The evolutionary genetics of canalization

Evolutionary genetics has recently made enormous progress in understanding how genetic variation maps into phenotypic variation. However why some traits are phenotypically invariant despite apparent genetic and environmental changes has remained a major puzzle. In the 1940s, Conrad Hal Waddington coined the concept and term "canalization" to describe the robustness of phenotypes to perturbation; a similar concept was proposed by Waddington's contemporary Ivan Ivanovich Schmalhausen. This paper reviews what has been learned about canalization since Waddington. Canalization implies that a genotype's phenotype remains relatively invariant when individuals of a particular genotype are exposed to different environments (environmental canalization) or when individuals of the same single- or multilocus genotype differ in their genetic background (genetic canalization). Consequently, genetic canalization can be viewed as a particular kind of epistasis, and environmental canalization and phenotypic plasticity are two aspects of the same phenomenon. Canalization results in the accumulation of phenotypically cryptic genetic variation, which can be released after a "decanalizing" event. Thus, canalized genotypes maintain a cryptic potential for expressing particular phenotypes, which are only uncovered under particular decanalizing environmental or genetic conditions. Selection may then act on this newly released genetic variation. The accumulation of cryptic genetic variation by canalization may therefore increase evolvability at the population level by leading to phenotypic diversification under decanalizing conditions. On the other hand, under canalizing conditions, a major part of the segregating genetic variation may remain phenotypically cryptic; canalization may therefore, at least temporarily, constrain phenotypic evolution. Mechanistically, canalization can be understood in terms of transmission patterns, such as epistasis, pleiotropy, and genotype by environment interactions, and in terms of genetic redundancy, modularity, and emergent properties of gene networks and biochemical pathways. While different forms of selection can favor canalization, the requirements for its evolution are typically rather restrictive. Although there are several methods to detect canalization, there are still serious problems with unambiguously demonstrating canalization, particularly its adaptive value.     

Quantitative trait loci mapping of phenotypic plasticity and genotype-environment interactions in plant and insect performance

Community genetic studies generally ignore the plasticity of the functional traits through which the effect is passed from individuals to the associated community. However, the ability of organisms to be phenotypically plastic allows them to rapidly adapt to changing environments and plasticity is commonly observed across all taxa. Owing to the fitness benefits of phenotypic plasticity, evolutionary biologists are interested in its genetic basis, which could explain how phenotypic plasticity is involved in the evolution of species interactions. Two current ideas exist: (i) phenotypic plasticity is caused by environmentally sensitive loci associated with a phenotype; (ii) phenotypic plasticity is caused by regulatory genes that simply influence the plasticity of a phenotype. Here, we designed a quantitative trait loci (QTL) mapping experiment to locate QTL on the barley genome associated with barley performance when the environment varies in the presence of aphids, and the composition of the rhizosphere. We simultaneously mapped aphid performance across variable rhizosphere environments. We mapped main effects, QTL × environment interaction (QTL×E), and phenotypic plasticity (measured as the difference in mean trait values) for barley and aphid performance onto the barley genome using an interval mapping procedure. We found that QTL associated with phenotypic plasticity were co-located with main effect QTL and QTL×E. We also located phenotypic plasticity QTL that were located separately from main effect QTL. These results support both of the current ideas of how phenotypic plasticity is genetically based and provide an initial insight into the functional genetic basis of how phenotypically plastic traits may still be important sources of community genetic effects.     

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.     

The phenotypic variance gradient – a novel concept

Evolutionary ecologists commonly use reaction norms, which show the range of phenotypes produced by a set of genotypes exposed to different environments, to quantify the degree of phenotypic variance and the magnitude of plasticity of morphometric and life‐history traits. Significant differences among the values of the slopes of the reaction norms are interpreted as significant differences in phenotypic plasticity, whereas significant differences among phenotypic variances (variance or coefficient of variation) are interpreted as differences in the degree of developmental instability or canalization. We highlight some potential problems with this approach to quantifying phenotypic variance and suggest a novel and more informative way to plot reaction norms: namely “a plot of log (variance) on the y‐axis versus log (mean) on the x‐axis, with a reference line added”. This approach gives an immediate impression of how the degree of phenotypic variance varies across an environmental gradient, taking into account the consequences of the scaling effect of the variance with the mean. The evolutionary implications of the variation in the degree of phenotypic variance, which we call a “phenotypic variance gradient”, are discussed together with its potential interactions with variation in the degree of phenotypic plasticity and canalization.     

