Whose trait is it anyways? Coevolution of joint phenotypes and genetic architecture in mutualisms

Evolutionary biologists typically envision a trait’s genetic basis and fitness effects occurring within a single species. However, traits can be determined by and have fitness consequences for interacting species, thus evolving in multiple genomes. This is especially likely in mutualisms, where species exchange fitness benefits and can associate over long periods of time. Partners may experience evolutionary conflict over the value of a multi-genomic trait, but such conflicts may be ameliorated by mutualism’s positive fitness feedbacks. Here, we develop a simulation model of a host–microbe mutualism to explore the evolution of a multi-genomic trait. Coevolutionary outcomes depend on whether hosts and microbes have similar or different optimal trait values, strengths of selection and fitness feedbacks. We show that genome-wide association studies can map joint traits to loci in multiple genomes and describe how fitness conflict and fitness feedback generate different multi-genomic architectures with distinct signals around segregating loci. Partner fitnesses can be positively correlated even when partners are in conflict over the value of a multi-genomic trait, and conflict can generate strong mutualistic dependency. While fitness alignment facilitates rapid adaptation to a new optimum, conflict maintains genetic variation and evolvability, with implications for applied microbiome science.     

Distinguishing driver and passenger mutations in an evolutionary history categorized by interference

In many biological scenarios, from the development of drug resistance in pathogens to the progression of healthy cells toward cancer, quantifying the selection acting on observed mutations is a central question. One difficulty in answering this question is the complexity of the background upon which mutations can arise, with multiple potential interactions between genetic loci. We here present a method for discerning selection from a population history that accounts for interference between mutations. Given sequences sampled from multiple time points in the history of a population, we infer selection at each locus by maximizing a likelihood function derived from a multilocus evolution model. We apply the method to the question of distinguishing between loci where new mutations are under positive selection (drivers) and loci that emit neutral mutations (passengers) in a Wright-Fisher model of evolution. Relative to an otherwise equivalent method in which the genetic background of mutations was ignored, our method inferred selection coefficients more accurately for both driver mutations evolving under clonal interference and passenger mutations reaching fixation in the population through genetic drift or hitchhiking. In a population history recorded by 750 sets of sequences of 100 individuals taken at intervals of 100 generations, a set of 50 loci were divided into drivers and passengers with a mean accuracy of >0.95 across a range of numbers of driver loci. The potential application of our model, either in full or in part, to a range of biological systems, is discussed.     

The long-term evolution of multilocus traits under frequency-dependent disruptive selection

Frequency-dependent disruptive selection is widely recognized as an important source of genetic variation. Its evolutionary consequences have been extensively studied using phenotypic evolutionary models, based on quantitative genetics, game theory, or adaptive dynamics. However, the genetic assumptions underlying these approaches are highly idealized and, even worse, predict different consequences of frequency-dependent disruptive selection. Population genetic models, by contrast, enable genotypic evolutionary models, but traditionally assume constant fitness values. Only a minority of these models thus addresses frequency-dependent selection, and only a few of these do so in a multilocus context. An inherent limitation of these remaining studies is that they only investigate the short-term maintenance of genetic variation. Consequently, the long-term evolution of multilocus characters under frequency-dependent disruptive selection remains poorly understood. We aim to bridge this gap between phenotypic and genotypic models by studying a multilocus version of Levene's soft-selection model. Individual-based simulations and deterministic approximations based on adaptive dynamics theory provide insights into the underlying evolutionary dynamics. Our analysis uncovers a general pattern of polymorphism formation and collapse, likely to apply to a wide variety of genetic systems: after convergence to a fitness minimum and the subsequent establishment of genetic polymorphism at multiple loci, genetic variation becomes increasingly concentrated on a few loci, until eventually only a single polymorphic locus remains. This evolutionary process combines features observed in quantitative genetics and adaptive dynamics models, and it can be explained as a consequence of changes in the selection regime that are inherent to frequency-dependent disruptive selection. Our findings demonstrate that the potential of frequency-dependent disruptive selection to maintain polygenic variation is considerably smaller than previously expected.     

