Evolvability and Robustness in Color Displays: Bridging the Gap between Theory and Data

Evolution of diet-derived sexual ornaments—some of the most spectacular and diverse traits in the living world—highlights the gap between modern evolutionary theory and empirical data on the origin and inheritance of complex environment-dependent traits. Specifically, current theory offers little insight into how strong environmental contingency of diet-dependent color biosynthesis and environmental variability in precursor supply can be reconciled with extensive evolutionary elaboration, diversification, and convergence of diet-dependent displays among animal taxa. Moreover, biosynthetic pathways of diet-derived displays combine seemingly irreconcilable robustness, lability, and modularity to facilitate elaboration under variable environmental conditions. Here I show that an ontogenetic decrease in the predictability of an association between organismal and environmental components of color biosynthesis and the corresponding evolutionary transition from short-term epigenetic inheritance of peripheral biosynthetic components to genetic inheritance of the most reliable upstream components link the causes of developmental variation with the causes of inheritance in diet-derived displays. Using carotenoid-based colors as an empirical model, I outline general principles of a testable evolutionary framework of diversification and functional robustness of diet-derived displays, and suggest that such a framework provides insight into the foundational question of evolutionary biology—how to connect causes of within-generation developmental variation with causes of among-generation and among-taxa variation and thus with causes of evolution?     

Evolutionary dynamics of transposable elements in prokaryotes and eukaryotes

This paper summarizes some recent theories about the evolution of transposable genetic elements in outbreeding, sexual eukaryotic organisms. The evolutionary possibilities available to self-replicating transposable elements are shown to vary depending on the reproductive biology of the host genome. This effect can be used to explain, in part, the differences in abundance of transposable elements between prokaryotes and eukaryotes. It is argued that the pattern of sexual outbreeding seen in mammals and plants is especially favorable to the spread of transposons. Moreover, because transposon spread is facilitated by zygote formation, the evolutionary origin of sexual conjugation may have been due to selection on transposon-encoded genes. Finally, evidence is also presented that introns could have originated as transposable genetic elements.     

Evolutionary Trends

The occurrence, generality, and causes of large-scale evolutionary trends—directional changes over long periods of time—have been the subject of intensive study and debate in evolutionary science. Large-scale patterns in the history of life have also been of considerable interest to nonspecialists, although misinterpretations and misunderstandings of this important issue are common and can have significant implications for an overall understanding of evolution. This paper provides an overview of how trends are identified, categorized, and explained in evolutionary biology. Rather than reviewing any particular trend in detail, the intent is to provide a framework for understanding large-scale evolutionary patterns in general and to highlight the fact that both the patterns and their underlying causes are usually quite complex.

Evolutionary stable strategies and game dynamics for n-person games

This note contains a generalization of the definition of an evolutionary stable strategy and of the corresponding game dynamics from 2-person to n-person games. This broader framework also allows modelling of several interacting populations or of populations containing different types of individuals, for example males and females.     

Mutate now, die later. Evolutionary dynamics with delayed selection

We analyze here the evolutionary consequences of selection with delay in a population genetics context. In the classical works on evolutionary dynamics, an individual produces off-springs in direct proportion to its fitness, a process in which mutations may occur. In the present scenario of delayed selection, individuals that acquire deleterious mutations can still reproduce unharmed for several generations. During this time delay, the damage passed on to off-springs can potentially be repaired by subsequent compensatory mutations. In the absence of such a repair, the individual becomes sterile. Here we study the population-genetic effects of such a time delay by means of both numerical simulations and theoretical modeling. The results show that delayed selection lowers the extinction threshold, endangering the survival of the population. Surprisingly, however, no traces of this delay effect are encountered in the sequence diversity of the population. These conclusions suggest that delayed selection is hard to detect in genetic data and thus could be a wide-spread but rarely detected phenomenon.     

