THE EVOLUTION OF CANALIZATION AND THE BREAKING OF VON BAER'S LAWS: MODELING THE EVOLUTION OF DEVELOPMENT WITH EPISTASIS

Evolution can change the developmental processes underlying a character without changing the average expression of the character itself. This sort of change must occur in both the evolution of canalization, in which a character becomes increasingly buffered against genetic or developmental variation, and in the phenomenon of closely related species that show similar adult phenotypes but different underlying developmental patterns. To study such phenomena, I develop a model that follows evolution on a surface representing adult phenotype as a function of underlying developmental characters. A contour on such a “phenotype landscape” is a set of states of developmental characters that produce the same adult phenotype. Epistasis induces curvature of this surface, and degree of canalization is represented by the slope along a contour. I first discuss the geometric properties of phenotype landscapes, relating epistasis to canalization. I then impose a fitness function on the phenotype and model evolution of developmental characters as a function of the fitness function and the local geometry of the surface. This model shows how canalization evolves as a population approaches an optimum phenotype. It further shows that under some circumstances, “decanalization” can occur, in which the expression of adult phenotype becomes increasingly sensitive to developmental variation. This process can cause very similar populations to diverge from one another developmentally even when their adult phenotypes experience identical selection regimes.     

PERSPECTIVE: COMPLEX ADAPTATIONS AND THE EVOLUTION OF EVOLVABILITY

The problem of complex adaptations is studied in two largely disconnected research traditions: evolutionary biology and evolutionary computer science. This paper summarizes the results from both areas and compares their implications. In evolutionary computer science it was found that the Darwinian process of mutation, recombination and selection is not universally effective in improving complex systems like computer programs or chip designs. For adaptation to occur, these systems must possess “evolvability,” i.e., the ability of random variations to sometimes produce improvement. It was found that evolvability critically depends on the way genetic variation maps onto phenotypic variation, an issue known as the representation problem. The genotype-phenotype map determines the variability of characters, which is the propensity to vary. Variability needs to be distinguished from variations, which are the actually realized differences between individuals. The genotype-phenotype map is the common theme underlying such varied biological phenomena as genetic canalization, developmental constraints, biological versatility, developmental dissociability, and morphological integration. For evolutionary biology the representation problem has important implications: how is it that extant species acquired a genotype-phenotype map which allows improvement by mutation and selection? Is the genotype-phenotype map able to change in evolution? What are the selective forces, if any, that shape the genotype-phenotype map? We propose that the genotype-phenotype map can evolve by two main routes: epistatic mutations, or the creation of new genes. A common result for organismic design is modularity. By modularity we mean a genotype-phenotype map in which there are few pleiotropic effects among characters serving different functions, with pleiotropic effects falling mainly among characters that are part of a single functional complex. Such a design is expected to improve evolvability by limiting the interference between the adaptation of different functions. Several population genetic models are reviewed that are intended to explain the evolutionary origin of a modular design. While our current knowledge is insufficient to assess the plausibility of these models, they form the beginning of a framework for understanding the evolution of the genotype-phenotype map.     

THE LOCI OF REPEATED EVOLUTION: A CATALOG OF GENETIC HOTSPOTS OF PHENOTYPIC VARIATION

What is the nature of the genetic changes underlying phenotypic evolution? We have catalogued 1008 alleles described in the literature that cause phenotypic differences among animals, plants, and yeasts. Surprisingly, evolution of similar traits in distinct lineages often involves mutations in the same gene (“gene reuse”). This compilation yields three important qualitative implications about repeated evolution. First, the apparent evolution of similar traits by gene reuse can be traced back to two alternatives, either several independent causative mutations or a single original mutational event followed by sorting processes. Second, hotspots of evolution—defined as the repeated occurrence of de novo mutations at orthologous loci and causing similar phenotypic variation—are omnipresent in the literature with more than 100 examples covering various levels of analysis, including numerous gain‐of‐function events. Finally, several alleles of large effect have been shown to result from the aggregation of multiple small‐effect mutations at the same hotspot locus, thus reconciling micromutationist theories of adaptation with the empirical observation of large‐effect variants. Although data heterogeneity and experimental biases prevented us from extracting quantitative trends, our synthesis highlights the existence of genetic paths of least resistance leading to viable evolutionary change.     

