Artificial Selection Experiments Research Articles

Selection for stress tolerance and longevity in Drosophila melanogaster have strong impacts on microbiome profiles

There is experimental evidence that microbiomes have a strong influence on a range of host traits. Understanding the basis and importance of symbiosis between host and associated microorganisms is a rapidly developing research field, and we still lack a mechanistic understanding of ecological and genetic pressures affecting host-microbiome associations. Here Drosophila melanogaster lines from a large-scale artificial selection experiment were used to investigate whether the microbiota differ in lines selected for different stress resistance traits and longevity. Following multiple generations of artificial selection all selection regimes and corresponding controls had their microbiomes assessed. The microbiome was interrogated based on 16S rRNA sequencing. We found that the microbiome of flies from the different selection regimes differed markedly from that of the unselected control regime, and microbial diversity was consistently higher in selected relative to control regimes. Several common Drosophila bacterial species showed differentially abundance in the different selection regimes despite flies being exposed to similar environmental conditions for two generations prior to assessment. Our findings provide strong evidence for symbiosis between host and microbiomes but we cannot reveal whether the interactions are adaptive, nor whether they are caused by genetic or ecological factors.

Sexually discordant selection is associated with trait-specific morphological changes and a complex genomic response.

Sexes often have differing fitness optima, potentially generating intra-locus sexual conflict, as each sex bears a genetic "load" of alleles beneficial to the other sex. One strategy to evaluate conflict in the genome is to artificially select populations discordantly against established sexual dimorphism (SD), reintroducing attenuated conflict. We investigate a long-term artificial selection experiment reversing sexual size dimorphism in Drosophila melanogaster during ~350 generations of sexually discordant selection. We explore morphological and genomic changes to identify loci under selection between the sexes in discordantly and concordantly size-selected treatments. Despite substantial changes to overall size, concordant selection maintained ancestral SD. However, discordant selection altered size dimorphism in a trait-specific manner. We observe multiple possible soft selective sweeps in the genome, with size-related genes showing signs of selection. Patterns of genomic differentiation between the sexes within lineages identified potential sites maintained by sexual conflict. One discordant selected lineage shows a pattern of elevated genomic differentiation between males and females on chromosome 3L, consistent with the maintenance of sexual conflict. Our results suggest visible signs of conflict and differentially segregating alleles between the sexes due to discordant selection.

Selective breeding for high levels of voluntary exercise in mice does not reduce lifetime reproductive success or lifespan

The ways locomotor abilities may interact with life history traits are complicated and may involve shifts in resource allocation. For example, individuals that have large litters may have reduced energy available to support the organ systems required for high locomotor performance abilities. Alternatively, energy spent on excess physical activity might subtract from that available for somatic maintenance, and thus be negatively related to lifespan or to other fitness components that contribute to lifetime reproductive success (LRS). We studied lifetime reproductive successes, life span, and health span in mice from a long-term (>100 generations) artificial selection experiment that includes 4 replicate High Runner (HR) lines bred for voluntary locomotor activity on wheels and 4 lines that serve as non-selected Controls (C). Since reaching selection limits at around generation 17-27 (depending on line and sex), the HR mice have been running ~3-fold farther on a daily basis as compared with C mice, for both sexes, which leads to substantially increased energy expenditure and food consumption. Importantly, when housed without wheels, HR mice are not only more active, but also consume more food than C mice. In the present study, we tested for differences in LRS between the HR and C lines. We are also comparing lifespan (median, maximum) and healthspan (e.g., by measurement of maximal oxygen consumption [VO2max] during forced exercise and maximal sprint speed. Twelve male-female pairs per line from generation 97 (born Oct. 2021) are being maintained until their end of life. In addition to total number of pups weaned per pair, we record components of LRS, such as age at first and last litter for the pairs, number of litters, and inter-birth intervals. Here, we present a subset of results through the first 2+ years of the experiment. Only two of 100 pairs never gave birth to any litters, and 89 of 100 pairs weaned at least one litter. The total number of litters born to pairs ranged from 0 to 12, and the number of litters from which at least one pup was weaned ranged from 0 to 11, with a mean of 3.96+0.73 (SE) for C lines and 3.43+0.65 for HR lines (P=0.61). The total number of pups weaned (our measure of LRS) ranged from 0 to 80, with a mean of 29.1+8.1 (SE) for C lines and 25.8+4.4 for HR lines (P=0.73). Thus, we found no evidence that Darwinian fitness has been reduced by artificial selection for high voluntary exercise. As of 1 Nov. 2023, approximately 17% of the breeders are still alive, and preliminary analyses do not indicate significant differences between the C and HR lines in median or maximum lifespan. Supported by U.S. National Science Foundation grant IOS-2038528. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

