Genetic loads under fitness‐dependent mutation rates

Abstract Although much theory depends on the genome‐wide rate of deleterious mutations, good estimates of the mutation rate are scarce and remain controversial. Furthermore, mutation rate may not be constant, and a recent study suggests that mutation rates are higher in mildly stressful environments. If mutation rate is a function of condition, then individuals carrying more mutations will tend to be in worse condition and therefore produce more mutations. Here I examine the mean fitnesses of sexual and asexual populations evolving under such condition‐dependent mutation rates. The equilibrium mean fitness of a sexual population depends on the shape of the curve relating fitness to mutation rate. If mutation rate declines synergistically with increasing condition the mean fitness will be much lower than if mutation rate declines at a diminishing rate. In contrast, asexual populations are less affected by condition‐dependent mutation rates. The equilibrium mean fitness of an asexual population only depends on the mutation rate of the individuals in the least loaded class. Because such individuals have high fitness and therefore a low mutation rate, asexual populations experience less genetic load than sexual populations, thus increasing the twofold cost of sex.     

Ploidy and recombination proficiency shape the evolutionary adaptation to constitutive DNA replication stress

In haploid budding yeast, evolutionary adaptation to constitutive DNA replication stress alters three genome maintenance modules: DNA replication, the DNA damage checkpoint, and sister chromatid cohesion. We asked how these trajectories depend on genomic features by comparing the adaptation in three strains: haploids, diploids, and recombination deficient haploids. In all three, adaptation happens within 1000 generations at rates that are correlated with the initial fitness defect of the ancestors. Mutations in individual genes are selected at different frequencies in populations with different genomic features, but the benefits these mutations confer are similar in the three strains, and combinations of these mutations reproduce the fitness gains of evolved populations. Despite the differences in the selected mutations, adaptation targets the same three functional modules in strains with different genomic features, revealing a common evolutionary response to constitutive DNA replication stress.     

Impediments to replication fork movement: stabilisation, reactivation and genome instability

Maintaining genome stability is essential for the accurate transmission of genetic material. Genetic instability is associated with human genome disorders and is a near-universal hallmark of cancer cells. Genetic variation is also the driving force of evolution, and a genome must therefore display adequate plasticity to evolve while remaining sufficiently stable to prevent mutations and chromosome rearrangements leading to a fitness disadvantage. A primary source of genome instability are errors that occur during chromosome replication. More specifically, obstacles to the movement of replication forks are known to underlie many of the gross chromosomal rearrangements seen both in human cells and in model organisms. Obstacles to replication fork progression destabilize the replisome (replication protein complex) and impact on the integrity of forked DNA structures. Therefore, to ensure the successful progression of a replication fork along with its associated replisome, several distinct strategies have evolved. First, there are well-orchestrated mechanisms that promote continued movement of forks through potential obstacles. Second, dedicated replisome and fork DNA stabilization pathways prevent the dysfunction of the replisome if its progress is halted. Third, should stabilisation fail, there are mechanisms to ensure damaged forks are accurately fused with a converging fork or, when necessary, re-associated with the replication proteins to continue replication. Here, we review what is known about potential barriers to replication fork progression, how these are tolerated and their impact on genome instability.     

The units of selection and measures of fitness

This paper presents a unified account of the properties of the measures, Malthusian parameter and entropy in predicting evolutionary change in populations of macromolecules, cells and individuals. The Malthusian parameter describes the intrinsic rate of increase of the population. The entropy describes the intrinsic variability in populations: it characterizes the variability in mutation and replication rates in populations of macromolecules; the rate of decay of synchrony in populations of cells; and the degree of iteroparity in populations of individuals. The Malthusian parameter determines ultimate population numbers: under constant environmental conditions, it is the rate of increase when equilibrium conditions are attained. Entropy determines population stability: the gain in the Malthusian parameter due to small fluctuations in the life-cycle variables is determined by entropy. These properties, which are valid for populations of macromolecules, cells and individuals, show that the Malthusian parameter and entropy act as complimentary fitness indices in understanding evolutionary change in populations.     

