Showing papers on "Evolvability published in 2010"
TL;DR: It is demonstrated, using a general population genetics model, that mutational robustness can either impede or facilitate adaptation, depending on the population size, the mutation rate and the structure of the fitness landscape, which provides a quantitative resolution to a significant ambiguity in evolutionary theory.
Abstract: The role of mutational robustness in evolution has been a topic of much debate and controversy. On the one hand, it would seem to impede adaptation by making it less easy for a new phenotype to develop in the event of environmental changes; on the other it is surely advantageous for an organism to buffer its phenotype against possibly unhelpful mutations. How can an organism handle this paradox, and be both robust and adaptable? A quantitative population genetics model gives a possible resolution to this problem, by showing that mutational robustness can either impede or facilitate adaptation, depending on the population size, the mutation rate and the structure of the fitness landscape. If robustness is the opposite of evolvability, we might expect that a robust population would have difficulty adapting to environmental change; however, some studies have suggested that genetic robustness facilitates adaptation. Here, using a general population genetics model, mutational robustness is found to either impede or facilitate adaptation depending on the population size, the mutation rate and the structure of the fitness landscape. Robustness seems to be the opposite of evolvability. If phenotypes are robust against mutation, we might expect that a population will have difficulty adapting to an environmental change, as several studies have suggested1,2,3,4. However, other studies contend that robust organisms are more adaptable5,6,7,8. A quantitative understanding of the relationship between robustness and evolvability will help resolve these conflicting reports and will clarify outstanding problems in molecular and experimental evolution, evolutionary developmental biology and protein engineering. Here we demonstrate, using a general population genetics model, that mutational robustness can either impede or facilitate adaptation, depending on the population size, the mutation rate and the structure of the fitness landscape. In particular, neutral diversity in a robust population can accelerate adaptation as long as the number of phenotypes accessible to an individual by mutation is smaller than the total number of phenotypes in the fitness landscape. These results provide a quantitative resolution to a significant ambiguity in evolutionary theory.
352 citations
TL;DR: Tropical Drosophila species do not appear more threatened than temperate species by higher temperatures associated with global warming, contrary to recent conjectures, but species from the humid tropics may be threatened if they cannot adapt genetically to drier conditions.
Abstract: Physiological limits determine susceptibility to environmental changes, and can be assessed at the individual, population or species/lineage levels. Here I discuss these levels in Drosophila, and consider implications for determining species susceptibility to climate change. Limits at the individual level in Drosophila depend on experimental technique and on the context in which traits are evaluated. At the population level, evidence from selection experiments particularly involving Drosophila melanogaster indicate high levels of heritable variation and evolvability for coping with thermal stresses and aridity. An exception is resistance to high temperatures, which reaches a plateau in selection experiments and has a low heritability/evolvability when temperatures are ramped up to a stressful level. In tropical Drosophila species, populations are limited in their ability to evolve increased desiccation and cold resistance. Population limits can arise from trait and gene interactions but results from different laboratory studies are inconsistent and likely to underestimate the strength of interactions under field conditions. Species and lineage comparisons suggest phylogenetic conservatism for resistance to thermal extremes and other stresses. Plastic responses set individual limits but appear to evolve slowly in Drosophila. There is more species-level variation in lower thermal limits and desiccation resistance compared with upper limits, which might reflect different selection pressures and/or low evolvability. When extremes are considered, tropical Drosophila species do not appear more threatened than temperate species by higher temperatures associated with global warming, contrary to recent conjectures. However, species from the humid tropics may be threatened if they cannot adapt genetically to drier conditions.
331 citations
TL;DR: The evidence supports the claim that robustness promotes evolvability by showing that the true distinction is whether recombination rates are high or low.
267 citations
TL;DR: The concept of ‘developmental encoding’ (as opposed to the classical one of genetic encoding) provides a promising computational–theoretical underpinning to coherently integrate ideas on evolvability, modularity and robustness and foster a fruitful framing of the G→P mapping problem.