The evolutionary genomics of pathogen recombination

A pressing problem in studying the evolution of microbial pathogens is to determine the extent to which these genomes recombine. This information is essential for locating pathogenicity loci by using association studies or population genetic approaches. Recombination also complicates the use of phylogenetic approaches to estimate evolutionary parameters such as selection pressures. Reliable methods that detect and estimate the rate of recombination are, therefore, vital. This article reviews the approaches that are available for detecting and estimating recombination in microbial pathogens and how they can be used to understand pathogen evolution and to identify medically relevant loci.     

Specific resistance prevents the evolution of general resistance and facilitates disease emergence

Host-shifts, where pathogens jump from an ancestral host to a novel host, can be facilitated or impeded by standing variation in disease resistance, but only if resistance provides broad-spectrum general resistance against multiple pathogen species. Host resistance comes in many forms and includes both general resistance, as well as specific resistance, which may only be effective against a single pathogen species or even genotype. However, most evolutionary models consider only one of these forms of resistance, and we have less understanding of how these two forms of resistance evolve in tandem. Here, we develop a model that allows for the joint evolution of specific and general resistance and asks if the evolution of specific resistance drives a decrease in the evolution of general resistance. We also explore how these evolutionary outcomes affect the risk of foreign pathogen invasion and persistence. We show that in the presence of a single endemic pathogen, the two forms of resistance are strongly exclusionary. Critically, we find that specific resistance polymorphisms can prevent the evolution of general resistance, facilitating the invasion of foreign pathogens. We also show that specific resistance polymorphisms are a necessary condition for the successful establishment of foreign pathogens following invasion, as they prevent the exclusion of the foreign pathogen by the more transmissible endemic pathogen. Our results demonstrate the importance of considering the joint evolution of multiple forms of resistance when evaluating a population's susceptibility to foreign pathogens.     

Evolution of plant resistance at the molecular level: ecological context of species interactions

Molecular data regarding the diversity of plant loci involved in resistance to herbivores or pathogens are becoming increasingly available. These genes demonstrate variable patterns of diversity, suggesting that they differ in their evolutionary history. In parallel, the study of natural variation for resistance, generally conducted at the phenotypic level, has shown that resistance does not evolve solely under selection pressures exerted by enemies. Metapopulation dynamics and other ecological characteristics of interacting species also appear to have a large impact on resistance evolution. Until now, studies of resistance at the molecular level have been conducted separately from ecological studies in extant populations. Future progress requires an evolutionary approach integrating both molecular and ecological aspects of resistance evolution. Such an approach will contribute greatly to our understanding of the evolution of molecular diversity at loci involved in biotic stress.     

Fast drug rotation reduces bacterial resistance evolution in a microcosm experiment

Drug rotation (cycling), in which multiple drugs are administrated alternatively, has the potential for limiting resistance evolution in pathogens. The frequency of drug alternation could be a major factor to determine the effectiveness of drug rotation. Drug rotation practices often have low frequency of drug alternation, with an expectation of resistance reversion. Here we, based on evolutionary rescue and compensatory evolution theories, suggest that fast drug rotation can limit resistance evolution in the first place. This is because fast drug rotation would give little time for the evolutionarily rescued populations to recover in population size and genetic diversity, and thus decrease the chance of future evolutionary rescue under alternate environmental stresses. We experimentally tested this hypothesis using the bacterium Pseudomonas fluorescens and two antibiotics (chloramphenicol and rifampin). Increasing drug rotation frequency reduced the chance of evolutionary rescue, and most of the finally surviving bacterial populations were resistant to both drugs. Drug resistance incurred significant fitness costs, which did not differ among the drug treatment histories. A link between population sizes during the early stages of drug treatment and the end-point fates of populations (extinction vs survival) suggested that population size recovery and compensatory evolution before drug shift increase the chance of population survival. Our results therefore advocate fast drug rotation as a promising approach to reduce bacterial resistance evolution, which in particular could be a substitute for drug combination when the latter has safety risks.     