A Meta Analysis of Whole-Body and Heart Mass Effect Sizes From a Long-Term Artificial Selection Experiment for High Voluntary Exercise

Effect sizes are a quantitative measure of the magnitude and direction of a phenomenon. These estimates can be compiled across multiple studies to summarize the weight of evidence for a particular alternative hypothesis, which is generally termed a meta-analysis. A meta-analytic approach allows one to summarize information from a wide array of similar studies and reach conclusions that may not be apparent on a case-by-case basis (e.g., to determine the overall effectiveness of a drug). Meta-analyses may be particularly useful in selection experiments, where the magnitude of a correlated response is necessarily expected to increase across generations, perhaps eventually reaching a plateau. Here, we examined the effect of artificial selection for high voluntary wheel running on heart mass in mice, which was expected to increase with selection for aerobic exercise behavior. The experiment spans nearly 30 years and 100 generations. All 4 of the replicate High Runner (HR) lines reached selection limits around generations 17-27, running approximately 2.5-3-fold more revolutions per day than the 4 non-selected Control (C) lines. These selection limits cannot be explained simply by a complete loss of heritability. Functional studies have tried to elucidate subordinate traits that affect motivational and/or ability for endurance exercise and have shown that HR mice differ from C in several other behavioral, physiological, and morphological traits. Several studies of heart ventricle mass have reported larger values in HR mice (with body mass as a covariate), but the differences often do not reach statistical significance (p<0.05). We compiled Least-Square Means, standard errors, F-statistics, degrees of freedom, and p-values from multiple studies. We also recorded pertinent information, such as: covariates used, age, generation, and whether other main effects were present (e.g., sex, wheel access). We calculated a common measure of effect size (Pearson’s R) and associated confidence intervals. This work is part of a larger meta-analysis to quantify effects of selection on various traits across multiple levels of biological organization. Preliminary results indicate that, despite a lack of statistical significance in many generations, HR mice have evolved larger hearts and smaller bodies relative to Controls. Moreover, a plateau in effect sizes for both of these traits coincide with the generational range during which the selection limit for wheel-running behavior was reached. NSF IOS-2038528. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Transcriptional signature of host shift in the seed beetle Zabrotes subfasciatus.

In phytophagous insects, adaptation to a new host is a dynamic process, in which early and later steps may be underpinned by different features of the insect genome. Here, we tested the hypothesis that early steps of this process are underpinned by a shift in gene expression patterns. We set up a short-term artificial selection experiment (10 generations) for the use of an alternative host (Cicer arietinum) on populations of the bean beetle Zabrotes subfasciatus. Using Illumina sequencing on young adult females, we show the selected populations differ in the expression of genes associated to stimuli, signalling, and developmental processes. Particularly, the "C. arietinum" population shows upregulation of histone methylation genes, which may constitute a strategy for fine-tuning the insect global gene expression network. Using qPCR on body regions, we demonstrated that the "Phaseolus vulgaris" population upregulates the genes polygalacturonase and egalitarian and that the expression of an odorant receptor transcript variant changes over generations. Moreover, in this population we detected the existence of vitellogenin (Vg) variants in both males and females, possibly harbouring canonical reproductive function in females and extracellular unknown functions in males. This study provides the basis for future genomic investigations seeking to shed light on the nature of the proximate mechanisms involved in promoting differential gene expression associated to insect development and adaptation to new hosts.

