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The contribution of non-additive genetic effects to the genetic architecture of fitness and to the evolutionary potential of populations has been a topic of theoretical and empirical interest for a long time. Yet, the empirical study of these effects in natural populations remains scarce, perhaps because measuring dominance and epistasis relies heavily on experimental line crosses. In this study, we explored the contribution of dominance and epistasis in natural alpine populations of Arabidopsis thaliana for 2 fitness traits, the dry biomass and the estimated number of siliques, measured in a greenhouse. We found that, on average, crosses between inbred lines of A. thaliana led to mid-parent heterosis for dry biomass but outbreeding depression for an estimated number of siliques. While heterosis for dry biomass was due to dominance, we found that outbreeding depression for an estimated number of siliques could be attributed to the breakdown of beneficial epistatic interactions. We simulated and discussed the implication of these results for the adaptive potential of the studied populations, as well as the use of line-cross analyses to detect non-additive genetic effects. [ABSTRACT FROM AUTHOR]

Physiological status can influence social behavior, which in turn can affect physiology and health. Previously, we reported that tumor growth in Drosophila virgin females depends on the social context, but did not investigate the underlying physiological mechanisms. Here, we sought to characterize the signal perceived between tumorous flies, ultimately discovering that the tumor suppressive effect varies depending on reproductive status. Firstly, we show that the tumor suppressive effect is neither dependent on remnant pheromone-like products nor on the microbiota. Transcriptome analysis of the heads of these tumorous flies reveals social-dependent gene-expression changes related to nervous-system activity, suggesting that a cognitive-like relay might mediate the tumor suppressive effect. The transcriptome also reveals changes in the expression of genes related to mating behavior. Surprisingly, we observed that this social-dependent tumor-suppressive effect is lost in fertilized females. After mating, Drosophila females change their behavior—favoring offspring survival—in response to peptides transferred via the male ejaculate, a phenomenon called “male manipulation”. Remarkably, the social-dependent tumor suppressive effect is restored in females mated by sex-peptide deficient males. Since male manipulation has likely been selected to favor male gene transmission, our findings indicate that this evolutionary trait impedes social-dependent tumor growth slowdown. [ABSTRACT FROM AUTHOR]

In many studies, related individuals are phenotyped in order to infer how their genotype contributes to their phenotype, through the estimation of parameters such as breeding values or locus effects. When it is not possible to phenotype all the individuals, it is important to properly sample the population to improve the precision of the statistical analysis. This article studies how to optimize such sampling designs for pedigrees and association studies. Two sampling methods are developed, stratified sampling and D optimality. It is found that it is important to take account of mutation when sampling pedigrees with many generations: as the size of mutation effects increases, optimized designs sample more individuals in late generations. Optimized designs for association studies tend to improve the joint estimation of breeding values and locus effects, all the more as sample size is low and the genetic architecture of the trait is simple. When the trait is determined by few loci, they are reminiscent of classical experimental designs for regression models and tend to select homozygous individuals. When the trait is determined by many loci, locus effects may be difficult to estimate, even if an optimized design is used. [ABSTRACT FROM AUTHOR]

Deciphering the genotype–phenotype map necessitates relating variation at the genetic level to variation at the phenotypic level. This endeavour is inherently limited by the availability of standing genetic variation, the rate of spontaneous mutation to novo genetic variants, and possible biases associated with induced mutagenesis. An interesting alternative is to instead rely on the environment as a source of variation. Many phenotypic traits change plastically in response to the environment, and these changes are generally underlain by changes in gene expression. Relating gene expression plasticity to the phenotypic plasticity of more integrated organismal traits thus provides useful information about which genes influence the development and expression of which traits, even in the absence of genetic variation. We here appraise the prospects and limits of such an environment-for-gene substitution for investigating the genotype–phenotype map. We review models of gene regulatory networks, and discuss the different ways in which they can incorporate the environment to mechanistically model phenotypic plasticity and its evolution. We suggest that substantial progress can be made in deciphering this genotype–environment–phenotype map, by connecting theory on gene regulatory network to empirical patterns of gene co-expression, and by more explicitly relating gene expression to the expression and development of phenotypes, both theoretically and empirically. [ABSTRACT FROM AUTHOR]