Abstract: In a now classic paper published in 1991, Alberch introduced the concept of genotype–phenotype (G→P) mapping to provide a framework for a more sophisticated discussion of the integration between genetics and developmental biology that was then available. The advent of evo-devo first and of the genomic era later would seem to have superseded talk of transitions in phenotypic space and the like, central to Alberch's approach. On the contrary, this paper shows that recent empirical and theoretical advances have only sharpened the need for a different conceptual treatment of how phenotypes are produced. Old-fashioned metaphors like genetic blueprint and genetic programme are not only woefully inadequate but positively misleading about the nature of G→P, and are being replaced by an algorithmic approach emerging from the study of a variety of actual G→P maps. These include RNA folding, protein function and the study of evolvable software. Some generalities are emerging from these disparate fields of analysis, and I suggest that the concept of ‘developmental encoding’ (as opposed to the classical one of genetic encoding) provides a promising computational–theoretical underpinning to coherently integrate ideas on evolvability, modularity and robustness and foster a fruitful framing of the G→P mapping problem.
241 citations
TL;DR: It is demonstrated that both humans and apes exhibit significantly reduced integration between limbs when compared to quadrupedal monkeys, indicating that fossil hominins likely escaped constraints on independent limb variation via reductions to genetic pleiotropy in an ape-like last common ancestor (LCA).
Abstract: The long legs and short arms of humans are distinctive for a primate, the result of selection acting in opposite directions on each limb at different points in our evolutionary history. This mosaic pattern challenges our understanding of the relationship of development and evolvability because limbs are serially homologous and genetic correlations should act as a significant constraint on their independent evolution. Here we test a developmental model of limb covariation in anthropoid primates and demonstrate that both humans and apes exhibit significantly reduced integration between limbs when compared to quadrupedal monkeys. This result indicates that fossil hominins likely escaped constraints on independent limb variation via reductions to genetic pleiotropy in an ape-like last common ancestor (LCA). This critical change in integration among hominoids, which is reflected in macroevolutionary differences in the disparity between limb lengths, facilitated selection for modern human limb proportions and demonstrates how development helps shape evolutionary change.
219 citations
TL;DR: It is shown that the design principles used to achieve robustness dramatically influence whether robustness leads to evolvability, and that degeneracy, a ubiquitous characteristic in biological systems, may be an important enabler of natural evolution.
190 citations
TL;DR: Evidence is presented that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability.
Abstract: A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology. This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability.
173 citations
TL;DR: Approaches for gaining further insights into the causes of genetic convergence and their potential contribution to the authors' understanding of how the genetic background determines the evolvability of complex organismal traits are discussed.
169 citations
TL;DR: It is demonstrated here that replication of compositional information is so inaccurate that fitter compositional genomes cannot be maintained by selection and the system lacks evolvability, cautions against metabolism-first theories of the origin of life, although ancient metabolic systems could have provided a stable habitat within which polymer replicators later evolved.
Abstract: A basic property of life is its capacity to experience Darwinian evolution. The replicator concept is at the core of genetics-first theories of the origin of life, which suggest that self-replicating oligonucleotides or their similar ancestors may have been the first “living” systems and may have led to the evolution of an RNA world. But problems with the nonenzymatic synthesis of biopolymers and the origin of template replication have spurred the alternative metabolism-first scenario, where self-reproducing and evolving proto-metabolic networks are assumed to have predated self-replicating genes. Recent theoretical work shows that “compositional genomes” (i.e., the counts of different molecular species in an assembly) are able to propagate compositional information and can provide a setup on which natural selection acts. Accordingly, if we stick to the notion of replicator as an entity that passes on its structure largely intact in successive replications, those macromolecular aggregates could be dubbed “ensemble replicators” (composomes) and quite different from the more familiar genes and memes. In sharp contrast with template-dependent replication dynamics, we demonstrate here that replication of compositional information is so inaccurate that fitter compositional genomes cannot be maintained by selection and, therefore, the system lacks evolvability (i.e., it cannot substantially depart from the asymptotic steady-state solution already built-in in the dynamical equations). We conclude that this fundamental limitation of ensemble replicators cautions against metabolism-first theories of the origin of life, although ancient metabolic systems could have provided a stable habitat within which polymer replicators later evolved.
164 citations
Book•
04 Jun 2010
TL;DR: This book discusses Evolutionary Biology since Darwin, the Origin and Early Evolution of Life, and the role of culture in Human Evolution in the next 150 years.
