John R. Stinchcombe

Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits

A central challenge in evolutionary biology is to identify genes underlying ecologically important traits and describe the fitness consequences of naturally occurring variation at these loci. To address this goal, several novel approaches have been developed, including ‘population genomics,’ where a large number of molecular markers are scored in individuals from different environments with the goal of identifying markers showing unusual patterns of variation, potentially due to selection at linked sites. Such approaches are appealing because of (1) the increasing ease of generating large numbers of genetic markers, (2) the ability to scan the genome without measuring phenotypes and (3) the simplicity of sampling individuals without knowledge of their breeding history. Although such approaches are inherently applicable to non-model systems, to date these studies have been limited in their ability to uncover functionally relevant genes. By contrast, quantitative genetics has a rich history, and more recently, quantitative trait locus (QTL) mapping has had some success in identifying genes underlying ecologically relevant variation even in novel systems. QTL mapping, however, requires (1) genetic markers that specifically differentiate parental forms, (2) a focus on a particular measurable phenotype and (3) controlled breeding and maintenance of large numbers of progeny. Here we present current advances and suggest future directions that take advantage of population genomics and quantitative genetic approaches – in both model and non-model systems. Specifically, we discuss advantages and limitations of each method and argue that a combination of the two provides a powerful approach to uncovering the molecular mechanisms responsible for adaptation.

ESTIMATING NONLINEAR SELECTION GRADIENTS USING QUADRATIC REGRESSION COEFFICIENTS: DOUBLE OR NOTHING?

Abstract The use of regression analysis has been instrumental in allowing evolutionary biologists to estimate the strength and mode of natural selection. Although directional and correlational selection gradients are equal to their corresponding regression coefficients, quadratic regression coefficients must be doubled to estimate stabilizing/disruptive selection gradients. Based on a sample of 33 papers published in Evolution between 2002 and 2007, at least 78% of papers have not doubled quadratic regression coefficients, leading to an appreciable underestimate of the strength of stabilizing and disruptive selection. Proper treatment of quadratic regression coefficients is necessary for estimation of fitness surfaces and contour plots, canonical analysis of the γ matrix, and modeling the evolution of populations on an adaptive landscape.

Testing for Environmentally Induced Bias in Phenotypic Estimates of Natural Selection: Theory and Practice

Measuring natural selection has been a fundamental goal of evolutionary biology for more than a century, and techniques developed in the last 20 yr have provided relatively simple means for biologists to do so. Many of these techniques, however, share a common limitation: when applied to phenotypic data, environmentally induced covariances between traits and fitness can lead to biased estimates of selection and misleading predictions about evolutionary change. Utilizing estimates of breeding values instead of phenotypic data with these methods can eliminate environmentally induced bias, although this approach is more difficult to implement. Despite this potential limitation to phenotypic methods and the availability of a potential solution, little empirical evidence exists on the extent of environmentally induced bias in phenotypic estimates of selection. In this article, we present a method for detecting bias in phenotypic estimates of selection and demonstrate its use with three independent data sets. Nearly 25% of the phenotypic selection gradients estimated from our data are biased by environmental covariances. We find that bias caused by environmental covariances appears mainly to affect quantitative estimates of the strength of selection based on phenotypic data and that the magnitude of these biases is large. As our estimates of selection are based on data from spatially replicated field experiments, we suggest that our findings on the prevalence of bias caused by environmental covariances are likely to be conservative.

