Detecting patterns of correlational selection with sampling error: A simulation study.

The adoption of a multivariate perspective of selection implies the existence of multivariate adaptive peaks and pervasive correlational selection that promotes co-adaptation between traits. However, to test for the ubiquity of correlational selection in nature, we must first have a sense of how well can we estimate multivariate nonlinear selection (i.e., the γ-matrix) in the face of sampling error. To explore the sampling properties of estimated γ-matrices, we simulated inidividual traits and fitness under a wide range of sample sizes, using different strengths of correlational selection and of stabilizing selection, combined with different number of traits under selection, different amounts of residual variance in fitness, and distinct patterns of selection. We then ran nonlinear regressions with these simulated datasets to simulate γ-matrices after adding random error to individual fitness. To test how well could we detect the imposed pattern of correlational selection at different sample sizes, we measured the similarity between simulated and imposed γ-matrices. We show that detection of the pattern of correlational selection is highly dependent on the total strength of selection on traits and on the amount of residual variance in fitness. Minimum sample size needs to be at least 500 to precisely estimate the pattern of correlational selection. Furthermore, a pattern of selection in which different sets of traits contribute to different functions is the easiest to diagnose, even when using a large number of traits (10 traits), but with sample sizes in the order of 1000 individuals. Consequently, we recommend working with sets of traits from distinct functional complexes and fitness proxies less prone to effects of environmental and demographic stochasticity to test for correlational selection with lower sample sizes.

Correlational selection in the age of genomics.

Ecologists and evolutionary biologists are well aware that natural and sexual selection do not operate on traits in isolation, but instead act on combinations of traits. This long-recognized and pervasive phenomenon is known as multivariate selection, or-in the particular case where it favours correlations between interacting traits-correlational selection. Despite broad acknowledgement of correlational selection, the relevant theory has often been overlooked in genomic research. Here, we discuss theory and empirical findings from ecological, quantitative genetic and genomic research, linking key insights from different fields. Correlational selection can operate on both discrete trait combinations and quantitative characters, with profound implications for genomic architecture, linkage, pleiotropy, evolvability, modularity, phenotypic integration and phenotypic plasticity. We synthesize current knowledge and discuss promising research approaches that will enable us to understand how correlational selection shapes genomic architecture, thereby linking quantitative genetic approaches with emerging genomic methods. We suggest that research on correlational selection has great potential to integrate multiple fields in evolutionary biology, including developmental and functional biology, ecology, quantitative genetics, phenotypic polymorphisms, hybrid zones and speciation processes.

The Effects of Epistasis and Pleiotropy on Genome-Wide Scans for Adaptive Outlier Loci.

With the advent of next-generation sequencing approaches, the search for individual loci underlying local adaptation has become a major enterprise in evolutionary biology. One promising method to identify such loci is to examine genome-wide patterns of differentiation, using an FST-outlier approach. The effects of pleiotropy and epistasis on this approach are not yet known. Here, we model 2 populations of a sexually reproducing, diploid organism with 2 quantitative traits, one of which is involved in local adaptation. We consider genetic architectures with and without pleiotropy and epistasis. We also model neutral marker loci on an explicit genetic map as the 2 populations diverge and apply FST outlier approaches to determine the extent to which quantitative trait loci (QTL) are detectable. Our results show, under a wide range of conditions, that only a small number of QTL are typically responsible for most of the trait divergence between populations, even when inheritance is highly polygenic. We find that the loci making the largest contributions to trait divergence tend to be detectable outliers. These loci also make the largest contributions to within-population genetic variance. The addition of pleiotropy reduces the extent to which quantitative traits can evolve independently but does not reduce the efficacy of outlier scans. The addition of epistasis, however, reduces the mean FST values for causative QTL, making these loci more difficult, but not impossible, to detect in outlier scans.

The G-matrix Simulator Family: Software for Research and Teaching.