Evolutionary dynamics of predator-prey systems: an ecological perspective

 Evolution takes place in an ecological setting that typically involves interactions with other organisms. To describe such evolution, a structure is needed which incorporates the simultaneous evolution of interacting species. Here a formal framework for this purpose is suggested, extending from the microscopic interactions between individuals – the immediate cause of natural selection, through the mesoscopic population dynamics responsible for driving the replacement of one mutant phenotype by another, to the macroscopic process of phenotypic evolution arising from many such substitutions. The process of coevolution that results from this is illustrated in the context of predator–prey systems. With no more than qualitative information about the evolutionary dynamics, some basic properties of predator–prey coevolution become evident. More detailed understanding requires specification of an evolutionary dynamic; two models for this purpose are outlined, one from our own research on a stochastic process of mutation and selection and the other from quantitative genetics. Much of the interest in coevolution has been to characterize the properties of fixed points at which there is no further phenotypic evolution. Stability analysis of the fixed points of evolutionary dynamical systems is reviewed and leads to conclusions about the asymptotic states of evolution rather different from those of game-theoretic methods. These differences become especially important when evolution involves more than one species. Received 10 November 1993; received in revised form 25 July 1994     

Geometric robustness theory and biological networks

We provide a geometric framework for investigating the robustness of information flows over biological networks. We use information measures to quantify the impact of knockout perturbations on simple networks. Robustness has two components, a measure of the causal contribution of a node or nodes, and a measure of the change or exclusion dependence, of the network following node removal. Causality is measured as statistical contribution of a node to network function, wheras exclusion dependence measures a distance between unperturbed network and reconfigured network function. We explore the role that redundancy plays in increasing robustness, and how redundacy can be exploited through error-correcting codes implemented by networks. We provide examples of the robustness measure when applied to familiar boolean functions such as the AND, OR and XOR functions. We discuss the relationship between robustness measures and related measures of complexity and how robustness always implies a minimal level of complexity.     

细菌基因组进化的分子策略

论述了细菌基因组进化的 4个分子策略 :点突变 ,基因组内重排 ,基因水平转移 ,基因缺失。从经典的达尔文进化论角度探讨了细菌基因组进化与表型进化的关系。     

Pathway Length and Evolutionary Constraint in Amino Acid Biosynthesis

The evolutionary properties of a metabolic network may be determined by the topology of the network. One attribute of pathways that make up the network is the number of enzymatic steps between initial substrates and final products. To determine the effect of pathway length on evolutionary lability of pathway structure, we examined amino acid biosynthetic pathways across 48 sequenced organisms. We demonstrate that longer pathways exhibit lower rates of change in pathway structure than shorter pathways. This finding suggests that increasing complexity may increase constraint on evolutionary change. (Matthew T. Rutter and Rebecca A. Zufall) Both authors contributed equally to this work.     

Evolutionary Aspects of Enzyme Dynamics

The role of evolutionary pressure on the chemical step catalyzed by enzymes is somewhat enigmatic, in part because chemistry is not rate-limiting for many optimized systems. Herein, we present studies that examine various aspects of the evolutionary relationship between protein dynamics and the chemical step in two paradigmatic enzyme families, dihydrofolate reductases and alcohol dehydrogenases. Molecular details of both convergent and divergent evolution are beginning to emerge. The findings suggest that protein dynamics across an entire enzyme can play a role in adaptation to differing physiological conditions. The growing tool kit of kinetics, kinetic isotope effects, molecular biology, biophysics, and bioinformatics provides means to link evolutionary changes in structure-dynamics function to the vibrational and conformational states of each protein.     

A test of highly optimized tolerance reveals fragile cell-cycle mechanisms are molecular targets in clinical cancer trials

Robustness, a long-recognized property of living systems, allows function in the face of uncertainty while fragility, i.e., extreme sensitivity, can potentially lead to catastrophic failure following seemingly innocuous perturbations. Carlson and Doyle hypothesized that highly-evolved networks, e.g., those involved in cell-cycle regulation, can be resistant to some perturbations while highly sensitive to others. The "robust yet fragile" duality of networks has been termed Highly Optimized Tolerance (HOT) and has been the basis of new lines of inquiry in computational and experimental biology. In this study, we tested the working hypothesis that cell-cycle control architectures obey the HOT paradigm. Three cell-cycle models were analyzed using monte-carlo sensitivity analysis. Overall state sensitivity coefficients, which quantify the robustness or fragility of a given mechanism, were calculated using a monte-carlo strategy with three different numerical techniques along with multiple parameter perturbation strategies to control for possible numerical and sampling artifacts. Approximately 65% of the mechanisms in the G1/S restriction point were responsible for 95% of the sensitivity, conversely, the G2-DNA damage checkpoint showed a much stronger dependence on a few mechanisms; approximately 32% or 13 of 40 mechanisms accounted for 95% of the sensitivity. Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex. Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems. Comparison of the predicted fragile mechanisms with literature and current preclinical and clinical trials suggested a strong correlation between efficacy and fragility. Thus, when taken together, these results support the working hypothesis that cell-cycle control architectures are HOT networks and establish the mathematical estimation and subsequent therapeutic exploitation of fragile mechanisms as a novel strategy for anti-cancer lead generation.     