Multi-Generation Ecosystem Selection of Rhizosphere Microbial Communities Associated with Plant Genotype and Biomass in Arabidopsis thaliana.

The role of the microbiome in shaping the host's phenotype has emerged as a critical area of investigation, with implications in ecology, evolution, and host health. The complex and dynamic interactions involving plants and their diverse rhizospheres' microbial communities are influenced by a multitude of factors, including but not limited to soil type, environment, and plant genotype. Understanding the impact of these factors on microbial community assembly is key to yielding host-specific and robust benefits for plants, yet it remains challenging. Here, we conducted an artificial ecosystem selection experiment for eight generations of Arabidopsis thaliana Ler and Cvi to select soil microbiomes associated with a higher or lower biomass of the host. This resulted in divergent microbial communities shaped by a complex interplay between random environmental variations, plant genotypes, and biomass selection pressures. In the initial phases of the experiment, the genotype and the biomass selection treatment had modest but significant impacts. Over time, the plant genotype and biomass treatments gained more influence, explaining ~40% of the variation in the microbial community's composition. Furthermore, a genotype-specific association of plant-growth-promoting rhizobacterial taxa, Labraceae with Ler and Rhizobiaceae with Cvi, was observed under selection for high biomass.

Pervasive G × E interactions shape adaptive trajectories and the exploration of the phenotypic space in artificial selection experiments.

Quantitative genetics models have shown that long-term selection responses depend on initial variance and mutational influx. Understanding limits of selection requires quantifying the role of mutational variance. However, correlative responses to selection on nonfocal traits can perturb the selection response on the focal trait; and generations are often confounded with selection environments so that genotype by environment (G×E) interactions are ignored. The Saclay divergent selection experiments (DSEs) on maize flowering time were used to track the fate of individual mutations combining genotyping data and phenotyping data from yearly measurements (DSEYM) and common garden experiments (DSECG) with four objectives: (1) to quantify the relative contribution of standing and mutational variance to the selection response, (2) to estimate genotypic mutation effects, (3) to study the impact of G×E interactions in the selection response, and (4) to analyze how trait correlations modulate the exploration of the phenotypic space. We validated experimentally the expected enrichment of fixed beneficial mutations with an average effect of +0.278 and +0.299 days to flowering, depending on the genetic background. Fixation of unfavorable mutations reached up to 25% of incoming mutations, a genetic load possibly due to antagonistic pleiotropy, whereby mutations fixed in the selection environment (DSEYM) turned to be unfavorable in the evaluation environment (DSECG). Global patterns of trait correlations were conserved across genetic backgrounds but exhibited temporal patterns. Traits weakly or uncorrelated with flowering time triggered stochastic exploration of the phenotypic space, owing to microenvironment-specific fixation of standing variants and pleiotropic mutational input.

The effectiveness of artificial microbial community selection: a conceptual framework and a meta-analysis.

The potential for artificial selection at the community level to improve ecosystem functions has received much attention in applied microbiology. However, we do not yet understand what conditions in general allow for successful artificial community selection. Here we propose six hypotheses about factors that determine the effectiveness of artificial microbial community selection, based on previous studies in this field and those on multilevel selection. In particular, we emphasize selection strategies that increase the variance among communities. We then report a meta-analysis of published artificial microbial community selection experiments. The reported responses to community selection were highly variable among experiments; and the overall effect size was not significantly different from zero. The effectiveness of artificial community selection was greater when there was no migration among communities, and when the number of replicated communities subjected to selection was larger. The meta-analysis also suggests that the success of artificial community selection may be contingent on multiple necessary conditions. We argue that artificial community selection can be a promising approach, and suggest some strategies for improving the performance of artificial community selection programs.

Nonlinear expression patterns and multiple shifts in gene network interactions underlie robust phenotypic change in Drosophila melanogaster selected for night sleep duration.