MEASURING SELECTION AND CONSTRAINT IN THE EVOLUTION OF GROWTH

We present a quantitative genetic model for the evolution of growth trajectories that makes no assumptions about the shapes of growth trajectories that are possible. Evolution of a population's mean growth trajectory is governed by the selection gradient function and the additive genetic covariance function. The selection gradient function is determined by the impact of changes in size on the birth and death rates at different ages, and can be estimated for natural populations. The additive genetic covariance function can also be estimated empirically, as we demonstrate with four vertebrate populations. Using the genetic data from mice, a computer simulation shows that evolution of a growth trajectory can be constrained by the absence of genetic variation for certain changes in the trajectory's shape. These constraints can be visualized with an analysis of the covariance function. Results from four vertebrate populations show that while each has substantial genetic variation for some evolutionary changes in its growth trajectory, most types of changes have little or no variation available. This suggests that constraints may often play an important role in the evolution of growth.     

THE DETERMINATION OF GENETIC COVARIANCES AND PREDICTION OF EVOLUTIONARY TRAJECTORIES BASED ON A GENETIC CORRELATION MATRIX

There is much interest in measuring selection, quantifying evolutionary constraints, and predicting evolutionary trajectories in natural populations. For these studies, genetic (co)variances among fitness traits play a central role. We explore the conditions that determine the sign of genetic covariances and demonstrate a critical role of selection in shaping genetic covariances. In addition, we show that genetic covariance matrices rather than genetic correlation matrices should be characterized and studied in order to infer genetic basis of population differentiation and/or to predict evolutionary trajectories.     

THE MIXED-MODEL ANALYSIS OF VARIANCE APPLIED TO QUANTITATIVE GENETICS: BIOLOGICAL MEANING OF THE PARAMETERS

The mixed-model factorial analysis of variance has been used in many recent studies in evolutionary quantitative genetics. Two competing formulations of the mixed-model ANOVA are commonly used, the “Scheffe” model and the “SAS” model; these models differ in both their assumptions and in the way in which variance components due to the main effect of random factors are defined. The biological meanings of the two variance component definitions have often been unappreciated, however. A full understanding of these meanings leads to the conclusion that the mixed-model ANOVA could have been used to much greater effect by many recent authors. The variance component due to the random main effect under the two-way SAS model is the covariance in true means associated with a level of the random factor (e.g., families) across levels of the fixed factor (e.g., environments). Therefore the SAS model has a natural application for estimating the genetic correlation between a character expressed in different environments and testing whether it differs from zero. The variance component due to the random main effect under the two-way Scheffe model is the variance in marginal means (i.e., means over levels of the fixed factor) among levels of the random factor. Therefore the Scheffe model has a natural application for estimating genetic variances and heritabilities in populations using a defined mixture of environments. Procedures and assumptions necessary for these applications of the models are discussed. While exact significance tests under the SAS model require balanced data and the assumptions that family effects are normally distributed with equal variances in the different environments, the model can be useful even when these conditions are not met (e.g., for providing an unbiased estimate of the across-environment genetic covariance). Contrary to statements in a recent paper, exact significance tests regarding the variance in marginal means as well as unbiased estimates can be readily obtained from unbalanced designs with no restrictive assumptions about the distributions or variance-covariance structure of family effects.     

PHYLOGENETIC ANALYSIS OF THE EVOLUTIONARY CORRELATION USING LIKELIHOOD

Many evolutionary processes can lead to a change in the correlation between continuous characters over time or on different branches of a phylogenetic tree. Shifts in genetic or functional constraint, in the selective regime, or in some combination thereof can influence both the evolution of continuous traits and their relation to each other. These changes can often be mapped on a phylogenetic tree to examine their influence on multivariate phenotypic diversification. We propose a new likelihood method to fit multiple evolutionary rate matrices (also called evolutionary variance–covariance matrices) to species data for two or more continuous characters and a phylogeny. The evolutionary rate matrix is a matrix containing the evolutionary rates for individual characters on its diagonal, and the covariances between characters (of which the evolutionary correlations are a function) elsewhere. To illustrate our approach, we apply the method to an empirical dataset consisting of two features of feeding morphology sampled from 28 centrarchid fish species, as well as to data generated via phylogenetic numerical simulations. We find that the method has appropriate type I error, power, and parameter estimation. The approach presented herein is the first to allow for the explicit testing of how and when the evolutionary covariances between characters have changed in the history of a group.     