Abstract: PART I: EVOLUTION SINCE DARWIN Evolutionary Biology: 150 Years of Progress D.J.Futuyma Rethinking Darwin's Position in the History of Science P.J.Bowler Commentary 1: Where Are We? Historical Reflections on Evolutionary Biology in the Twentieth Century V.B.Smocovitis PART II: POPULATION, GENES, AND GENOMES The Concepts of 'Population' and 'Metapopulation' in Evolutionary Biology and Ecology R.L.Millstein Evolutionary Genetics: Progresses and Challenges J.G.Zhang Natural Selection and Coalescent Theory J.Wakeley On the Power of Comparative Genomics: Does Conservation Imply Function? B.Kolaczkowski & A.D.Kern Commentary 2: The Potential for Microorganisms and Experimental Studies in Evolutionary Biology D.E.Dykhuizen PART III: THE EVOLUTION OF FORM Limits on Rates of Adaptation: Why Is Darwin's Machine So Slow? M.Kirkpatrick Evolvability: The Missing Piece of the Neo-Darwinian Synthesis G.P.Wagner Embryos and Evolution: 150 Years of Reciprocal Illumination G.A.Wray PART IV: ADAPTATION AND SPECIATION Tradeoffs and Negative Correlations in Evolutionary Ecology A.Agrawal, J.K.Conner & S.Rasmann Elucidating Evolutionary Mechanisms in Plant--Insect Interactions: Key Residues as Key Innovations M.Berenbaum & M.A.Schuler Behavioral Ecology: The Natural History of Evolutionary Theory H.Kokko & M.D.Jennions Understanding the Origin of Species: Where Have We Been, Where Are We Going? R.G.Harrison Commentary 3: The Role of Ecology in Evolutionary Biology M.A.McPeek PART V: DIVERSITY AND THE TREE OF LIFE The Origin and Early Evolution of Life: Did It All Start in Darwin's Warm Little Pond? A.Lazcano Commentary 4: The Genomic Imprint of Endosymbiosis C.E.Lane Adaptive Radiation: The Interaction of Ecological Opportunity, Adaptation, and Speciation J.B.Losos & D.L.Mahler Phylogenetic Progress and Applications of the Tree of Life D.M.Hillis Paleontological Perspectives on Morphological Change P.J.Wagner The Geological History of Biodiversity M.Foote Commentary 5: Thinking about Diversity and Diversification: What If Biotic History Is Not Equilibrial? J.Cracraft PART VI: HUMAN EVOLUTION Hominid Paleobiology: How Has Darwin Done? T.D.White Darwin on the Role of Culture in Human Evolution P.J.Richerson & R.Boyd PART VII: APPLICATIONS OF EVOLUTIONARY BIOLOGY Applying Evolutionary Biology: From Retrospective Analysis to Direct Manipulation F.Gould Commentary 6: A Clade's-Eye View of Global Climate Change C.C.Davis, E.J.Edwards & M.J.Donoghue PART VIII: PROSPECTS Evolutionary Biology: The Next 150 Years H.E.Hoekstra Commentary 7: Towards a More Richly Integrated Biology C.Marshall Commentary 8: Balance between Organismal and Molecular Training J.Rest
154 citations
TL;DR: This article reviews some of the mechanisms that have been identified in viral emergence, with a focus on the importance of genetic variation of viruses, and on the general concept of biological complexity.
Abstract: A number of virologic and environmental factors are involved in the emergence and re-emergence of viral disease. Viruses do not conservatively occupy a single and permanent ecological niche. Rather, due to their intrinsic capacity for genetic change, and to the evolvability of fitness levels, viruses display a potential to parasitize alternative host species. Mutation, recombination and genome segment reassortment, and combination of these molecular events, produce complex and phenotypically diverse populations of viruses, which constitute the raw material on which selection acts. The majority of emerging viral diseases of humans have a zoonotic origin. Sociologic and ecologic factors produce diverse and changing environments in which viral subpopulations have ample opportunities to be selected from intrinsically heterogeneous viral populations, particularly in the case of RNA viruses. In this manner, new human, animal and plant viruses have emerged periodically and, from all evidence, will continue to emerge. This article reviews some of the mechanisms that have been identified in viral emergence, with a focus on the importance of genetic variation of viruses, and on the general concept of biological complexity.
TL;DR: The results establish quantitative expectations for how a mutation with a given deleterious fitness effect should influence evolvability, and they will inform future studies of how deleteriously, neutral, and beneficial mutations targeting other cellular processes impact the evolutionary potential of microorganisms.