The adaptive value of epigenetic mutation: Limited in large but high in small peripheral populations

The fate of populations during range expansions, invasions and environmental changes is largely influenced by their ability to adapt to peripheral habitats. Recent models demonstrate that stable epigenetic modifications of gene expression that occur more frequently than genetic mutations can both help and hinder adaptation in panmictic populations. However, these models do not consider interactions between epimutations and evolutionary forces in peripheral populations. Here, we use mainland–island mathematical models and simulations to explore how the faster rate of epigenetic mutation compared to genetic mutations interacts with migration, selection and genetic drift to affect adaptation in peripheral populations. Our model focuses on cases where epigenetic marks are stably inherited. In a large peripheral population, where the effect of genetic drift is negligible, our analyses suggest that epimutations with random fitness impacts that occur at rates as high as 10^–3 increase local adaptation when migration is strong enough to overwhelm divergent selection. When migration is weak relative to selection and epimutations with random fitness impacts decrease adaptation, we find epigenetic modifications must be highly adaptively biased to enhance adaptation. Finally, in small peripheral populations, where genetic drift is strong, epimutations contribute to adaptation under a wider range of evolutionary conditions. Overall, our results suggest that epimutations can change outcomes of adaptation in peripheral populations, which has implications for understanding conservation and range expansions and contractions, especially of small populations.     

Vesicular stomatitis virus evolution during alternation between persistent infection in insect cells and acute infection in mammalian cells is dominated by the persistence phase

Vesicular stomatitis virus has the potential for very rapid evolution in the laboratory, but like many other arboviruses, it evolves at a relatively slow rate in the natural environment. Previous work showed that alternating replication in different cell types does not promote stasis. In order to determine whether other factors promote stasis, we compared the fitness trajectories of populations evolving during acute infections in mammalian cells, populations evolving during persistent infections in insect cells, and populations evolving during alternating acute and persistent infection cycles. Populations evolving under constant conditions increased in fitness in the environment in which they replicated. An asymmetric trade-off was observed such that acute infection had no cost for persistence but persistent replication had a dramatic cost for acute infection in mammalian cells. After an initial period of increase, fitness remained approximately constant in all the populations that included persistent replication, but fitness continuously increased in populations evolving during acute infections. Determination of the consensus sequence of the genes encoding the N, P, M, and G proteins showed that the pattern of mutation accumulation was coherent with fitness changes during persistence so that once fitness reached a maximum, the rate of mutation accumulation dropped. Persistent replication dominated both the genetic and the phenotypic evolution of the populations that alternated between acute infection of mammalian cells and persistence in insect cells, and fitness loss was observed in the mammalian environment despite periodic replication in mammalian cells. These results show that stasis can be achieved without good levels of adaptation to both the mammalian and the insect environments.     

Evolutionary rescue and the limits of adaptation

Populations subject to severe stress may be rescued by natural selection, but its operation is restricted by ecological and genetic constraints. The cost of natural selection expresses the limited capacity of a population to sustain the load of mortality or sterility required for effective selection. Genostasis expresses the lack of variation that prevents many populations from adapting to stress. While the role of relative fitness in adaptation is well understood, evolutionary rescue emphasizes the need to recognize explicitly the importance of absolute fitness. Permanent adaptation requires a range of genetic variation in absolute fitness that is broad enough to provide a few extreme types capable of sustained growth under a stress that would cause extinction if they were not present. This principle implies that population size is an important determinant of rescue. The overall number of individuals exposed to selection will be greater when the population declines gradually under a constant stress, or is progressively challenged by gradually increasing stress. In gradually deteriorating environments, survival at lethal stress may be procured by prior adaptation to sublethal stress through genetic correlation. Neither the standing genetic variation of small populations nor the mutation supply of large populations, however, may be sufficient to provide evolutionary rescue for most populations.     