Anticipating the genetic and phenotypic changes induced by natural or artificial selection requires reliable estimates of trait evolvabilities (genetic variances and covariances). However, whether or not multivariate quantitative genetics models are able to predict precisely the evolution of traits of interest, especially fitness‐related, life history traits, remains an open empirical question. Here, we assessed to what extent the response to bivariate artificial selection on both body size and maturity in the medaka Oryzias latipes, a model fish species, fits the theoretical predictions. Three lines (Large, Small, and Control lines) were differentially selected for body length at 75 days of age, conditional on maturity. As maturity and body size were phenotypically correlated, this selection procedure generated a bi‐dimensional selection pattern on two life history traits. After removal of nonheritable trends and noise with a random effect ("animal") model, the observed selection response did not match the expected bidirectional response. For body size, Large and Control lines responded along selection gradients (larger body size and stasis, respectively), but, surprisingly, the Small did not evolve a smaller body length and remained identical to the Control line throughout the experiment. The magnitude of the empirical response was smaller than the theoretical prediction in both selected directions. For maturity, the response was opposite to the expectation (the Large line evolved late maturity compared to the Control line, while the Small line evolved early maturity, while the opposite pattern was predicted due to the strong positive genetic correlation between both traits). The mismatch between predicted and observed response was substantial and could not be explained by usual sources of uncertainties (including sampling effects, genetic drift, and error in G matrix estimates). [ABSTRACT FROM AUTHOR]

Anthropogenic perturbations such as harvesting often select against a large body size and are predicted to induce rapid evolution toward smaller body sizes and earlier maturation. However, body‐size evolvability and, hence, adaptability to anthropogenic perturbations remain seldom evaluated in wild populations. Here, we use a laboratory experiment over 6 generations to measure the ability of wild‐caught medaka fish (Oryzias latipes) to evolve in response to bidirectional size‐dependent selection mimicking opposite harvest regimes. Specifically, we imposed selection against a small body size (Large line), against a large body size (Small line) or random selection (Control line), and measured correlated responses across multiple phenotypic, life‐history, and endocrine traits. As expected, the Large line evolved faster somatic growth and delayed maturation, but also evolved smaller body sizes at hatch, with no change in average levels of pituitary gene expressions of luteinizing, follicle‐stimulating, or growth hormones (GH). In contrast, the Small medaka line was unable to evolve smaller body sizes or earlier maturation, but evolved smaller body sizes at hatch and showed marginally significant signs of increased reproductive investment, including larger egg sizes and elevated pituitary GH production. Natural selection on medaka body size was too weak to significantly hinder the effect of artificial selection, indicating that the asymmetric body‐size response to size‐dependent selection reflected an asymmetry in body‐size evolvability. Our results show that trait evolvability may be contingent upon the direction of selection and that a detailed knowledge of trait evolutionary potential is needed to forecast population response to anthropogenic change. [ABSTRACT FROM AUTHOR]

Dissecting the genetic basis of intraspecific variations in life history traits is essential to understand their evolution, notably for potential biocontrol agents. Such variations are observed in the endoparasitoid Cotesia typhae (Hymenoptera: Braconidae), specialized on the pest Sesamia nonagrioides (Lepidoptera: Noctuidae). Previously, we identified two strains of C. typhae that differed significantly for life history traits on an allopatric host population. To investigate the genetic basis underlying these phenotypic differences, we used a quantitative trait locus (QTL) approach based on restriction site‐associated DNA markers. The characteristic of C. typhae reproduction allowed us generating sisters sharing almost the same genetic content, named clonal sibship. Crosses between individuals from the two strains were performed to generate F2 and F8 recombinant CSS. The genotypes of 181 clonal sibships were determined as well as the phenotypes of the corresponding 4,000 females. Informative markers were then used to build a high‐quality genetic map. These 465 markers spanned a total length of 1,300 cM and were organized in 10 linkage groups which corresponded to the number of C. typhae chromosomes. Three QTLs were detected for parasitism success and two for offspring number, while none were identified for sex ratio. The QTLs explained, respectively, 27.7% and 24.5% of the phenotypic variation observed. The gene content of the genomic intervals was investigated based on the genome of C. congregata and revealed 67 interesting candidates, as potentially involved in the studied traits, including components of the venom and of the symbiotic virus (bracovirus) shown to be necessary for parasitism success in related wasps. [ABSTRACT FROM AUTHOR]