Eco‐evolutionary feedbacks between prey densities and linkage disequilibrium in the predator maintain diversity

Diversity occurs at multiple scales. Within a single population, there is diversity in genotypes and phenotypes. At a larger scale, within ecological communities, there is diversity in species. A number of studies have investigated how diversity at these two scales influence each other through what has been termed eco‐evolutionary feedbacks. Here we study a three‐species ecological module called apparent competition, in which the predator is evolving in a trait that determines its interaction with two prey species. Unlike previous studies on apparent competition, which employed evolutionary frameworks with very simple genetics, we study an eco‐evolutionary model in which the predator's trait is determined by two recombining diallelic loci, so that its mean and variance can evolve, as well as associations (linkage disequilibrium) between the loci. We ask how eco‐evolutionary feedbacks with these two loci affect the coexistence of the prey species and the maintenance of polymorphisms within the predator species. We uncover a novel eco‐evolutionary feedback between the prey densities and the linkage disequilibrium between the predator's loci. Through a stability analysis, we demonstrate how these feedbacks affect polymorphisms at both loci and, among others, may generate stable cycling.     

Genetic diversity in cytokines associated with immune variation and resistance to multiple pathogens in a natural rodent population

Pathogens are believed to drive genetic diversity at host loci involved in immunity to infectious disease. To date, studies exploring the genetic basis of pathogen resistance in the wild have focussed almost exclusively on genes of the Major Histocompatibility Complex (MHC); the role of genetic variation elsewhere in the genome as a basis for variation in pathogen resistance has rarely been explored in natural populations. Cytokines are signalling molecules with a role in many immunological and physiological processes. Here we use a natural population of field voles (Microtus agrestis) to examine how genetic diversity at a suite of cytokine and other immune loci impacts the immune response phenotype and resistance to several endemic pathogen species. By using linear models to first control for a range of non-genetic factors, we demonstrate strong effects of genetic variation at cytokine loci both on host immunological parameters and on resistance to multiple pathogens. These effects were primarily localized to three cytokine genes (Interleukin 1 beta (Il1b), Il2, and Il12b), rather than to other cytokines tested, or to membrane-bound, non-cytokine immune loci. The observed genetic effects were as great as for other intrinsic factors such as sex and body weight. Our results demonstrate that genetic diversity at cytokine loci is a novel and important source of individual variation in immune function and pathogen resistance in natural populations. The products of these loci are therefore likely to affect interactions between pathogens and help determine survival and reproductive success in natural populations. Our study also highlights the utility of wild rodents as a model of ecological immunology, to better understand the causes and consequences of variation in immune function in natural populations including humans.     

The red queen coupled with directional selection favours the evolution of sex

Why sexual reproduction has evolved to be such a widespread mode of reproduction remains a major question in evolutionary biology. Although previous studies have shown that increased sex and recombination can evolve in the presence of host-parasite interactions (the 'Red Queen hypothesis' for sex), many of these studies have assumed that multiple loci mediate infection vs. resistance. Data suggest, however, that a major locus is typically involved in antigen presentation and recognition. Here, we explore a model where only one locus mediates host-parasite interactions, but a second locus is subject to directional selection. Even though the effects of these genes on fitness are independent, we show that increased rates of sex and recombination are favoured at a modifier gene that alters the rate of genetic mixing. This result occurs because of selective interference in finite populations (the 'Hill-Robertson effect'), which also favours sex. These results suggest that the Red Queen hypothesis may help to explain the evolution of sex by contributing a form of persistent selection, which interferes with directional selection at other loci and thereby favours sex and recombination.     

Nonheritable cellular variability accelerates the evolutionary processes of cancer

Recent cancer studies emphasize that genetic and heritable epigenetic changes drive the evolutionary rate of cancer progression and drug resistance. We discuss the ways in which nonheritable aspects of cellular variability may significantly increase evolutionary rate. Nonheritable variability arises by stochastic fluctuations in cells and by physiological responses of cells to the environment. New approaches to drug design may be required to control nonheritable variability and the evolution of resistance to chemotherapy.     