Natural selection fails to optimize mutation rates for long-term adaptation on rugged fitness landscapes

The rate of mutation is central to evolution. Mutations are required for adaptation, yet most mutations with phenotypic effects are deleterious. As a consequence, the mutation rate that maximizes adaptation will be some intermediate value. Here, we used digital organisms to investigate the ability of natural selection to adjust and optimize mutation rates. We assessed the optimal mutation rate by empirically determining what mutation rate produced the highest rate of adaptation. Then, we allowed mutation rates to evolve, and we evaluated the proximity to the optimum. Although we chose conditions favorable for mutation rate optimization, the evolved rates were invariably far below the optimum across a wide range of experimental parameter settings. We hypothesized that the reason that mutation rates evolved to be suboptimal was the ruggedness of fitness landscapes. To test this hypothesis, we created a simplified landscape without any fitness valleys and found that, in such conditions, populations evolved near-optimal mutation rates. In contrast, when fitness valleys were added to this simple landscape, the ability of evolving populations to find the optimal mutation rate was lost. We conclude that rugged fitness landscapes can prevent the evolution of mutation rates that are optimal for long-term adaptation. This finding has important implications for applied evolutionary research in both biological and computational realms.     

Evolution of migration in a periodically changing environment

The ability to migrate can evolve in response to various forces. In particular, when selection is heterogeneous in space but constant in time, local adaptation induces a fitness cost on immigrants and selects against migration. The evolutionary outcome, however, is less clear when selection also varies temporally. Here, we present a two-locus model analyzing the effects of spatial and temporal variability in selection on the evolution of migration. The first locus is under temporally varying selection (various periodic functions are considered, but a general nonparametric framework is used), and the second locus is a modifier controlling migration ability. First, we study the dynamics of local adaptation and derive the migration rate that maximizes local adaptation as a function of the speed and geometry of the fluctuations in the environment. Second, we derive an analytical expression for the evolutionarily stable migration rate. When there is no cost of migration, we show that higher migration rates are favored when selection changes fast. When migration is costly, however, the evolutionarily stable migration rate is maximal for an intermediate speed of the variation of selection. This model may help in understanding the evolution of migration in a broad range of scenarios and, in particular, in host-parasite systems, where selection is thought to vary quickly in both space and time.     

Recombination Accelerates Adaptation on a Large-Scale Empirical Fitness Landscape in HIV-1

Recombination has the potential to facilitate adaptation. In spite of the substantial body of theory on the impact of recombination on the evolutionary dynamics of adapting populations, empirical evidence to test these theories is still scarce. We examined the effect of recombination on adaptation on a large-scale empirical fitness landscape in HIV-1 based on in vitro fitness measurements. Our results indicate that recombination substantially increases the rate of adaptation under a wide range of parameter values for population size, mutation rate and recombination rate. The accelerating effect of recombination is stronger for intermediate mutation rates but increases in a monotonic way with the recombination rates and population sizes that we examined. We also found that both fitness effects of individual mutations and epistatic fitness interactions cause recombination to accelerate adaptation. The estimated epistasis in the adapting populations is significantly negative. Our results highlight the importance of recombination in the evolution of HIV-I.     

Patterns of quantitative genetic variation in multiple dimensions

A fundamental question for both evolutionary biologists and breeders is the extent to which genetic correlations limit the ability of populations to respond to selection. Here I view this topic from three perspectives. First, I propose several nondimensional statistics to quantify the genetic variation present in a suite of traits and to describe the extent to which correlations limit their selection response. A review of five data sets suggests that the total variation differs substantially between populations. In all cases analyzed, however, the “effective number of dimensions” is less than two: more than half of the total genetic variation is explained by a single combination of traits. Second, I consider how patterns of variation affect the average evolutionary response to selection in a random direction. When genetic variation lies in a small number of dimensions but there are a large number of traits under selection, then the average selection response will be reduced substantially from its potential maximum. Third, I discuss how a low genetic correlation between male fitness and female fitness limits the ability of populations to adapt. Data from two recent studies of natural populations suggest this correlation can diminish or even erase any genetic benefit to mate choice. Together these results suggest that adaptation (in natural populations) and genetic improvement (in domesticated populations) may often be as much constrained by patterns of genetic correlation as by the overall amount of genetic variation.     

