Fitness-associated recombination on rugged adaptive landscapes

A negative correlation between fitness and recombination rates seems to exist in various organisms. In this article we suggest that a correlation of that kind may play an important role in the evolution of complex traits. We study the effects of such fitness-associated recombination (FAR) in a simple two-locus deterministic model, as well as in a multi-loci NK rugged adaptive landscape. In both models studied, FAR results in faster adaptation and higher average population fitness, compared with uniform-rate recombination.     

Evolution and speciation on holey adaptive landscapes

Sewall Wright's powerful metaphor of rugged adaptive landscapes has formed the basis for discussing evolution and speciation for more than 60 years. However, this metaphor, with its emphasis on adaptive peaks and valleys, is to a large degree a reflection of our three-dimensional experience. Both genotypes and phenotypes of biological organisms differ in numerous characteristics, and, thus, the dimension of 'real' adaptive landscapes is much larger than three. Properties of multidimensional adaptive landscapes are very different from those of low dimension. Consequently, something that is seen as a theoretical challenge in a low-dimensional case might be a trivial problem in a multidimensional context and vice versa. In particular, the problem of how a population crosses an adaptive valley on its way from one adaptive peak to another, which Wright attempted to solve with his shifting balance theory, may be non-existent. A new framework is emerging for deepening our understanding of evolution and speciation, which provides a plausible multidimensional alternative to the conventional view of rugged adaptive landscapes.     

Extracting viability landscapes from mutagen-response experiments

This paper outlines a novel approach for determining the importance of various genes to the viability of an organism. The basic idea is to treat a population of cells at various concentrations of mutagen, and determine which genes lose functionality due to genetic drift at the various mutagen concentrations. The more strongly a given collection of genes contributes to the fitness of an organism, the higher the mutation rate required to induce loss of functionality in those genes via genetic drift. We argue that mutagen-based methods, if reliably implementable, can elucidate correlations amongst genes, and determine which sets of genes correspond to redundant pathways in the cell. The data obtained from mutagen-based methods could also be used to organize the genes in a genome into hierarchies of increasing importance to the fitness of the cell. Thus, such methods could shed light on the evolutionary history of an organism.     

Rapid parapatric speciation on holey adaptive landscapes.

A classical view of speciation is that reproductive isolation arises as a by-product of genetic divergence. Here, individual-based simulations are used to evaluate whether the mechanisms implied by this view may result in rapid speciation if the only source of genetic divergence are mutation and random genetic drift. Distinctive features of the simulations are the consideration of the complete process of speciation (from initiation until completion), and of a large number of loci, which was only one order of magnitude smaller than that of bacteria. It is demonstrated that rapid speciation on the time-scale of hundreds of generations is plausible without the need for extreme founder events, complete geographic isolation, the existence of distinct adaptive peaks or selection for local adaptation. The plausibility of speciation is enhanced by population subdivision. Simultaneous emergence of more than two new species from a subdivided population is highly probable. Numerical examples relevant to the theory of centrifugal speciation and to the conjectures about the fate of ''ring species'' and ''sexual continuums'' are presented.     

Microbial adaptive evolution

Bacterial species can adapt to significant changes in their environment by mutation followed by selection, a phenomenon known as “adaptive evolution.” With the development of bioinformatics and genetic engineering, research on adaptive evolution has progressed rapidly, as have applications of the process. In this review, we summarize various mechanisms of bacterial adaptive evolution, the technologies used for studying it, and successful applications of the method in research and industry. We particularly highlight the contributions of Dr. L. O. Ingram. Microbial adaptive evolution has significant impact on our society not only from its industrial applications, but also in the evolution, emergence, and control of various pathogens.     

