HOW CLOSELY CORRELATED ARE MOLECULAR AND QUANTITATIVE MEASURES OF GENETIC VARIATION? A META‐ANALYSIS

The ability of populations to undergo adaptive evolution depends on the presence of quantitative genetic variation for ecologically important traits. Although molecular measures are widely used as surrogates for quantitative genetic variation, there is controversy about the strength of the relationship between the two. To resolve this issue, we carried out a meta-analysis based on 71 datasets. The mean correlation between molecular and quantitative measures of genetic variation was weak (r = 0.217). Furthermore, there was no significant relationship between the two measures for life-history traits (r = -0.11) or for the quantitative measure generally considered as the best indicator of adaptive potential, heritability (r = -0.08). Consequently, molecular measures of genetic diversity have only a very limited ability to predict quantitative genetic variability. When information about a population's short-term evolutionary potential or estimates of local adaptation and population divergence are required, quantitative genetic variation should be measured directly.     

The genetics of phenotypic plasticity I. Heritability

Methods for estimating the genetic component of phenotypic plasticity are presented. In the general case of clonal replicates or full-sibs raised in several environments, the heritability of plasticity can be measured as the ratio of the genotype-environment interaction variance to the total phenotypic variance. In the special case of only two environments plasticity also can be measured as the difference among environments in genotype or family means. In that case, the heritability of plasticity can be measured as either a ratio of variance components or as the slope of a parent-offspring regression. The general measure suffers because no least-square standard errors have been developed, although they can be calculated by maximum-likelihood or bootstrapping techniques. For the other two methods least-square standard errors can be calculated but require very large experiments for statistical significance to be achieved. The heritability measures are compared using data on plasticity of thorax size in response to temperature in Drosophila melanogaster. The heritability estimates are all in close agreement. Models of the evolution of phenotypic plasticity have treated it as a trait in its own right and as a cross-environment genetic correlation. Although the first approach is the one used here, neither one is preferred.     

EVOLUTIONARY PREDICTABILITY IN NATURAL POPULATIONS: DO MATING SYSTEM AND NONADDITIVE GENETIC VARIANCE INTERACT TO AFFECT HERITABILITIES IN PLANTAGO LANCEOLATA?

Quantitative genetics has been an immensely powerful tool in manipulating the phenotypes of domesticated plants and animals. Much of the predictive power of quantitative genetics depends on the breeder's control over the context in which phenotype and mating are being expressed. In the natural world, these contexts are often difficult to describe, let alone control. We are left, therefore, with a poor understanding of the limits of quantitative genetics in natural populations. One of the crucial contextual elements for assessing breeding value is the genetic background in which an individual's genes are being assessed. When interacting genes are polymorphic within a population, the degree of mating among relatives can influence the correlations among mates and the predictions of a response to selection. Population structure can strongly influence the degree to which dominance and epistasis influences additive genetic variance and heritability. The extent of inbreeding can also influence heritabilities through its effect on the environmental component of phenotypic variance. The applicability of standard quantitative genetic breeding designs to the measurement of heritabilities in natural populations therefore depends in part on: (1) the mating system of the population; and (2) the importance of gene interactions in determining phenotypic variation. We tested for an effect of mating structure on the partitioning of phenotypic variance and heritability by comparing two breeding designs in a common environment. Both breeding designs used 139 pollen parents taken from mapped locations in a population of Plantago lanceolata L., and crossed to 280 seed parents from the same population. One design was random-mating, the second was biased toward near-neighbor matings to an extent determined by field measure of pollen-mediated gene flow distances. The offspring were grown randomly mixed in a common garden. Nine traits were measured: central corm diameter, number of leaves, area of the most recently fully expanded leaf, density of hairs (cm^-2) on the leaves, dry weight per unit leaf area, photosynthetic capacity, transpiration rates, water use efficiency, and reproductive dry weight. Heritabilities and variance components from the two designs were compared using randomization tests. None of the variance components or the heritabilities differed significantly between breeding designs at the 0.05 level. The test could distinguish differences between the heritabilities measured in the two breeding designs as small as 0.11, on average. Thus, for the degree of inbreeding normally exhibited in P. lanceolata there is insufficient gene interaction present within populations to influence the partitioning of variance between additive and nonadditive components or to influence heritability estimates to a meaningful extent. We suggest that for Plantago other sources of variation in heritability estimates, such as maternal effects and genotype × environment interactions, are more important influences than the interaction between inbreeding and gene interactions, and standard heritability estimate based on random breeding is as accurate as one taking the natural mating structure into account.     