Abstract: Evolvability is the capacity of an organism or population for generating descendants with increased fitness. Simulations and comparative studies have shown that evolvability can vary among individuals and identified characteristics of genetic architectures that can promote evolvability. However, little is known about how the evolvability of biological organisms typically varies along a lineage at each mutational step in its history. Evolvability might increase upon sustaining a deleterious mutation because there are many compensatory paths in the fitness landscape to reascend the same fitness peak or because shifts to new peaks become possible. We use genetic marker divergence trajectories to parameterize and compare the evolvability--defined as the fitness increase realized by an evolving population initiated from a test genotype--of a series of Escherichia coli mutants on multiple timescales. Each mutant differs from a common progenitor strain by a mutation in the rpoB gene, which encodes the beta subunit of RNA polymerase. Strains with larger fitness defects are proportionally more evolvable in terms of both the beneficial mutations accessible in their immediate mutational neighborhoods and integrated over evolutionary paths that traverse multiple beneficial mutations. Our results establish quantitative expectations for how a mutation with a given deleterious fitness effect should influence evolvability, and they will thus inform future studies of how deleterious, neutral, and beneficial mutations targeting other cellular processes impact the evolutionary potential of microorganisms.
TL;DR: It is concluded that complex multicellular organisms and colonies of eusocial insects satisfy these three criteria, but that, in most cases (with at least one notable exception), colonies of modular organisms and genetic chimeras do not.
Abstract: Most biologists implicitly define an individual organism as “one genome in one body.” This definition is based on physiological and genetic criteria, but it is problematic for colonial organisms. We propose a definition based instead on the evolutionary criteria of alignment of fitness, export of fitness by germ‐soma specialization, and adaptive functional organization. We consider how these concepts apply to various putative individual organisms. We conclude that complex multicellular organisms and colonies of eusocial insects satisfy these three criteria, but that, in most cases (with at least one notable exception), colonies of modular organisms and genetic chimeras do not. While species do not meet these criteria, they may meet the criteria for a broader concept—that of an evolutionary individual—and sexual reproduction may be a species‐level exaptation for enhancing evolvability. We also review the costs and benefits of internal genetic heterogeneity within putative individuals, demonstratin...
TL;DR: The results suggest that high levels of resistance may be selected for without necessarily jeopardizing overall fitness.
Abstract: Whether a trade-off exists between robustness and evolvability is an important issue for protein evolution. Although traditional viewpoints have assumed that existing functions must be compromised by the evolution of novel activities, recent research has suggested that existing phenotypes can be robust to the evolution of novel protein functions. Enzymes that are targets of antibiotics that are competitive inhibitors must evolve decreased drug affinity while maintaining their function and sustaining growth. Utilizing a transgenic Saccharomyces cerevisiae model expressing the dihydrofolate reductase (DHFR) enzyme from the malarial parasite Plasmodium falciparum, we examine the robustness of growth rate to drug-resistance mutations. We assay the growth rate and resistance of all 48 combinations of 6 DHFR point mutations associated with increased drug resistance in field isolates of the parasite. We observe no consistent relationship between growth rate and resistance phenotypes among the DHFR alleles. The three evolutionary pathways that dominate DHFR evolution show that mutations with increased resistance can compensate for initial declines in growth rate from previously acquired mutations. In other words, resistance mutations that occur later in evolutionary trajectories can compensate for the fitness consequences of earlier mutations. Our results suggest that high levels of resistance may be selected for without necessarily jeopardizing overall fitness.
TL;DR: Five emerging themes from the molecular study of osmotic stress response are discussed: the multigenic nature of adaptive response, the modular organization of response to specific cues, the pleiotropic effects of key signaling proteins, the integration of many environmental signals, and the abundant cross‐talk between signaling pathways.
Abstract: Progress in understanding the mechanisms of adaptive plant abiotic stress response has historically come from two separate fields. Molecular biologists employ mutagenic screens, experimental manipulations, and controlled stress treatment to identify genes that, when perturbed, have fairly large effects on phenotype. By contrast, quantitative and evolutionary geneticists generally study naturally occurring variants to inform multigenic models of trait architecture in an effort to predict, for example, the evolutionary response to selection. We discuss five emerging themes from the molecular study of osmotic stress response: the multigenic nature of adaptive response, the modular organization of response to specific cues, the pleiotropic effects of key signaling proteins, the integration of many environmental signals, and the abundant cross-talk between signaling pathways. We argue that these concepts can be incorporated into existing models of trait evolution and provide examples of what may constitute the molecular basis of plasticity and evolvability of abiotic stress response. We conclude by considering future directions in the study of the functional molecular evolution of abiotic stress response that may facilitate new discoveries in molecular biology, evolutionary studies, and plant breeding.