Genetic variation plays a fundamental role in all models of evolution. For phenotypes composed of multiple quantitative traits, genetic variation is best quantified as additive genetic variances and covariances, as these values determine the rate and trajectory of evolution. Additive genetic variances and covariances are often summarized conveniently in the G-matrix, which has additive genetic variances for each trait on the diagonal and additive genetic covariances as its off-diagonal elements. The evolution of the G-matrix is an interesting topic in its own right, because the processes that affect trait means also affect the distribution of standing genetic variation, which, in turn, feeds back to affect the rate of change of trait means. Theoretical studies of the G-matrix have profitably employed simulation-based models because the topic is often too complex to yield meaningful analytical results. Here, we present a series of G-matrix simulation software packages, which have emerged from about 15 years of research on this topic. These simulation models are useful for research and for building intuition regarding the evolution of the G-matrix under a wide variety of circumstances. A tutorial and source code also provide a foundation upon which future models can be built. These tools will be useful to students as well as researchers.

Can the Fisher-Lande Process Account for Birds of Paradise and Other Sexual Radiations?

Models of the Fisher-Lande process (FLP) have been used successfully to explore many aspects of evolution by sexual selection. Despite this success, quantitative tests of these models using data from sexual radiations are rare. Consequently, we do not know whether realistic versions of the FLP can account for the extent and the rate of evolution of sexually selected traits. To answer this question, we generalize the basic FLP model of sexual coevolution and compare predictions of that basic model with patterns observed in an iconic sexual radiation, birds of paradise. Our model tracks the coevolution of male and female traits (two in each sex) while relaxing some restrictive assumptions. Using computer simulations, we evaluate the behavior of the model and confirm that it is an Ornstein-Uhlenbeck (OU) process. We also assess the ability of the FLP to account for the quantitative aspects of ornament evolution in the genus Paradisaea using published measurements of display traits and a phylogeny of the genus. Finally, we use the program OUwie to compare model fits to generic OU and Brownian motion processes and to estimate FLP parameters. We show that to explain the sexual radiation of the genus Paradisaea one must either invoke extremely weak stabilizing selection on female mating preferences or allow the preference optimum to undergo Brownian motion at a modest rate.

Epistasis and natural selection shape the mutational architecture of complex traits.

The evolutionary trajectories of complex traits are constrained by levels of genetic variation as well as genetic correlations among traits. As the ultimate source of all genetic variation is mutation, the distribution of mutations entering populations profoundly affects standing variation and genetic correlations. Here we use an individual-based simulation model to investigate how natural selection and gene interactions (that is, epistasis) shape the evolution of mutational processes affecting complex traits. We find that the presence of epistasis allows natural selection to mould the distribution of mutations, such that mutational effects align with the selection surface. Consequently, novel mutations tend to be more compatible with the current forces of selection acting on the population. These results suggest that in many cases mutational effects should be seen as an outcome of natural selection rather than as an unbiased source of genetic variation that is independent of other evolutionary processes.

Phenotypic evolution: the ongoing synthesis (American Society of Naturalists address).

I explore the proposition that evolutionary biology is currently in the midst of its greatest period of synthesis. This period, which I call the Ongoing Synthesis, began in 1963 and continues at the present time. I use analysis of citations, conduct, and content to compare the Ongoing Synthesis to widely recognized periods of synthesis in the nineteenth and twentieth centuries. To compare content, I focus on phenotypic evolution and compare current efforts with George Gaylord Simpson's struggle to understand evolution in deep geological time. The essence of current effort is captured by the question, What is the best model for phenotypic evolution? Although many investigators are actively engaged in answering this question, I single out two examples of my own collaborative work for emphasis here. These two studies share three important characteristics: diagnosis of evolutionary pattern using massive data sets, validation of model parameter values using compilations of estimates (e.g., heritability, stabilizing selection, distance to an intermediate optimum), and identification of evolutionary process using alternative models of stochastic evolution. Our primary findings (discovery of the blunderbuss pattern and the result that rare bursts of evolution carry lineages out of established adaptive zones) compare favorably with important insights from the Modern Synthesis.

Concurrent speciation in the eastern woodland salamanders (Genus Plethodon): DNA sequences of the complete albumin nuclear and partial mitochondrial 12s genes.

