Adaptation in a spider mite population after long-term evolution on a single host plant

Evolution in a single environment is expected to erode genetic variability, thereby precluding adaptation to novel environments. To test this, a large population of spider mites kept on cucumber for approximately 300 generations was used to establish populations on novel host plants (tomato or pepper), and changes in traits associated to adaptation were measured after 15 generations. Using a half-sib design, we investigated whether trait changes were related to genetic variation in the base population. Juvenile survival and fecundity exhibited genetic variation and increased in experimental populations on novel hosts. Conversely, no variation was detected for host choice and developmental time and these traits did not evolve. Longevity remained unchanged on novel hosts despite the presence of genetic variation, suggesting weak selection for this trait. Hence, patterns of evolutionary changes generally matched those of genetic variation, and changes in some traits were not hindered by long-term evolution in a constant environment.     

EXPERIMENTAL EVIDENCE FOR THE EVOLUTION OF INDIRECT GENETIC EFFECTS: CHANGES IN THE INTERACTION EFFECT COEFFICIENT,PSI (Ψ), DUE TO SEXUAL SELECTION

Indirect genetics effects (IGEs)—when the genotype of one individual affects the phenotypic expression of a trait in another—may alter evolutionary trajectories beyond that predicted by standard quantitative genetic theory as a consequence of genotypic evolution of the social environment. For IGEs to occur, the trait of interest must respond to one or more indicator traits in interacting conspecifics. In quantitative genetic models of IGEs, these responses (reaction norms) are termed interaction effect coefficients and are represented by the parameter psi (Ψ). The extent to which Ψ exhibits genetic variation within a population, and may therefore itself evolve, is unknown. Using an experimental evolution approach, we provide evidence for a genetic basis to the phenotypic response caused by IGEs on sexual display traits in Drosophila serrata. We show that evolution of the response is affected by sexual but not natural selection when flies adapt to a novel environment. Our results indicate a further mechanism by which IGEs can alter evolutionary trajectories—the evolution of interaction effects themselves.     

Experimental evolution of evolutionary potential in fluctuating environments

Variation is the raw material for evolution. Evolutionary potential is determined by the amount of genetic variation, but evolution can also alter the visibility of genetic variation to natural selection. Fluctuating environments are suggested to maintain genetic variation but they can also affect environmental variance, and thus, the visibility of genetic variation to natural selection. However, experimental studies testing these ideas are relatively scarce. In order to determine differences in evolutionary potential we quantified variance attributable to population, genotype and environment for populations of the bacterium Serratia marcescens. These populations had been experimentally evolved in constant and two fluctuating environments. We found that strains that evolved in fluctuating environments exhibited larger environmental variation suggesting that adaptation to fluctuations has decreased the visibility of genetic variation to selection.     

Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

The objectives of the present study were: (1) to evaluate the importance of genotype×production environment interaction for the genetic evaluation of birth weight (BW) and weaning weight (WW) in a population of composite beef cattle in Brazil, and (2) to investigate the importance of sire×contemporary group interaction (S×CG) to model G×E and improve the accuracy of prediction in routine genetic evaluations of this population. Analyses were performed with one, two (favorable and unfavorable) or three (favorable, intermediate, unfavorable) different definitions of production environments. Thus, BW and WW records of animals in a favorable environment were assigned to either trait 1, in an intermediate environment to trait 2 or in an unfavorable environment to trait 3. The (co)variance components were estimated using Gibbs sampling in single-, bi- or three-trait animal models according to the definition of number of production environments. In general, the estimates of genetic parameters for BW and WW were similar between environments. The additive genetic correlations between production environments were close to unity for BW; however, when examining the highest posterior density intervals, the correlation between favorable and unfavorable environments reached a value of only 0.70, a fact that may lead to changes in the ranking of sires across environments. The posterior mean genetic correlation between direct effects was 0.63 in favorable and unfavorable environments for WW. When S×CG was included in two- or three-trait analyses, all direct genetic correlations were close to unity, suggesting that there was no evidence of a genotype×production environment interaction. Furthermore, the model including S×CG contributed to prevent overestimation of the accuracy of breeding values of sires, provided a lower error of prediction for both direct and maternal breeding values, lower squared bias, residual variance and deviance information criterion than the model omitting S×CG. Thus, the model that included S×CG can therefore be considered the best model on the basis of these criteria. The genotype×production environment interaction should not be neglected in the genetic evaluation of BW and WW in the present population of beef cattle. The inclusion of S×CG in the model is a feasible and plausible alternative to model the effects of G×E in the genetic evaluations.     