Most species live in a variable environment in nature. Yet understanding the evolutionary processes underlying molecular adaptation to fluctuations remains a challenge. In this study we investigate the transcriptome of the fungal wheat pathogen Zymoseptoria tritici after experimental evolution under stable or fluctuating temperature, by comparing ancestral and evolved populations simultaneously. We found that temperature regimes could have a large and pervasive effect on the transcriptome evolution, with as much as 38% of the genes being differentially expressed between selection regimes. Although evolved lineages showed different changes of gene expression based on ancestral genotypes, we identified a set of genes responding specifically to fluctuation. We found that transcriptome evolution in fluctuating conditions was repeatable between parallel lineages initiated from the same genotype for about 60% of the differentially expressed genes. Further, we detected several hotspots of significantly differentially expressed genes in the genome, in regions known to be enriched in repetitive elements, including accessory chromosomes. Our findings also evidenced gene expression evolution toward a gain of robustness (loss of phenotypic plasticity) associated with the fluctuating regime, suggesting robustness is adaptive in changing environment. This work provides valuable insight into the role of transcriptional rewiring for rapid adaptation to abiotic changes in filamentous plant pathogens. [ABSTRACT FROM AUTHOR]

Microbial symbionts are ubiquitous associates of living organisms but their role in mediating reproductive isolation (RI) remains controversial. We addressed this knowledge gap by employing the Drosophila paulistorum-Wolbachia model system. Semispecies in the D. paulistorum species complex exhibit strong RI between each other and knockdown of obligate mutualistic Wolbachia bacteria in female D. paulistorum flies triggers loss of assortative mating behavior against males carrying incompatible Wolbachia strains. Here we set out to determine whether de novo RI can be introduced by Wolbachia-knockdown in D. paulistorum males. We show that Wolbachia-knockdown D. paulistorum males (i) are rejected as mates by wild type females, (ii) express altered sexual pheromone profiles, and (iii) are devoid of the endosymbiont in pheromone producing cells. Our findings suggest that changes in Wolbachia titer and tissue tropism can induce de novo premating isolation by directly or indirectly modulating sexual behavior of their native D. paulistorum hosts. [ABSTRACT FROM AUTHOR]

Abstract: Understanding the importance of nongenetic heredity in the evolutionary process is a major topic in modern evolutionary biology. We modified a classical gene‐network model by allowing parental transmission of gene expression and studied its evolutionary properties through individual‐based simulations. We identified ontogenetic time (i.e. the time gene networks have to stabilize before being submitted to natural selection) as a crucial factor in determining the evolutionary impact of this phenotypic inheritance. Indeed, fast‐developing organisms display enhanced adaptation and greater robustness to mutations when evolving in presence of nongenetic inheritance (NGI). In contrast, in our model, long development reduces the influence of the inherited state of the gene network. NGI thus had a negligible effect on the evolution of gene networks when the speed at which transcription levels reach equilibrium is not constrained. Nevertheless, simulations show that intergenerational transmission of the gene‐network state negatively affects the evolution of robustness to environmental disturbances for either fast‐ or slow‐developing organisms. Therefore, these results suggest that the evolutionary consequences of NGI might not be sought only in the way species respond to selection, but also on the evolution of emergent properties (such as environmental and genetic canalization) in complex genetic architectures. [ABSTRACT FROM AUTHOR]

Transposable elements (TEs) are repeated DNA sequences that can constitute a substantial part of genomes. Studying TEs' activity, interactions, and accumulation dynamics is thus of major interest to understand genome evolution. Here, we describe the transposition dynamics of cut-and-paste mariner elements during experimental (short- and longer-term) evolution in Drosophila melanogaster. Flies with autonomous and nonautonomous mariner copies were introduced in populations containing no active mariner, and TE accumulation was tracked by quantitative PCR for up to 100 generations. Our results demonstrate that (i) active mariner elements are highly invasive and characterized by an elevated transposition rate, confirming their capacity to spread in populations, as predicted by the "selfish-DNA" mechanism; (ii) nonautonomous copies act as parasites of autonomous mariner elements by hijacking the transposition machinery produced by active mariner, which can be considered as a case of hyperparasitism; (iii) this behavior resulted in a failure of active copies to amplify which systematically drove the whole family to extinction in less than 100 generations. This study nicely illustrates how the presence of transposition-competitive variants can deeply impair TE dynamics and gives clues to the extraordinary diversity of TE evolutionary histories observed in genomes. [ABSTRACT FROM AUTHOR]