The fitness costs of developmental canalization and plasticity

Organisms are capable of an astonishing repertoire of phenotypic responses to the environment, and these often define important adaptive solutions to heterogeneous and unpredictable conditions. The terms ‘phenotypic plasticity’ and ‘canalization’ indicate whether environmental variation has a large or small effect on the phenotype. The evolution of canalization and plasticity is influenced by optimizing selection‐targeting traits within environments, but inherent fitness costs of plasticity may also be important. We present a meta‐analysis of 27 studies (of 16 species of plant and 7 animals) that have measured selection on the degree of plasticity independent of the characters expressed within environments. Costs of plasticity and canalization were equally frequent and usually mild; large costs were observed only in studies with low sample size. We tested the importance of several covariates, but only the degree of environmental stress was marginally positively related to the cost of plasticity. These findings suggest that costs of plasticity are often weak, and may influence phenotypic evolution only under stressful conditions.     

From QTL to QTN: Candidate Gene Set Approach and a Case Study in Porcine IGF1-FoxO Pathway

Unraveling the genetic background of economic traits is a major goal in modern animal genetics and breeding. Both candidate gene analysis and QTL mapping have previously been used for identifying genes and chromosome regions related to studied traits. However, most of these studies may be limited in their ability to fully consider how multiple genetic factors may influence a particular phenotype of interest. If possible, taking advantage of the combined effect of multiple genetic factors is expected to be more powerful than analyzing single sites, as the joint action of multiple loci within a gene or across multiple genes acting in the same gene set will likely have a greater influence on phenotypic variation. Thus, we proposed a pipeline of gene set analysis that utilized information from multiple loci to improve statistical power. We assessed the performance of this approach by both simulated and a real IGF1-FoxO pathway data set. The results showed that our new method can identify the association between genetic variation and phenotypic variation with higher statistical power and unravel the mechanisms of complex traits in a point of gene set. Additionally, the proposed pipeline is flexible to be extended to model complex genetic structures that include the interactions between different gene sets and between gene sets and environments.     

Life history responses to irradiance at the early seedling stage of Picea omorika (Pančić) Purkyňe: adaptiveness and evolutionary limits

A multivariate selection analysis has been implemented for testing the adaptiveness of life history plasticity to irradiance during the seedling establishment in Picea omorika plants raised in a growth-room. Siblings of a synthetic population comprising 21 families from six natural populations were exposed to contrasting light levels to explore variation in phenotypic expression of three seedling traits: days from germination to cotyledon opening (DGTOC), days from cotyledon opening to epicotyl appearance (DCTOE), and epicotyl length at 6 weeks (EPL6). Ambient light conditions significantly affected DCTOE and EPL6, but not DGTOC. Phenotypic selection analysis revealed that DGTOC was under negative directional selection in both radiation environments, suggesting that canalization of DGTOC was promoted across different light conditions, as well as that the observed pattern of canalization might be regarded as adaptive. DCTOE was also found to be under negative directional selection in both light treatments, but the plastic responses of this trait were opposite to the values favoured by selection within environments. Since there was evidence for selection against plasticity in DCTOE, the pattern of plastic responses in DCTOE to variation in light conditions could be diagnosed as maladaptive. Multiple regression analysis revealed a cost of canalization in DGTOC regardless of light environment, as well as a cost of plasticity in DCTOE under high light intensity. All genetic correlations across light environments were significantly different from unity, indicating the existence of heritable variation for plasticity in these traits. However, since DGTOC and DCTOE were involved in a genetic trade-off with respect to both trait mean and plasticity, these early life histories would never reach their optimal values across radiation environments.     