Plasticity and evolution in correlated suites of traits

When organisms are faced with new or changing environments, a central challenge is the coordination of adaptive shifts in many different phenotypic traits. Relationships among traits may facilitate or constrain evolutionary responses to selection, depending on whether the direction of selection is aligned or opposed to the pattern of trait correlations. Attempts to predict evolutionary potential in correlated traits generally assume that correlations are stable across time and space; however, increasing evidence suggests that this may not be the case, and flexibility in trait correlations could bias evolutionary trajectories. We examined genetic and environmental influences on variation and covariation in a suite of behavioural traits to understand if and how flexibility in trait correlations influences adaptation to novel environments. We tested the role of genetic and environmental influences on behavioural trait correlations by comparing Trinidadian guppies (Poecilia reticulata) historically adapted to high‐ and low‐predation environments that were reared under native and non‐native environmental conditions. Both high‐ and low‐predation fish exhibited increased behavioural variance when reared under non‐native vs. native environmental conditions, and rearing in the non‐native environment shifted the major axis of variation among behaviours. Our findings emphasize that trait correlations observed in one population or environment may not predict correlations in another and that environmentally induced plasticity in correlations may bias evolutionary divergence in novel environments.     

A history of phenotypic plasticity accelerates adaptation to a new environment

Can a history of phenotypic plasticity increase the rate of adaptation to a new environment? Theory suggests it can be through two different mechanisms. Phenotypically plastic organisms can adapt rapidly to new environments through genetic assimilation, or the fluctuating environments that result in phenotypic plasticity can produce evolvable genetic architectures. In this article, I studied a model of a gene regulatory network that determined a phenotypic character in one population selected for phenotypic plasticity and a second population in a constant environment. A history of phenotypic plasticity increased the rate of adaptation in a new environment, but the amount of this increase was dependent on the strength of selection in the original environment. Phenotypic variance in the original environment predicted the adaptive capacity of the trait within, but not between, plastic and nonplastic populations. These results have implications for invasive species and ecological studies of rapid adaptation.     

The genetics of phenotypic plasticity. VI. Theoretical predictions for directional selection

We explore the effects of linear and quadratic reaction norms on heritability and directional selection. Genetic variation for reaction norm parameters can alter the heritability of traits; the magnitude of the heritability depends upon both the environment and the correlation among the parameters. Genetic variation for reaction norm parameters can alter the response to directional selection. Selection on a trait in one environment can shift both the mean of the trait measured across environments and the plasticity of the trait; the signs and magnitudes of these responses depend on the correlations among the parameters of the reaction norm. Our model is consistent with the results of ten experiments for selection on a trait in a single environment. In all experiments, selection towards the overall mean of the population always resulted in a relatively lower plasticity than selection away from the overall mean. Our model was able to predict the results of two experiments for selection on a trait index calculated over more than one environment. Predictions were good for the direct response to selection but poorer for the correlated response to selection. Our results indicate the need for more data on the effects of environment on genetic parameters, especially correlations among reaction norm parameters.     

Pollution Breaks Down the Genetic Architecture of Life History Traits in Caenorhabditis elegans

When pollution occurs in an environment, populations present suffer numerous negative and immediate effects on their life history traits. Their evolutionary potential to live in a highly stressful environment will depend on the selection pressure strengths and on the genetic structure, the trait heritability, and the genetic correlations between them. If expression of this structure changes in a stressful environment, it becomes necessary to quantify these changes to estimate the evolutionary potential of the population in this new environment. We studied the genetic structure for survival, fecundity, and early and late growth in isogenic lines of a Caenorhabditis elegans population subject to three different environments: a control environment, an environment polluted with uranium, and a high salt concentration environment. We found a heritability decrease in the polluted environments for fecundity and early growth, two traits that were the most heritable in the control environment. The genetic structure of the traits was particularly affected in the uranium polluted environment, probably due to generally low heritability in this environment. This could prevent selection from acting on traits despite the strong selection pressures exerted on them. Moreover, phenotypic traits were more strongly affected in the salt than in the uranium environment and the heritabilities were also lower in the latter environment. Consequently the decrease in heritability was not proportional to the population fitness reduction in the polluted environments. Our results suggest that pollution can alter the genetic structure of a C. elegans population, and thus modify its evolutionary potential.     