Understanding and predicting evolution is a central challenge in both population and quantitative genetics. The amount of genetic variance for quantitative traits available in a population conditions the particular way in which this population will (or will not) evolve under natural or artificial selection. Here, we explore the potential of gene-gene interactions (epistasis) to induce evolutionary plateaus at which evolutionary change virtually collapses for a number of generations, followed by the release of previously cryptic genetic variation. First, we demonstrate theoretically that a wide range of epistatic interactions has the potential to generate temporary decelerations in the course of response to selection. Second, we perform simulations to show that such microevolutionary plateaus may occur in selection responses under empirically based assumptions. Finally, we show that such events can be traced in artificial selection experiments, thus providing further empirical evidence for this phenomenon. [ABSTRACT FROM AUTHOR]

Background: Genetic canalization reflects the capacity of an organism's phenotype to remain unchanged in spite of mutations. As selection on genetic canalization is weak and indirect, whether or not genetic canalization can reasonably evolve in complex genetic architectures is still an open question. In this paper, we use a quantitative model of gene regulatory network to describe the conditions in which substantial canalization is expected to emerge in a stable environment. Results: Through an individual-based simulation framework, we confirmed that most parameters associated with the network topology (complexity and size of the network) have less influence than mutational parameters (rate and size of mutations) on the evolution of genetic canalization. We also established that selecting for extreme phenotypic optima (nil or full gene expression) leads to much higher canalization levels than selecting for intermediate expression levels. Overall, constrained networks evolve less canalization than networks in which some genes could evolve freely (i.e. without direct stabilizing selection pressure on gene expression). Conclusions: Taken together, these results lead us to propose a two-fold mechanism involved in the evolution of genetic canalization in gene regulatory networks: the shrinkage of mutational target (useless genes are virtually removed from the network) and redundancy in gene regulation (so that some regulatory factors can be lost without affecting gene expression). [ABSTRACT FROM AUTHOR]

Transposable elements (TEs) are genomic repeated sequences that display complex evolutionary patterns. They are usually inherited vertically, but can occasionally be transmitted between sexually independent species, through so-called horizontal transposon transfers (HTTs). Recurrent HTTs are supposed to be essential in life cycle of TEs, which are otherwise destined for eventual decay. HTTs also impact the host genome evolution. However, the extent of HTTs in eukaryotes is largely unknown, due to the lack of efficient, statistically supportedmethods that can be applied to multiple species sequence data sets. Here, we developed a new automated method available as a R package "vhica" that discriminates whether a given TE family was vertically or horizontally transferred, and potentially infers donor and receptor species. Themethod is well suited for TE sequences extracted from complete genomes, and applicable tomultiple TEs and species at the same time. We first validated our method using Drosophila TE families with well-known evolutionary histories, displaying both HTTs and vertical transmission. We then tested 26 different lineages of mariner elements recently characterized in 20 Drosophila genomes, and found HTTs in 24 of them. Furthermore, several independent HTT events could often be detected within the same mariner lineage. The VHICA (Vertical and Horizontal Inheritance Consistence Analysis) method thus appears as a valuable tool to analyze the evolutionary history of TEs across a large range of species. [ABSTRACT FROM AUTHOR]

Drosophila yakuba is widespread in Africa. Here we compare the cuticular hydrocarbon (CHC) profiles and mating behavior of mainland (Kounden, Cameroon) and island (Mayotte, Sao-Tome, Bioko) populations. The strains each had different CHC profiles: Bioko and Kounden were the most similar, while Mayotte and Sao-Tome contained significant amounts of 7-heptacosene. The CHC profile of the Sao-Tome population differed the most, with half the 7-tricosene of the other populations and more 7-heptacosene and 7-nonacosene. We also studied the characteristics of the mating behavior of the four strains: copulation duration was similar but latency times were higher in Mayotte and Sao-Tome populations. We found partial reproductive isolation between populations, especially in male-choice experiments with Sao-Tome females. [ABSTRACT FROM AUTHOR]