The sensory ecology of adaptive landscapes

In complex environments, behavioural plasticity depends on the ability of an animal to integrate numerous sensory stimuli. The multidimensionality of factors interacting to shape plastic behaviour means it is difficult for both organisms and researchers to predict what constitutes an adaptive response to a given set of conditions. Although researchers may be able to map the fitness pay-offs of different behavioural strategies in changing environments, there is no guarantee that the study species will be able to perceive these pay-offs. We thus risk a disconnect between our own predictions about adaptive behaviour and what is behaviourally achievable given the umwelt of the animal being studied. This may lead to erroneous conclusions about maladaptive behaviour in circumstances when the behaviour exhibited is the most adaptive possible given sensory limitations. With advances in the computational resources available to behavioural ecologists, we can now measure vast numbers of interactions among behaviours and environments to create adaptive behavioural surfaces. These surfaces have massive heuristic, predictive and analytical potential in understanding adaptive animal behaviour, but researchers using them are destined to fail if they ignore the sensory ecology of the species they study. Here, we advocate the continued use of these approaches while directly linking them to perceptual space to ensure that the topology of the generated adaptive landscape matches the perceptual reality of the animal it intends to study. Doing so will allow predictive models of animal behaviour to reflect the reality faced by the agents on adaptive surfaces, vastly improving our ability to determine what constitutes an adaptive response for the animal in question.     

Conserving adaptive genetic diversity in dynamic landscapes

Genetic variation supplies the raw material for adaptation, evolution and survival of populations and has therefore been a key focus of conservation biology ever since its foundation (Soulé 1985). In previous decades, the neutral component of genetic diversity (generated by mutation and shaped by drift) has been the subject of intense scientific research, fuelled by the increasing availability of molecular markers. On the other hand, the adaptive component of genetic diversity, which is shaped by the action of natural selection, has long remained elusive and difficult to assess, especially at small spatial or temporal scales (Ouborg et al. 2010). Fortunately, new technological and methodological developments now make it possible to identify loci in the genome that are influenced by selection, and thus to get a more complete view of genetic diversity. One article featured in this issue of Molecular Ecology is a good example of this recent breakthrough. Richter-Boix et al. (2011) examined a network of moor frog populations breeding in contrasting habitats in order to understand how landscape features influence patterns of genetic variation. They combined information from both neutral markers and loci putatively under selection to quantify the relative roles of selection and isolation in the evolution of fine-scale local adaptations in these populations. This study nicely illustrates how data on polymorphisms of neutral and adaptive loci can now be judiciously synthesized to help identify the best strategies for preserving adaptive variation, and more generally to enlighten conservation and population-management plans.     

Towards a general theory of adaptive walks on rugged landscapes

Adaptive evolution, to a large extent, is a complex combinatorial optimization process. In this article we take beginning steps towards developing a general theory of adaptive "walks" via fitter variants in such optimization processes. We introduce the basic idea of a space of entities, each a 1-mutant neighbor of many other entities in the space, and the idea of a fitness ascribed to each entity. Adaptive walks proceed from an initial entity, via fitter neighbors, to locally or globally optimal entities that are fitter than their neighbors. We develop a general theory for the number of local optima, lengths of adaptive walks, and the number of alternative local optima accessible from any given initial entity, for the baseline case of an uncorrelated fitness landscape. Most fitness landscapes are correlated, however. Therefore we develop parts of a universal theory of adaptation on correlated landscapes by adaptive processes that have sufficient numbers of mutations per individual to "jump beyond" the correlation lengths in the underlying landscape. In addition, we explore the statistical character of adaptive walks in two independent complex combinatorial optimization problems, that of evolving a specific cell type in model genetic networks, and that of finding good solutions to the traveling salesman problem. Surprisingly, both show similar statistical features, encouraging the hope that a general theory for adaptive walks on correlated and uncorrelated landscapes can be found. In the final section we explore two limits to the efficacy of selection. The first is new, and surprising: for a wide class of systems, as the complexity of the entities under selection increases, the local optima that are attainable fall progressively closer to the mean properties of the underlying space of entities. This may imply that complex biological systems, such as genetic regulatory systems, are "close" to the mean properties of the ensemble of genomic regulatory systems explored by evolution. The second limit shows that with increasing complexity and a fixed mutation rate, selection often becomes unable to pull an adapting population to those local optima to which connected adaptive walks via fitter variants exist. These beginning steps in theory development are applied to maturation of the immune response, and to the problem of radiation and stasis. Despite the limitations of the adaptive landscape metaphor, we believe that further development along the lines begun here will prove useful.     

Microbial landscapes: new paths to biofilm research

It is the best of times for biofilm research. Systems biology approaches are providing new insights into the genetic regulation of microbial functions, and sophisticated modelling techniques are enabling the prediction of microbial community structures. Yet it is also clear that there is a need for ecological theory to contribute to our understanding of biofilms. Here, we suggest a concept for biofilm research that is spatially explicit and solidly rooted in ecological theory, which might serve as a universal approach to the study of the numerous facets of biofilms.     