TL;DR: Epigenetic mechanisms appear to function primarily as genome defences, but result in the maintenance of plasticity together with a degree of buffering of developmental programmes; periodic breakdown of epigenetic buffering could potentially cause variation in rates of phenotypic evolution.
Abstract: Epigenetics has progressed rapidly from an obscure quirk of heredity into a data-heavy ‘omic’ science. Our understanding of the molecular mechanisms of epigenomic regulation, and the extent of its importance in nature, are far from complete, but in spite of such drawbacks, population-level studies are extremely valuable: epigenomic regulation is involved in several processes central to evolutionary biology including phenotypic plasticity, evolvability and the mediation of intragenomic conflicts. The first studies of epigenomic variation within populations suggest high levels of phenotypically relevant variation, with the patterns of epigenetic regulation varying between individuals and genome regions as well as with environment. Epigenetic mechanisms appear to function primarily as genome defences, but result in the maintenance of plasticity together with a degree of buffering of developmental programmes; periodic breakdown of epigenetic buffering could potentially cause variation in rates of phenotypic evolution.
TL;DR: It is hoped that the findings put forward here can be used to design computational models of evolution that produce significant gains in evolvability and evolutionary speed.
Abstract: Biological and artificial evolutionary systems exhibit varying degrees of evolvability and different rates of evolution. Such quantities can be affected by various factors. Here, we review some evolutionary mechanisms and discuss new developments in biology that can potentially improve evolvability or accelerate evolution in artificial systems. Biological notions are discussed to the degree they correspond to notions in Evolutionary Computation. We hope that the findings put forward here can be used to design computational models of evolution that produce significant gains in evolvability and evolutionary speed.
TL;DR: This work compares several multivariate methods that calculate genetic constraint using a quantitative genetic field study in the ivyleaf morning glory, Ipomoea hederacea, and finds high levels of inferred constraint and discordance between methods that consider the geometric orientation of G and β and those that evaluate how covariances affect the short-term rate of adaptation.
Abstract: The ability of a population to respond to natural selection will be determined by the patterns of genetic variation and covariation in traits under selection. In the quantitative genetic framework, these patterns of genetic variation and covariation are described by the G matrix, which for a given pattern of selection will determine the size and direction of evolutionary responses. Several methods have been developed to evaluate the nature of evolutionary constraints imposed by G, although this multitude of methods has never been applied to a common data set to compare their strengths and weaknesses, or the similarity of evolutionary inferences they produce. Here we compare several multivariate methods that calculate genetic constraint using a quantitative genetic field study in the ivyleaf morning glory, Ipomoea hederacea. We focus on a tractable number of traits (size at flowering, final size, and flowering time), which allows us to pair multivariate quantitative methods with qualitative interpretations...
Journal Article•
TL;DR: The population dynamics and evolution of multiple species competing for discrete, substitutable resources, and the evolution of equivalence determines diversity within functional groups, but niche processes drive diversity among groups.
Abstract: Question: Under what conditions do species using distinct niches evolve and converge to become ecologically equivalent? Does evolution in a community context affect functional group diversity? Mathematical methods: We simulated the population dynamics and evolution of multiple species competing for discrete, substitutable resources. Key assumptions: Species’ competitive effect and response are based on resource-use overlap. Evolution occurs via selection on mutations of small effect. Intraspecific genetic variation is the same for each species. Predictions: Evolution of equivalence is possible when species evolve in a community context. A combination of convergence, divergence, and extinctions occurs when the number of species exceeds the number of resources. Species avoid competitive exclusion via convergence or divergence in their resource use. Ecological and evolutionary outcomes depend on an interaction between the rate of evolution and the initial similarity of competitors. The evolution of equivalence determines diversity within functional groups, but niche processes drive diversity among groups.
TL;DR: The evolution of complex GRNs is remarkably promoted by fixation of beneficial gene duplications under unpredictably fluctuating environmental conditions and that some internal factors inherent in organisms, such as mutational bias, gene expression costs, and constraints on expression dynamics, are also important for the evolution of GRNs.
