Major role of positive selection in the evolution of conservative segments of Drosophila proteins

Slow evolution of conservative segments of coding and non-coding DNA is caused by the action of negative selection, which removes new mutations. However, the mode of selection that affects the few substitutions that do occur within such segments remains unclear. Here, we show that the fraction of allele replacements that were driven by positive selection, and the strength of this selection, is the highest within the conservative segments of Drosophila protein-coding genes. The McDonald-Kreitman test, applied to the data on variation in Drosophila melanogaster and in Drosophila simulans, indicates that within the most conservative protein segments, approximately 72 per cent (approx. 80%) of allele replacements were driven by positive selection, as opposed to only approximately 44 per cent (approx. 53%) at rapidly evolving segments. Data on multiple non-synonymous substitutions at a codon lead to the same conclusion and additionally indicate that positive selection driving allele replacements at conservative sites is the strongest, as it accelerates evolution by a factor of approximately 40, as opposed to a factor of approximately 5 at rapidly evolving sites. Thus, random drift plays only a minor role in the evolution of conservative DNA segments, and those relatively rare allele replacements that occur within such segments are mostly driven by substantial positive selection.     

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.     

Population-Genomic Analysis Identifies a Low Rate of Global Adaptive Fixation in the Proteins of the Cyclical Parthenogen Daphnia magna

Daphnia are well-established ecological and evolutionary models, and the interaction between D. magna and its microparasites is widely considered a paragon of the host-parasite coevolutionary process. Like other well-studied arthropods such as Drosophila melanogaster and Anopheles gambiae, D. magna is a small, widespread, and abundant species that is therefore expected to display a large long-term population size and high rates of adaptive protein evolution. However, unlike these other species, D. magna is cyclically asexual and lives in a highly structured environment (ponds and lakes) with moderate levels of dispersal, both of which are predicted to impact upon long-term effective population size and adaptive protein evolution. To investigate patterns of adaptive protein fixation, we produced the complete coding genomes of 36 D. magna clones sampled from across the European range (Western Palaearctic), along with draft sequences for the close relatives D. similis and D. lumholtzi, used as outgroups. We analyzed genome-wide patterns of adaptive fixation, with a particular focus on genes that have an a priori expectation of high rates, such as those likely to mediate immune responses, RNA interference against viruses and transposable elements, and those with a strongly male-biased expression pattern. We find that, as expected, D. magna displays high levels of diversity and that this is highly structured among populations. However, compared with Drosophila, we find that D. magna proteins appear to have a high proportion of weakly deleterious variants and do not show evidence of pervasive adaptive fixation across its entire range. This is true of the genome as a whole, and also of putative ‘arms race’ genes that often show elevated levels of adaptive substitution in other species. In addition to the likely impact of extensive, and previously documented, local adaptation, we speculate that these findings may reflect reduced efficacy of selection associated with cyclical asexual reproduction.     

Dissecting Genomic Determinants of Positive Selection with an Evolution-Guided Regression Model

In evolutionary genomics, it is fundamentally important to understand how characteristics of genomic sequences, such as gene expression level, determine the rate of adaptive evolution. While numerous statistical methods, such as the McDonald–Kreitman (MK) test, are available to examine the association between genomic features and the rate of adaptation, we currently lack a statistical approach to disentangle the independent effect of a genomic feature from the effects of other correlated genomic features. To address this problem, I present a novel statistical model, the MK regression, which augments the MK test with a generalized linear model. Analogous to the classical multiple regression model, the MK regression can analyze multiple genomic features simultaneously to infer the independent effect of a genomic feature, holding constant all other genomic features. Using the MK regression, I identify numerous genomic features driving positive selection in chimpanzees. These features include well-known ones, such as local mutation rate, residue exposure level, tissue specificity, and immune genes, as well as new features not previously reported, such as gene expression level and metabolic genes. In particular, I show that highly expressed genes may have a higher adaptation rate than their weakly expressed counterparts, even though a higher expression level may impose stronger negative selection. Also, I show that metabolic genes may have a higher adaptation rate than their nonmetabolic counterparts, possibly due to recent changes in diet in primate evolution. Overall, the MK regression is a powerful approach to elucidate the genomic basis of adaptation.     