All but the simplest phenotypes are believed to result from interactions between two or more genes forming complex networks of gene regulation. Sleep is a complex trait known to depend on the system of feedback loops of the circadian clock, and on many other genes; however, the main components regulating the phenotype and how they interact remain an unsolved puzzle. Genomic and transcriptomic data may well provide part of the answer, but a full account requires a suitable quantitative framework. Here we conducted an artificial selection experiment for sleep duration with RNA-seq data acquired each generation. The phenotypic results are robust across replicates and previous experiments, and the transcription data provides a high-resolution, time-course data set for the evolution of sleep-related gene expression. In addition to a Hierarchical Generalized Linear Model analysis of differential expression that accounts for experimental replicates we develop a flexible Gaussian Process model that estimates interactions between genes. 145 gene pairs are found to have interactions that are different from controls. Our method appears to be not only more specific than standard correlation metrics but also more sensitive, finding correlations not significant by other methods. Statistical predictions were compared to experimental data from public databases on gene interactions. Mutations of candidate genes implicated by our results affected night sleep, and gene expression profiles largely met predicted gene-gene interactions.

Selective breeding for high voluntary exercise in mice increases maximal (VO2max), but not basal metabolic rate.

In general, sustained high rates of physical activity require a high maximal aerobic capacity (VO2max), which may also necessitate a high basal aerobic metabolism (BMR), given that the two metabolic states are linked via shared organ systems, cellular properties, and metabolic pathways. We tested the hypotheses that (a) selective breeding for high voluntary exercise in mice would elevate both VO2max and BMR, and (b) these increases are accompanied by increases in the sizes of some internal organs (ventricle, triceps surae muscle, liver, kidney, spleen, lung, brain). We measured 72 females from generations 88 and 96 of an ongoing artificial selection experiment comprising 4 replicate High Runner (HR) lines bred for voluntary daily wheel-running distance and 4 non-selected Control (C) lines. With body mass as a covariate, HR lines as a group had significantly higher VO2max (+13.6%, P<0.0001), consistent with previous studies, but BMR did not significantly differ between HR and C lines (+6.5%, P=0.181). Additionally, HR mice did not statistically differ from C mice for whole-body lean or fat mass, or for the mass of any organ collected (with body mass as a covariate). Finally, mass-independent VO2max and BMR were uncorrelated (r=0.073, P=0.552) and the only statistically significant correlation with an organ mass was for VO2max and ventricle mass (r=0.285, P=0.015). Overall, our results indicate that selection for a behavioral trait can yield large changes in behavior without proportional modifications to underlying morphological or physiological traits.

Artificial selection for reversal learning reveals limited repeatability and no heritability of cognitive flexibility in great tits (Parus major).

Cognitive flexibility controls how animals respond to changing environmental conditions. Individuals within species vary considerably in cognitive flexibility but the micro-evolutionary potential in animal populations remains enigmatic. One prerequisite for cognitive flexibility to be able to evolve is consistent and heritable among-individual variation. Here we determine the repeatability and heritability of cognitive flexibility among great tits (Parus major) by performing an artificial selection experiment on reversal learning performance using a spatial learning paradigm over three generations. We found low, yet significant, repeatability (R = 0.15) of reversal learning performance. Our artificial selection experiment showed no evidence for narrow-sense heritability of associative or reversal learning, while we confirmed the heritability of exploratory behaviour. We observed a phenotypic, but no genetic, correlation between associative and reversal learning, showing the importance of prior information on reversal learning. We found no correlation between cognitive and personality traits. Our findings emphasize that cognitive flexibility is a multi-faceted trait that is affected by memory and prior experience, making it challenging to retrieve reliable values of temporal consistency and assess the contribution of additive genetic variation. Future studies need to identify what cognitive components underlie variation in reversal learning and study their between-individual and additive genetic components.

Hybridisation between host races broadens the host range of offspring in Eotetranychus asiaticus (Acari: Tetranychidae).