Inbreeding depression and mating-distance dependent offspring fitness in large and small populations of Lychnis flos-cuculi (Caryophyllaceae)

The spatial structure of four Lychnis flos-cuculi populations, varying in size and degree of isolation, was studied by comparing the fitness of offspring resulting from self-pollination and pollinations by neighbouring plants, plants within the same population, and plants from other populations. Selfed offspring had the lowest fitness of the four offspring groups. No significant difference was found between the performance of offspring from pollinations by neighbouring plants and offspring pollinated by plants further apart but within the same population. A lower fitness of offspring from pollinations between neighbours would be expected if these matings, on average, yielded inbred offspring which suffered from inbreeding depression. These results imply that either a tight neighbourhood structuring is not present, or that the inbreeding depression for offspring by neighbours is too low to detect, although these are inbred. Crossings between populations produced offspring with a significantly higher fitness than offspring sired within populations. There were no significant differences in response to inbreeding among the populations, and differences in mean fitness among populations had no clear relation to the population size or degree of isolation. A reduced fitness of small populations due to inbreeding depression or a less severe response to experimental inbreeding due to purging of deleterious alleles is therefore not supported by our results.     

Molecular ecological approaches to studying the evolutionary impact of selective harvesting in wildlife

Harvesting of wildlife populations by humans is usually targeted by sex, age or phenotypic criteria, and is therefore selective. Selective harvesting has the potential to elicit a genetic response from the target populations in several ways. First, selective harvesting may affect population demographic structure (age structure, sex ratio), which in turn may have consequences for effective population size and hence genetic diversity. Second, wildlife-harvesting regimes that use selective criteria based on phenotypic characteristics (e.g. minimum body size, horn length or antler size) have the potential to impose artificial selection on harvested populations. If there is heritable genetic variation for the target characteristic and harvesting occurs before the age of maturity, then an evolutionary response over time may ensue. Molecular ecological techniques offer ways to predict and detect genetic change in harvested populations, and therefore have great utility for effective wildlife management. Molecular markers can be used to assess the genetic structure of wildlife populations, and thereby assist in the prediction of genetic impacts by delineating evolutionarily meaningful management units. Genetic markers can be used for monitoring genetic diversity and changes in effective population size and breeding systems. Tracking evolutionary change at the phenotypic level in the wild through quantitative genetic analysis can be made possible by genetically determined pedigrees. Finally, advances in genome sequencing and bioinformatics offer the opportunity to study the molecular basis of phenotypic variation through trait mapping and candidate gene approaches. With this understanding, it could be possible to monitor the selective impacts of harvesting at a molecular level in the future. Effective wildlife management practice needs to consider more than the direct impact of harvesting on population dynamics. Programs that utilize molecular genetic tools will be better positioned to assess the long-term evolutionary impact of artificial selection on the evolutionary trajectory and viability of harvested populations.     

From icons to symbols: Some speculations on the origins of language

This paper is divided into three sections. In the first section we offer a retooling of some traditional concepts, namely icons and symbols, which allows us to describe an evolutionary continuum of communication systems. The second section consists of an argument from theoretical biology. In it we explore the advantages and disadvantages of phenotypic plasticity. We argue that a range of the conditions that selectively favor phenotypic plasticity also favor a nongenetic transmission system that would allow for the inheritance of acquired characters. The first two sections are independent, the third depends on both of them. In it we offer an argument that human natural languages have just the features required of an ideal transmission mechanism under the conditions described in section 2.We would like to thank Robert Boyd, Noam Chomsky, Gerald Feinberg, Ken Glander, David Hull, Ernst Mayr, John Rawls, Peter Richerson, william Wimsatt and Paul Ziff for helpful comments on earlier drafts of this paper. Special thanks go to Doug Stalker who was instrumental in both the origins and development of this work.     

NATURAL HERITABILITIES: CAN THEY BE RELIABLY ESTIMATED IN THE LABORATORY?