Salamanders of the North American plethodontid genus Plethodon are important model organisms in a variety of studies that depend on a phylogenetic framework (e.g., chemical communication, ecological competition, life histories, hybridization, and speciation), and consequently their systematics has been intensively investigated over several decades. Nevertheless, we lack a synthesis of relationships among the species. In the analyses reported here we use new DNA sequence data from the complete nuclear albumin gene (1818 bp) and the 12s mitochondrial gene (355 bp), as well as published data for four other genes (Wiens et al., 2006), up to a total of 6989 bp, to infer relationships. We relate these results to past systematic work based on morphology, allozymes, and DNA sequences. Although basal relationships show a strong consensus across studies, many terminal relationships remain in flux despite substantial sequencing and other molecular and morphological studies. This systematic instability appears to be a consequence of contemporaneous bursts of speciation in the late Miocene and Pliocene, yielding many closely related extant species in each of the four eastern species groups. Therefore we conclude that many relationships are likely to remain poorly resolved in the face of additional sequencing efforts. On the other hand, the current classification of the 45 eastern species into four species groups is supported. The Plethodon cinereus group (10 species) is the sister group to the clade comprising the other three groups, but these latter groups (Plethodon glutinosus [28 species], Plethodon welleri [5 species], and Plethodon wehrlei [2 species]) probably diverged from each other at approximately the same time.

Expression of vomeronasal receptors and related signaling molecules in the nasal cavity of a caudate amphibian (Plethodon shermani).

G-protein-coupled receptors are responsible for binding to chemosensory cues and initiating responses in vertebrate olfactory neurons. We investigated the genetic diversity and expression of one family of G-protein-coupled receptors in a terrestrial caudate amphibian (the red-legged salamander, Plethodon shermani). We used degenerate RT-PCR to isolate vomeronasal type 2 receptors (V2Rs)--including full-length sequences--and compared them with other vertebrate V2Rs with phylogenetic analyses. We also amplified a salamander Golf, a G-protein usually expressed in the main olfactory epithelium (MOE) of vertebrates, and an ion channel expressed in the rodent vomeronasal organ: trpc2. We then localized mRNA expression of V2Rs, trpc2, and Golf in the olfactory and vomeronasal epithelia with in situ hybridization. The mRNA transcripts of V2Rs and trpc2 were detected solely in the vomeronasal epithelium of P. shermani. Furthermore, there were differences in the density of cells that expressed particular subclasses of V2Rs: 2 probes showed sexually dimorphic expression, whereas a third did not. Although Golf mRNA was expressed primarily in the MOE, Golf transcripts also were found in the vomeronasal epithelium. Thus, some aspects of mRNA expression of vomeronasal receptors and related molecules differ between salamanders and frogs, and between salamanders and mice.

Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories.

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (lambda(s)) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on lambda(s). The magnitude of variation in the proportion of gravid females and its effect on lambda(s) was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on lambda(s) was 4 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution.

The million-year wait for macroevolutionary bursts.

We lack a comprehensive understanding of evolutionary pattern and process because short-term and long-term data have rarely been combined into a single analytical framework. Here we test alternative models of phenotypic evolution using a dataset of unprecedented size and temporal span (over 8,000 data points). The data are body-size measurements taken from historical studies, the fossil record, and among-species comparative data representing mammals, squamates, and birds. By analyzing this large dataset, we identify stochastic models that can explain evolutionary patterns on both short and long timescales and reveal a remarkably consistent pattern in the timing of divergence across taxonomic groups. Even though rapid, short-term evolution often occurs in intervals shorter than 1 Myr, the changes are constrained and do not accumulate over time. Over longer intervals (1-360 Myr), this pattern of bounded evolution yields to a pattern of increasing divergence with time. The best-fitting model to explain this pattern is a model that combines rare but substantial bursts of phenotypic change with bounded fluctuations on shorter timescales. We suggest that these rare bursts reflect permanent changes in adaptive zones, whereas the short-term fluctuations represent local variations in niche optima due to restricted environmental variation within a stable adaptive zone.

Characterization of two putative cytokine receptors, gp130 and ciliary neurotrophic factor receptor, from terrestrial salamanders.

