and the insertion, deletion and rewiring of links at the network level. These network-level mutational operators are sufficient to allow the statistical analysis of network structure, but impose limitations on the way networks are evolved. There are a wide variety of mutations in DNA sequences that have yet to be analysed for their network-level effects. By modelling an artificial genome at the level of nucleotide sequences and mapping it to a regulatory network, biologically grounded mutation operators can be mapped to network-level mutations. This paper analyses five such sequence level mutations (single-point mutation, transposition, inversion, deletion and gene duplication) for their effects at the network level. Using analytic and simulation techniques, we show that it is rarely the case that nodes and links are cleanly added or deleted, with even the simplest point mutation causing a wide variety of network-level modifications. As expected, the vast majority of simple (single-point) mutations are neutral, resulting in a neutral plateau from which a range of functional behaviours can be reached. By analysing the effects of sequence-level mutations at the network level of gene regulation, we aim to stimulate more careful consideration of mutation operators in gene regulation models than has previously been given.

Generative Entrenchment, Modularity and Evolvability: When Genic Selection meets the Whole Organism 1

Abstract: Generative Entrenchment, Modularity and Evolvability: When Genic Selection meets the Whole Organism W. C. Wimsatt Department of Philosophy, Committee on the Conceptual Foundations of Science, and the Committee on Evolutionary Biology The University of Chicago w-wimsatt@midway.uchicago.edu and J. C. Schank Department of Psychology and Animal Behavior Graduate Group University of California, Davis jcschank@ucdavis.edu June 25, 2002 Proof revisions: (minor add’s 6-2-03)

Evolvable social agents for bacterial systems modeling

Abstract: We present two approaches to the individual-based modeling (IbM) of bacterial ecologies and evolution using computational tools. The IbM approach is introduced, and its important complementary role to biosystems modeling is discussed. A fine-grained model of bacterial evolution is then presented that is based on networks of interactivity between computational objects representing genes and proteins. This is followed by a coarser grained agent-based model, which is designed to explore the evolvability of adaptive behavioral strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of the two proposed individual-based bacterial models are discussed, and some results from simulation experiments are presented, illustrating their adaptive properties.

Natural selection, evolvability and bias due to environmental covariance in the field in an annual plant

Abstract: Estimates of the form and magnitude of natural selection based on phenotypic relationships between traits and fitness measures can be biased when environmental factors influence both relative fitness and phenotypic trait values. I quantified genetic variances and covariances, and estimated linear and quadratic selection coefficients, for seven traits of an annual plant grown in the field. For replicates of 50 paternal half-sib families, coefficients of selection were calculated both for individual phenotypic values of the traits and for half-sib family mean values. The potential for evolutionary response was supported by significant heritability and phenotypic directional selection for several traits but contradicted by the absence of significant genetic variation for fitness estimates and evidence of bias in phenotypic selection coefficients due to environmental covariance for at least two of the traits analysed. Only studies of a much wider range of organisms and traits will reveal the frequency and extent of such bias.

The influence of the level of abstraction on the evolvability of conceptual models of information systems

Abstract: Over the years, we have seen an increase in the level of abstraction used in building software. Academic and practitioners' literature contains numerous but vague claims that software based on abstract conceptual models (such as analysis and design patterns, frameworks and software architectures) has evolvability advantages. Our study validates these claims. We investigate evolvability at the analysis level, i.e. at the level of the conceptual models that are built of information systems (e.g. UML-models). More specifically, we focus on the influence of the level of abstraction of the conceptual model on the evolvability of the model. Hypotheses were tested with regard to whether the level of abstraction influences the time needed to apply a change, the correctness of the change and the structure degradation incurred. Two controlled experiments were conducted with 136 subjects. Correctness and structure degradation were rated by human experts. Results indicate that, for some types of change, abstract models are better evolvable than concrete ones. Our results provide insight into how the rather vague claims in literature should be interpreted.

Modelling biological evolvability: implicit context and variation filtering in enzyme genetic programming.

Abstract: This paper describes recent insights into the role of implicit context within the representations of evolving artefacts and specifically within the program representation used by enzyme genetic programming. Implicit context occurs within self-organising systems where a component’s connectivity is both determined implicitly by its own definition and is specified in terms of the behavioural context of other components. This paper argues that implicit context is an important source of evolvability and presents experimental evidence that supports this assertion. In particular, it introduces the notion of variation filtering, suggesting that the use of implicit context within representations leads to meaningful variation filtering whereby inappropriate change is ignored and meaningful change is encouraged during evolution.

Scuba search: when selection meets innovation

Abstract: We proposed a search heuristic using the scuba diving metaphor. This approach is based on the concept of evolvability and tends to exploit neutrality in fitness landscape. Despite the fact that natural evolution does not directly select for evolvability, the basic idea behind the scuba search heuristic is to explicitly push evolvability to increases. Globally the search process switches between two phases: conquest-of-the-waters and invasion-of-the-land. A comparative study of the algorithm and standard local search heuristics on the NKq-landscapes has shown advantage and limit of the scuba search. To enlighten qualitative differences between neutral search processes, the space is transformed into a connected graph to visualize the pathways that the search is likely to follow.