Foraging environment determines the genetic architecture and evolutionary potential of trophic morphology in cichlid fishes

Phenotypic plasticity allows organisms to change their phenotype in response to shifts in the environment. While a central topic in current discussions of evolutionary potential, a comprehensive understanding of the genetic underpinnings of plasticity is lacking in systems undergoing adaptive diversification. Here, we investigate the genetic basis of phenotypic plasticity in a textbook adaptive radiation, Lake Malawi cichlid fishes. Specifically, we crossed two divergent species to generate an F₃ hybrid mapping population. At early juvenile stages, hybrid families were split and reared in alternate foraging environments that mimicked benthic/scraping or limnetic/sucking modes of feeding. These alternate treatments produced a variation in morphology that was broadly similar to the major axis of divergence among Malawi cichlids, providing support for the flexible stem theory of adaptive radiation. Next, we found that the genetic architecture of several morphological traits was highly sensitive to the environment. In particular, of 22 significant quantitative trait loci (QTL), only one was shared between the environments. In addition, we identified QTL acting across environments with alternate alleles being differentially sensitive to the environment. Thus, our data suggest that while plasticity is largely determined by loci specific to a given environment, it may also be influenced by loci operating across environments. Finally, our mapping data provide evidence for the evolution of plasticity via genetic assimilation at an important regulatory locus, ptch1. In all, our data address long‐standing discussions about the genetic basis and evolution of plasticity. They also underscore the importance of the environment in affecting developmental outcomes, genetic architectures, morphological diversity and evolutionary potential.     

Unifying Genetic Canalization,Genetic Constraint,and Genotype-by-Environment Interaction: QTL by Genomic Background by Environment Interaction of Flowering Time in Boechera stricta

Natural populations exhibit substantial variation in quantitative traits. A quantitative trait is typically defined by its mean and variance, and to date most genetic mapping studies focus on loci altering trait means but not (co)variances. For single traits, the control of trait variance across genetic backgrounds is referred to as genetic canalization. With multiple traits, the genetic covariance among different traits in the same environment indicates the magnitude of potential genetic constraint, while genotype-by-environment interaction (GxE) concerns the same trait across different environments. While some have suggested that these three attributes of quantitative traits are different views of similar concepts, it is not yet clear, however, whether they have the same underlying genetic mechanism. Here, we detect quantitative trait loci (QTL) influencing the (co)variance of phenological traits in six distinct environments in Boechera stricta, a close relative of Arabidopsis. We identified nFT as the QTL altering the magnitude of phenological trait canalization, genetic constraint, and GxE. Both the magnitude and direction of nFT''s canalization effects depend on the environment, and to our knowledge, this reversibility of canalization across environments has not been reported previously. nFT''s effects on trait covariance structure (genetic constraint and GxE) likely result from the variable and reversible canalization effects across different traits and environments, which can be explained by the interaction among nFT, genomic backgrounds, and environmental stimuli. This view is supported by experiments demonstrating significant nFT by genomic background epistatic interactions affecting phenological traits and expression of the candidate gene, FT. In contrast to the well-known canalization gene Hsp90, the case of nFT may exemplify an alternative mechanism: Our results suggest that (at least in traits with major signal integrators such as flowering time) genetic canalization, genetic constraint, and GxE may have related genetic mechanisms resulting from interactions among major QTL, genomic backgrounds, and environments.     

A statistical model for testing the pleiotropic control of phenotypic plasticity for a count trait

The differences of a phenotypic trait produced by a genotype in response to changes in the environment are referred to as phenotypic plasticity. Despite its importance in the maintenance of genetic diversity via genotype-by-environment interactions, little is known about the detailed genetic architecture of this phenomenon, thus limiting our ability to predict the pattern and process of microevolutionary responses to changing environments. In this article, we develop a statistical model for mapping quantitative trait loci (QTL) that control the phenotypic plasticity of a complex trait through differentiated expressions of pleiotropic QTL in different environments. In particular, our model focuses on count traits that represent an important aspect of biological systems, controlled by a network of multiple genes and environmental factors. The model was derived within a multivariate mixture model framework in which QTL genotype-specific mixture components are modeled by a multivariate Poisson distribution for a count trait expressed in multiple clonal replicates. A two-stage hierarchic EM algorithm is implemented to obtain the maximum-likelihood estimates of the Poisson parameters that specify environment-specific genetic effects of a QTL and residual errors. By approximating the number of sylleptic branches on the main stems of poplar hybrids by a Poisson distribution, the new model was applied to map QTL that contribute to the phenotypic plasticity of a count trait. The statistical behavior of the model and its utilization were investigated through simulation studies that mimic the poplar example used. This model will provide insights into how genomes and environments interact to determine the phenotypes of complex count traits.     