Evolutionary optimization and neural network models of behavior

One of the main challenges to the adaptionist program in general and the use of optimization models in behavioral and evolutionary ecology, in particular, is that organisms are so constrained' by ontogeny and phylogeny that they may not be able to attain optimal solutions, however those are defined. This paper responds to the challenge through the comparison of optimality and neural network models for the behavior of an individual polychaete worm. The evolutionary optimization model is used to compute behaviors (movement in and out of a tube) that maximize a measure of Darwinian fitness based on individual survival and reproduction. The neural network involves motor, sensory, energetic reserve and clock neuronal groups. Ontogeny of the neural network is the change of connections of a single individual in response to its experiences in the environment. Evolution of the neural network is the natural selection of initial values of connections between groups and learning rules for changing connections. Taken together, these can be viewed as design parameters. The best neural networks have fitnesses between 85% and 99% of the fitness of the evolutionary optimization model. More complicated models for polychaete worms are discussed. Formulation of a neural network model for host acceptance decisions by tephritid fruit flies leads to predictions about the neurobiology of the flies. The general conclusion is that neural networks appear to be sufficiently rich and plastic that even weak evolution of design parameters may be sufficient for organisms to achieve behaviors that give fitnesses close to the evolutionary optimal fitness, particularly if the behaviors are relatively simple.     

Evolutionary dynamics of invasion and escape

Whenever life wants to invade a new habitat or escape from a lethal selection pressure, some mutations may be necessary to yield sustainable replication. We imagine situations like (i) a parasite infecting a new host, (ii) a species trying to invade a new ecological niche, (iii) cancer cells escaping from chemotherapy, (iv) viruses or microbes evading anti-microbial therapy, and also (v) the repeated attempts of combinatorial chemistry in the very beginning of life to produce self-replicating molecules. All such seemingly unrelated situations have a common structure in terms of Darwinian dynamics: a replicator with a basic reproductive ratio less than one attempts to find some mutations that allow indefinite survival. We develop a general theory, based on multitype branching processes, to describe the evolutionary dynamics of invasion and escape.     

Evolutionary dynamics and strong Allee effects

We describe the dynamics of an evolutionary model for a population subject to a strong Allee effect. The model assumes that the carrying capacity k(u), inherent growth rate r(u), and Allee threshold a(u) are functions of a mean phenotypic trait u subject to evolution. The model is a plane autonomous system that describes the coupled population and mean trait dynamics. We show bounded orbits equilibrate and that the Allee basin shrinks (and can even disappear) as a result of evolution. We also show that stable non-extinction equilibria occur at the local maxima of k(u) and that stable extinction equilibria occur at local minima of r(u). We give examples that illustrate these results and demonstrate other consequences of an Allee threshold in an evolutionary setting. These include the existence of multiple evolutionarily stable, non-extinction equilibria, and the possibility of evolving to a non-evolutionary stable strategy (ESS) trait from an initial trait near an ESS.     

Evolutionary dynamics of fearfulness and boldness

A negative relationship between reproductive effort and survival is consistent with life-history. Evolutionary dynamics and evolutionarily stable strategy (ESS) for the trade-off between survival and reproduction are investigated using a simple model with two phenotypes, fearfulness and boldness. The dynamical stability of the pure strategy model and analysis of ESS conditions reveal that: (i) the simple coexistence of fearfulness and boldness is impossible; (ii) a small population size is favorable to fearfulness, but a large population size is favorable to boldness, i.e., neither fearfulness, nor boldness is always favored by natural selection; and (iii) the dynamics of population density is crucial for a proper understanding of the strategy dynamics.     