Evolving beyond perfection: an investigation of the effects of long-term evolution on fractal gene regulatory networks

Abstract: This paper continues a theme of exploring algorithms based on principles of biological development for tasks such as pattern generation, machine learning and robot control. Previous work has investigated the use of genes expressed as fractal proteins to enable greater evolvability of gene regulatory networks (GRNs). Here, the evolution of such GRNs is investigated further to determine whether evolution exhibits natural tendencies towards efficiency and graceful degradation of developmental programs. Experiments where "perfect" GRNs are evolved for a further thousand generations without the addition of any further selection pressure, confirm this hypothesis. After further evolution, the perfect GRNs operate in a more efficient manner (using fewer proteins) and show an improved ability to function correctly with missing genes. When the algorithm is applied to applications (e.g. robot control) this equates to efficient and fault-tolerant controllers.

Using Embryonic Stages to increase the evolvability of development

Abstract: Indirect encoding methods are aimed at the reduction of the combinatorial explosion of search spaces, therefore increasing the evolvability of large phenotypes. These so called Artificial Embryogeny systems have so far shown increased scalability for problems involving solutions of low complexity. This leaves open the more general question about the evolvability of complex phenotypes. In this paper, we introduce a novel method of cellular growth regulated by a developmental program. Genotypes are selected for their ability to develop organisms of specific shape and cell types. Results show that the use of Embryonic Stages, which involves the incremental addition of growth programs, displays positive effects on the evolvability of development.

Implicit Evolvability: An Investigation into the Evolvability of an Embryogeny

Abstract: This paper investigates the evolvability of an implicit embryogeny-based representation for the evolution of 3-D morphologies Previous results using this representation have shown that this particular incarnation of an implicit embryogeny does not lend itself well to evolution Two different experiments are described, the results of which suggest that a many-to-one genotypeto-phenotype mapping is not sufficient to ensure evolvability The paper concludes by suggesting attributes that a better representation should have

Modularity and the evolution of software evolvability

Abstract: Drawing on models of the evolution of living systems, this dissertation explores the principle of modularity, both biological and in software, and its role in creating structures that are easy to change. These ideas are captured in the Software Evolvability Change Optimization (SECO) model, a framework for investigating how modularity can enhance evolvability in software. SEGO abstracts software history by dividing the code into non-overlapping elements that are linked together by a series of changes. These changes are either gathered from the recorded histories of real software, or modeled using evolutionary computation, change propagation among elements, or correlations in changes between elements. The dissertation uses SECO in both an analytic and synthetic role, investigating aspects of modularity such as encapsulation and code factoring, and using automatic techniques to optimize the modular structure of real code. The dissertation contributes to the further understanding of modularity as a means of improving software evolvability by adding the dimension of time to the analysis. In this way, it can discover dependency links between software elements that are not evident from a static analysis of the program.

Individual-Based Modelling of Bacterial Ecologies and Evolution

Abstract: This paper presents two approaches to the individual-based modelling of bacterial ecologies and evolution using computational tools. The first approach is a fine-grained model that is based on networks of interactivity between computational objects representing genes and proteins. The second approach is a coarser-grained, agent-based model, which is designed to explore the evolvability of adaptive behavioural strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of these computational models is discussed, and some results from simulation experiments are presented. Finally, the potential applications of the proposed models to the solution of real-world computational problems, and their use in improving our understanding of the mechanisms of evolution, are briefly outlined.

Channelling evolution: canalization and the nervous system.

Abstract: Individuals within a wild population show remarkably little morphological variation, given the amount of environmental variation they encounter during development and the amount of genetic variation within the population. This phenotypic constancy led to the proposal that individuals were somehow buffered, or canalized, against genetic and environmental variation (Waddington 1942). Clearly, such a mechanism would have important evolutionary consequences; because natural selection acts upon phenotypic variation within a population, canalization first appears to reduce the evolvability of the trait upon which it is acting (Gibson and Wagner 2000). However, canalization also reduces the effects of new mutations (which may be deleterious), potentially allowing individuals to store this genetic variation without suffering the consequences. If canalization breaks down due to genetic or environmental circumstances, then the stored genetic variation will be released, providing an additional substrate for natural selection. In this way, individuals could potentially undergo large, rapid phenotypic changes. Experiments in both Drosophila and Arabidopsis have suggested that Hsp90 (heat shock protein 90), a member of a family of proteins expressed at high temperatures (heat shock), may be an excellent candidate for bringing about canalization (Rutherford and Lindquist 1998; Queitsch et al. 2002). Several features of Hsp90 suggest that it is an evolutionary buffer, capable of hiding and then releasing genetic variation: (1) individuals heterozygous for mutations in Hsp83 (the gene encoding Hsp90) show increased levels of morphological abnormalities; (2) individuals treated with a pharmacological inhibitor of Hsp90 show severe morphological abnormalities; (3) the normal function of Hsp90 is to stabilise the tertiary structure of signal transduction molecules involved in developmental pathways; and (4) this function may be compromised by environmental factors, e.g., heat shock.