Experimental evolution reveals habitat‐specific fitness dynamics among Wolbachia clades in Drosophila melanogaster

The diversity and infection dynamics of the endosymbiont Wolbachia can be influenced by many factors, such as transmission rate, cytoplasmic incompatibility, environment, selection and genetic drift. The interplay of these factors in natural populations can result in heterogeneous infection patterns with substantial differences between populations and strains. The causes of these heterogeneities are not yet understood, partly due to the complexity of natural environments. We present experimental evolution as a new approach to study Wolbachia infection dynamics in replicate populations exposed to a controlled environment. A natural Drosophila melanogaster population infected with strains of Wolbachia belonging to different clades evolved in two laboratory environments (hot and cold) for 1.5 years. In both treatments, the rate of Wolbachia infection increased until fixation. In the hot environment, the relative frequency of different Wolbachia clades remained stable over 37 generations. In the cold environment, however, we observed marked changes in the composition of the Wolbachia population: within 15 generations, one Wolbachia clade increased more than 50% in frequency, whereas the other two clades decreased in frequency, resulting in the loss of one clade. The frequency change was highly reproducible not only among replicates, but also when flies that evolved for 42 generations in the hot environment were transferred to the cold environment. These results document how environmental factors can affect the composition of Wolbachia in D. melanogaster. The high reproducibility of the pattern suggests that experimental evolution studies can efficiently determine the functional basis of habitat‐specific fitness among Wolbachia strains.     

Fine‐scale temporal adaptation within a salmonid population: mechanism and consequences

We demonstrate a clear example of local adaptation of seasonal timing of spawning and embryo development. The consequence is a population of pink salmon that is segmented into spawning groups that use the same limited habitat. We synthesize published observations with results of new analyses to demonstrate that genetic variation of these traits results in survival differentials related to that variation, and that density‐dependent embryo mortality and seasonally variable juvenile mortality are a mechanism of selection. Most examples of local adaptation in natural systems depend on observed correlations between environments and fitness traits, but do not fully demonstrate local adaptation: that the trait is genetically determined, exhibits different fitness in common environments or across different environments, and its variation is mechanistically connected to fitness differences. The geographic or temporal scales of local adaptation often remain obscure. Here, we show that heritable, fine‐scale differences of timing of reproductive migration in a pink salmon (Oncorhynchus gorbuscha) resulted in temporal structure that persisted several generations; the differences enable a density‐dependent population to pack more spawners into limited spawning habitat, that is, enhance its fitness. A balanced trade‐off of survivals results because embryos from early‐migrating fish have a lower freshwater survival (harsh early physical conditions and disturbance by late spawners), but emigrant fry from late‐migrating fish have lower marine survivals (timing of their vernal emergence into the estuarine environment). Such fine‐scale local adaptations increase the genetic portfolio of the populations and may provide a buffer against the impacts of climate change.     

QTL mapping and the genetic basis of adaptation: recent developments

Quantitative trait loci (QTL) mapping has been used in a number of evolutionary studies to study the genetic basis of adaptation by mapping individual QTL that explain the differences between differentiated populations and also estimating their effects and interaction in the mapping population. This analysis can provide clues about the evolutionary history of populations and causes of the population differentiation. QTL mapping analysis methods and associated computer programs provide us tools for such an inference on the genetic basis and architecture of quantitative trait variation in a mapping population. Current methods have the capability to separate and localize multiple QTL and estimate their effects and interaction on a quantitative trait. More recent methods have been targeted to provide a comprehensive inference on the overall genetic architecture of multiple traits in a number of environments. This development is important for evolutionary studies on the genetic basis of multiple trait variation, genotype by environment interaction, host–parasite interaction, and also microarray gene expression QTL analysis.     

A unified statistical model for functional mapping of environment-dependent genetic expression and genotype x environment interactions for ontogenetic development

The effects of quantitative trait loci (QTL) on phenotypic development may depend on the environment (QTL x environment interaction), other QTL (genetic epistasis), or both. In this article, we present a new statistical model for characterizing specific QTL that display environment-dependent genetic expressions and genotype x environment interactions for developmental trajectories. Our model was derived within the maximum-likelihood-based mixture model framework, incorporated by biologically meaningful growth equations and environment-dependent genetic effects of QTL, and implemented with the EM algorithm. With this model, we can characterize the dynamic patterns of genetic effects of QTL governing growth curves and estimate the global effect of the underlying QTL during the course of growth and development. In a real example with rice, our model has successfully detected several QTL that produce differences in their genetic expression between two contrasting environments. These detected QTL cause significant genotype x environment interactions for some fundamental aspects of growth trajectories. The model provides the basis for deciphering the genetic architecture of trait expression adjusted to different biotic and abiotic environments and genetic relationships for growth rates and the timing of life-history events for any organism.     