Cytokines of the gp130 family are fundamental regulators of immune responses and signal through multimeric receptors to initiate intracellular second-messenger cascades. Here, we provide the first characterization of two full-length gp130 cytokine receptors from the cDNA of the red-legged salamander (Plethodon shermani). The first, gp130 (2745 bp), is a common signaling receptor for several multi-functional cytokines in vertebrates. We also isolated the full-length (1104 bp) sequence of the ciliary neurotrophic factor receptor (CNTFR), which forms a heteromeric signaling complex with gp130. The open reading frames of both receptors were predicted to contain many of the conserved features found in mammalian gp130s, such as cytokine binding homology regions and residues known to form disulfide bonds. Finally, we used RT-PCR to show that gp130 and CNTFR were expressed in most P. shermani tissues, including brain, intestine and muscle. The expression profiles, along with the structural predictions, show that gp130, CNTFR, and their cytokine ligands are parts of the immune system of P. shermani and other caudate amphibians.

Dimensionality of mate choice, sexual isolation, and speciation.

Multiple cues, across multiple sensory modalities, are involved in mate choice in a wide range of animal taxa. This multiplicity leads to the prediction that, in adaptive radiations, sexual isolation results from divergence in multiple dimensions. However, difficulties in directly measuring preferences and detecting multiple effects limit our ability to empirically assess the number of independent traits contributing to mate choice and sexual isolation. We present an approach to estimate the dimensionality of sexual isolation using mating trials across groups of related populations. We analyze nine radiations: seven in fruit flies (Drosophila) and one each in salamanders (Desmognathus) and cichlid fishes (Pseudotropheus). We find strong evidence that multiple latent traits--linear combinations of phenotypic traits and preferences--are responsible for the patterns of sexual isolation in all nine radiations but that dimensionality has a strong upper limit. Just two latent traits are implicated in the majority of cases. Mapping along latent trait axes tests predictions of sexual-selection models and allows correlation with specific phenotypic traits and functional components of mate choice. We find support for the role of stabilizing natural selection on the sexually selected (male) traits. In the cichlids, latent-trait axes incorporate male-coloration patterns and exhibit convergence as well as divergence among populations. In the salamanders, temporal patterning in sensory modalities and male vs. female preferences are reflected in different latent-trait axes.

A test of the conjecture that G-matrices are more stable than B-matrices.

The G-matrix occupies an important position in evolutionary biology both as a summary of the inheritance of quantitative traits and as an ingredient in predicting how those traits will respond to selection and drift. Consequently, the stability of G has an important bearing on the accuracy of predicted evolutionary trajectories. Furthermore, G should evolve in response to stable features of the adaptive landscape and their trajectories through time. Although the stability and evolution of G might be predicted from knowledge of selection in natural populations, most empirical comparisons of G-matrices have been made in the absence of such a priori predictions. We present a theoretical argument that within-sex G-matrices should be more stable than between-sex B-matrices because they are more powerfully exposed to multivariate stabilizing selection. We tested this conjecture by comparing estimates of B- and within-sex G-matrices among three populations of the garter snake Thamnophis elegans. Matrix comparisons using Flury's hierarchical approach revealed that within-sex G-matrices had four principal components in common (full CPC), whereas B-matrices had only a single principal component in common and eigenvalues that were more variable among populations. These results suggest that within-sex G is more stable than B, as predicted by our theoretical argument.

Rapid evolution of plethodontid modulating factor, a hypervariable salamander courtship pheromone, is driven by positive selection.