A major challenge in evolutionary biology is understanding how stochastic and deterministic factors interact and influence macroevolutionary dynamics in natural populations. One classical approach is to record frequency changes of heritable and visible genetic polymorphisms over multiple generations. Here, we combined this approach with a maximum likelihood-based population-genetic model with the aim of understanding and quantifying the evolutionary processes operating on a female mating polymorphism in the blue-tailed damselfly Ischnura elegans. Previous studies on this colorpolymorphic species have suggested that males form a search image for females, which leads to excessive mating harassment of common female morphs. We analyzed a large temporally and spatially replicated data set of between-generation morph frequency changes in I. elegans. Morph frequencies were more stable than expected from genetic drift alone, suggesting the presence of selection toward a stable equilibrium that prevents local loss or fixation of morphs. This can be interpreted as the signature of negative frequency-dependent selection maintaining the phenotypic stasis and genetic diversity in these populations. Our novel analytical approach allows the estimation of the strength of frequency-dependent selection fromthe morph frequency fluctuations around their inferred long-term equilibria. This approach can be extended and applied to other polymorphic organisms for which time-series data across multiple generations are available. [ABSTRACT FROM AUTHOR]

Even though laboratory evolution experiments have demonstrated genetic variation for learning ability, we know little about the underlying genetic architecture and genetic relationships with other ecologically relevant traits. With a full diallel cross among twelve inbred lines of Drosophila melanogaster originating from a natural population (0.75 < F < 0.93), we investigated the genetic architecture of olfactory learning ability and compared it to that for another behavioral trait (unconditional preference for odors), as well as three traits quantifying the ability to deal with environmental challenges: egg-to-adult survival and developmental rate on a low-quality food, and resistance to a bacterial pathogen. Substantial additive genetic variation was detected for each trait, highlighting their potential to evolve. Genetic effects contributed more than nongenetic parental effects to variation in traits measured at the adult stage: learning, odorant perception, and resistance to infection. In contrast, the two traits quantifying larval tolerance to low-quality food were more strongly affected by parental effects. We found no evidence for genetic correlations between traits, suggesting that these traits could evolve at least to some degree independently of one another. Finally, inbreeding adversely affected all traits. [ABSTRACT FROM AUTHOR]

Fatty acid (FA) metabolism is deregulated in several human diseases including metabolic syndrome, type 2 diabetes and cancers. Therefore, FA-metabolic enzymes are potential targets for drug therapy, although the consequence of these treatments must be precisely evaluated at the organismal and cellular levels. In healthy organism, synthesis of triacylglycerols (TAGs)—composed of three FA units esterified to a glycerol backbone—is increased in response to dietary sugar. Saturation in the storage and synthesis capacity of TAGs is associated with type 2 diabetes progression. Sugar toxicity likely depends on advanced-glycation-end-products (AGEs) that form through covalent bounding between amine groups and carbonyl groups of sugar or their derivatives α-oxoaldehydes. Methylglyoxal (MG) is a highly reactive α-oxoaldehyde that is derived from glycolysis through a non-enzymatic reaction. Glyoxalase 1 (Glo1) works to neutralize MG, reducing its deleterious effects. Here, we have used the power of Drosophila genetics to generate Fatty acid synthase (FASN) mutants, allowing us to investigate the consequence of this deficiency upon sugar-supplemented diets. We found that FASN mutants are lethal but can be rescued by an appropriate lipid diet. Rescued animals do not exhibit insulin resistance, are dramatically sensitive to dietary sugar and accumulate AGEs. We show that FASN and Glo1 cooperate at systemic and cell-autonomous levels to protect against sugar toxicity. We observed that the size of FASN mutant cells decreases as dietary sucrose increases. Genetic interactions at the cell-autonomous level, where glycolytic enzymes or Glo1 were manipulated in FASN mutant cells, revealed that this sugar-dependent size reduction is a direct consequence of MG-derived-AGE accumulation. In summary, our findings indicate that FASN is dispensable for cell growth if extracellular lipids are available. In contrast, FA-synthesis appears to be required to limit a cell-autonomous accumulation of MG-derived-AGEs, supporting the notion that MG is the most deleterious α-oxoaldehyde at the intracellular level. [ABSTRACT FROM AUTHOR]

Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions—a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences. [ABSTRACT FROM AUTHOR]

Epistasis, i.e. the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions - a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences. [ABSTRACT FROM AUTHOR]

Using a multilinear model of epistasis we explore the evolution of canalization (reduced mutational effects) and evolvability (levels of additive genetic variance) under different forms of stabilizing and fluctuating selection. We show that the total selection acting on an allele can be divided into a component deriving from adaptation of the trait mean, a component of canalizing selection favoring alleles that epistatically reduce the effects of other allele substitutions, and a component of conservative selection disfavoring rare alleles. While canalizing selection operates in both stable and fluctuating environments, it may not typically maximize canalization, because it gets less efficient with increasing canalization, and reaches a balance with drift, mutation and indirect selection. Fluctuating selection leads to less canalized equilibria than stabilizing selection of comparable strength, because canalization then becomes influenced by erratic correlated responses to shifting trait adaptation. We conclude that epistatic systems under bounded fluctuating selection will become less canalized than under stabilizing selection and may support moderately increased evolvability if the amplitude of fluctuations is large, but canalization is still stronger and evolvability lower than expected under neutral evolution or under patterns of selection that shift the trait in directions of positive (reinforcing) epistasis. [ABSTRACT FROM AUTHOR]

The impact of transposable elements (TEs) on genome structure, plasticity, and evolution is still not well understood. The recent availability of complete genome sequences makes it possible to get new insights on the evolutionary dynamics of TEs from the phylogenetic analysis of their multiple copies in a wide range of species. However, this source of information is not always fully exploited. Here, we show how the history of transposition activity may be qualitatively and quantitatively reconstructed by considering the distribution of transposition events in the phylogenetic tree, along with the tree topology. Using statistical models developed to infer speciation and extinction rates in species phylogenies, we demonstrate that it is possible to estimate the past transposition rate of a TE family, as well as how this rate varies with time. This methodological framework may not only facilitate the interpretation of genomic data, but also serve as a basis to develop new theoretical and statistical models. [ABSTRACT FROM AUTHOR]

A major challenge in complex trait genetics is to unravel how multiple loci and environmental factors together cause phenotypic diversity. Both first (F1) and second (F2) generation hybrids often display phenotypes that deviate from what is expected under intermediate inheritance. We have here studied two chicken F2 populations generated by crossing divergent chicken lines to assess how epistatic loci, identified in earlier quantitative trait locus (QTL) studies, contribute to hybrid deviations from the mid-parent phenotype. Empirical evidence suggests that the average phenotypes of the intercross birds tend to be lower than the midpoint between the parental means in both crosses. Our results confirm that epistatic interactions, despite a relatively small contribution to the phenotypic variance, play an important role in the deviation of hybrid phenotypes from the mid-parent values (i.e. multi-locus hybrid genotypes lead to lower rather than higher body weights). To a lesser extent, dominance also appears to contribute to the mid-parent deviation, at least in one of the crosses. This observation coincides with the hypothesis that hybridization tends to break up co-adapted gene complexes, i.e. generate Bateson–Dobzhansky–Muller incompatibilities. [ABSTRACT FROM PUBLISHER]

Measuring the strength of natural selection is tremendously important in evolutionary biology, but remains a challenging task. In this work, we analyse the characteristics of selection for a morphological change (lateral-plate reduction) in the threespine stickleback Gasterosteus aculeatus. Adaptation to freshwater, leading with the reduction or loss of the bony lateral armour, has occurred in parallel on numerous occasions in this species. Completely-plated and low-plated sticklebacks were introduced into a pond, and the phenotypic changes were tracked for 20 years. Fish from the last generation were genotyped for the Ectodysplasin-A ( Eda) locus, the major gene involved in armour development. We found a strong fitness advantage for the freshwater-type fish (on average, 20% fitness advantage for the freshwater morph, and 92% for the freshwater genotype). The trend is best explained by assuming that this fitness advantage is maximum at the beginning of the invasion and decreases with time. Such fitness differences provide a quantifiable example of rapid selection-driven phenotypic evolution associated with environmental change in a natural population. [ABSTRACT FROM AUTHOR]