Heterogeneous adaptive trajectories of small populations on complex fitness landscapes

Background

Small populations are thought to be adaptively handicapped, not only because they suffer more from deleterious mutations but also because they have limited access to new beneficial mutations, particularly those conferring large benefits.

Methodology/Principal Findings

Here, we test this widely held conjecture using both simulations and experiments with small and large bacterial populations evolving in either a simple or a complex nutrient environment. Consistent with expectations, we find that small populations are adaptively constrained in the simple environment; however, in the complex environment small populations not only follow more heterogeneous adaptive trajectories, but can also attain higher fitness than the large populations. Large populations are constrained to near deterministic fixation of rare large-benefit mutations. While such determinism speeds adaptation on the smooth adaptive landscape represented by the simple environment, it can limit the ability of large populations from effectively exploring the underlying topography of rugged adaptive landscapes characterized by complex environments.

Conclusions

Our results show that adaptive constraints often faced by small populations can be circumvented during evolution on rugged adaptive landscapes.     

Experimental excursions on adaptive landscapes: density-dependent selection on egg size

Abstract. Theories of density-dependent natural selection suggest that intraspecific competition will favor juveniles of high competitive ability. Empirical evidence has been provided from laboratory selection experiments, but field studies are lacking due to the logistical difficulties of experimentally manipulating population densities in natural settings. Here, we present data from a decade-long experimental field study of side-blotched lizards, Uta stansburiana that overcomes these difficulties. We tested the hypothesis that density-dependent natural selection causes egg size to increase from early to late clutches in this and many other species. Using a novel combination of environmental manipulations of hatchling density and phenotypic manipulations of egg size, we demonstrate that the nature of selection on egg size changes dramatically in the absence of older competitors. The strength of selection on egg size among later-clutch hatchlings released in areas without competitors from early clutches became almost doubled in magnitude, compared to that among hatchlings released in the presence of older competitors. These experimental findings demonstrate density-dependent natural selection on egg size; however, they contradict the classical idea that egg size increases during the reproductive season because of competition between early and late hatchlings. The results indicate that competitive age or size asymmetries between early and late hatchlings can override within-cohort asymmetries due to egg size. We suggest that competition could be an important mediator of oscillating selection pressures in this and other systems. Finally, we discuss the utility of "double-level," simultaneous experimental manipulation of both phenotypic traits that are targets of selection (e.g., egg size) as well the environmental agents of selection (e.g., population density).     

Rugged adaptive landscapes shape a complex,sympatric radiation

Strong disruptive ecological selection can initiate speciation, even in the absence of physical isolation of diverging populations. Species evolving under disruptive ecological selection are expected to be ecologically distinct but, at least initially, genetically weakly differentiated. Strong selection and the associated fitness advantages of narrowly adapted individuals, coupled with assortative mating, are predicted to overcome the homogenizing effects of gene flow. Theoretical plausibility is, however, contrasted by limited evidence for the existence of rugged adaptive landscapes in nature. We found evidence for multiple, disruptive ecological selection regimes that have promoted divergence in the sympatric, incipient radiation of ‘sharpfin’ sailfin silverside fishes in ancient Lake Matano (Sulawesi, Indonesia). Various modes of ecological specialization have led to adaptive morphological differences between the species, and differently adapted morphs display significant but incomplete reproductive isolation. Individual fitness and variation in morphological key characters show that disruptive selection shapes a rugged adaptive landscape in this small but complex incipient lake fish radiation.     

Folding landscapes of ankyrin repeat proteins: experiments meet theory

Nearly 6% of eukaryotic protein sequences contain ankyrin repeat (AR) domains, which consist of several repeats and often function in binding. AR proteins show highly cooperative folding despite a lack of long-range contacts. Both theory and experiment converge to explain that formation of the interface between elements is more favorable than formation of any individual repeat unit. IkappaBalpha and Notch both undergo partial folding upon binding perhaps influencing the binding free energy. The simple architecture, combined with identification of consensus residues that are important for stability, has enabled systematic perturbation of the energy landscape by single point mutations that affect stability or by addition of consensus repeats. The folding energy landscapes appear highly plastic, with small perturbations re-routing folding pathways.     