MODELING STABILIZING SELECTION: EXPANDING THE ORNSTEIN-UHLENBECK MODEL OF ADAPTIVE EVOLUTION

Comparative methods used to study patterns of evolutionary change in a continuous trait on a phylogeny range from Brownian motion processes to models where the trait is assumed to evolve according to an Ornstein-Uhlenbeck (OU) process. Although these models have proved useful in a variety of contexts, they still do not cover all the scenarios biologists want to examine. For models based on the OU process, model complexity is restricted in current implementations by assuming that the rate of stochastic motion and the strength of selection do not vary among selective regimes. Here, we expand the OU model of adaptive evolution to include models that variously relax the assumption of a constant rate and strength of selection. In its most general form, the methods described here can assign each selective regime a separate trait optimum, a rate of stochastic motion parameter, and a parameter for the strength of selection. We use simulations to show that our models can detect meaningful differences in the evolutionary process, especially with larger sample sizes. We also illustrate our method using an empirical example of genome size evolution within a large flowering plant clade.     

GENETIC CONSTRAINTS ON MACROEVOLUTION: THE EVOLUTION OF HOST AFFILIATION IN THE LEAF BEETLE GENUS OPHRAELLA

We hypothesize that the evolution of an ecologically important character, the host associations of specialized phytophagous insects, has been influenced by limitations on genetic variation. Using as a historical framework a phylogenetic reconstruction of the history of host associations in the beetle genus Ophraella (Chrysomelidae), we have employed quantitative-genetic methods to screen four species for genetic variation in larval survival, oviposition (in one species only), and feeding responses to their congeners' host plants, in the Asteraceae. We here report results of studies of one species and evaluate the results from all four. Analysis of half-sib/full-sib families and of progenies of wild females of O. notulata, a specialist on Iva (Ambrosiinae), provided evidence of genetic variation in larval consumption of five of six test plants and in adult consumption of four of six. Larval mortality was complete on five plants; only on Ambrosia, a close relative of the natural host, was there appreciable, and genetically variable, survival. Oviposition on Ambrosia showed marginally significant evidence of genetic variation; a more distantly related plant elicited no oviposition at all. In compiling results from four Ophraella species, reported in this and two other papers, we found no evidence of genetic variation in 18 of 39 tests of feeding responses and 14 of 16 tests of larval survival on congeners' hosts. This result is consistent with the hypothesis that absence or paucity of genetic variation may constrain or at least bias the evolution of host associations. The lower incidence of genetic variation in survival than in feeding behavior may imply, according to recent models, that avoidance is a more common evolutionary response to novel plants than adaptation. The usually great disparity between mean performance on congeners' hosts and the species' natural hosts, and an almost complete lack of evidence for negative genetic correlations, argue against the likelihood that speciation has occurred by sympatric host shift. The presence versus apparent absence of genetic variation in consumption was correlated with the propinquity of relationship between the beetle species tested and the species that normally feeds on the test plant, suggesting that the history of host shifts in Ophraella has been guided in part by restrictions on genetic variation. It was also correlated with the propinquity of relationship between a test plant and the beetle's natural host. The contributions of plant relationships and insect relationships, themselves correlated in part, to the pattern of genetic variation, are not readily distinguishable, but together accord with phylogenetic evidence that these and other phytophagous insects adapt most readily to related plants. In this instance, therefore, the macroevolution of an ecologically important character appears to have been influenced by genetic constraints. We hypothesize that absence of the structural prerequisites for genetic variation in complex characters may affect genetic variation and the trajectory of evolution.     

THE EVOLUTION OF ASYMMETRY IN SEXUAL ISOLATION: A MODEL AND A TEST CASE

We constructed a model for the evolution of sexual isolation by extending Lande's (1981) model of sexual selection. The model predicts that asymmetric sexual isolation is a transient phenomenon, characteristic of intermediate stages of divergence in sexually selected traits. Unlike the Kaneshiro (1976, 1980) proposal, our model does not depend upon drift and the loss of courtship elements to produce asymmetries in sexual isolation. According to our model, the direction of evolution cannot be predicted from asymmetry in sexual isolation. We tested some features of the model using data from an experimental study of sexual isolation in the salamander Desmognathus ochrophaeus. We tested for sexual isolation between 12 allopatric populations and found significant asymmetry in sexual isolation in about a quarter of the test cases. The highest degrees of asymmetry were associated with intermediate levels of divergence. A curvilinear relationship between isolation asymmetry and divergence was predicted by our model and was supported by statistical analysis of the salamander data.     

