A modular concept of phenotypic plasticity in plants

Based on empirical evidence from the literature we propose that, in nature, phenotypic plasticity in plants is usually expressed at a subindividual level. While reaction norms (i.e. the type and the degree of plant responses to environmental variation) are a property of genotypes, they are expressed at the level of modular subunits in most plants. We thus contend that phenotypic plasticity is not a whole-plant response, but a property of individual meristems, leaves, branches and roots, triggered by local environmental conditions. Communication and behavioural integration of interconnected modules can change the local responses in different ways: it may enhance or diminish local plastic effects, thereby increasing or decreasing the differences between integrated modules exposed to different conditions. Modular integration can also induce qualitatively different responses, which are not expressed if all modules experience the same conditions. We propose that the response of a plant to its environment is the sum of all modular responses to their local conditions plus all interaction effects that are due to integration. The local response rules to environmental variation, and the modular interaction rules may be seen as evolving traits targeted by natural selection. Following this notion, whole-plant reaction norms are an integrative by-product of modular plasticity, which has far-reaching methodological, ecological and evolutionary implications.     

Phenotypic integration plasticity in Daphnia magna: an integral facet of G × E interactions

Phenotypic integration can be defined as the network of multivariate relationships among behavioural, physiological and morphological traits that describe the organism. Phenotypic integration plasticity refers to the change in patterns of phenotypic integration across environments or ontogeny. Because studies of phenotypic plasticity have predominantly focussed on single traits, a G × E interaction is typically perceived as differences in the magnitude of trait expression across two or more environments. However, many plastic responses involve coordinated responses in multiple traits, raising the possibility that relative differences in trait expression in different environments are an important, but often overlooked, source of G × E interaction. Here, we use phenotypic change vectors to statistically compare the multivariate life‐history plasticity of six Daphnia magna clones collected from four disparate European populations. Differences in the magnitude of plastic responses were statistically distinguishable for two of the six clones studied. However, differences in phenotypic integration plasticity were statistically distinguishable for all six of the clones studied, suggesting that phenotypic integration plasticity is an important component of G × E interactions that may be missed unless appropriate multivariate analyses are used.     

The adaptive value of phenotypic floral integration

Floral integration has been deemed an adaptation to increase the benefits of animal pollination, yet no attempts have been made to estimate its adaptive value under natural conditions. Here, the variation in the magnitude and pattern of phenotypic floral integration and the variance-covariance structure of floral traits in four species of Rosaceae were examined. The intensity of natural selection acting on floral phenotypic integration was also estimated and the available evidence regarding the magnitude of floral integration reviewed. The species studied had similar degrees of floral integration, although significant differences were observed in their variance-covariance structure. Selection acted on subsets of floral traits (i.e. selection on intrafloral integration) rather than on the integration of the whole flower. Average integration was 20% and similar to the estimated mean value of flowering plants. The review indicated that flowering plants present lower integration than expected by chance. Numerical simulations suggest that this pattern may result from selection favouring intrafloral integration. Phenotypic integration at the flower level seems to have a low adaptive value among the species surveyed. Moreover, it is proposed that pollinator-mediated selection promotes the evolution of intrafloral integration.     

Effects of phenotypic complementarity and phylogeny on the nested structure of mutualistic networks

Recent studies have started to unravel the structure of mutualistic networks, although few functional explanations underlying such structure have been explored. We used computer simulations to test whether complementarity between phenotypic traits of plants and animals can explain the pervasive tendency of specialists to interact with proper subsets of species that generalists interact with (nested interactions), and how phylogeny affects such interaction patterns. Simultaneously, we assessed whether complementarity and phylogenetic structure were associated with patterns of interaction in a real mutualistic community. Simulation results support that highly nested networks can emerge from phenotypic complementarity, particularly when several traits are involved. The hierarchical structure of phylogenetic relations can also contribute to increased nestedness because traits determining complementarity are then inherited in a correlated fashion. Phylogenetic effects on resulting generalization levels are often low, but can be detected. Results from the empirical network support a relevant role of complementarity and phylogenetic history on interaction patterns. Our results demonstrate that these factors can contribute to nestedness, which emphasize the necessity of considering evolutionary mechanisms in studies of community structure.     