Fitness consequences of avian personalities in a fluctuating environment

Individual animals differ in the way they cope with challenges in their environment, comparable with variation in human personalities. The proximate basis of variation in personality traits has received considerable attention, and one general finding is that personality traits have a substantial genetic basis. This poses the question of how variation in personality is maintained in natural populations. We show that selection on a personality trait with high heritability fluctuates across years within a natural bird population. Annual adult survival was related to this personality trait (behaviour in novel environments) but the effects were always opposite for males and females, and reversed between years. The number of offspring surviving to breeding was also related to their parents' personalities, and again selection changed between years. The observed annual changes in selection pressures coincided with changes in environmental conditions (masting of beeches) that affect the competitive regimes of the birds. We expect that the observed fluctuations in environmental factors lead to fluctuations in competition for space and food, and these, in association with variations in population density, lead to a variation in selection pressure, which maintains genetic variation in personalities.     

Genotype by environment interaction for adult body weights of shrimp Penaeus vannamei when grown at low and high densitie

Shrimp is one of few marine species cultured worldwide for which several selective breeding programs are being conducted. One environmental factor that can affect the response to selection in breeding programs is the density at which the shrimp are cultured (low-medium-high). Phenotypic plasticity in the growth response to different densities might be accompanied by a significant genotype by environment interaction, evidenced by a change in heritabilities between environments and by a genetic correlation less than one for a unique trait between environments. Our goal was to understand whether different growth densities affect estimates of those genetic parameters for adult body weight (BW) in the Pacific white shrimp (Penaeus vannamei). BW heritabilities were significantly different between environments, with the largest at high density. These differences resulted from both an increased additive genetic variance and a decreased environmental variance when grown at high density. The genetic correlation between BWs at the two environmental conditions was significantly less than one. Whereas these results might be suggestive for carrying out shrimp selective breeding for BW under high density conditions, further understanding of genetic correlations between growth and reproductive traits within a given environment is necessary, as there are indications of reduced reproductive fitness for shrimp grown at high densities.     

Detection of grain protein content QTLs across environments in tetraploid wheats

Grain protein content (GPC) is an important quality factor in both durum and bread wheats. GPC is considered to be a polygenic trait influenced by environmental factors and management practice. The objectives of this study were both to compare the quantitative trait loci (QTL) for GPC in a population of 65 recombinant inbred lines of tetraploid wheats evaluated in three locations for several years (eight data sets), and to investigate the genetic relationship among GPC and grain yield. QTLs were determined based on the Messapia × dicoccoides linkage map which covers 217 linked loci on the 14 chromosomes with 42 additional loci as yet unassigned to linkage groups. The map extends to 1352 cM; the average distance between adjacent markers was 6.3 cM. Seven QTLs for GPC, located on the chromosome arms 4BS, 5AL, 6AS (two loci), 6BS, 7AS and 7BS, were detected that were significant in at least one environment at P<0.001 or in at least two environments at P<0.01. One QTL was significant in all but one environment, two were significant in four or five environments, and four were significant in two out of eight environments. Six out of seven protein content QTLs had pleiotropic effects or were associated to QTLs for grain yield and explained the negative correlation among GPC and yield components. The present results support the concept that studies conducted in a single environment are likely to underestimate the number of QTLs that can influence a trait and that the phenotypic data for a quantitative trait should be collected over a range of locations to identify putative QTLs and determine their phenotypic effects.     

Species range expansion by beneficial mutations

A species' range can be limited when there is no genetic variation for a trait that allows for adaptation to more extreme environments. We study how range expansion occurs by the establishment of a new mutation that affects a quantitative trait in a spatially continuous population. The optimal phenotype for the trait varies linearly in space. The survival probabilities of new mutations affecting the trait are found by simulation. Shallow environmental gradients favour mutations that arise nearer to the range margin and that have smaller phenotypic effects than do steep gradients. Mutations that become established in shallow environmental gradients typically result in proportionally larger range expansions than those that establish in steep gradients. Mutations that become established in populations with high maximum growth rates tend to originate nearer to the range edge and to cause relatively smaller range expansion than mutations that establish in populations with low maximum growth rates. Under plausible parameter values, mutations that allow for range expansion tend to have large phenotypic effects (more than one phenotypic standard deviation) and cause substantial range expansions (15% or more). Sexual reproduction allows for larger range expansions and adaptation to more extreme environments than asexual reproduction.     