Towards a molecular characterization of adaptation in local populations

Adaptation of local populations to their environment is central to our understanding of biodiversity and processes of speciation; nevertheless, the genetic changes that are required for such local adaptations are understood poorly. Recent studies have shown that multilocus scans that compare different populations for several loci can identify genomic regions carrying a mutation that results in a local adaptation.     

Influence of Gene Interaction on Complex Trait Variation with Multilocus Models

Although research effort is being expended into determining the importance of epistasis and epistatic variance for complex traits, there is considerable controversy about their importance. Here we undertake an analysis for quantitative traits utilizing a range of multilocus quantitative genetic models and gene frequency distributions, focusing on the potential magnitude of the epistatic variance. All the epistatic terms involving a particular locus appear in its average effect, with the number of two-locus interaction terms increasing in proportion to the square of the number of loci and that of third order as the cube and so on. Hence multilocus epistasis makes substantial contributions to the additive variance and does not, per se, lead to large increases in the nonadditive part of the genotypic variance. Even though this proportion can be high where epistasis is antagonistic to direct effects, it reduces with multiple loci. As the magnitude of the epistatic variance depends critically on the heterozygosity, for models where frequencies are widely dispersed, such as for selectively neutral mutations, contributions of epistatic variance are always small. Epistasis may be important in understanding the genetic architecture, for example, of function or human disease, but that does not imply that loci exhibiting it will contribute much genetic variance. Overall we conclude that theoretical predictions and experimental observations of low amounts of epistatic variance in outbred populations are concordant. It is not a likely source of missing heritability, for example, or major influence on predictions of rates of evolution.     

Estimation of genetic distance and coefficient of gene diversity from single-probe multilocus DNA fingerprinting data

DNA fingerprinting exhibits multilocus genotypes of individuals, detected by the use of a single multilocus probe. Consequently, population data on DNA fingerprinting do not provide a complete characterization of the genetic variation in terms of allele-frequency distributions, since neither the number of loci nor the locus affiliation of alleles is directly observable. Yet DNA fingerprinting has been proved to be a cost-effective method of detecting hypervariable polymorphisms in several organisms, where the traditional loci fail to detect enough variation for microevolutionary studies. In the present paper we demonstrate that the above-mentioned features of DNA fingerprinting data do not cause any serious problem when they are used in evolutionary studies. Bias-corrected estimators of Nei's standard and minimum genetic distances are derived, and, by an application of this theory to data on seven short tandem repeat loci in three major human populations, it is shown that these modified measures of genetic distances based on DNA fingerprint patterns are quite close to Nei's distances based on locus-specific allele frequencies. Empirical as well as theoretical support of the adequacy of such genetic distances from DNA fingerprinting data is also discussed, and it indicates that the technical limitations of DNA fingerprinting should not deter the use of the method for short-term evolutionary studies.      

Environmental, pharmacological and genetic influences on the spread of drug-resistant malaria

Plasmodium falciparum malaria is subject to artificial selection from antimalarial drugs that select for drug-resistant parasites. We describe and apply a flexible new approach to investigate how epistasis, inbreeding, selection heterogeneity and multiple simultaneous drug deployments interact to influence the spread of drug-resistant malaria. This framework recognizes that different human 'environments' within which treatment may occur (such as semi- and non-immune humans taking full or partial drug courses) influence the genetic interactions between parasite loci involved in resistance. Our model provides an explanation for how the rate of spread varies according to different malaria transmission intensities, why resistance might stabilize at intermediate frequencies and also identifies several factors that influence the decline of resistance after a drug is removed. Results suggest that studies based on clinical outcomes might overestimate the spread of resistant parasites, especially in high-transmission areas. We show that when transmission decreases, prevalence might decrease without a corresponding change in frequency of resistance and that this relationship is heavily influenced by the extent of linkage disequilibrium between loci. This has important consequences on the interpretation of data from areas where control is being successful and suggests that reducing transmission might have less impact on the spread of resistance than previously expected.     

