TYPE I ERROR RATES FOR TESTING GENETIC DRIFT WITH PHENOTYPIC COVARIANCE MATRICES: A SIMULATION STUDY

Studies of evolutionary divergence using quantitative genetic methods are centered on the additive genetic variance–covariance matrix ( G ) of correlated traits. However, estimating G properly requires large samples and complicated experimental designs. Multivariate tests for neutral evolution commonly replace average G by the pooled phenotypic within‐group variance–covariance matrix ( W ) for evolutionary inferences, but this approach has been criticized due to the lack of exact proportionality between genetic and phenotypic matrices. In this study, we examined the consequence, in terms of type I error rates, of replacing average G by W in a test of neutral evolution that measures the regression slope between among‐population variances and within‐population eigenvalues (the Ackermann and Cheverud [AC] test) using a simulation approach to generate random observations under genetic drift. Our results indicate that the type I error rates for the genetic drift test are acceptable when using W instead of average G when the matrix correlation between the ancestral G and P is higher than 0.6, the average character heritability is above 0.7, and the matrices share principal components. For less‐similar G and P matrices, the type I error rates would still be acceptable if the ratio between the number of generations since divergence and the effective population size (t/N_e) is smaller than 0.01 (large populations that diverged recently). When G is not known in real data, a simulation approach to estimate expected slopes for the AC test under genetic drift is discussed.     

Environmental effects on the structure of the G‐matrix

Genetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. Although individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance–covariance ( G ) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between‐environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between‐population differences. Neither environmental novelty, nor the difference in mean phenotype predicted these differences in G . Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments.     

The genetic variance but not the genetic covariance of life‐history traits changes towards the north in a time‐constrained insect

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life‐history traits and the correlations among these traits. To predict the response of life‐history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance‐covariance matrix, G . Here, we estimated G for key life‐history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set‐up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude‐specific covariance of the life‐history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance–covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance–covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments.     

EPISTASIS AND THE EVOLUTION OF ADDITIVE GENETIC VARIANCE IN POPULATIONS THAT PASS THROUGH A BOTTLENECK

Traditional models of genetic drift predict a linear decrease in additive genetic variance for populations passing through a bottleneck. This perceived lack of heritable variance limits the scope of founder-effect models of speciation. We produced 55 replicate bottleneck populations maintained at two male-female pairs through four generations of inbreeding (average F = 0.39). These populations were formed from an F₂ intercross of the LG/J and SM/J inbred mouse strains. Two contemporaneous control strains maintained with more than 60 mating pairs per generation were formed from this same source population. The average level of within-strain additive genetic variance for adult body weight was compared between the control and experimental lines. Additive genetic variance for adult body weight within experimental bottleneck strains was significantly higher than expected under an additive genetic model This enhancement of additive genetic variance under inbreeding is likely to be due to epistasis, which retards or reverses the loss of additive genetic variance under inbreeding for adult body weight in this population. Therefore, founder-effect speciation processes may not be constrained by a loss of heritable variance due to population bottlenecks.     

Gene flow and effective population size in Lepanthes (Orchidaceae): a case for genetic drift

Genetic drift can play an important role in population differentiation, particularly when effective population sizes are small and gene flow is limited. Such conditions are suspected to be common in the species-rich Orchidaceae. We investigated the likelihood of genetic drift in natural populations of three endemic species of Lepanthes (Orchidaceae) from Puerto Rico. We estimated effective population size, Ne, using three ecologically based methods. Two of the three estimates were based on variance in reproductive potential and the third was based on coalescence time. All estimates of Ne were usually <40% of the standing population size, resulting in values of <20 individuals per population. Based on starch gel electrophoresis of isozymes, Nm estimates suggest restricted gene flow among populations in the range of one or less successful migrant per generation. Genetic differentiation among populations is expected under such conditions from random genetic drift. Indeed we observed high genetic differentiation among populations (L. rubripetala, F_ST> G_ST, 6; θ.248, 0.266, 0.293; L. rupestris, 0.148, 0.169, 0.138; L. eltoroensis, 0.251, 0.219, 0.218, respectively). Genetic drift is likely to be important for population differentiation in Lepanthes as a result of small effective population sizes and restricted gene flow.     