Properties of adaptive walks on uncorrelated landscapes under strong selection and weak mutation

We examine properties of adaptive walks on uncorrelated (i.e. random) fitness landscapes starting from moderately fit genotypes under strong selection weak mutation. As an extension of Orr's model for a single step in an adaptive walk under these conditions, we show that the fitness rank of the dominant genotype in a population after the fixation of a beneficial mutation is, on average, (i+6)/4, where i is the fitness rank of the starting genotype. This accounts for the change in rank due to acquiring a new set of single-mutation neighbors after fixing a new allele through natural selection. Under this scenario, adaptive walks can be modeled as a simple Markov chain on the space of possible fitness ranks with an absorbing state at i = 1, from which no beneficial mutations are accessible. We find that these walks are typically short and are often completed in a single step when starting from a moderately fit genotype. As in Orr's original model, these results are insensitive to both the distribution of fitness effects and most biological details of the system under consideration.     

The fitness threshold model: Random environmental change alters adaptive landscapes

We used a probabilistic optimization model to explore the joint evolutionary effects of random phenotypic and environmental variation. Two forms of environmental noise were defined in which the optimal phenotype remained constant but all organisms experienced either the same proportionate or the same absolute fitness gains and losses. There was no evolutionary effect of proportionate fitness fluctuations. In contrast, the optimal genotype varied with absolute fitness fluctuations, despite the environmental effect being phenotype-independent. We refer to such phenotype-independent fluctuation in absolute fitness as the fitness threshold model, because shared fitness effects determine the zero-fitness points (i.e. the baseline) on an intrinsic fitness function. Thus, environmental effects that are unrelated to a focal trait can cause peak shifts in the genetic optimum for the trait. Changes in the fitness threshold not only changed peak locations, but also altered the slopes defining the peaks, and so should alter the rate of evolution towards optima. This model pertains to evolution in any system, unless there is no phenotypic or environmental variance, or the selection function and distribution of phenotypic error assume similar shapes. Our results have many basic and applied implications for topics such as the maintenance of genetic variation, the canalization of development and the management of natural populations.     

Scaling from plot experiments to landscapes: studying grasshoppers to inform forest ecosystem management

Ecologists studying food web interactions routinely conduct their experiments at scales of 1–10 m² whereas real-world landscape-level management problems exist on scales of 10⁶ m² or larger. It is often asserted that the experimental tradition in ecology has little to offer to environmental management because small scale empirical insights are not easily, if at all, translatable to the large scale problems. Small scale experiments are very local in nature and they are conducted in ways that tend to homogenize background environmental variation. Real world management is conducted across vast landscapes. Managers routinely must wrestle with complexity that is introduced by the heterogeneous structure of those landscapes and they often have limited recourse to do careful experimentation. How then is empirical ecological science ever to inform landscape-level management? The solution to this dilemma lies in arriving at good working conceptualizations of ecosystem structure and function that embody principles that are relatively scale independent. In this paper, the evolutionary ecological principle of foraging versus predation risk avoidance trade-offs is proffered as one central organizing conceptualization for plant-herbivore interactions across all systems. The utility of this conceptualization is first illustrated by presenting results of detailed experiments involving spider predators, grasshopper herbivores, and two classes of plant resources that afford grasshoppers differential protection from predators: nutritionally superior but risky grasses and less nutritious but safer herbs. The paper then shows how the foraging versus predation risk avoidance conceptualization in the context of a “landscape of fear” can be applied to manage large herbivore impacts of forest regeneration following forest harvesting. I present results of landscape-scale experiments that mediate predation risk of the herbivores through manipulation of safe habitat in order to enlist herbivores to facilitate boreal forest mixed species regeneration through preferential foraging of certain woody species.     

对微生物工程类虚拟仿真实验建设与共享应用的思考

微生物工程是一门实践性和应用性较强的课程。让学生走进企业的生产线进行实践性学习是必不可少的教学环节。实习资源不足一直是限制微生物工程课程开展高水平实习教学的瓶颈。利用信息技术搭建的虚拟化生产线不但可以使学生从中学习复杂的生产系统中的理论性知识,还能进行更深层次的虚拟操作,从而促进学生实践能力和创新能力的形成。为了更好地发挥虚拟仿真实验项目在本科教学中的作用,文中对微生物工程类虚拟仿真实验项目的教学价值进行了归纳,对其建设进展和特点进行了总结,对限制其共享应用的主要问题进行了分析并提出了解决方案。