INFLUENCE OF POLLINATION SPECIALIZATION AND BREEDING SYSTEM ON FLORAL INTEGRATION AND PHENOTYPIC VARIATION IN IPOMOEA

Natural selection should reduce phenotypic variation and increase integration of floral traits involved in placement of pollen grains on stigmas. In this study, we examine the role of pollinators and breeding system on the evolution of floral traits by comparing the patterns of floral phenotypic variances and covariances in 20 Ipomoea species that differ in their level of pollination specialization and pollinator dependence incorporating phylogenetic relatedness. Plants with specialized pollination (i.e., those pollinated by one functional group or by few morphospecies) displayed less phenotypic variation and greater floral integration than generalist plants. Self‐compatible species also displayed greater floral integration than self‐incompatible species. Floral traits involved in pollen placement and pick up showed less variation and greater integration than floral traits involved in pollinator attraction. Analytical models indicate that both breeding system and the number of morphospecies had significant effects on floral integration patterns although only differences in the former were significant after accounting for phylogeny. These results suggest that specialist/self‐compatible plants experience more consistent selection on floral traits than generalist/self‐incompatible plants. Furthermore, pollinators and breeding system promote integration of floral traits involved in pollen placement and pick up rather than integration of the whole flower.     

Genetic drift and polygenic inheritance

The interaction of random gene drift and selection was studied by computer simulation for two quantitative traits, which were considered to approximate stature and skin color differences in human populations. The expected effects of gene drift, fixation of alleles and reduction of genotypic and phenotypic variances, were found in the simulation. Stabilizing selection, which seems to be the type of selection operating on these traits, was found to increase the effects of gene drift. Since there seems to be no evidence of reduction in phenotypic and presumably genotypic variability in small human populations, the applicability of these simple genetic models to human traits raises problems for which several possible solutions exist.     

Bayesian species delimitation combining multiple genes and traits in a unified framework

Delimitation of species based exclusively on genetic data has been advocated despite a critical knowledge gap: how might such approaches fail because they rely on genetic data alone, and would their accuracy be improved by using multiple data types. We provide here the requisite framework for addressing these key questions. Because both phenotypic and molecular data can be analyzed in a common Bayesian framework with our program iBPP, we can compare the accuracy of delimited taxa based on genetic data alone versus when integrated with phenotypic data. We can also evaluate how the integration of phenotypic data might improve species delimitation when divergence occurs with gene flow and/or is selectively driven. These two realities of the speciation process are ignored by currently available genetic approaches. Our model accommodates phenotypic characters that exhibit different degrees of divergence, allowing for both neutral traits and traits under selection. We found a greater accuracy of estimated species boundaries with the integration of phenotypic and genetic data, with a strong beneficial influence of phenotypic data from traits under selection when the speciation process involves gene flow. Our results highlight the benefits of multiple data types, but also draws into question the rationale of species delimitation based exclusively on genetic data.     

Shifts and disruptions in resource-use trait syndromes during the evolution of herbaceous crops

Trait-based ecology predicts that evolution in high-resource agricultural environments should select for suites of traits that enable fast resource acquisition and rapid canopy closure. However, crop breeding targets specific agronomic attributes rather than broad trait syndromes. Breeding for specific traits, together with evolution in high-resource environments, might lead to reduced phenotypic integration, according to predictions from the ecological literature. We provide the first comprehensive test of these hypotheses, based on a trait-screening programme of 30 herbaceous crops and their wild progenitors. During crop evolution plants became larger, which enabled them to compete more effectively for light, but they had poorly integrated phenotypes. In a subset of six herbaceous crop species investigated in greater depth, competitiveness for light increased during early plant domestication, whereas diminished phenotypic integration occurred later during crop improvement. Mass-specific leaf and root traits relevant to resource-use strategies (e.g. specific leaf area or tissue density of fine roots) changed during crop evolution, but in diverse and contrasting directions and magnitudes, depending on the crop species. Reductions in phenotypic integration and overinvestment in traits involved in competition for light may affect the chances of upgrading modern herbaceous crops to face current climatic and food security challenges.     

The evolution of social interactions changes predictions about interacting phenotypes

In many traits involved in social interactions, such as courtship and aggression, the phenotype is an outcome of interactions between individuals. Such traits whose expression in an individual is partly determined by the phenotype of its social partner are called "interacting phenotypes." Quantitative genetic models suggested that interacting phenotypes can evolve much faster than nonsocial traits. Current models, however, consider the interaction between phenotypes of social partners as a fixed phenotypic response rule, represented by an interaction coefficient (ψ). Here, we extend existing theoretical models and incorporate the interaction coefficient as a trait that can evolve. We find that the evolution of the interaction coefficient can change qualitatively the predictions about the rate and direction of evolution of interacting phenotypes. We argue that it is crucial to determine whether and how the phenotypic response of an individual to its social partner can evolve to make accurate predictions about the evolution of traits involved in social interactions.     