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.     

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.     

Context dependence in complex adaptive landscapes: frequency and trait‐dependent selection surfaces within an adaptive radiation of Caribbean pupfishes

The adaptive landscape provides the foundational bridge between micro‐ and macroevolution. One well‐known caveat to this perspective is that fitness surfaces depend on ecological context, including competitor frequency, traits measured, and resource abundance. However, this view is based largely on intraspecific studies. It is still unknown how context‐dependence affects the larger features of peaks and valleys on the landscape which ultimately drive speciation and adaptive radiation. Here, I explore this question using one of the most complex fitness landscapes measured in the wild in a sympatric pupfish radiation endemic to San Salvador Island, Bahamas by tracking survival and growth of laboratory‐reared F2 hybrids. I present new analyses of the effects of competitor frequency, dietary isotopes, and trait subsets on this fitness landscape. Contrary to expectations, decreasing competitor frequency increased survival only among very common phenotypes, whereas less common phenotypes rarely survived despite few competitors, suggesting that performance, not competitor frequency, shapes large‐scale features of the fitness landscape. Dietary isotopes were weakly correlated with phenotype and growth, but did not explain additional survival variation. Nonlinear fitness surfaces varied substantially among trait subsets, revealing one‐, two‐, and three‐peak landscapes, demonstrating the complexity of selection in the wild, even among similar functional traits.     

Compensatory adaptation and diversification subsequent to evolutionary rescue in a model adaptive radiation

Biological populations may survive lethal environmental stress through evolutionary rescue. The rescued populations typically suffer a reduction in growth performance and harbor very low genetic diversity compared with their parental populations. The present study addresses how population size and within‐population diversity may recover through compensatory evolution, using the experimental adaptive radiation of bacterium Pseudomonas fluorescens. We exposed bacterial populations to an antibiotic treatment and then imposed a one‐individual‐size population bottleneck on those surviving the antibiotic stress. During the subsequent compensatory evolution, population size increased and leveled off very rapidly. The increase of diversity was of slower paces and persisted longer. In the very early stage of compensatory evolution, populations of large sizes had a greater chance to diversify; however, this productivity–diversification relationship was not observed in later stages. Population size and diversity from the end of the compensatory evolution was not contingent on initial population growth performance. We discussed the possibility that our results be explained by the emergence of a “holey” fitness landscape under the antibiotic stress.     

Defining the landscape of adaptive genetic diversity

Whether they are used to describe fitness, genome architecture or the spatial distribution of environmental variables, the concept of a landscape has figured prominently in our collective reasoning. The tradition of landscapes in evolutionary biology is one of fitness mapped onto axes defined by phenotypes or molecular sequence states. The characteristics of these landscapes depend on natural selection, which is structured across both genomic and environmental landscapes, and thus, the bridge among differing uses of the landscape concept (i.e. metaphorically or literally) is that of an adaptive phenotype and its distribution across geographical landscapes in relation to selective pressures. One of the ultimate goals of evolutionary biology should thus be to construct fitness landscapes in geographical space. Natural plant populations are ideal systems with which to explore the feasibility of attaining this goal, because much is known about the quantitative genetic architecture of complex traits for many different plant species. What is less known are the molecular components of this architecture. In this issue of Molecular Ecology, Parchman et al. (2012) pioneer one of the first truly genome-wide association studies in a tree that moves us closer to this form of mechanistic understanding for an adaptive phenotype in natural populations of lodgepole pine (Pinus contorta Dougl. ex Loud.).     