TRANSLATING BETWEEN MICROEVOLUTIONARY PROCESS AND MACROEVOLUTIONARY PATTERNS: THE CORRELATION STRUCTURE OF INTERSPECIFIC DATA

As species evolve along a phylogenetic tree, we expect closely related species to retain some phenotypic similarities due to their shared evolutionary histories. The amount of expected similarity depends both on the hierarchical phylogenetic structure, and on the specific magnitude and types of evolutionary changes that accumulate during each generation. In this study, we show how models of microevolutionary change can be translated into the resulting macroevolutionary patterns. We illustrate how the structure of phenotypic covariances expected in interspecific measurements can be derived, and how this structure depends on the microevolutionary forces guiding phenotypic change at each generation. We then explore the covariance structure expected from several simple microevolutionary models of phenotypic evolution, including various combinations of random genetic drift, directional selection, stabilizing selection, and environmental change, as well as models of punctuated or burst-like evolution. We find that stabilizing selection leads to patterns of exponential decrease of between species covariance with phylogenetic distance. This is different from the usual linear patterns of decrease assumed in most comparative and systematic methods. Nevertheless, linear patterns of decrease can result from many processes in addition to random genetic drift, such as directional and fluctuating selection as well as modes of punctuated change. Our framework can be used to develop methods for (1) phylogenetic reconstruction; (2) inference of the evolutionary process from comparative data; and (3) conducting or evaluating statistical analyses of comparative data while taking phylogenetic history into account.     

5_S rRNA分子进化的研究

截至目前为止,人们已测出了300余种5SrRNA分子的一级结构。本文在其中选择了具有代表性的脊椎动物、无脊椎动物、原生动物以及植物和细菌等共130个种的5SrRNA一级结构,通过运用分子进化研究中的“今祖法”,在TRS—80型微机上,进行了比较和计算,作出了相应的系统树,并得到了与其它一些研究结果基本一致的结论。同时,讨论了分子进化的研究本身以及“今祖法”在分子进化研究中的问题和局限性。     

EVOLUTION OF SPRINT SPEED IN LACERTID LIZARDS: MORPHOLOGICAL,PHYSIOLOGICAL, AND BEHAVIORAL COVARIATION

Organismal performance abilities occupy a central position in phenotypic evolution; they are determined by suites of interacting lower-level traits (e.g., morphology and physiology) and they are a primary focus of natural selection. The mechanisms by which higher levels of organismal performance are achieved during evolution are therefore fundamentally important for understanding correlated evolution in general and coadaptation in particular. Here we address correlated evolution of morphological, physiological, and behavioral characteristics that influence interspecific variation in sprint speed in a clade of lacertid lizards. Phylogenetic analyses using independent contrasts indicate that the evolution of high maximum sprinting abilities (measured on a photocell-timed racetrack) has occurred via the evolution of (1) longer hind limbs relative to body size, and (2) a higher physiologically optimum temperature for sprinting. For ectotherms, which experience variable body temperatures while active, sprinting abilities in nature depend on both maximum capacities and relative performance levels (i.e., percent of maximum) that can be attained. With respect to temperature effects, relative performance levels are determined by the interaction between thermal physiology and thermoregulatory behavior. Among the 13 species or subspecies of lizards in the present study, differences in the optimal temperature for sprinting (body temperature at which lizards run fastest) closely matched interspecific variation in median preferred body temperature (measured in a laboratory photothermal gradient), indicating correlated evolution of thermal physiology and thermal preferences. Variability of the preferred body temperatures maintained by each species is, across species, negatively correlated with the thermal-performance breadth (range of body temperatures over which lizards can run relatively fast). This pattern leads to interspecific differences in the levels of relative sprint speed that lizards are predicted to attain while active at their preferred temperatures. The highest levels of predicted relative performance are achieved by species that combine a narrow, precise distribution of preferred temperatures with the ability to sprint at near-maximum speeds over a wide range of body temperatures. The observed among-species differences in predicted relative speed were positively correlated with the interspecific variation in maximum sprinting capacities. Thus, species that attain the highest maximum speeds are (1) also able to run at near-maximum levels over a wide range of temperatures and (2) also maintain body temperatures within a narrow zone near the optimal temperature for sprinting. The observed pattern of correlated evolution therefore has involved traits at distinct levels of biological organization, that is, morphology, physiology, and behavior; and trade-offs are not evident. We hypothesize that this particular trait combination has evolved in response to coadaptational selection pressures. We also discuss our results in the context of possible evolutionary responses to global climatic change.     