Floral integration,phenotypic covariance structure and pollinator variation in bumblebee‐pollinated Helleborus foetidus

By analysing patterns of phenotypic integration and multivariate covariance structure of five metric floral traits in nine Iberian populations of bumblebee‐pollinated Helleborus foetidus (Ranunculaceae), this paper attempts to test the general hypothesis that pollinators enhance floral integration and selectively modify phenotypic correlations between functionally linked floral traits. The five floral traits examined exhibited significant phenotypic integration at all populations, and both the magnitude and the pattern of integration differed widely among populations. Variation in extent and pattern of integration was neither distance‐dependent nor significantly related to between‐population variation in taxonomical composition and morphological diversity of the pollinator assemblage. Patterns of floral integration were closer to expectations derived from consideration of developmental affinities between floral whorls than to expectations based on a pollinator‐mediated adaptive hypothesis. Taken together, results of this study suggest that between‐population differences in magnitude and pattern of floral integration in H. foetidus are probably best explained as a consequence of random genetic sampling in the characteristically small and ephemeral populations of this species, rather than reflecting the selective action of current pollinators.     

Online Mendelian Inheritance in Animals (OMIA): a comparative knowledgebase of genetic disorders and other familial traits in non-laboratory animals

Online Mendelian Inheritance in Animals (OMIA) provides up-to-date information on inherited disorders and other familial traits in non-laboratory animals. It is freely available online at http://www.angis.org.au/omia. With a strong emphasis on comparative biology, OMIA is modelled on, and reciprocally hyperlinked with, Online Mendelian Inheritance in Man (OMIM). It provides a comprehensive catalog of animal models of human inherited disorders, and also provides comprehensive access to information on potential human homologues of inherited disorders and traits in animals. Because its whole structure is based on comparative biology, it provides phenotypic information in a format that is complementary to all the relevant mapping and sequence databases now existing or being created across the animal kingdom.     

Integration and Evolvability in Primate Hands and Feet

Morphological integration theory predicts that sets of phenotypic traits that covary strongly due to developmental and/or functional connections between them eventually co-evolve because of a coordinated response to selection, and accordingly become less independently evolvable. This process is not irreversible, however, and phenotypic traits can become less integrated, and hence more independently evolvable, in the context of selection for divergent functions and morphologies. This study examines the reciprocal relationship between shared function, integration and evolvability by comparing integration patterns among serially homologous skeletal elements in the hands and feet of a functionally diverse sample of catarrhine primates. Two hypotheses are tested: (1) species in which the autopods are functionally more similar (e.g. quadrupedal monkeys) have more strongly integrated autopods than species in which the autopods are functionally divergent (e.g. gibbons, humans) and (2) the latter have autopods that are more evolvable, collectively and independently. Morphometric data from selected hand and foot digital rays were used to derive phenotypic variance/covariance matrices. The strength of integration among autopods was quantified using eigenanalysis and a measure of trait variational autonomy. Evolvability was estimated by subjecting phenotypic variance/covariance matrices to simulated random selection gradients, and comparing evolutionary responses among species. Results indicate that integration decreases as hands and feet become functionally divergent, and that the strongly integrated hand and foot skeletons of quadrupedal monkeys respond to selection in a highly collinear manner, even when simulated selective pressures acting on each autopod are in opposite directions in phenotypic space. Results confirm that the evolvability of morphological traits depends largely on how strongly they covary with other traits, but also with body size. The role of pleiotropy as a developmental mechanism underlying integration and evolvability is also discussed.     