Artificial-selection experiments constitute an important source of empirical information for breeders, geneticists and evolutionary biologists. Selected characters can generally be shifted far from their initial state, sometimes beyond what is usually considered as typical inter-specific divergence. A careful analysis of the data collected during such experiments may thus reveal the dynamical properties of the genetic architecture that underlies the trait under selection. Here, we propose a statistical framework describing the dynamics of selection-response time series. We highlight how both phenomenological models (which do not make assumptions on the nature of genetic phenomena) and mechanistic models (explaining the temporal trends in terms of e.g. mutations, epistasis or canalization) can be used to understand and interpret artificial-selection data. The practical use of the models and their implementation in a software package are demonstrated through the analysis of a selection experiment on the shape of the wing in Drosophila melanogaster. [ABSTRACT FROM AUTHOR]

Transposable elements (TEs) were first discovered more than 50 years ago, but were totally ignored for a long time. Over the last few decades they have gradually attracted increasing interest from research scientists. Initially they were viewed as totally marginal and anecdotic, but TEs have been revealed as potentially harmful parasitic entities, ubiquitous in genomes, and finally as unavoidable actors in the diversity, structure, and evolution of the genome. Since Darwin's theory of evolution, and the progress of molecular biology, transposable elements may be the discovery that has most influenced our vision of (genome) evolution. In this review, we provide a synopsis of what is known about the complex interactions that exist between transposable elements and the host genome. Numerous examples of these interactions are provided, first from the standpoint of the genome, and then from that of the transposable elements. We also explore the evolutionary aspects of TEs in the light of post-Darwinian theories of evolution. Reviewers: This article was reviewed by Jerzy Jurka, Jürgen Brosius and I. King Jordan. For complete reports, see the Reviewers' reports section. [ABSTRACT FROM AUTHOR]

Both analytical and molecular tools currently exist that can be used to prolifically apply quantitative trait loci (QTL) analysis to the study of natural populations. In this communication, we review and exemplify the use of QTL mapping tools and genetic modeling for conservation geneticists. We simulate populations inspired by relevant cases that can be encountered in the field and analyze them using the recently developed flexible intercross analysis (FIA) method. We then reanalyze these results with the also recently developed natural and orthogonal interactions (NOIA) model of genetic effects. Next, we further exemplify the potential of genetic modeling for the interpretation of the output of QTL analyses by reviewing studies on hybrids between wild individuals and their domesticated relatives. Based on the results here presented we emphasize several points that are pertinent in conservation genetics including (i) the advantages of FIA as a powerful tool to be applied to line crosses in which the parental lines are not inbred, (ii) the importance of obtaining estimates of genetic effects that are adequate to address the research issue under consideration, (iii) the versatility of genetic modeling, particularly NOIA, to dissect complex genetic architectures and (iv) the possibility of using currently available methods to address non-equilibrium multiallelic systems. [ABSTRACT FROM AUTHOR]

Although the genotype-phenotype map plays a central role both in Quantitative and Evolutionary Genetics, the formalization of a completely general and satisfactory model of genetic effects, particularly accounting for epistasis, remains a theoretical challenge. Here, we use a two-locus genetic system in simulated populations with epistasis to show the convenience of using a recently developed model, NOIA, to perform estimates of genetic effects and the decomposition of the genetic variance that are orthogonal even under deviations from the Hardy-Weinberg proportions. We develop the theory for how to use this model in interval mapping of quantitative trait loci using Halley-Knott regressions, and we analyze a real data set to illustrate the advantage of using this approach in practice. In this example, we show that departures from the Hardy-Weinberg proportions that are expected by sampling alone substantially alter the orthogonal estimates of genetic effects when other statistical models, like F2 or G2A, are used instead of NOIA. Finally, for the first time from real data, we provide estimates of functional genetic effects as sets of effects of natural allele substitutions in a particular genotype, which enriches the debate on the interpretation of genetic effects as implemented both in functional and in statistical models. We also discuss further implementations leading to a completely general genotype-phenotype map. [ABSTRACT FROM AUTHOR]