TESTING FOR UNEQUAL AMOUNTS OF EVOLUTION IN A CONTINUOUS CHARACTER ON DIFFERENT BRANCHES OF A PHYLOGENETIC TREE USING LINEAR AND SQUARED-CHANGE PARSIMONY: AN EXAMPLE USING LESSER ANTILLEAN ANOLIS LIZARDS

Although a large body of work investigating tests of correlated evolution of two continuous characters exists, hypotheses such as character displacement are really tests of whether substantial evolutionary change has occurred on a particular branch or branches of the phylogenetic tree. In this study, we present a methodology for testing such a hypothesis using ancestral character state reconstruction and simulation. Furthermore, we suggest how to investigate the robustness of the hypothesis test by varying the reconstruction methods or simulation parameters. As a case study, we tested a hypothesis of character displacement in body size of Caribbean Anolis lizards. We compared squared-change, weighted squared-change, and linear parsimony reconstruction methods, gradual Brownian motion and speciational models of evolution, and several resolution methods for linear parsimony. We used ancestor reconstruction methods to infer the amount of body size evolution, and tested whether evolutionary change in body size was greater on branches of the phylogenetic tree in which a transition from occupying a single-species island to a two-species island occurred. Simulations were used to generate null distributions of reconstructed body size change. The hypothesis of character displacement was tested using Wilcoxon Rank-Sums. When tested against simulated null distributions, all of the reconstruction methods resulted in more significant P-values than when standard statistical tables were used. These results confirm that P-values for tests using ancestor reconstruction methods should be assessed via simulation rather than from standard statistical tables. Linear parsimony can produce an infinite number of most parsimonious reconstructions in continuous characters. We present an example of assessing the robustness of our statistical test by exploring the sample space of possible resolutions. We compare ACCTRAN and DELTRAN resolutions of ambiguous character reconstructions in linear parsimony to the most and least conservative resolutions for our particular hypothesis.     

EVOLUTION IN FLUCTUATING ENVIRONMENTS: DECOMPOSING SELECTION INTO ADDITIVE COMPONENTS OF THE ROBERTSON–PRICE EQUATION

We analyze the stochastic components of the Robertson–Price equation for the evolution of quantitative characters that enables decomposition of the selection differential into components due to demographic and environmental stochasticity. We show how these two types of stochasticity affect the evolution of multivariate quantitative characters by defining demographic and environmental variances as components of individual fitness. The exact covariance formula for selection is decomposed into three components, the deterministic mean value, as well as stochastic demographic and environmental components. We show that demographic and environmental stochasticity generate random genetic drift and fluctuating selection, respectively. This provides a common theoretical framework for linking ecological and evolutionary processes. Demographic stochasticity can cause random variation in selection differentials independent of fluctuating selection caused by environmental variation. We use this model of selection to illustrate that the effect on the expected selection differential of random variation in individual fitness is dependent on population size, and that the strength of fluctuating selection is affected by how environmental variation affects the covariance in Malthusian fitness between individuals with different phenotypes. Thus, our approach enables us to partition out the effects of fluctuating selection from the effects of selection due to random variation in individual fitness caused by demographic stochasticity.     

FISHER'S MODEL AND THE GENOMICS OF ADAPTATION: RESTRICTED PLEIOTROPY,HETEROGENOUS MUTATION,AND PARALLEL EVOLUTION

Genetic theories of adaptation generally overlook the genes in which beneficial substitutions occur, and the likely variation in their mutational effects. We investigate the consequences of heterogeneous mutational effects among loci on the genetics of adaptation. We use a generalization of Fisher's geometrical model, which assumes multivariate Gaussian stabilizing selection on multiple characters. In our model, mutation has a distinct variance–covariance matrix of phenotypic effects for each locus. Consequently, the distribution of selection coefficients s varies across loci. We assume each locus can only affect a limited number of independent linear combinations of phenotypic traits (restricted pleiotropy), which differ among loci, an effect we term “orientation heterogeneity.” Restricted pleiotropy can sharply reduce the overall proportion of beneficial mutations. Orientation heterogeneity has little impact on the shape of the genomic distribution, but can substantially increase the probability of parallel evolution (the repeated fixation of beneficial mutations at the same gene in independent populations), which is highest with low pleiotropy. We also consider variation in the degree of pleiotropy and in the mean s across loci. The latter impacts the genomic distribution of s, but has a much milder effect on parallel evolution. We discuss these results in the light of evolution experiments.     