Host adaptation in herbivorous arthropods is one of the first steps to sympatric speciation, and spider mites (Acari: Tetranychidae) are useful model organisms for studying this phenomenon. Many researchers have studied the process of host adaptation via artificial selection experiments. Recent analyses suggest that hybridisation has diversified host ranges, although empirical evidence is scarce. We explored the host exploitation of two strains of Eotetranychus asiaticus established from Ternstroemia gymnanthera (Pentaphylacaceae) and Japanese cinnamon, Cinnamomum yabunikkei (Lauraceae), and evaluated the effect of hybridisation on offspring host use. Transplant experiments showed that females oviposited and immature mites developed only on their native hosts, suggesting specialisation to the secondary metabolites of each host plant. However, F1 hybrids from reciprocal crosses developed on both host plants (survival rate: 92-100%) with normal female-biased sex ratios. Furthermore, all backcrosses to the parental strains yielded B1 offspring that were also viable on both host plants with normal sex ratios (69-87% and39-92%femalesonT. gymnanthera andC. yabunikkei, respectively). B1 survival rates in interstrain crosses were varied (11-63%) and lower than those in intrastrain crosses (88-93%). We could not detect any reproductive barriers in these experiments, and host preference may be the sole factor determining pre-mating isolation. The survival rates and sex ratios we observed suggest cytochromosome interactions. In conclusion, hybridisation, which results in heterozygotes and recombination, is an underexplored way to provide spider mites with a novel host plant.

William George Hill. 7 August 1940—17 December 2021

William (Bill) Hill was an internationally acclaimed statistical, population and quantitative geneticist. His work was inspired by practical problems in animal breeding, but is widely applicable to evolutionary biology and human genetics. Bill's work focused on the joint effects of linkage, mutation and genetic architecture in finite populations. He showed that linked loci under selection can interfere with each other, reducing the rate of response to selection. He derived a widely used metric for linkage disequilibrium and showed that there is likely to be substantial linkage disequilibrium between closely linked variants in finite populations. He also showed that the sampling variance of linkage disequilibrium is very large, hampering its use in estimating effective population size or recombination rates. Bill derived sampling variances for inbreeding and realized relatedness between individuals with the same expected degree of relatedness. He raised awareness about the importance of new mutations for quantitative genetic variation and the response to artificial selection, and developed models for the maintenance of quantitative genetic variation by a balance between mutation and stabilizing selection. His experimental designs for estimating heritability and conducting artificial selection experiments have been widely adopted, and were utilized in his own long-term mouse selection experiments. Bill influenced animal breeding directly through consultancies with breeding companies, and his influence on quantitative genetics continues today via his numerous mentees.

Developing Lines of Queensland Fruit Flies with Different Levels of Response to a Kairomone Lure.

Simple SummaryQueensland fruit fly (Q-fly) is widely recognized as one of the world’s worst economic pests of fruit. In this project, a series of artificial selection experiments were conducted to develop lines of Q-fly with different levels of response to the male-specific lure Cue-lure® (CL) and to assess the heritability of this particular trait. Although lines of high and low responsive males to Cl were successfully developed through five cycles of artificial selection, the response to CL did not completely disappear. I have demonstrated that relaxing artificial selection results in the loss of 35–46% of the selection response after a further two generations.The Queensland fruit fly (Q-fly), Bactrocera tryoni (Froggatt) is a serious horticultural pest in Australia because it is highly invasive and destructive. Among all pest management practices, sterile insect techniques (SIT) and male annihilation techniques (MAT) are important control options for many tephritid fruit fly pests, including Q-fly. However, simultaneous applications of MAT and SIT require the wild males to be responsive to a lure while the released sterile males remain largely unresponsive. In this study, a series of artificial selection experiments was conducted to develop lines of Q-fly with different levels of response to the male-specific lure Cue-lure® (CL). After only five cycles of artificial selections, lines of high responsiveness (HR) and low responsiveness (LR) males diverging significantly in their response to the lure were developed. In the field cage experiment, the number of trapped males in fruit fly traps was significantly lower in the LR line than both the HR line and the control which supports the laboratory results. However, when artificial selection was stopped at F5 and retested after two generations, the number of unresponsive males dropped drastically compared to the rate of response of wild flies. Because the selection can be conducted only on males, it would be difficult to eliminate the dominant responsive alleles in the system without continuous selection.