Scaling up phenotypic plasticity with hierarchical population models

Individuals respond to different environments by developing different phenotypes, which is generally seen as a mechanism through which individuals can buffer adverse environmental conditions and increase their fitness. To understand the consequences of phenotypic plasticity it is necessary to study how changing a particular trait of an individual affects either its survival, growth, reproduction or a combination of these demographic vital rates (i.e. fitness components). Integrating vital rate changes due to phenotypic plasticity into models of population dynamics allows detailed study of how phenotypic changes scale up to higher levels of integration and forms an excellent tool to distinguish those plastic trait changes that really matter at the population level. A modeling approach also facilitates studying systems that are even more complex: traits and vital rates often co-vary or trade-off with other traits that may show plastic responses over environmental gradients. Here we review recent developments in the literature on population models that attempt to include phenotypic plasticity with a range of evolutionary assumptions and modeling techniques. We present in detail a model framework in which environmental impacts on population dynamics can be followed analytically through direct and indirect pathways that importantly incorporate phenotypic plasticity, trait-trait and trait-vital rate relationships. We illustrate this framework with two case studies: the population-level consequences of phenotypic responses to nutrient enrichment of plant species occurring in nutrient-poor habitats and of responses to changes in flooding regimes due to climate change. We conclude with exciting prospects for further development of this framework: selection analyses, modeling advances and the inclusion of spatial dynamics by considering dispersal traits as well.     

Phenotypic Integration Without Modularity: Testing Hypotheses About the Distribution of Pleiotropic Quantitative Trait Loci in a Continuous Space

Theories of phenotypic integration have relied heavily on the concept of modularity in order to model the ways in which traits in an organism correlate and covary. Recent investigations suggest that, while some functional and developmental processes may be morphologically and ontogenetically localized, and thus modular in a developmental sense, there is a great deal of overlap among these influences on patterns of integration in the adult form. This can result in blurry boundaries between hypothesized modules constructed to test hypotheses about phenotypic integration. This investigation tests hypotheses about the contribution of pleiotropic quantitative trait loci (QTL) to phenotypic integration in the mouse mandible without using a priori categorical hypotheses about which traits constitute a module. We ask two main questions: (1) Are the effects of pleiotropic QTL localized to highly correlated traits or more spread out among traits than one might expect by chance? (2) Does the pattern of trait influence when all pleiotropic QTL are considered together deviate from what we might expect if QTL affect traits without regard for the correlations among traits? We find that a large proportion of pleiotropic QTL affect traits that are more highly correlated than we expect by chance with the remainder having effects that are distributed as if by chance. Furthermore, the overall distribution of the effects of pleiotropic QTL differs significantly from the null distribution of no association between pleiotropic effects on traits and correlations among traits. The main modular hypothesis used by earlier studies often does not predict the distribution of sets of traits sharing a common QTL. These results suggest that there is a clear tendency for pleiotropic effects of QTL to be localized but that the localization may be best thought of as occurring in a continuous space rather being clustered in discrete modules.     

How trophic interaction strength depends on traits

A key problem in community ecology is to understand how individual-level traits give rise to population-level trophic interactions. Here, we propose a synthetic framework based on ecological considerations to address this question systematically. We derive a general functional form for the dependence of trophic interaction coefficients on trophically relevant quantitative traits of consumers and resources. The derived expression encompasses—and thus allows a unified comparison of—several functional forms previously proposed in the literature. Furthermore, we show how a community’s, potentially low-dimens ional, effective trophic niche space is related to its higher-dimensional phenotypic trait space. In this manner, we give ecological meaning to the notion of the “dimensionality of trophic niche space.” Our framework implies a method for directly measuring this dimensionality. We suggest a procedure for estimating the relevant parameters from empirical data and for verifying that such data matches the assumptions underlying our derivation.     

Cranial modularity shifts during mammalian evolution

The mammalian skull has been studied as several separate functional components for decades, but the study of modularity is a more recent, integrative approach toward quantitative examination of independent subsets of highly correlated traits, or modules. Although most studies of modularity focus on developmental and genetic systems, phenotypic modules have been noted in many diverse morphological structures. However, few studies have provided empirical data for comparing modules across higher taxonomic levels, limiting the ability to assess the broader evolutionary significance of modularity. This study uses 18-32 three-dimensional cranial landmarks to analyze phenotypic modularity in 106 mammalian species and demonstrates that cranial modularity is generally conserved in the evolution of therian mammals (marsupials and placentals) but differs between therians and monotremes, the two extant subclasses of Mammalia. Within therians, cluster analyses identify six distinct modules, but only three modules display significant integration in all species. Monotremes display only two highly integrated modules. Specific hypotheses of functional and developmental influences on cranial bones were tested. Theoretical correlation matrices for bones were constructed on the basis of shared function, tissue origin, or mode of ossification, and all three of these models are significantly correlated with observed correlation matrices for the mammalian cranium.     

Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection

Association mapping based on the linkage disequilibrium provides a promising tool to identify genes responsible for quantitative variations underlying complex traits. Presented here is a maize association mapping panel consisting of 155 inbred lines with mainly temperate germplasm, which was phenotyped for 34 traits and genotyped using 82 SSRs and 1,536 SNPs. Abundant phenotypic and genetic diversities were observed within the panel based on the phenotypic and genotypic analysis. A model-based analysis using 82 SSRs assigned all inbred lines to two groups with eight subgroups. The relative kinship matrix was calculated using 884 SNPs with minor allele frequency ≥20% indicating that no or weak relationships were identified for most individual pairs. Three traits (total tocopherol content in maize kernel, plant height and kernel length) and 1,414 SNPs with missing data <20% were used to evaluate the performance of four models for association mapping analysis. For all traits, the model controlling relative kinship (K) performed better than the model controlling population structure (Q), and similarly to the model controlling both population structure and relative kinship (Q + K) in this panel. Our results suggest this maize panel can be used for association mapping analysis targeting multiple agronomic and quality traits with optimal association model.     

A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize

Complex quantitative traits of plants as measured on collections of genotypes across multiple environments are the outcome of processes that depend in intricate ways on genotype and environment simultaneously. For a better understanding of the genetic architecture of such traits as observed across environments, genotype-by-environment interaction should be modeled with statistical models that use explicit information on genotypes and environments. The modeling approach we propose explains genotype-by-environment interaction by differential quantitative trait locus (QTL) expression in relation to environmental variables. We analyzed grain yield and grain moisture for an experimental data set composed of 976 F(5) maize testcross progenies evaluated across 12 environments in the U.S. corn belt during 1994 and 1995. The strategy we used was based on mixed models and started with a phenotypic analysis of multi-environment data, modeling genotype-by-environment interactions and associated genetic correlations between environments, while taking into account intraenvironmental error structures. The phenotypic mixed models were then extended to QTL models via the incorporation of marker information as genotypic covariables. A majority of the detected QTL showed significant QTL-by-environment interactions (QEI). The QEI were further analyzed by including environmental covariates into the mixed model. Most QEI could be understood as differential QTL expression conditional on longitude or year, both consequences of temperature differences during critical stages of the growth.     

Beyond mean allelic effects: A locus at the major color gene MC1R associates also with differing levels of phenotypic and genetic (co)variance for coloration in barn owls

The mean phenotypic effects of a discovered variant help to predict major aspects of the evolution and inheritance of a phenotype. However, differences in the phenotypic variance associated to distinct genotypes are often overlooked despite being suggestive of processes that largely influence phenotypic evolution, such as interactions between the genotypes with the environment or the genetic background. We present empirical evidence for a mutation at the melanocortin‐1‐receptor gene, a major vertebrate coloration gene, affecting phenotypic variance in the barn owl, Tyto alba. The white MC1R allele, which associates with whiter plumage coloration, also associates with a pronounced phenotypic and additive genetic variance for distinct color traits. Contrarily, the rufous allele, associated with a rufous coloration, relates to a lower phenotypic and additive genetic variance, suggesting that this allele may be epistatic over other color loci. Variance differences between genotypes entailed differences in the strength of phenotypic and genetic associations between color traits, suggesting that differences in variance also alter the level of integration between traits. This study highlights that addressing variance differences of genotypes in wild populations provides interesting new insights into the evolutionary mechanisms and the genetic architecture underlying the phenotype.     

Phenotypic integration between claw and toepad traits promotes microhabitat specialization in the Anolis adaptive radiation

The performance of an organism in its environment frequently depends more on its composite phenotype than on individual phenotypic traits. Thus, understanding environmental adaptation requires investigating patterns of covariation across functionally related traits. The replicated adaptive radiations of Greater Antillean Anolis lizards are characterized by ecological and morphological convergence, thus, providing an opportunity to examine the role of multiple phenotypes in microhabitat adaptation. Here, we examine integrated claw and toepad morphological evolution in relation to habitat partitioning across the adaptive radiations of Greater Antillean anoles. Based on analysis of 428 specimens from 57 species, we found that different aspects of claw morphology were associated with different perch dimensions, with claw height positively associated with perch diameter and claw curvature positively associated with perch height. Patterns of integration also varied across claw and toepad traits, likely driven by correlative selection for performance on smoother and rougher substrates. Finally, rates of evolution differed between claw and toepad traits, with claw length evolving faster than all other traits despite having no predicted functional importance. Our results highlight the multivariate nature of phenotypic adaptation and suggest that phenotypic integration across Greater Antillean anoles is driven by fine‐scale correlative selection based on structural habitat specialization.