Evolutionary dynamics and strong Allee effects

We describe the dynamics of an evolutionary model for a population subject to a strong Allee effect. The model assumes that the carrying capacity k(u), inherent growth rate r(u), and Allee threshold a(u) are functions of a mean phenotypic trait u subject to evolution. The model is a plane autonomous system that describes the coupled population and mean trait dynamics. We show bounded orbits equilibrate and that the Allee basin shrinks (and can even disappear) as a result of evolution. We also show that stable non-extinction equilibria occur at the local maxima of k(u) and that stable extinction equilibria occur at local minima of r(u). We give examples that illustrate these results and demonstrate other consequences of an Allee threshold in an evolutionary setting. These include the existence of multiple evolutionarily stable, non-extinction equilibria, and the possibility of evolving to a non-evolutionary stable strategy (ESS) trait from an initial trait near an ESS.     

Evolutionary insights from Erwinia amylovora genomics

Evolutionary genomics is coming into focus with the recent availability of complete sequences for many bacterial species. A hypothesis on the evolution of virulence factors in the plant pathogen Erwinia amylovora, the causative agent of fire blight, was generated using comparative genomics with the genomes E. amylovora, Erwinia pyrifoliae and Erwinia tasmaniensis. Putative virulence factors were mapped to the proposed genealogy of the genus Erwinia that is based on phylogenetic and genomic data. Ancestral origin of several virulence factors was identified, including levan biosynthesis, sorbitol metabolism, three T3SS and two T6SS. Other factors appeared to have been acquired after divergence of pathogenic species, including a second flagellar gene and two glycosyltransferases involved in amylovoran biosynthesis. E. amylovora singletons include 3 unique T3SS effectors that may explain differential virulence/host ranges. E. amylovora also has a unique T1SS export system, and a unique third T6SS gene cluster. Genetic analysis revealed signatures of foreign DNA suggesting that horizontal gene transfer is responsible for some of these differential features between the three species.     

Complex tool sets for honey extraction among chimpanzees in Loango National Park, Gabon

Homo faber was once proposed as a label for humans specifically to highlight their unique propensity for tool use. However, new observations on complex tool use by the chimpanzees of Loango National Park, Gabon, expand our knowledge about tool-using abilities in Pan troglodytes. Chimpanzees in Loango, when using tools to extract honey from three types of bee nests, were observed to regularly use three- to five-element tool sets. In other words, different types of tools were used sequentially to access a single food source. Such tool sets included multi-function tools that present typical wear for two distinct uses. In addition, chimpanzees exploited underground bee nests and used ground-perforating tools to locate nest chambers that were not visible from the ground surface. These new observations concur with others from Central African chimpanzees to highlight the importance of honey extraction in arguments favoring the emergence of complex tool use in hominoids, including different tool types, expanded tool sets, multifunction tools, and the exploitation of underground resources. This last technique requires sophisticated cognitive abilities concerning unseen objects. A sequential analysis reveals a higher level of complexity in honey extraction than previously proposed for nut cracking or hunting tools, and compares with some technologies attributed to early hominins from the Early and Middle Stone Age. A better understanding of similarities in human and chimpanzee tool use will allow for a greater understanding of tool-using skills that are uniquely human.     

Evolutionary dynamics of taxonomic structure

The distribution of species among genera and higher taxa has largely untapped potential to reveal among-clade variation in rates of origination and extinction. The probability distribution of the number of species within a genus is modelled with a stochastic, time-homogeneous birth-death model having two parameters: the rate of species extinction, μ, and the rate of genus origination, γ, each scaled as a multiple of the rate of within-genus speciation, λ. The distribution is more sensitive to γ than to μ, although μ affects the size of the largest genera. The species : genus ratio depends strongly on both γ and μ, and so is not a good diagnostic of evolutionary dynamics. The proportion of monotypic genera, however, depends mainly on γ, and so may provide an index of the genus origination rate. Application to living marine molluscs of New Zealand shows that bivalves have a higher relative rate of genus origination than gastropods. This is supported by the analysis of palaeontological data. This concordance suggests that analysis of living taxonomic distributions may allow inference of macroevolutionary dynamics even without a fossil record.