Abstract: Various characteristics of complex gene regulatory networks (GRNs) have been discovered during the last decade, e.g., redundancy, exponential indegree distributions, scale-free outdegree distributions, mutational robustness, and evolvability. Although progress has been made in this field, it is not well understood whether these characteristics are the direct products of selection or those of other evolutionary forces such as mutational biases and biophysical constraints. To elucidate the causal factors that promoted the evolution of complex GRNs, we examined the effect of fluctuating environmental selection and some intrinsic constraining factors on GRN evolution by using an individual-based model. We found that the evolution of complex GRNs is remarkably promoted by fixation of beneficial gene duplications under unpredictably fluctuating environmental conditions and that some internal factors inherent in organisms, such as mutational bias, gene expression costs, and constraints on expression dynamics, are also important for the evolution of GRNs. The results indicate that various biological properties observed in GRNs could evolve as a result of not only adaptation to unpredictable environmental changes but also non-adaptive processes owing to the properties of the organisms themselves. Our study emphasizes that evolutionary models considering such intrinsic constraining factors should be used as null models to analyze the effect of selection on GRN evolution.
Journal Article•
TL;DR: It is shown that selected changes to connections in the regulation network make the currently selected gene expression pattern more robust to environmental variation, and that, in principle, a gene regulation network has the potential to develop ‘recall’ capabilities normally reserved for cognitive systems.
Abstract: The pattern of gene expression in the phenotype of an organism is determined in part by the dynamical attractors of the organism’s gene regulation network. Changes to the connections in this network over evolutionary time alter the adult gene expression pattern and hence the fitness of the organism. However, the evolution of structure in gene expression networks (potentially reflecting past selective environments) and its affordances and limitations with respect to enhancing evolvability is poorly understood in general. In this paper we model the evolution of a gene regulation network in a controlled scenario. We show that selected changes to connections in the regulation network make the currently selected gene expression pattern more robust to environmental variation. Moreover, such changes to connections are necessarily ‘Hebbian’ – ‘genes that fire together wire together’ – i.e. genes whose expression is selected for in the same selective environments become co3regulated. Accordingly, in a manner formally equivalent to well3understood learning behaviour in artificial neural networks, a gene expression network will therefore develop a generalised associative memory of past selected phenotypes. This theoretical framework helps us to better understand the relationship between homeostasis and evolvability (i.e. selection to reduce variability facilitates structured variability), and shows that, in principle, a gene regulation network has the potential to develop ‘recall’ capabilities normally reserved for cognitive systems.
TL;DR: This work presents a hypothesis‐testing framework for estimating the genetic variance in a focal trait that is independent of variance in other traits, and illustrates the analytical approach using two Drosophila bunnanda trait sets.
Abstract: Genetic covariation among multiple traits will bias the direction of evolution. Although a trait's phenotypic context is crucial for understanding evolutionary constraints, the evolutionary potential of one (focal) trait, rather than the whole phenotype, is often of interest. The extent to which a focal trait can evolve independently depends on how much of the genetic variance in that trait is unique. Here, we present a hypothesis-testing framework for estimating the genetic variance in a focal trait that is independent of variance in other traits. We illustrate our analytical approach using two Drosophila bunnanda trait sets: a contact pheromone system comprised of cuticular hydrocarbons (CHCs), and wing shape, characterized by relative warps of vein position coordinates. Only 9% of the additive genetic variation in CHCs was trait specific, suggesting individual traits are unlikely to evolve independently. In contrast, most (72%) of the additive genetic variance in wing shape was trait specific, suggesting relative warp representations of wing shape could evolve independently. The identification of genetic variance in focal traits that is independent of other traits provides a way of studying the evolvability of individual traits within the broader context of the multivariate phenotype.
TL;DR: Humanity’s increasing understanding of the evolution of life in the universe is rapidly bringing it to the threshold of this major evolutionary transition, and organisms that complete this transition to intentional evolution will drive the further development of life and intelligence in the universes.
Abstract: The evolution of life on Earth has produced an organism that is beginning to model and understand its own evolution and the possible future evolution of life in the universe. These models and associated evidence show that evolution on Earth has a trajectory. The scale over which living processes are organized cooperatively has increased progressively, as has its evolvability. Recent theoretical advances raise the possibility that this trajectory is itself part of a wider developmental process. According to these theories, the developmental process has been shaped by a yet larger evolutionary dynamic that involves the reproduction of universes. This evolutionary dynamic has tuned the key parameters of the universe to increase the likelihood that life will emerge and produce outcomes that are successful in the larger process (e.g. a key outcome may be to produce life and intelligence that intentionally reproduces the universe and tunes the parameters of ‘offspring’ universes). Theory suggests that when life emerges on a planet, it moves along this trajectory of its own accord. However, at a particular point evolution will continue to advance only if organisms emerge that decide to advance the developmental process intentionally. The organisms must be prepared to make this commitment even though the ultimate nature and destination of the process is uncertain, and may forever remain unknown. Organisms that complete this transition to intentional evolution will drive the further development of life and intelligence in the universe. Humanity’s increasing understanding of the evolution of life in the universe is rapidly bringing it to the threshold of this major evolutionary transition.