Population Size Affects Adaptation in Complex Ways: Simulations on Empirical Adaptive Landscapes

Do large populations always outcompete smaller ones? Does increasing the mutation rate have a similar effect to increasing the population size, with respect to the adaptation of a population? How important are substitutions in determining the adaptation rate? In this study, we ask how population size and mutation rate interact to affect adaptation on empirical adaptive landscapes. Using such landscapes, we do not need to make many ad hoc assumption about landscape topography, such as about epistatic interactions among mutations or about the distribution of fitness effects. Moreover, we have a better understanding of all the mutations that occur in a population and their effects on the average fitness of the population than we can know in experimental studies. Our results show that the evolutionary dynamics of a population cannot be fully explained by the population mutation rate \(N\mu\); even at constant \(N\mu\), there can be dramatic differences in the adaptation of populations of different sizes. Moreover, the substitution rate of mutations is not always equivalent to the adaptation rate, because we observed populations adapting to high adaptive peaks without fixing any mutations. Finally, in contrast to some theoretical predictions, even on the most rugged landscapes we study, small population size is never an advantage over larger population size. These result show that complex interactions among multiple factors can affect the evolutionary dynamics of populations, and simple models should be taken with caution.     

Detecting sexual conflict and sexually antagonistic coevolution

We begin by providing an operational definition of sexual conflict that applies to both inter- and intralocus conflict. Using this definition, we examine a series of simple coevolutionary models to elucidate fruitful approaches for detecting interlocus sexual conflict and resultant sexually antagonistic coevolution. We then use published empirical examples to illustrate the utility of these approaches. Three relevant attributes emerge. First, the dynamics of sexually antagonistic coevolution may obscure the conflict itself. Second, competing models of inter-sexual coevolution may yield similar population patterns near equilibria. Third, a variety of evolutionary forces underlying competing models may be acting simultaneously near equilibria. One main conclusion is that studies of emergent patterns in extant populations (e.g. studies of population and/or female fitness) are unlikely to allow us to distinguish among competing coevolutionary models. Instead, we need more research aimed at identifying the forces of selection acting on shared traits and sexually antagonistic traits. More specifically, we need a greater number of functional studies of female traits as well as studies of the consequences of both male and female traits for female fitness. A mix of selection and manipulative studies on these is likely the most promising route.     

Lethal mutagenesis and evolutionary epidemiology

The lethal mutagenesis hypothesis states that within-host populations of pathogens can be driven to extinction when the load of deleterious mutations is artificially increased with a mutagen, and becomes too high for the population to be maintained. Although chemical mutagens have been shown to lead to important reductions in viral titres for a wide variety of RNA viruses, the theoretical underpinnings of this process are still not clearly established. A few recent models sought to describe lethal mutagenesis but they often relied on restrictive assumptions. We extend this earlier work in two novel directions. First, we derive the dynamics of the genetic load in a multivariate Gaussian fitness landscape akin to classical quantitative genetics models. This fitness landscape yields a continuous distribution of mutation effects on fitness, ranging from deleterious to beneficial (i.e. compensatory) mutations. We also include an additional class of lethal mutations. Second, we couple this evolutionary model with an epidemiological model accounting for the within-host dynamics of the pathogen. We derive the epidemiological and evolutionary equilibrium of the system. At this equilibrium, the density of the pathogen is expected to decrease linearly with the genomic mutation rate U. We also provide a simple expression for the critical mutation rate leading to extinction. Stochastic simulations show that these predictions are accurate for a broad range of parameter values. As they depend on a small set of measurable epidemiological and evolutionary parameters, we used available information on several viruses to make quantitative and testable predictions on critical mutation rates. In the light of this model, we discuss the feasibility of lethal mutagenesis as an efficient therapeutic strategy.     