Variation and constraint in plant evolution and development

The goal of this short review is to consider the interrelated phenomena of phenotypic variation and genetic constraint with respect to plant diversity. The unique aspects of plants, including sessile habit, modular growth and diverse developmental programs expressed at the phytomer level, merit a specific examination of the genetic basis of their phenotypic variation, and how they experience and escape genetic constraint. Numerous QTL studies with wild and domesticated plants reveal that most phenotypic traits are polygenic but vary in the number and effect of the loci contributing, from a few loci of large effects to many with small effects. Further, somatic mutations, developmental plasticity and epigenetic variation, especially gene methylation, can contribute to increases in phenotypic variation. The flip side of these processes, genetic constraint, can similarly be the result of many factors, including pleiotropy, canalization and genetic redundancy. Genetic constraint is not only a mechanism to prevent change, however, it can also serve to direct evolution along certain paths. Ultimately, genetic constraint often comes full circle and is released through events such as hybridization, genome duplication and epigenetic remodeling. We are just beginning to understand how these processes can operate simultaneously during the evolution of ecologically important traits in plants.     

Stage‐ and thermal‐specific genetic architecture for preadult viability in natural populations of Drosophila melanogaster

Studying the processes affecting variation for preadult viability is essential to understand the evolutionary trajectories followed by natural populations. This task requires focusing on the complex nature of the phenotype–genotype relationship by taking into account usually neglected aspects of the phenotype and recognizing the modularity between different ontogenetic stages. Here, we describe phenotypic variability for viability during the larval and pupal stages in lines derived from three natural populations of Drosophila melanogaster, as well as the variability for phenotypic plasticity and canalization at two different rearing temperatures. The results indicate that the three populations present significant phenotypic differences for preadult viability. Furthermore, distinct aspects of the phenotype (means, plasticity, canalization, plasticity of canalization) are affected by different genetic bases underlying changes in viability in a stage‐ and environment‐specific manner. These findings explain the generalized maintenance of genetic variability for this fitness trait.     

Conditional QTL underlying resistance to late blight in a diploid potato population

A large number of quantitative trait loci (QTL) for resistance to late blight of potato have been reported with a "conventional" method in which each phenotypic trait reflects the cumulative genetic effects for the duration of the disease process. However, as genes controlling response to disease may have unique contributions with specific temporal features, it is important to consider the phenotype as dynamic. Here, using the net genetic effects evidenced at consecutive time points during disease development, we report the first conditional mapping of QTL underlying late blight resistance in potato under five environments in Peru. Six conditional QTL were mapped, one each on chromosome 2, 7 and 12 and three on chromosome 9. These QTL represent distinct contributions to the phenotypic variation at different stages of disease development. By comparison, when conventional mapping was conducted, only one QTL was detected on chromosome 9. This QTL was the same as one of the conditional QTL. The results imply that conditional QTL reflect genes that function at particular stages during the host-pathogen interaction. The dynamics revealed by conditional QTL mapping could contribute to the understanding of the molecular mechanism of late blight resistance and these QTL could be used to target genes for marker development or manipulation to improve resistance.     

Two reproductive traits show contrasting genetic architectures in Plantago lanceolata