Genetic diversity at neutral and adaptive loci determines individual fitness in a long-lived territorial bird

There is compelling evidence about the manifest effects of inbreeding depression on individual fitness and populations' risk of extinction. The majority of studies addressing inbreeding depression on wild populations are generally based on indirect measures of inbreeding using neutral markers. However, the study of functional loci, such as genes of the major histocompatibility complex (MHC), is highly recommended. MHC genes constitute an essential component of the immune system of individuals, which is directly related to individual fitness and survival. In this study, we analyse heterozygosity fitness correlations of neutral and adaptive genetic variation (22 microsatellite loci and two loci of the MHC class II, respectively) with the age of recruitment and breeding success of a decimated and geographically isolated population of a long-lived territorial vulture. Our results indicate a negative correlation between neutral genetic diversity and age of recruitment, suggesting that inbreeding may be delaying reproduction. We also found a positive correlation between functional (MHC) genetic diversity and breeding success, together with a specific positive effect of the most frequent pair of cosegregating MHC alleles in the population. Globally, our findings demonstrate that genetic depauperation in small populations has a negative impact on the individual fitness, thus increasing the populations' extinction risk.     

How Biochemical Constraints of Cellular Growth Shape Evolutionary Adaptations in Metabolism

Evolutionary adaptations in metabolic networks are fundamental to evolution of microbial growth. Studies on unneeded-protein synthesis indicate reductions in fitness upon nonfunctional protein synthesis, showing that cell growth is limited by constraints acting on cellular protein content. Here, we present a theory for optimal metabolic enzyme activity when cells are selected for maximal growth rate given such growth-limiting biochemical constraints. We show how optimal enzyme levels can be understood to result from an enzyme benefit minus cost optimization. The constraints we consider originate from different biochemical aspects of microbial growth, such as competition for limiting amounts of ribosomes or RNA polymerases, or limitations in available energy. Enzyme benefit is related to its kinetics and its importance for fitness, while enzyme cost expresses to what extent resource consumption reduces fitness through constraint-induced reductions of other enzyme levels. A metabolic fitness landscape is introduced to define the fitness potential of an enzyme. This concept is related to the selection coefficient of the enzyme and can be expressed in terms of its fitness benefit and cost.     

A minimum on the mean number of steps taken in adaptive walks

I consider the adaptation of a DNA sequence when mutant fitnesses are drawn randomly from a probability distribution. I focus on "gradient" adaptation in which the population jumps to the best mutant sequence available at each substitution. Given a random starting point, I derive the distribution of the number of substitutions that occur during adaptive walks to a locally optimal sequence. I show that the mean walk length is a constant:L = e-1, where e approximately 2.72. I argue that this result represents a limit on what is possible under any form of adaptation. No adaptive algorithm on any fitness landscape can arrive at a local optimum in fewer than a mean of L = e-1 steps when starting from a random sequence. Put differently, evolution must try out at least e wild-type sequences during an average bout of adaptation.     

Surfing on the seascape: Adaptation in a changing environment

The environment changes constantly at various time scales and, in order to survive, species need to keep adapting. Whether these species succeed in avoiding extinction is a major evolutionary question. Using a multilocus evolutionary model of a mutation‐limited population adapting under strong selection, we investigate the effects of the frequency of environmental fluctuations on adaptation. Our results rely on an “adaptive‐walk” approximation and use mathematical methods from evolutionary computation theory to investigate the interplay between fluctuation frequency, the similarity of environments, and the number of loci contributing to adaptation. First, we assume a linear additive fitness function, but later generalize our results to include several types of epistasis. We show that frequent environmental changes prevent populations from reaching a fitness peak, but they may also prevent the large fitness loss that occurs after a single environmental change. Thus, the population can survive, although not thrive, in a wide range of conditions. Furthermore, we show that in a frequently changing environment, the similarity of threats that a population faces affects the level of adaptation that it is able to achieve. We check and supplement our analytical results with simulations.     