Complex genetics control natural variation in Arabidopsis thaliana resistance to Botrytis cinerea

The genetic architecture of plant defense against microbial pathogens may be influenced by pathogen lifestyle. While plant interactions with biotrophic pathogens are frequently controlled by the action of large-effect resistance genes that follow classic Mendelian inheritance, our study suggests that plant defense against the necrotrophic pathogen Botrytis cinerea is primarily quantitative and genetically complex. Few studies of quantitative resistance to necrotrophic pathogens have used large plant mapping populations to dissect the genetic structure of resistance. Using a large structured mapping population of Arabidopsis thaliana, we identified quantitative trait loci influencing plant response to B. cinerea, measured as expansion of necrotic lesions on leaves and accumulation of the antimicrobial compound camalexin. Testing multiple B. cinerea isolates, we identified 23 separate QTL in this population, ranging in isolate-specificity from being identified with a single isolate to controlling resistance against all isolates tested. We identified a set of QTL controlling accumulation of camalexin in response to pathogen infection that largely colocalized with lesion QTL. The identified resistance QTL appear to function in epistatic networks involving three or more loci. Detection of multilocus connections suggests that natural variation in specific signaling or response networks may control A. thaliana-B. cinerea interaction in this population.     

The interpretation of selection coefficients

Evolutionary biologists have an array of powerful theoretical techniques that can accurately predict changes in the genetic composition of populations. Changes in gene frequencies and genetic associations between loci can be tracked as they respond to a wide variety of evolutionary forces. However, it is often less clear how to decompose these various forces into components that accurately reflect the underlying biology. Here, we present several issues that arise in the definition and interpretation of selection and selection coefficients, focusing on insights gained through the examination of selection coefficients in multilocus notation. Using this notation, we discuss how its flexibility—which allows different biological units to be identified as targets of selection—is reflected in the interpretation of the coefficients that the notation generates. In many situations, it can be difficult to agree on whether loci can be considered to be under “direct” versus “indirect” selection, or to quantify this selection. We present arguments for what the terms direct and indirect selection might best encompass, considering a range of issues, from viability and sexual selection to kin selection. We show how multilocus notation can discriminate between direct and indirect selection, and describe when it can do so.     

Host-parasite coevolution in a multilocus gene-for-gene system.

This paper examines a mathematical model for the coevolution of parasite virulence and host resistance under a multilocus gene-for-gene interaction. The degrees of parasite virulence and host resistance show coevolutionary cycles for sufficiently small costs of virulence and resistance. Besides these coevolutionary cycles of a longer period, multilocus genotype frequencies show complex fluctuations over shorter periods. All multilocus genotypes are maintained within host and parasite classes having the same number of resistant/virulent alleles and their frequencies fluctuate with approximately equally displaced phases. If either the cost of virulence or the number of resistance loci is larger then a threshold, the host maintains the static polymorphism of singly (or doubly or more, depending on the cost of resistance) resistant genotypes and the parasite remains universally avirulent. In other words, host polymorphism can prevent the invasion of any virulent strain in the parasite. Thus, although assuming an empirically common type of asymmetrical gene-for-gene interaction, both host and parasite populations can maintain polymorphism in each locus and retain complex fluctuations. Implications for the red queen hypothesis of the evolution of sex and the control of multiple drug resistance are discussed.     

Kin selection and the evolution of sexual conflict

Males and females do not always share the same evolutionary interests. This is particularly true in the case of multiple mating, where male–male competition can often lead to adaptations that are harmful to the female, and females can evolve counter adaptations to reduce the benefits males gain from such traits. Although social evolution has made substantial progress from kin selection theory, most studies of sexual conflict have ignored the effects of genetic relatedness. Here, I use a model of male harm and female resistance to investigate how kin selection affects the evolution of sexual conflict. Building on models of social evolution, I show that relatedness inhibits sexual conflict, in terms of male harm, whereas it has no effect on the evolution female resistance. This study examines a previously neglected mechanism that can potentially help to resolve sexual conflict over mating and highlights the potential importance of considering relatedness in empirical studies of sexual conflict.