An atlas of over 90,000 conserved noncoding sequences provides insight into crucifer regulatory regions

Despite the central importance of noncoding DNA to gene regulation and evolution, understanding of the extent of selection on plant noncoding DNA remains limited compared to that of other organisms. Here we report sequencing of genomes from three Brassicaceae species (Leavenworthia alabamica, Sisymbrium irio and Aethionema arabicum) and their joint analysis with six previously sequenced crucifer genomes. Conservation across orthologous bases suggests that at least 17% of the Arabidopsis thaliana genome is under selection, with nearly one-quarter of the sequence under selection lying outside of coding regions. Much of this sequence can be localized to approximately 90,000 conserved noncoding sequences (CNSs) that show evidence of transcriptional and post-transcriptional regulation. Population genomics analyses of two crucifer species, A. thaliana and Capsella grandiflora, confirm that most of the identified CNSs are evolving under medium to strong purifying selection. Overall, these CNSs highlight both similarities and several key differences between the regulatory DNA of plants and other species.

The adaptive evolution of plasticity: Phytochrome-mediated shade avoidance responses

Abstract Many plants display a characteristic suite of developmental “shade avoidance” responses, such as stem elongation and accelerated reproduction, to the low ratio of red to far-red wavelengths (R:FR) reflected or transmitted from green vegetation. This R:FR cue of crowding and vegetation shade is perceived by the phytochrome family of photoreceptors. Phytochrome-mediated responses provide an ideal system for investigating the adaptive evolution of phenotypic plasticity in natural environments. The molecular and developmental mechanisms underlying shade avoidance responses are well studied, and testable ecological hypotheses exist for their adaptive significance. Experimental manipulation of phenotypes demonstrates that shade avoidance responses may be adaptive, resulting in phenotypes with high relative fitness in the environments that induce those phenotypes. The adaptive value of shade avoidance depends upon the competitive environment, resource availability, and the reliability of the R:FR cue for predicting the selective environment experienced by an induced phenotype. Comparative studies and a reciprocal transplant experiment with Impatiens capensis provide evidence of adaptive divergence in shade avoidance responses between woodland and clearing habitats, which may result from population differences in the frequency of selection on shade avoidance traits, as well as differences in the reliability of the R:FR cue. Recent rapid progress in elucidating phytochrome signaling pathways in the genetic model Arabidopsis thaliana and other species now provides the opportunity for studying how selection on shade avoidance traits in natural environments acts upon the molecular mechanisms underlying natural phenotypic variation.

How much do genetic covariances alter the rate of adaptation

Genetically correlated traits do not evolve independently, and the covariances between traits affect the rate at which a population adapts to a specified selection regime. To measure the impact of genetic covariances on the rate of adaptation, we compare the rate fitness increases given the observed G matrix to the expected rate if all the covariances in the G matrix are set to zero. Using data from the literature, we estimate the effect of genetic covariances in real populations. We find no net tendency for covariances to constrain the rate of adaptation, though the quality and heterogeneity of the data limit the certainty of this result. There are some examples in which covariances strongly constrain the rate of adaptation but these are balanced by counter examples in which covariances facilitate the rate of adaptation; in many cases, covariances have little or no effect. We also discuss how our metric can be used to identify traits or suites of traits whose genetic covariances to other traits have a particularly large impact on the rate of adaptation.

Diffuse Selection on Resistance to Deer Herbivory in the Ivyleaf Morning Glory, Ipomoea hederacea

Recent work defines coevolution between plants and herbivores as pairwise when the pattern of selection on resistance traits and the response to selection are both independent of the presence or absence of other herbivores. In addition, for a pairwise response to selection, resistance to a focal herbivore must have the same genetic basis in the presence and absence of other herbivores. None of these conditions were satisfied for the ivyleaf morning glory, Ipomoea hederacea, and its insect, fungal, and mammalian natural enemies with a quantitative genetics field experiment. A significant negative genetic correlation exists between resistance to deer and generalist insect herbivory that would preclude an independent response to selection. In addition, resistance loci under selection differ depending on the composition of the natural enemy community as indicated by genetic correlations between deer resistances in the presence and absence of other natural enemies that differ substantially from 1. Finally, selection on deer resistance depends on the presence or absence of insects; in the presence of insects, greater deer resistance is favored, but in the absence of insects, deer resistance is effectively neutral. These results indicate that the composition of the natural enemy community can alter both the pattern of selection and the likely response to selection of resistance traits.