HOMOGENEITY OF THE GENETIC VARIANCE-COVARIANCE MATRIX FOR ANTIPREDATOR TRAITS IN TWO NATURAL POPULATIONS OF THE GARTER SNAKE THAMNOPHIS ORDINOIDES

Quantitative genetic models of evolution rely on the genetic variance-covariance matrix to predict the phenotypic response to selection. Both prospective and retrospective studies of phenotypic evolution across generations rely on assumptions about the constancy of patterns of genetic covariance through time. In the absence of robust theoretical predictions about the stability of genetic covariances, this assumption must be tested with empirical comparisons of genetic parameters among populations and species. Genetic variance-covariance matrices were estimated for a suite of antipredator traits in two populations of the northwestern garter snake, Thamnophis ordinoides. The characters studied include color pattern and antipredator behaviors that interact to facilitate escape from predators. Significant heritabilities for all traits were detected in both populations. Genetic correlations and covariances were found among behaviors in both populations and between color pattern and behavior in one of the populations. Phenotypic means differed among populations, but pairwise comparisons revealed no heterogeneity of genetic parameters between the populations. The structure of the genetic variance-covariance matrix has apparently not changed significantly during the divergence of these two populations.     

Nonlinear selection and the evolution of variances and covariances for continuous characters in an anole

The pattern of genetic variances and covariances among characters, summarized in the additive genetic variance‐covariance matrix, G , determines how a population will respond to linear natural selection. However, G itself also evolves in response to selection. In particular, we expect that, over time, G will evolve correspondence with the pattern of multivariate nonlinear natural selection. In this study, we substitute the phenotypic variance‐covariance matrix ( P ) for G to determine if the pattern of multivariate nonlinear selection in a natural population of Anolis cristatellus, an arboreal lizard from Puerto Rico, has influenced the evolution of genetic variances and covariances in this species. Although results varied among our estimates of P and fitness, and among our analytic techniques, we find significant evidence for congruence between nonlinear selection and P , suggesting that natural selection may have influenced the evolution of genetic constraint in this species.     

Bottleneck Effects on Genetic Variance for Courtship Repertoire

Bottleneck effects on evolutionary potential in mating behavior were addressed through assays of additive genetic variances and resulting phenotypic responses to drift in the courtship repertoires of six two-pair founder-flush lines and two control populations of the housefly. A simulation addressed the complication that an estimate of the genetic variance for a courtship trait (e.g., male performance vigor or the female requirement for copulation) must involve assays against the background behavior of the mating partners. The additive ``environmental' effect of the mating partner's phenotype simply dilutes the net parent-offspring covariance for a trait. However, if there is an interaction with this ``environmental' component, negative parent-offspring covariances can result under conditions of high incompatibility between the population's distributions for male performance and female choice requirements, despite high levels of genetic variance. All six bottlenecked lines exhibited significant differentiation from the controls in at least one measure of the parent-offspring covariance for male performance or female choice (estimated by 50 parent-son and 50 parent-daughter covariances for 10 courtship traits per line) which translated to significant phenotypic drift. However, the average effect across traits or across lines did not yield a significant net increase in genetic variance due to bottlenecks. Concerted phenotypic differentiation due to the founder-flush event provided indirect evidence of directional dominance in a subset of traits. Furthermore, indirect evidence of genotype-environment interactions (potentially producing genotype-genotype effects) was found in the negative parent-offspring covariances predicted by the male-female interaction simulation and by the association of the magnitude of phenotypic drift with the absolute value of the parent-offspring covariance. Hence, nonadditive genetic effects on mating behavior may be important in structuring genetic variance for courtship, although most of the increases in genetic variance would be expected to reflect inbreeding depression with relatively rare situations representing the facilitation of speciation by bottlenecks.     