06 Apr 2010
TL;DR: A systematic review of the existing studies in promoting software evolvability at architectural level finds techniques that support quality considerations during software architecture design, architectural quality evaluation, economic valuation, architectural knowledge management and modeling techniques.
Abstract: For long-lived systems, there is a need to address evolvability (i.e. a system’s ability to easily accommodate changes) explicitly during the entire lifecycle. In this paper, we undertake a systematic review to obtain an overview of the existing studies in promoting software evolvability at architectural level. The search strategy identified 58 studies that were catalogued as primary studies for this review after using multi-step selection process. The studies are classified into five main categories of themes, including techniques that support quality considerations during software architecture design, architectural quality evaluation, economic valuation, architectural knowledge management and modeling techniques. The review investigates what is currently known about architecting software evolvability at architecture level. Implications for research and practice are presented.
TL;DR: It is shown that the burden concept was consistent with most major tenets of the Modern Synthesis, and Riedl attempted to explain patterns of large-scale evolutionary trends exclusively by microevolutionary (gradualistic) processes.
Abstract: Rupert Riedl's concept of burden forms a causal hypothesis on organismic integration and evolutionary constraints. Defined as the hierarchically nested interdependence of characters within the organism, burden was seen as (1) defining and conserving body plans and (2) constraining and directing evolutionary trajectories. A review of the components of the burden concept reveals important consistencies with the modern tenets of evo-devo. This concept differs from the current consensus of evolutionary theory in that it (1) grants evolution less options for changing tightly integrated, "locked-in" characters and (2) in deducing from this an ever decreasing freedom for evolution, with cyclism and typostrophism as resulting macroevolutionary phenomena. Despite these differences, I show that the burden concept was consistent with most major tenets of the Modern Synthesis, and Riedl attempted to explain patterns of large-scale evolutionary trends exclusively by microevolutionary (gradualistic) processes. The burden concept is fruitful and unique in its focus on hierarchically nested constraints and resembles the hierarchical architecture of gene regulatory networks. However, such networks are more high-dimensional and most of their components appear to be easier to evolve than Riedl's burden. Yet in combination with evolvability, a modified concept of burden might contribute substantially to the understanding of organismic integration and the long-term evolution of body plans.
TL;DR: It is found that sperm number may be limited by low heritability and evolvability whereas sperm quality has moderate VA and CVA but does not evolve, and the female reproductive tract, suggested to drive the evolution of sperm, did not respond to experimental sexual selection even though there was sufficient genetic variation.
Abstract: Studies of experimental sexual selection have tested the effect of variation in the intensity of sexual selection on male investment in reproduction, particularly sperm. However, in several species, including Drosophila pseudoobscura, no sperm response to experimental evolution has occurred. Here, we take a quantitative genetics approach to examine whether genetic constraints explain the limited evolutionary response. We quantified direct and indirect genetic variation, and genetic correlations within and between the sexes, in experimental populations of D. pseudoobscura. We found that sperm number may be limited by low heritability and evolvability whereas sperm quality (length) has moderate V A and CV A but does not evolve. Likewise, the female reproductive tract, suggested to drive the evolution of sperm, did not respond to experimental sexual selection even though there was sufficient genetic variation. The lack of genetic correlations between the sexes supports the opportunity for sexual conflict over investment in sperm by males and their storage by females. Our results suggest no absolute constraint arising from a lack of direct or indirect genetic variation or patterns of genetic covariation. These patterns show why responses to experimental evolution are hard to predict, and why research on genetic variation underlying interacting reproductive traits is needed.
Posted Content•
TL;DR: In this article, the authors used Artificial Homeostatic Hormone Systems (AHHS) to evolve a controller for a robot built from five autonomous, cooperating modules to achieve fast locomotion by using the modules' main hinges.