Sexual communication in plethodontid salamanders is mediated by a proteinaceous pheromone that a male delivers to a female during courtship, boosting her receptivity. The pheromone consists of three proteins from three unrelated protein families. These proteins are among a small group of pheromones known to affect female receptivity in vertebrates. Previously, we showed that the genes of two of these proteins (PRF and SPF) are prone to incessant evolution driven by positive selection, presumably as a consequence of coevolution with female receptors. In this report, we focus on the evolution of the third pheromone protein gene family, plethodontid modulating factor (PMF), to determine whether it shows the same pattern of diversification. We used RT-PCR in mental gland cDNA to survey PMF sequences from three genera of plethodontid salamanders (27 spp.) to measure rates of evolution, level of gene diversification, modes of selection, and types of amino acid substitution. Like PRF and SPF, PMF is produced by a multigene family characterized by gene duplication and high levels of polymorphism. PMF evolution is rapid, incessant, and driven by positive selection. PMF is more extreme in these dimensions than both PRF and SPF. Nestled within this extraordinary variation, however, is a signature of purifying selection, acting to preserve important structural and biochemical features of the PMF protein (i.e., secretion signal, cysteine residues, and pI). Although a pattern of persistent diversification exists at the molecular level, the morphological and behavioral aspects of the pheromone delivery system show evolutionary stasis over millions of years.

Evolutionary shifts in courtship pheromone composition revealed by EST analysis of plethodontid salamander mental glands.

Courtship behavior in salamanders of the family Plethodontidae can last more than an hour. During courtship, males use stereotyped behaviors to repeatedly deliver a variety of proteinaceous pheromones to the female. These pheromones are produced and released from a specialized gland on the male's chin (the mental gland). Several pheromone components are well characterized and represented by high frequency transcripts in cDNA pools derived from plethodontid mental glands. However, evolutionary trends in the overall composition of the pheromonal signal are poorly understood. To address this issue, we used random sequencing to survey the pheromone composition of the mental gland in a representative species from each of three distantly related plethodontid genera. We analyzed 856 high-quality expressed sequence tags (ESTs) derived from unamplified primary cDNA libraries constructed from mental glands of Desmognathus ocoee, Eurycea guttolineata, and Plethodon shermani. We found marked differences among these species in the transcript frequency for three previously identified, functional pheromone components: Plethodontid Receptivity Factor (PRF), Sodefrin Precursor-Like Factor (SPF), and Plethodontid Modulating Factor (PMF). In P. shermani mental glands, transcripts predominately encoded PMF (45% of all ESTs) and PRF (15%), with less than 0.5% SPF. In contrast, in D. ocoee and E. guttolineata the proportions were approximately 20% SPF, 5% PMF, and PRF was absent. For both D. ocoee and E. guttolineata, peptide hormone-like transcripts occur at high frequency and may encode peptides that change the physiological state of the female, influencing the female's likelihood to complete courtship. These and previous results indicate that the evolution of courtship pheromones in the Plethodontidae is dynamic, contrasting with the predominant mode of evolutionary stasis for courtship behavior and morphology.

Drift promotes speciation by sexual selection.

Quantitative genetic models of sexual selection have generally failed to provide a direct connection to speciation and to explore the consequences of finite population size. The connection to speciation has been indirect because the models have treated only the evolution of male and female traits and have stopped short of modeling the evolution of sexual isolation. In this article we extend Lande's (1981) model of sexual selection to quantify predictions about the evolution of sexual isolation and speciation. Our results, based on computer simulations, support and extend Lande's claim that drift along a line of equilibria can rapidly lead to sexual isolation and speciation. Furthermore, we show that rapid speciation can occur by drift in populations of appreciable size (N(e) >or= 1000). These results are in sharp contrast to the opinion of many researchers and textbook writers who have argued that drift does not play an important role in speciation. We argue that drift may be a powerful amplifier of speciation under a wide variety of modeling assumptions, even when selection acts directly on female mating preferences.

Understanding the evolution and stability of the G-matrix.

The G-matrix summarizes the inheritance of multiple, phenotypic traits. The stability and evolution of this matrix are important issues because they affect our ability to predict how the phenotypic traits evolve by selection and drift. Despite the centrality of these issues, comparative, experimental, and analytical approaches to understanding the stability and evolution of the G-matrix have met with limited success. Nevertheless, empirical studies often find that certain structural features of the matrix are remarkably constant, suggesting that persistent selection regimes or other factors promote stability. On the theoretical side, no one has been able to derive equations that would relate stability of the G-matrix to selection regimes, population size, migration, or to the details of genetic architecture. Recent simulation studies of evolving G-matrices offer solutions to some of these problems, as well as a deeper, synthetic understanding of both the G-matrix and adaptive radiations.