MATERNAL INHERITANCE AND ITS EFFECT ON ADAPTIVE EVOLUTION: A QUANTITATIVE GENETIC ANALYSIS OF MATERNAL EFFECTS IN A NATURAL PLANT POPULATION

A mother can influence a trait in her offspring both by the genes she transmits (Mendelian inheritance) and by maternal attributes that directly affect that trait in her offspring (maternal inheritance). Maternal inheritance can alter the direction, rate, and duration of adaptive evolution from standard Mendelian models and its impact on adaptive evolution is virtually unexplored in natural populations. In a hierarchical quantitative genetic analysis to determine the magnitude and structure of maternal inheritance in the winter annual plant, Collinsia verna, I consider three potential models of inheritance. These range from a standard Mendelian model estimating only direct (i.e., Mendelian) additive and environmental variance components to a maternal inheritance model estimating six additive and environmental variance components: direct additive and environmental variances; maternal additive and environmental variances; and the direct-maternal additive () and environmental covariances. The structure of maternal inheritance differs among the 10 traits considered at four stages in the life cycle. Early in the life cycle, seed weight and embryo weight display substantial , a negative , and a positive . Subsequently, cotyledon diameter displays and of roughly the same magnitude and negative . For fall rosettes, leaf number and length are best described by a Mendelian model. In the spring, leaf length displays maternal inheritance with significant and and a negative . All maternally inherited traits show significant negative . Predicted response to selection under maternal inheritance depends on and as well as . Negative results in predicted responses in the opposite direction to selection for seed weight and embryo weight and predicted responses near zero for all subsequent maternally inherited traits. Maternal inheritance persists through the life cycle of this annual plant for a number of size-related traits and will alter the direction and rate of evolutionary response in this population.     

THE QUANTITATIVE AND MOLECULAR GENETIC ARCHITECTURE OF A SUBDIVIDED SPECIES

In an effort to elucidate the evolutionary mechanisms that determine the genetic architecture of a species, we have analyzed 17 populations of the microcrustacean Daphnia pulex for levels of genetic variation at the level of life-history characters and molecular markers in the nuclear and mitochondrial genomes. This species is highly subdivided, with approximately 30% of the variation for nuclear molecular markers and 50% of the variation for mitochondrial markers being distributed among populations. The average level of genetic subdivision for quantitative traits is essentially the same as that for nuclear markers, which superficially suggests that the life-history characters are diverging at the neutral rate. However, the existence of a strong correlation between the levels of population subdivision and broadsense heritabilities of individual traits argues against this interpretation, suggesting instead that the among-population divergence of some quantitative traits (most notably body size) is being driven by local adaptation to different environments. The fact that the mean phenotypes of the individual populations are also strongly correlated with local levels of homozygosity indicates that variation in local inbreeding plays a role in population differentiation. Rather than being a passive consequence of local founder effects, levels of homozygosity may be selected for directly for their effects on the phenotype (adaptive inbreeding depression). There is no relationship between the levels of variation within populations for molecular markers and quantitative characters, and this is explained by the fact that the average standing genetic variation for life-history characters in this species is equivalent to only 33 generations of variation generated by mutation.     

THE QUANTITATIVE GENETICS AND COEVOLUTION OF MALE AND FEMALE REPRODUCTIVE TRAITS

Studies of experimental sexual selection have tested the effect of variation in the intensity of sexual selection on male investment in reproduction, particularly sperm. However, in several species, including Drosophila pseudoobscura, no sperm response to experimental evolution has occurred. Here, we take a quantitative genetics approach to examine whether genetic constraints explain the limited evolutionary response. We quantified direct and indirect genetic variation, and genetic correlations within and between the sexes, in experimental populations of D. pseudoobscura. We found that sperm number may be limited by low heritability and evolvability whereas sperm quality (length) has moderate V_A and CV_A but does not evolve. Likewise, the female reproductive tract, suggested to drive the evolution of sperm, did not respond to experimental sexual selection even though there was sufficient genetic variation. The lack of genetic correlations between the sexes supports the opportunity for sexual conflict over investment in sperm by males and their storage by females. Our results suggest no absolute constraint arising from a lack of direct or indirect genetic variation or patterns of genetic covariation. These patterns show why responses to experimental evolution are hard to predict, and why research on genetic variation underlying interacting reproductive traits is needed.