Fitness Effects Associated with the Major Flowering Time Gene FRIGIDA in Arabidopsis thaliana in the Field

To date, the effect of natural selection on candidate genes underlying complex traits has rarely been studied experimentally, especially under ecologically realistic conditions. Here we report that the effect of selection on the flowering time gene FRIGIDA (FRI) reverses depending on the season of germination and allelic variation at the interacting gene FLOWERING LOCUS C (FLC). In field studies of 136 European accessions of Arabidopsis thaliana, accessions with putatively functional FRI alleles had higher winter survival in one FLC background in a fall‐germinating cohort, but accessions with deletion null FRI alleles had greater seed production in the other FLC background in a spring‐germinating cohort. Consistent with FRI’s role in flowering, selection analyses suggest that the difference in winter survival can be attributed to time to bolting. However, in the spring cohort, the fitness difference was associated with rosette size. Our analyses also reveal that controlling for population structure with estimates of inferred ancestry and a geographical restriction was essential for detecting fitness associations. Overall, our results suggest that the combined effects of seasonally varying selection and epistasis could explain the maintenance of variation at FRI and, more generally, may be important in the evolution of genes underlying complex traits.

EVOLUTIONARY GENETICS OF RESISTANCE AND TOLERANCE TO NATURAL HERBIVORY IN ARABIDOPSIS THALIANA

Abstract.— Resistance and tolerance are widely viewed as two alternative adaptive responses to herbivory. However, the traits underlying resistance and tolerance remain largely unknown, as does the genetic architecture of herbivory responses and the prevalence of genetic trade‐offs. To address these issues, we measured resistance and tolerance to natural apical meristem damage (AMD) by rabbits in a large field experiment with recombinant inbred lines (RILs) ofArabidopsis thaliana (developed from a cross between the Columbia X Landsberg erecta ecotypes). We also measured phenological and morphological traits hypothesized to underlie resistance and tolerance to AMD. Recombinant inbred lines differed significantly in resistance (the proportion of replicates within an RIL that resisted herbivory), and early flowering plants with tall apical inflorescences were more likely to experience damage. Tolerance (the difference in fitness between the damaged and undamaged states), also differed significantly among RILs, with some lines over‐compensating for damage and producing more fruit in the damaged than undamaged state. Plastic increases in basal branch number, basal branch height, and senescence date in response to damage were all associated with greater tolerance. There was no evidence for a genetic trade‐off between resistance and tolerance, an observation consistent with the underlying differences in associated morphological and phenological characters. Selection gradient analysis detected no evidence for direct selection on either resistance or tolerance in this experiment. However, a statistical model indicates that the pattern of selection on resistance depends strongly on the mean level of tolerance, and selection on tolerance depends strongly on the mean level of resistance. These observations are consistent with the hypothesis that selection may act to maintain resistance and tolerance at intermediate levels in spatially or temporally varying environments or those with varying herbivore populations.

POPULATION VIABILITY ANALYSIS IN ENDANGERED SPECIES RECOVERY PLANS: PAST USE AND FUTURE IMPROVEMENTS

Using the results of a survey of recovery plans for threatened and endangered species, we evaluated the role that Population Viability Analysis (PVA) has played in recovery planning and management of rare species in the United States. Although there was a significant increase over time in the percentage of plans presenting information on PVA and assigning recovery tasks to collect more such information, the use of PVA was still called for in less than half of the plans approved since 1991. Because scarcity of data for rare species may be limiting the application of PVA to endangered species, we also assessed how often recovery plans proposed to collect the full complement of data required to perform four general types of PVA. For most of the species in the database, proposed monitoring data would allow the simplest type of PVA method (i.e., analysis of total population counts) to be applied, but more complex PVAs would be possible for <25% of the species. We conclude with brief recommendations for how the use of PVA in endangered species recovery planning might be improved in the future.