Global view of bionetwork dynamics: adaptive landscape

Based on recent work, I will give a nontechnical brief review of a powerful quantitative concept in biology, adaptive landscape, ini- tially proposed by S. Wright over 70 years ago, reintroduced by one of the founders of molecular biology and by others in different bio- logical contexts, but apparently forgotten by modem biologists for many years. Nevertheless, this concept finds an increasingly important role in the development of systems biology and bionetwork dynamics modeling, from phage lambda genetic switch to endogenous net- work for cancer genesis and progression. It is an ideal quantification to describe the robustness and stability of bionetworks. Here, I will first introduce five landmark proposals in biology on this concept, to demonstrate an important common thread in theoretical biology. Then I will discuss a few recent results, focusing on the studies showing theoretical consistency of adaptive landscape. From the perspec- tive of a working scientist and of what is needed logically for a dynamical theory when confronting empirical data, the adaptive landscape is useful both metaphorically and quantitatively, and has captured an essential aspect of biological dynamical processes. Though at the theoretical level the adaptive landscape must exist and it can be used across hierarchical boundaries in biology, many associated issues are indeed vague in their initial formulations and their quantitative realizations are not easy, and are good research topics for quantitative biologists. I will discuss three types of open problems associated with the adaptive landscape in a broader perspective.     

Ecological variation in South American geophagine cichlids arose during an early burst of adaptive morphological and functional evolution

Diversity and disparity are unequally distributed both phylogenetically and geographically. This uneven distribution may be owing to differences in diversification rates between clades resulting from processes such as adaptive radiation. We examined the rate and distribution of evolution in feeding biomechanics in the extremely diverse and continentally distributed South American geophagine cichlids. Evolutionary patterns in multivariate functional morphospace were examined using a phylomorphospace approach, disparity-through-time analyses and by comparing Brownian motion (BM) and adaptive peak evolutionary models using maximum likelihood. The most species-rich and functionally disparate clade (CAS) expanded more efficiently in morphospace and evolved more rapidly compared with both BM expectations and its sister clade (GGD). Members of the CAS clade also exhibited an early burst in functional evolution that corresponds to the development of modern ecological roles and may have been related to the colonization of a novel adaptive peak characterized by fast oral jaw mechanics. Furthermore, reduced ecological opportunity following this early burst may have restricted functional evolution in the GGD clade, which is less species-rich and more ecologically specialized. Patterns of evolution in ecologically important functional traits are consistent with a pattern of adaptive radiation within the most diverse clade of Geophagini.     

Temperature fluctuations during development reduce male fitness and may limit adaptive potential in tropical rainforest Drosophila

Understanding the potential for organisms to tolerate thermal stress through physiological or evolutionary responses is crucial given rapid climate change. Although climate models predict increases in both temperature mean and variance, such tolerances are typically assessed under constant conditions. We tested the effects of temperature variability during development on male fitness in the rainforest fly Drosophila birchii, by simulating thermal variation typical of the warm and cool margins of its elevational distribution, and estimated heritabilities and genetic correlations of fitness traits. Reproductive success was reduced for males reared in warm (mean 24 °C) fluctuating (±3 °C) vs. constant conditions but not in cool fluctuating conditions (mean 17 °C), although fluctuations reduced body size at both temperatures. Male reproductive success under warm fluctuating conditions was similar to that at constant 27 °C, indicating that briefly exceeding critical thermal limits has similar fitness costs to continuously stressful conditions. There was substantial heritable variation in all traits. However, reproductive success traits showed no genetic correlation between treatments reflecting temperature variation at elevational extremes, which may constrain evolutionary responses at these ecological margins. Our data suggest that even small increases in temperature variability will threaten tropical ectotherms living close to their upper thermal limits, both through direct effects on fitness and by limiting their adaptive potential.     

The length of adaptive walks is insensitive to starting fitness in Aspergillus nidulans

Adaptation involves the successive substitution of beneficial mutations by selection, a process known as an adaptive walk. Gradualist models of adaptation, which assume that all mutations are small relative to the distance to a fitness optimum, predict that adaptive walks should be longer when the founding genotype is less well adapted. More recent work modeling adaptation as a sequence of moves in phenotype or genotype space predicts, by contrast, much shorter adaptive walks irrespective of the fitness of the founding genotype. Here, we provide what is, to the best of our knowledge, the first direct test of these alternative models, measuring the length of adaptive walks in evolving lineages of fungus that differ initially in fitness. Contrary to the gradualist view, we show that the length of adaptive walks in the fungus Aspergillus nidulans is insensitive to starting fitness and involves just two mutations on average. This arises because poorly adapted populations tend to fix mutations of larger average effect than those of better-adapted populations. Our results suggest that the length of adaptive walks may be independent of the fitness of the founding genotype and, moreover, that poorly adapted populations can quickly adapt to novel environments.     