Trait Associations across Evolutionary Time within a Drosophila Phylogeny: Correlated Selection or Genetic Constraint?

Traits do not evolve independently. To understand how trait changes under selection might constrain adaptive changes, phenotypic and genetic correlations are typically considered within species, but these capture constraints across a few generations rather than evolutionary time. For longer-term constraints, comparisons are needed across species but associations may arise because of correlated selection pressures rather than genetic interactions. Implementing a unique approach, we use known patterns of selection to separate likely trait correlations arising due to correlated selection from those reflecting genetic constraints. We examined the evolution of stress resistance in >90 Drosophila species adapted to a range of environments, while controlling for phylogeny. Initially we examined the role of climate and phylogeny in shaping the evolution of starvation and body size, two traits previously not examined in this context. Following correction for phylogeny only a weak relationship between climate and starvation resistance was detected, while all of the variation in the relationship between body size and climate could be attributed to phylogeny. Species were divided into three environmental groups (hot and dry, hot and wet, cold) with the expectation that, if genetic correlations underpin trait correlations, these would persist irrespective of the environment, whereas selection-driven evolution should produce correlations dependent on the environment. We found positive associations between most traits in hot and dry environments coupled with high trait means. In contrast few trait correlations were observed in hot/wet and cold environments. These results suggest trait associations are primarily driven by correlated selection rather than genetic interactions, highlighting that such interactions are unlikely to limit evolution of stress resistance.     

Genetic architecture of plastic methyl jasmonate responses in Arabidopsis thaliana

The ability of a single genotype to generate different phenotypes in disparate environments is termed phenotypic plasticity, which reflects the interaction of genotype and environment on developmental processes. However, there is controversy over the definition of plasticity genes. The gene regulation model states that plasticity loci influence trait changes between environments without altering the means within a given environment. Alternatively, the allelic sensitivity model argues that plasticity evolves due to selection of phenotypic values expressed within particular environments; hence plasticity must be controlled by loci expressed within these environments. To identify genetic loci controlling phenotypic plasticity and address this controversy, we analyzed the plasticity of glucosinolate accumulation under methyl jasmonate (MeJa) treatment in Arabidopsis thaliana. We found genetic variation influencing multiple MeJa signal transduction pathways. Analysis of MeJa responses in the Landsberg erecta x Columbia recombinant inbred lines identified a number of quantitative trait loci (QTL) that regulate plastic MeJa responses. All significant plasticity QTL also impacted the mean trait value in at least one of the two "control" or "MeJa" environments, supporting the allelic sensitivity model. Additionally, we present an analysis of MeJa and salicylic acid cross-talk in glucosinolate regulation and describe the implications for glucosinolate physiology and functional understanding of Arabidopsis MeJa signal transduction.     

Do mites evolving in alternating host plants adapt to host switch?

A fluctuating environment may be perceived as a composition of different environments, or as an environment per se, in which it is the fluctuation itself that poses a selection pressure. If so, then organisms may adapt to this alternation. We tested this using experimental populations of spider mites that have been evolving for 45 generations in a homogeneous environment (pepper or tomato plants), or in a heterogeneous environment composed of an alternation of these two plants approximately at each generation. The performance (daily oviposition rate and juvenile survival) of individuals from these populations was tested in each of the homogeneous environments, and in two alternating environments, one every 3 days and the other between generations. To discriminate between potential genetic interactions between alleles conferring adaptation to each host plant and environmental effects of evolving in a fluctuating environment, we compared the performance of all lines with that of a cross between tomato and pepper lines. As a control, two lines within each selection regime were also crossed. We found that crosses between alternating lines and between pepper and tomato lines performed worse than crosses between lines evolving in homogeneous environments when tested in that environment. In contrast, alternating lines performed either better or similarly to lines evolving in homogeneous environments when tested in a fluctuating environment. Our results suggest that fluctuating environments are more than the juxtaposition of two environments. Hence, tests for adaptation of organisms evolving in such environments should be carried out in fluctuating conditions.