In many species, temperature‐sensitive phenotypic plasticity (i.e., an individual's phenotypic response to temperature) displays a positive correlation with latitude, a pattern presumed to reflect local adaptation. This geographical pattern raises two general questions: (a) Do a few large‐effect genes contribute to latitudinal variation in a trait? (b) Is the thermal plasticity of different traits regulated pleiotropically? To address the questions, we crossed individuals of Plantago lanceolata derived from northern and southern European populations. Individuals naturally exhibited high and low thermal plasticity in floral reflectance and flowering time. We grew parents and offspring in controlled cool‐ and warm‐temperature environments, mimicking what plants would encounter in nature. We obtained genetic markers via genotype‐by‐sequencing, produced the first recombination map for this ecologically important nonmodel species, and performed quantitative trait locus (QTL) mapping of thermal plasticity and single‐environment values for both traits. We identified a large‐effect QTL that largely explained the reflectance plasticity differences between northern and southern populations. We identified multiple smaller‐effect QTLs affecting aspects of flowering time, one of which affected flowering time plasticity. The results indicate that the genetic architecture of thermal plasticity in flowering is more complex than for reflectance. One flowering time QTL showed strong cytonuclear interactions under cool temperatures. Reflectance and flowering plasticity QTLs did not colocalize, suggesting little pleiotropic genetic control and freedom for independent trait evolution. Such genetic information about the architecture of plasticity is environmentally important because it informs us about the potential for plasticity to offset negative effects of climate change.     

Reaction norms of Arabidopsis (Brassicaceae). III. Response to nutrients in 26 populations from a worldwide collection

The study of phenotypic plasticity, the ability of a given genotype to express different phenotypes as environments change, is becoming a central focus of ecological genetics and evolutionary theory. To help address the most pressing questions about plasticity (its genetic control, ecological relevance, and macroevolutionary consequences) we advocate the use of Arabidopsis thaliana (and eventually other related species of the same genus) as a model system. In this study we present experimental data concerning: (a) the extent of reaction norm variation to two levels of nutrients in a worldwide collection of 26 A. thaliana populations; and (b) the existence of multivariate associations among key phenotypic characters, and their reaction to changes in the environment. We found significant among-population genetic variation for eight of the nine traits measured, as well as plasticity in four traits. Five traits showed significant differences in genetic variation between the two environments. The multivariate association of the nine traits defines four major groups of covarying characters, each of which may be plastic or not, depending on the particular population. The use of populations that can be easily obtained by any researcher, because they are part of a worldwide collection, implies that it will be easy to build on our results during future investigations of phenotypic plasticity in this species.     

Role of genetic architecture in phenotypic plasticity

Phenotypic plasticity, the ability of an organism to display different phenotypes across environments, is widespread in nature. Plasticity aids survival in novel environments. Herein, we review studies from yeast that allow us to start uncovering the genetic architecture of phenotypic plasticity. Genetic variants and their interactions impact the phenotype in different environments, and distinct environments modulate the impact of genetic variants and their interactions on the phenotype. Because of this, certain hidden genetic variation is expressed in specific genetic and environmental backgrounds. A better understanding of the genetic mechanisms of phenotypic plasticity will help to determine short- and long-term responses to selection and how wide variation in disease manifestation occurs in human populations.     

Mapping phenotypic plasticity and genotype-environment interactions affecting life-history traits in Caenorhabditis elegans

Phenotypic plasticity and genotype-environment interactions (GEI) play an important role in the evolution of life histories. Knowledge of the molecular genetic basis of plasticity and GEI provides insight into the underlying mechanisms of life-history changes in different environments. We used a genomewide single-nucleotide polymorphism map in a recombinant N2 x CB4856 inbred panel of the nematode Caenorhabditis elegans to study the genetic control of phenotypic plasticity to temperature in four fitness-related traits, that is, age at maturity, fertility, egg size and growth rate. We mapped quantitative trait loci (QTL) for the respective traits at 12 and 24 degrees C, as well as their plasticities. We found genetic variation and GEI for age at maturity, fertility, egg size and growth rate. GEI in fertility and egg size was attributed to changes in rank order of reaction norms. In case of age at maturity and growth rate, GEI was caused mainly by differences in the among-line variance. In total, 11 QTLs were detected, five QTL at 12 degrees C and six QTL at 24 degrees C, which were associated with life-history traits. Five QTL associated with age at maturity, fertility and growth rate showed QTL x environment interaction. These colocalized with plasticity QTL for the respective traits suggesting allelic sensitivity to temperature. Further fine mapping, complementation analyses and gene silencing are planned to identify candidate genes underlying phenotypic plasticity for age at maturity, fertility and growth.     

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.