Determining the genetic architecture of complex traits is a necessary step to understand phenotypic changes in natural, experimental and domestic populations. However, this is still a major challenge for modern genetics, since the estimation of genetic effects tends to be complicated by genetic interactions, which lead to changes in the effect of allelic substitutions depending on the genetic background. Recent progress in statistical tools aiming to describe and quantify genetic effects meaningfully improves the efficiency and the availability of genotype-to-phenotype mapping methods. In this contribution, we facilitate the practical use of the recently published 'NOIA' quantitative framework by providing an implementation of linear and multilinear regressions, change of reference operation and genotype-to-phenotype mapping in a package ('noia') for the software R, and we discuss theoretical and practical benefits evolutionary and quantitative geneticists may find in using proper modeling strategies to quantify the effects of genes. [ABSTRACT FROM AUTHOR]

Transposable elements are often considered parasitic DNA sequences, able to invade the genome of their host thanks to their self-replicating ability. This colonization process has been extensively studied, both theoretically and experimentally, but their long-term coevolution with the genomes is still poorly understood. In this work, we aim to challenge previous population genetics models by considering features of transposable elements as quantitative, rather than discrete, variables. We also describe more realistic transposable element dynamics by accounting for the variability of the insertion effect, from deleterious to adaptive, as well as mutations leading to a loss of transposition activity and to nonautonomous copies. Individual-based simulations of the behavior of a transposable-element family over several thousand generations show different ways in which active or inactive copies can be maintained for a very long time. Results reveal an unexpected impact of genetic drift on the "junk DNA" content of the genome and strongly question the likelihood of the sustainable long-term stable transposition-selection equilibrium on which numerous previous works were based. [ABSTRACT FROM AUTHOR]

Background: The genetic architecture of a quantitative trait influences the phenotypic response to natural or artificial selection. One of the main objectives of genetic mapping studies is to identify the genetic factors underlying complex traits and understand how they contribute to phenotypic expression. Presently, we are good at identifying and locating individual loci with large effects, but there is a void in describing more complex genetic architectures. Although large networks of connected genes have been reported, there is an almost complete lack of information on how polymorphisms in these networks contribute to phenotypic variation and change. To date, most of our understanding comes from theoretical, model-based studies, and it remains difficult to assess how realistic their conclusions are as they lack empirical support. Results: A previous study provided evidence that nearly half of the difference in eight-week body weight between two divergently selected lines of chickens was a result of four loci organized in a 'radial' network (one central locus interacting with three 'radial' loci that, in turn, only interacted with the central locus). Here, we study the relationship between phenotypic change and genetic polymorphism in this empirically detected network. We use a model-free approach to study, through individual-based simulations, the dynamic properties of this polymorphic and epistatic genetic architecture. The study provides new insights to how epistasis can modify the selection response, buffer and reveal effects of major loci leading to a progressive release of genetic variation. We also illustrate the difficulty of predicting genetic architecture from observed selection response, and discuss mechanisms that might lead to misleading conclusions on underlying genetic architectures from quantitative trait locus (QTL) experiments in selected populations. Conclusion: Considering both molecular (QTL) and phenotypic (selection response) data, as suggested in this work, provides additional insights into the genetic mechanisms involved in the response to selection. Such dissection of genetic architectures and in-depth studies of their ability to contribute to short- or long-term selection response represents an important step towards a better understanding of the genetic bases of complex traits and, consequently, of the evolutionary properties of populations. [ABSTRACT FROM AUTHOR]

Predicting how a genetic change affects a given character is a major challenge in biology, and being able to tackle this problem relies on our ability to develop realistic models of gene networks. However, such models are rarely tractable mathematically. In this paper, we propose a mathematical analysis of the sigmoid variant of the Wagner gene-network model. By considering the simplest case, that is, one unique self-regulating gene, we show that numerical simulations are not the only tool available to study such models: theoretical studies can be done too, by mathematical analysis of discrete dynamical systems. It is first shown that the particular sigmoid function can be theoretically investigated. Secondly, we provide an illustration of how to apply such investigations in the case of the dynamical system representing the one self-regulating gene. In this context, we focused on the composite function f a ( m. x ) where f a is the parametric sigmoid function and m is a scalar not in { 0 , 1 } and we have proven that the number of fixed-point can be deduced theoretically, according to the values of a and m. [ABSTRACT FROM AUTHOR]