A Quantitative Approach to Assessing System Evolvability

Abstract: When selecting a system from multiple candidates, the customer seeks the one that best meets his or her needs. Recently the desire for evolvable systems has become more important and engineers are striving to develop systems that accommodate this need. In response to this search for evolvability, we present a historical perspective on evolvability, propose a refined definition of evolvability, and develop a quantitative method for measuring this property. We address this quantitative methodology from both a theoretical and practical perspective. This quantitative model is then applied to the problem of evolving a lunar mission to a Mars mission as a case study.

Enzyme Genetic Programming.

Abstract: The work reported in the paper follows from the hypothesis that better performance in certain domains of artificial evolution can be achieved by adhering more closely to the features that make natural evolution effective within biological systems. An important issue in evolutionary computation is the choice of solution representation. Genetic programming, whilst borrowing from biology in the evolutionary axis of behaviour, remains firmly rooted in the artificial domain with its use of a parse tree representation. Following concerns that this approach does not encourage solution evolvability, the paper presents an alternative method modelled upon representations used by biology. Early results are encouraging, demonstrating that the method is competitive when applied to problems in the area of combinatorial circuit design.

Investigating the evolvability of biologically inspired CA.

Abstract: The developmental processes studied by biologists are emergent self organised processes that are the result of natural evolution. Developmental biology can be a good inspiration for anyone interested in evolving self organised discrete systems like Cellular Automata: nature has proved that evolving self organisation is possible. In this paper, we will describe EmbryoCA, a model of 3D Cellular Automata for pattern generation. Developmental biology has been used as an inspiration to design EmbryoCA and make the model more gradual in the hope of having a more evolvable type of CA. Also, experiments comparing the evolvability of different setups of EmbryoCA with a conventional CA model are shown.

How to evolve the head-tail pattern from reaction-diffusion systems

Abstract: The possible application of evolving artificial embryos to build functional machinery is a promising area of research. Unfortunately, there are still many fundamental problems to be solved before artificial embryology can be applied to such tasks, not to mention the necessary hardware. In this paper we address the problem of how to evolve the head-tail pattern for an artificial embryo endogenously, without predefined asymmetric cell division or external guide through polar cells or exogenous sources of morphogenes. We examine the performance of an evolutionary algorithm on two different fitness functions. Further, we examine the evolvability of several mathematical models for regulatory networks, controlling the behavior of the digital embryo.

Effect of captivity on genetic variance for five traits in the large milkweed bug (Oncopeltus fasciatus).

Abstract: Understanding the changes in genetic variance which may occur as populations move from nature into captivity has been considered important when populations in captivity are used as models of wild ones. However, the inherent significance of these changes has not previously been appreciated in a conservation context: are the methods aimed at founding captive populations with gene diversity representative of natural populations likely also to capture representative quantitative genetic variation? Here, I investigate changes in heritability and a less traditional measure, evolvability, between nature and captivity for the large milkweed bug, Oncopeltus fasciatus, to address this question. Founders were collected from a 100-km transect across the north-eastern US, and five traits (wing colour, pronotum colour, wing length, early fecundity and later fecundity) were recorded for founders and for their offspring during two generations in captivity. Analyses reveal significant heritable variation for some life history and morphological traits in both environments, with comparable absolute levels of evolvability across all traits (0-30%). Randomization tests show that while changes in heritability and total phenotypic variance were highly variable, additive genetic variance and evolvability remained stable across the environmental transition in the three morphological traits (changing 1-2% or less), while they declined significantly in the two life-history traits (5-8%). Although it is unclear whether the declines were due to selection or gene-by-environment interactions (or both), such declines do not appear inevitable: captive populations with small numbers of founders may contain substantial amounts of the evolvability found in nature, at least for some traits.

Unifying static and dynamic approaches to evolution through the compliant systems architecture

Abstract: Support for evolution can be classified as static or dynamic. Static evolvability is principally concerned with structuring systems as separated abstractions. Dynamic evolvability is concerned with the means by which change is effected. Dynamic evolution provides the requisite flexibility for application evolution, however, the dynamic approach is not scalable in the absence of static measures to achieve separation of abstractions. This separation comes at a price in that issues of concern become trapped within static abstraction boundaries, thereby inhibiting dynamic evolution. The need for a unified approach has long been recognised but existing systems that attempt to address this need do so in an ad-hoc manner. The principal reason for this is that these approaches fail to resolve the incongruence in the underlying models. Our contention is that this disparity is incidental rather than fundamental to the problem. To this end, we propose an alternative model based on the compliant systems architecture (CSA), a structuring methodology for constructing software systems. The overriding benefit of this work is increased flexibility. Specifically our contribution is an instantiation of the CSA that supports unified static and dynamic evolution techniques. Our model is explored through a worked example in which we evolve an application's concurrency model.