The role of genetic constraints on the diversification of Iberian taxa of the genus Aquilegia (Ranunculaceae)

The microevolutionary process of adaptive phenotypic differentiation of quantitative traits between populations or closely‐related taxa depends on the response of populations to the action of natural selection. However, this response can be constrained by the structure of the matrix of additive genetic variance and covariance between traits in each population ( G matrix). In the present study, we obtained additive genetic variance and narrow sense heritability for 25 floral and vegetative traits of three subspecies of Aquilegia vulgaris, and one subspecies of Aquilegia pyrenaica through a common garden crossing experiment. For two vegetative and one floral trait, we also obtained the G matrix and genetic correlations between traits in each subspecies. The amount of genetic variation available in wild populations is not responsible for the larger differentiation of vegetative than floral traits found in this group of columbines. However, the low heritability of some traits constrained their evolution because phenotypic variability among taxa was larger for traits with larger heritability. We confirmed that the process of diversification of the studied taxa involved shifts in the G matrix, mainly determined by changes in the genetic covariance between floral and vegetative traits, probably caused by linkage disequilibrium in narrow endemic taxa. © 2013 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111 , 252–261.     

Population divergence along lines of genetic variance and covariance in the invasive plant Lythrum salicaria in eastern North America

Evolution during biological invasion may occur over contemporary timescales, but the rate of evolutionary change may be inhibited by a lack of standing genetic variation for ecologically relevant traits and by fitness trade-offs among them. The extent to which these genetic constraints limit the evolution of local adaptation during biological invasion has rarely been examined. To investigate genetic constraints on life-history traits, we measured standing genetic variance and covariance in 20 populations of the invasive plant purple loosestrife (Lythrum salicaria) sampled along a latitudinal climatic gradient in eastern North America and grown under uniform conditions in a glasshouse. Genetic variances within and among populations were significant for all traits; however, strong intercorrelations among measurements of seedling growth rate, time to reproductive maturity and adult size suggested that fitness trade-offs have constrained population divergence. Evidence to support this hypothesis was obtained from the genetic variance-covariance matrix (G) and the matrix of (co)variance among population means (D), which were 79.8% (95% C.I. 77.7-82.9%) similar. These results suggest that population divergence during invasive spread of L. salicaria in eastern North America has been constrained by strong genetic correlations among life-history traits, despite large amounts of standing genetic variation for individual traits.     

Evolution of the additive genetic variance–covariance matrix under continuous directional selection on a complex behavioural phenotype

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance–covariance matrix (G). Yet knowledge of G in a population experiencing new or altered selection is not sufficient to predict selection response because G itself evolves in ways that are poorly understood. We experimentally evaluated changes in G when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change.     

VARIANCE-INDUCED PEAK SHIFTS

The increase in phenotypic variance that occurs in some populations as a result of bottlenecks and founder events can cause a dramatic increase in the probability of a peak shift from one adaptive state to another. Periods of small population size allow drift in the amount of phenotypic variance. Increases in phenotypic variance, coupled with a constant individual fitness function with multiple peaks, can cause the mean fitness landscape to change from bimodal to unimodal, thereby allowing the population's mean phenotype to change deterministically by selection. As the amount of phenotypic variance is returned to an equilibrium state, the multiple peaks reemerge, but the population has moved from one stable state to another. These variance-induced peak shifts allow punctuational evolution from one peak to another at a rate that can be much higher than that predicted by Wright's shifting-balance process alone.     