A method to predict the response to directional selection using a Kalman filter

Predicting evolution remains challenging. The field of quantitative genetics provides predictions for the response to directional selection through the breeder's equation, but these predictions can have errors. The sources of these errors include omission of traits under selection, inaccurate estimates of genetic variance, and nonlinearities in the relationship between genetic and phenotypic variation. Previous research showed that the expected value of these prediction errors is often not zero, so predictions are systematically biased. Here, we propose that this bias, rather than being a nuisance, can be used to improve the predictions. We use this to develop a method to predict evolution, which is built on three key innovations. First, the method predicts change as the breeder's equation plus a bias term. Second, the method combines information from the breeder's equation and from the record of past changes in the mean to predict change using a Kalman filter. Third, the parameters of the filter are fitted in each generation using a learning algorithm on the record of past changes. We compare the method to the breeder's equation in two artificial selection experiments, one using the wing of the fruit fly and another using simulations that include a complex mapping of genotypes to phenotypes. The proposed method outperforms the breeder's equation, particularly when traits under selection are omitted from the analysis, when data are noisy, and when additive genetic variance is estimated inaccurately or not estimated at all. The proposed method is easy to apply, requiring only the trait means over past generations.

Brain size, gut size and cognitive abilities: the energy trade-offs tested in artificial selection experiment.

The enlarged brains of homeotherms bring behavioural advantages, but also incur high energy expenditures. The ‘expensive brain’ (EB) hypothesis posits that the energetic costs of the enlarged brain and the resulting increased cognitive abilities (CA) were met by either increased energy turnover or reduced allocation to other expensive organs, such as the gut. We tested the EB hypothesis by analysing correlated responses to selection in an experimental evolution model system, which comprises line types of laboratory mice selected for high or low basal metabolic rate (BMR), maximum (VO2max) metabolic rates and random-bred (unselected) lines. The traits are implicated in the evolution of homeothermy, having been pre-requisites for the encephalization and exceptional CA of mammals, including humans. High-BMR mice had bigger guts, but not brains, than mice of other line types. Yet, they were superior in the cognitive tasks carried out in both reward and avoidance learning contexts and had higher neuronal plasticity (indexed as the long-term potentiation) than their counterparts. Our data indicate that the evolutionary increase of CA in mammals was initially associated with increased BMR and brain plasticity. It was also fuelled by an enlarged gut, which was not traded off for brain size.

Artificial size selection experiment reveals telomere length dynamics and fitness consequences in a wild passerine.

Telomere dynamics could underlie life-history trade-offs among growth, size and longevity, but our ability to quantify such processes in natural, unmanipulated populations is limited. We investigated how 4years of artificial selection for either larger or smaller tarsus length, a proxy for body size, affected early-life telomere length (TL) and several components of fitness in two insular populations of wild house sparrows over a study period of 11years. The artificial selection was expected to shift the populations away from their optimal body size and increase the phenotypic variance in body size. Artificial selection for larger individuals caused TL to decrease, but there was little evidence that TL increased when selecting for smaller individuals. There was a negative correlation between nestling TL and tarsus length under both selection regimes. Males had longer telomeres than females and there was a negative effect of harsh weather on TL. We then investigated whether changes in TL might underpin fitness effects due to the deviation from the optimal body size. Mortality analyses indicated disruptive selection on TL because both short and long early-life telomeres tended to be associated with the lowest mortality rates. In addition, there was a tendency for a negative association between TL and annual reproductive success, but only in the population where body size was increased experimentally. Our results suggest that natural selection for optimal body size in the wild may be associated with changes in TL during growth, which is known to be linked to longevity in some bird species.

Evolutionary dynamics in an SI epidemic model with phenotype-structured susceptible compartment.