The population genetics of adaptation: the adaptation of DNA sequences

I describe several patterns characterizing the genetics of adaptation at the DNA level. Following Gillespie (1983, 1984, 1991), I consider a population presently fixed for the ith best allele at a locus and study the sequential substitution of favorable mutations that results in fixation of the fittest DNA sequence locally available. Given a wild type sequence that is less than optimal, I derive the fitness rank of the next allele typically fixed by natural selection as well as the mean and variance of the jump in fitness that results when natural selection drives a substitution. Looking over the whole series of substitutions required to reach the best allele, I show that the mean fitness jumps occurring throughout an adaptive walk are constrained to a twofold window of values, assuming only that adaptation begins from a reasonably fit allele. I also show that the first substitution and the substitution of largest effect account for a large share of the total fitness increase during adaptation. I further show that the distribution of selection coefficients fixed throughout such an adaptive walk is exponential (ignoring mutations of small effect), a finding reminiscent of that seen in Fisher's geometric model of adaptation. Last, I show that adaptation by natural selection behaves in several respects as the average of two idealized forms of adaptation, perfect and random.     

Dynamic RNA Fitness Landscapes of a Group I Ribozyme during Changes to the Experimental Environment

Fitness landscapes of protein and RNA molecules can be studied experimentally using high-throughput techniques to measure the functional effects of numerous combinations of mutations. The rugged topography of these molecular fitness landscapes is important for understanding and predicting natural and experimental evolution. Mutational effects are also dependent upon environmental conditions, but the effects of environmental changes on fitness landscapes remains poorly understood. Here, we investigate the changes to the fitness landscape of a catalytic RNA molecule while changing a single environmental variable that is critical for RNA structure and function. Using high-throughput sequencing of in vitro selections, we mapped a fitness landscape of the Azoarcus group I ribozyme under eight different concentrations of magnesium ions (1–48 mM MgCl₂). The data revealed the magnesium dependence of 16,384 mutational neighbors, and from this, we investigated the magnesium induced changes to the topography of the fitness landscape. The results showed that increasing magnesium concentration improved the relative fitness of sequences at higher mutational distances while also reducing the ruggedness of the mutational trajectories on the landscape. As a result, as magnesium concentration was increased, simulated populations evolved toward higher fitness faster. Curve-fitting of the magnesium dependence of individual ribozymes demonstrated that deep sequencing of in vitro reactions can be used to evaluate the structural stability of thousands of sequences in parallel. Overall, the results highlight how environmental changes that stabilize structures can also alter the ruggedness of fitness landscapes and alter evolutionary processes.     

Evolution toward a new adaptive optimum: phenotypic evolution in a fossil stickleback lineage

Natural selection has almost certainly shaped many evolutionary trajectories documented in fossil lineages, but it has proven difficult to demonstrate this claim by analyzing sequences of evolutionary changes. In a recently published and particularly promising test case, an evolutionary time series of populations displaying armor reduction in a fossil stickleback lineage could not be consistently distinguished from a null model of neutral drift, despite excellent temporal resolution and an abundance of indirect evidence implicating natural selection. Here, we revisit this case study, applying analyses that differ from standard approaches in that: (1) we do not treat genetic drift as a null model, and instead assess neutral and adaptive explanations on equal footing using the Akaike Information Criterion; and (2) rather than constant directional selection, the adaptive scenario we consider is that of a population ascending a peak on the adaptive landscape, modeled as an Orstein-Uhlenbeck process. For all three skeletal features measured in the stickleback lineage, the adaptive model decisively outperforms neutral evolution, supporting a role for natural selection in the evolution of these traits. These results demonstrate that, at least under favorable circumstances, it is possible to infer in fossil lineages the relationship between evolutionary change and features of the adaptive landscape.