A G matrix analogue to capture the cumulative effects of nongenetic inheritance

The genetic variance‐covariance ( G ) matrix describes the variances and covariances of genetic traits under strict genetic inheritance. Genetically expressed traits often influence trait expression in another via nongenetic forms of transmission and inheritance, however. The importance of non‐genetic influences on phenotypic evolution is increasingly clear, but how genetic and nongenetic inheritance interact to determine the response to selection is not well understood. Here, we use the ‘reachability matrix’ – a key analytical tool of geometric control theory – to integrate both forms of inheritance, capturing how the consequences of generation‐lagged maternal effects accumulate. Building on the classic Lande and Kirkpatrick model that showed how nongenetic (maternal) inheritance fundamentally alters the expected path of phenotypic evolution, we make novel inferences through decomposition of the reachability matrix. In particular, we quantify how nongenetic inheritance affects the distribution (orientation and shape) of ellipses of phenotypic change and how these distributions influence subsequent evolution. This interweaving of phenotypic means and variances accumulates generation by generation and is described analytically by the reachability matrix, which acts as an analogue of G when genetic and nongenetic inheritance both act.     

Effect of mass selection on the within-family genetic variance in finite populations

Summary The adequacy of an expression for the withinfamily genetic variance under pure random drift in an additive infinitesimal model was tested via simulation in populations undergoing mass selection. Two hundred or one thousand unlinked loci with two alleles at initial frequencies of 1/2 were considered. The size of the population was 100 (50 males and 50 females). Full-sib matings were carried out for 15 generations with only one male and one female chosen as parents each generation, either randomly or on an individual phenotypic value. In the unselected population, results obtained from 200 replicates were in agreement with predictions. With mass selection, within-family genetic variance was overpredicted by theory from the 12th and 4th generations for the 1,000 and 200 loci cases, respectively. Taking into account the observed change in gene frequencies in the algorithm led to a much better agreement with observed values. Results for the distribution of gene frequencies and the withinlocus genetic covariance are presented. It is concluded that the expression for the within-family genetic variance derived for pure random drift holds well for mass selection within the limits of an additive infinitesimal model.     

Characterizing the evolution of genetic variance using genetic covariance tensors

Determining how genetic variance changes under selection in natural populations has proved to be a very resilient problem in evolutionary genetics. In the same way that understanding the availability of genetic variance within populations requires the simultaneous consideration of genetic variance in sets of functionally related traits, determining how genetic variance changes under selection in natural populations will require ascertaining how genetic variance–covariance (G) matrices evolve. Here, we develop a geometric framework using higher-order tensors, which enables the empirical characterization of how G matrices have diverged among populations. We then show how divergence among populations in genetic covariance structure can then be associated with divergence in selection acting on those traits using key equations from evolutionary theory. Using estimates of G matrices of eight male sexually selected traits from nine geographical populations of Drosophila serrata, we show that much of the divergence in genetic variance occurred in a single trait combination, a conclusion that could not have been reached by examining variation among the individual elements of the nine G matrices. Divergence in G was primarily in the direction of the major axes of genetic variance within populations, suggesting that genetic drift may be a major cause of divergence in genetic variance among these populations.     

Demographic and genetic estimates of effective population size (Ne) reveals genetic compensation in steelhead trout

Estimates of effective population size (Ne) are required to predict the impacts of genetic drift and inbreeding on the evolutionary dynamics of populations. How the ratio of Ne to the number of sexually mature adults (N) varies in natural vertebrate populations has not been addressed. We examined the sensitivity of Ne/N to fluctuations of N and determined the major variables responsible for changing the ratio over a period of 17 years in a population of steelhead trout (Oncorhynchus mykiss) from Washington State. Demographic and genetic methods were used to estimate Ne. Genetic estimates of Ne were gained via temporal and linkage disequilibrium methods using data from eight microsatellite loci. DNA for genetic analysis was amplified from archived smolt scales. The Ne/N from 1977 to 1994, estimated using the temporal method, was 0.73 and the comprehensive demographic estimate of Ne/N over the same time period was 0.53. Demographic estimates of Ne indicated that variance in reproductive success had the most substantial impact on reducing Ne in this population, followed by fluctuations in population size. We found increased Ne/N ratios at low N, which we identified as genetic compensation. Combining the information from the demographic and genetic methods of estimating Ne allowed us to determine that a reduction in variance in reproductive success must be responsible for this compensation effect. Understanding genetic compensation in natural populations will be valuable for predicting the effects of changes in N (i.e. periods of high population density and bottlenecks) on the fitness and genetic variation of natural populations.     