We present an SI epidemic model whereby a continuous structuring variable captures variability in proliferative potential and resistance to infection among susceptible individuals. The occurrence of heritable, spontaneous changes in these phenotypic characteristics and the presence of a fitness trade-off between resistance to infection and proliferative potential are explicitly incorporated into the model. The model comprises an ordinary differential equation for the number of infected individuals that is coupled with a partial integrodifferential equation for the population density function of susceptible individuals through an integral term. The expression for the basic reproduction number [Formula: see text] is derived, the disease-free equilibrium and endemic equilibrium of the model are characterised and a threshold theorem involving [Formula: see text] is proved. Analytical results are integrated with the results of numerical simulations of a calibrated version of the model based on the results of artificial selection experiments in a host-parasite system. The results of our mathematical study disentangle the impact of different evolutionary parameters on the spread of infectious diseases and the consequent phenotypic adaption of susceptible individuals. In particular, these results provide a theoretical basis for the observation that infectious diseases exerting stronger selective pressures on susceptible individuals and being characterised by higher infection rates are more likely to spread. Moreover, our results indicate that heritable, spontaneous phenotypic changes in proliferative potential and resistance to infection can either promote or prevent the spread of infectious diseases depending on the strength of selection acting on susceptible individuals prior to infection. Finally, we demonstrate that, when an endemic equilibrium is established, higher levels of resistance to infection and lower degrees of phenotypic heterogeneity among susceptible individuals are to be expected in the presence of infections which are characterised by lower rates of death and exert stronger selective pressures.

How do invasion syndromes evolve? An experimental evolution approach using the ladybird Harmonia axyridis

Experiments comparing native to introduced populations or distinct introduced populations to each other show that phenotypic evolution is common and often involves a suit of interacting phenotypic traits. We define such sets of traits that evolve in concert and contribute to the success of invasive populations as an ‘invasion syndrome’. The invasive Harlequin ladybird Harmonia axyridis displays such an invasion syndrome with, for instance, females from invasive populations being larger and heavier than individuals from native populations, allocating more resources to reproduction, and spreading reproduction over a longer lifespan. Invasion syndromes could emerge due to selection acting jointly and directly on a multitude of traits, or due to selection on one or a few key traits that drive correlated indirect responses in other traits. Here, we investigated the degree to which the H. axyridis invasion syndrome would emerge in response to artificial selection on either female body mass or on age at first reproduction, two traits involved in their invasion syndrome. To further explore the interaction between environmental context and evolutionary change in molding the phenotypic response, we phenotyped the individuals from the selection experiments in two environments, one with abundant food resources and one with limited resources. The two artificial selection experiments show that the number of traits showing a correlated response depends upon the trait undergoing direct selection. Artificial selection on female body mass resulted in few correlated responses and hence poorly reproduced the invasion syndrome. In contrast, artificial selection on age at first reproduction resulted in more widespread phenotypic changes, which nevertheless corresponded only partly to the invasion syndrome. The artificial selection experiments also revealed a large impact of diet on the traits, with effects dependent on the trait considered and the selection regime. Overall, our results indicate that direct selection on multiple traits was likely necessary in the evolution of the H. axyridis invasion syndrome. Furthermore, they show the strength of using artificial selection to identify the traits that are correlated in different selective contexts, which represents a crucial first step in understanding the evolution of complex phenotypic patterns, including invasion syndromes.

Rapid mosaic brain evolution under artificial selection for relative telencephalon size in the guppy (Poecilia reticulata).

The mosaic brain evolution hypothesis, stating that brain regions can evolve relatively independently during cognitive evolution, is an important idea to understand how brains evolve with potential implications even for human brain evolution. Here, we provide the first experimental evidence for this hypothesis through an artificial selection experiment in the guppy (Poecilia reticulata). After four generations of selection on relative telencephalon volume (relative to brain size), we found substantial changes in telencephalon size but no changes in other regions. Further comparisons revealed that up-selected lines had larger telencephalon, while down-selected lines had smaller telencephalon than wild Trinidadian populations. Our results support that independent evolutionary changes in specific brain regions through mosaic brain evolution can be important facilitators of cognitive evolution.