Experimental evolution and the dynamics of genomic mutation rate modifiers

Because genes that affect mutation rates are themselves subject to mutation, mutation rates can be influenced by natural selection and other evolutionary forces. The population genetics of mutation rate modifier alleles has been a subject of theoretical interest for many decades. Here, we review experimental contributions to our understanding of mutation rate modifier dynamics. Numerous evolution experiments have shown that mutator alleles (modifiers that elevate the genomic mutation rate) can readily rise to high frequencies via genetic hitchhiking in non-recombining microbial populations. Whereas these results certainly provide an explanatory framework for observations of sporadically high mutation rates in pathogenic microbes and in cancer lineages, it is nonetheless true that most natural populations have very low mutation rates. This raises the interesting question of how mutator hitchhiking is suppressed or its phenotypic effect reversed in natural populations. Very little experimental work has addressed this question; with this in mind, we identify some promising areas for future experimental investigation.     

Thermoregulation, Flight, and the Evolution of Wing Pattern in Pierid Butterflies: The Topography of Adaptive Landscapes

SYNOPSIS. This paper describes a case study of adaptation, constraint,and evolutionary innovation in pierid butterflies. I developa framework for discussing these issues that focuses on thequestions: What is the form of the adaptive landscape relatingfitness to phenotypic characters? How do such landscapes differfor evolutionarily related groups? I examine the evolution ofwing pigment patterns and thermoregulatory behavior for butterfliesin two subfamilies in the family Pieridae, with three principalresults. First, I show that thermoregulation can be an importantcomponent of fitness in pierids, and that wing color and thermoregulatorybehavior are important phenotypic characters determining thermoregulatoryperformance and the adaptive landscape. Second, I show how limitson possible variation in wing color and behavior constrain evolutionwithin one subfamily of pierids, and how these constraints areset by the physical and biochemical mechanisms of adaptation.Third, I show how evolutionary innovation may have resultedfrom the addition of a new, behavioral dimension to the landscape,and how this addition has altered the functional interrelationsamong various elements of the wing color pattern. I suggestthat comparative analyses of the form and determinants of theadaptive landscape may be useful in identifying evolutionaryinnovations, and complement theoretical analyses of evolutionarydynamics on such fitness surfaces.     

EVOLUTIONARY REVERSALS OF ANTIBIOTIC RESISTANCE IN EXPERIMENTAL POPULATIONS OF PSEUDOMONAS AERUGINOSA

Antibiotic resistance mutations are accompanied by a fitness cost, and two mechanisms allow bacteria to adapt to this cost once antibiotic use is halted. First, it is possible for resistance to revert; second, it is possible for bacteria to adapt to the cost of resistance by compensatory mutations. Unfortunately, reversion to antibiotic sensitivity is rare, but the underlying factors that prevent reversion remain obscure. Here, we directly study the evolutionary dynamics of reversion by experimentally mimicking reversion mutations—sensitives—in populations of rifampicin‐resistant Pseudomonas aeruginosa. We show that, in our populations, most sensitives are lost due to genetic drift when they are rare. However, clonal interference from lineages carrying compensatory mutations causes a dramatic increase in the time to fixation of sensitives that escape genetic drift, and mutations surpassing the sensitives’ fitness are capable of driving transiently common sensitive lineages to extinction. Crucially, we show that the constraints on reversion arising from clonal interference are determined by the potential for compensatory adaptation of the resistant population. Although the cost of resistance provides the incentive for reversion, our study demonstrates that both the cost of resistance and the intrinsic evolvability of resistant populations interact to determine the rate and likelihood of reversion.