Abstract: The semi-automatic or automatic synthesis of robot controller software is both desirable and challenging. Synthesis of rather simple behaviors such as collision avoidance by applying artificial evolution has been shown multiple times. However, the difficulty of this synthesis increases heavily with increasing complexity of the task that should be performed by the robot. We try to tackle this problem of complexity with Artificial Homeostatic Hormone Systems (AHHS), which provide both intrinsic, homeostatic processes and (transient) intrinsic, variant behavior. By using AHHS the need for pre-defined controller topologies or information about the field of application is minimized. We investigate how the principle design of the controller and the hormone network size affects the overall performance of the artificial evolution (i.e., evolvability). This is done by comparing two variants of AHHS that show different effects when mutated. We evolve a controller for a robot built from five autonomous, cooperating modules. The desired behavior is a form of gait resulting in fast locomotion by using the modules' main hinges.
11 Sep 2010
TL;DR: It is found that degeneracy freely emerges within this framework, leading to MAS architectures that are robust towards a set of similar environments and quickly adaptable to large environmental changes.
Abstract: It has been proposed that degeneracy plays a fundamental role in biological evolution by facilitating robustness and adaptation within heterogeneous and time-variant environments. Degeneracy occurs whenever structurally distinct agents display similar functions within some contexts but unique functions in others. In order to test the broader applicability of this hypothesis, especially to the field of evolutionary dynamic optimisation, we evolve multi-agent systems (MAS) in time-variant environments and investigate how degeneracy amongst agents influences the system's robustness and evolvability. We find that degeneracy freely emerges within our framework, leading to MAS architectures that are robust towards a set of similar environments and quickly adaptable to large environmental changes. Detailed supplementary experiments, aimed particularly at the scaling behaviour of these results, demonstrate a broad range of validity for our findings and suggest that important general distinctions may exist between evolution in degenerate and non-degenerate agent-based systems.
TL;DR: It is argued that changes in evolvability along climatic gradients depend on the relative intensity of stabilizing selection, and may be high in Bromus and not only depends on environmental stress, but also on variability.
Abstract: Under global climate change, adaptation to new conditions is crucial for plant species persistence. This requires the ability to evolve in traits that are correlated with changing climatic variables. We studied between-year seed dormancy, which correlates with environmental variability, and tested for clinal trends in its evolvability along an aridity gradient in Israel. We conducted a germination experiment under five irrigation levels with two dryland winter annuals (Biscutella didyma, Bromus fasciculatus) from four sites along the gradient. Species differed in means and evolvability of dormancy. Biscutella had high dormancy, which significantly increased with aridity but decreased with higher irrigation. In Bromus, dormancy was low, similar among populations, and only marginally affected by irrigation. Evolvability in Biscutella was high and varied among populations, without a clinal trend along the gradient. Conversely, in Bromus, trait evolvability was low and declined with increasing aridity. We argue that changes in evolvability along climatic gradients depend on the relative intensity of stabilizing selection. This may be high in Bromus and not only depends on environmental stress, but also on variability. Our findings point to the importance of measuring evolvability of climate-related traits across different natural and artificial environments and for many coexisting species. © 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 100, 924–934.
28 Oct 2010
TL;DR: Views on Evolvability of Embedded Systems is targeted at both researchers and practitioners; they will find guidelines to make systems more evolvable and new industrially-validated techniques to improve the evolvable of embedded systems.
Abstract: Evolvability, the ability to respond effectively to change, represents a major challenge to today's high-end embedded systems, such as those developed in the medical domain by Philips Healthcare. These systems are typically developed by multi-disciplinary teams, located around the world, and are in constant need of upgrading to provide new advanced features, to deal with obsolescence, and to exploit emerging enabling technologies. Despite the importance of evolvability for these types of systems, the field has received scant attention from the scientific and engineering communities. Views on Evolvability of Embedded Systems focuses on the topic of evolvability of embedded systems from an applied scientific perspective. In particular, the book describes results from the Darwin project that researched evolvability in the context of Magnetic Resonance Imaging (MRI) systems. This project applied the Industry-as-Laboratory paradigm, in which industry and academia join forces to ensure continuous knowledge and technology transfer during the projects lifetime. The Darwin project was a collaboration between the Embedded Systems Institute, the MRI business unit of Philips Healthcare, Philips Research, and five Dutch universities. Evolvability was addressed from a system engineering perspective by a number of researchers from different disciplines such as software-, electrical- and mechanical engineering, with a clear focus on economic decision making. The research focused on four areas: data mining, reference architectures, mechanisms and patterns for evolvability, in particular visualization & modelling, and economic decision making. Views on Evolvability of Embedded Systems is targeted at both researchers and practitioners; they will not only find a state-of-the-art overview on evolvability research, but also guidelines to make systems more evolvable and new industrially-validated techniques to improve the evolvability of embedded systems.