EPISTASIS AS A SOURCE OF INCREASED ADDITIVE GENETIC VARIANCE AT POPULATION BOTTLENECKS

The role of epistasis in evolution and speciation has remained controversial. We use a new parameterization of physiological epistasis to examine the effects of epistasis on levels of additive genetic variance during a population bottleneck. We found that all forms of epistasis increase average additive genetic variance in finite populations derived from initial populations with intermediate allele frequencies. Average additive variance continues to increase over many generations, especially at larger population sizes (N = 32 to 64). Additive-by-additive epistasis is the most potent source of additive genetic variance in this situation, whereas dominance-by-dominance epistasis contributes smaller amounts of additive genetic variance. With additive-by-dominance epistasis, additive genetic variance decreases at a relatively high rate immediately after a population bottleneck, rebounding to higher levels after several generations. Empirical examples of epistasis for murine adult body weight based on measured genotypes are provided illustrating the varying effects of epistasis on additive genetic variance during population bottlenecks.     

Phenotypic plasticity in morphological traits in two populations of Drosophila melanogaster

Isofemale lines of two populations of Drosophila melanogaster, originating from France and Tanzania, were examined over a range of temperatures. Morphological traits showed distinct patterns in phenotypic plasticity; flies of the two populations differed in shape. Genotype-by-Environment (G*E) interactions were frequently found in the Tanzania population, but were hardly present in the France population. If G*E interaction was present over temperature, estimates of additive genetic variance and additive genetic covariance were made to compare theoretical models with our data. The conclusion is that in France Drosophila melanogaster has been selected over a wider range of temperatures, resulting in parallel reaction norms of more optimal slope. In contrast, selection must have taken place over a narrower temperature range in Tanzanian flies, and will have exerted no direct influence on the slope of the reaction norm.     

Does natural selection alter genetic architecture? An evaluation of quantitative genetic variation among populations of Allonemobiussocius and A. fasciatus

To make long-term predictions using present quantitative genetic theory it is necessary to assume that the genetic variance–covariance matrix ( G ) remains constant or at least changes by a constant fraction. In this paper we examine the stability of the genetic architecture of two traits known to be subject to natural selection; femur length and ovipositor length in two species of the cricket Allonemobius. Previous studies have shown that in A. fasciatus and A. socius natural selection favours an increased body size southwards but a decreased ovipositor length. Such countergradient selection should tend to favour a change in G . In the total sample of eight populations of A. socius and one of A. fasciatus we show that there is significant variation in all genetic covariance components, i.e. V_A for body size, V_A for ovipositor length, and Cov_A. This variation results entirely from an increase in the covariances of A. fasciatus. However, although larger, these components are approximately proportionally increased, thereby leading to no statistically significant change in the genetic correlation. A proportional increase in the covariance components is consistent with changes resulting from genetic drift. On the other hand, the genetic covariance components are significantly correlated with the length of the growing season suggesting that the change in the genetic architecture is the result of selection and drift.     

Effects of the demographic transition on the genetic variances and covariances of human life‐history traits

The recent demographic transitions to lower mortality and fertility rates in most human societies have led to changes and even quick reversals in phenotypic selection pressures. This can only result in evolutionary change if the affected traits are heritable, but changes in environmental conditions may also lead to subsequent changes in the genetic variance and covariance (the G matrix) of traits. It currently remains unclear if there have been concomitant changes in the G matrix of life‐history traits following the demographic transition. Using 300 years of genealogical data from Finland, we found that four key life‐history traits were heritable both before and after the demographic transition. The estimated heritabilities allow a quantifiable genetic response to selection during both time periods, thus facilitating continued evolutionary change. Further, the G matrices remained largely stable but revealed a trend for an increased additive genetic variance and thus evolutionary potential of the population after the transition. Our results demonstrate the validity of predictions of evolutionary change in human populations even after the recent dramatic environmental change, and facilitate predictions of how our biology interacts with changing environments, with implications for global public health and demography.