The validity of the assumption, that laboratory estimates of heritabilities will tend to overestimate natural heritabilities, due to a reduction in environmental variability and thus the phenotypic variance of traits, is examined. One hundred sixty-five field estimates of narrow sense heritabilities derived from the literature are compared with 189 estimates from laboratory studies on wild, outbred animal populations derived from the data set of Mousseau and Roff. The results indicate that 84% of field heritabilities are significantly different from zero and that for morphological, behavioral, and life-history traits there are no significant differences between laboratory and field estimates of heritability. Unexpectedly, mean heritabilities for morphological and life-history traits are actually higher in the field than in the lab. Twenty-two cases were found for which both laboratory and natural heritabilities had been estimated on the same traits. For this subset of the data, laboratory heritabilities tended to be higher than field estimates, but the difference was not significant. Also, the correlation between lab and field estimates was high (r = 0.6, P < 0.001), and the regression slope did not differ significantly from one. The major implications of this study are that laboratory estimates of heritability should generally provide reasonable estimations of both the magnitude and the significance of heritabilities in nature.     

The relationship between parental genetic or phenotypic divergence and progeny variation in the maize nested association mapping population

Appropriate selection of parents for the development of mapping populations is pivotal to maximizing the power of quantitative trait loci detection. Trait genotypic variation within a family is indicative of the family's informativeness for genetic studies. Accurate prediction of the most useful parental combinations within a species would help guide quantitative genetics studies. We tested the reliability of genotypic and phenotypic distance estimators between pairs of maize inbred lines to predict genotypic variation for quantitative traits within families derived from biparental crosses. We developed 25 families composed of ~200 random recombinant inbred lines each from crosses between a common reference parent inbred, B73, and 25 diverse maize inbreds. Parents and families were evaluated for 19 quantitative traits across up to 11 environments. Genetic distances (GDs) among parents were estimated with 44 simple sequence repeat and 2303 single-nucleotide polymorphism markers. GDs among parents had no predictive value for progeny variation, which is most likely due to the choice of neutral markers. In contrast, we observed for about half of the traits measured a positive correlation between phenotypic parental distances and within-family genetic variance estimates. Consequently, the choice of promising segregating populations can be based on selecting phenotypically diverse parents. These results are congruent with models of genetic architecture that posit numerous genes affecting quantitative traits, each segregating for allelic series, with dispersal of allelic effects across diverse genetic material. This architecture, common to many quantitative traits in maize, limits the predictive value of parental genotypic or phenotypic values on progeny variance.     

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.     

Variability and divergence in Pongamia pinnata (L.) Pierre germplasm – a candidate tree for biodiesel

Three explorations were undertaken in South East Coastal zone of India covering parts of Andhra Pradesh (AP) and Orissa states to collect Pongamia pinnata (L.) Pierre germplasm during March–June 2007. A total of 123 accessions were collected and seed data recorded were analyzed for morphometric traits viz., seed length, seed width, seed thickness, 100‐seed weight and oil content. Variation in the collected germplasm was analyzed using anova , simple measures of variation and D² statistics. Significant genetic variability between seed traits and oil content and association among the seed traits was recorded. Phenotypic variance was higher than genotypic variance for all the characters indicating dominant role of environment. High heritability (broad sense) for 100‐seed weight (97.6%) and oil content (86.7%) indicated the reliability of these characters as selection criteria for plus trees. Genetic gain was maximum for 100‐seed weight (62.6%) followed by oil content (30.5%). D² analysis grouped the accessions into 12 clusters. Cluster XII and cluster IX were the most diverse based on the intercluster distance. Based on the observed diversity, Chittoor, Srikakulam and Adilabad districts of AP are most suitable for collecting diverse germplasm lines and also for in situ conservation.     

Additive and testcross genetic variances in crosses among recombinant inbreds

 Breeders desire populations with a high mean performance and a large genetic variance. Theory and methods are lacking for predicting additive variance (V _A ) and testcross variance (V _T ) in biparental populations. Breeders have unsuccessfully attempted to predict V _A based on the coefficient of coancestry ( f ) or molecular-marker similarity between parents. In this paper, we derive the expected values of V _A and V _T in biparental populations, examine the variability of V _A among biparental crosses, and discuss how V _A and V _T may be predicted in applied breeding programs. Suppose i is a recombinant inbred derived from the cross between inbreds P ₁ and P ₂, and inbred j is not a direct descendant of i. Let V _A(i,j) be the additive variance in the F₂ of the (i×j) biparental cross. Let V _T(i, j) be the variance among testcrosses of F₂ individuals with a specific unrelated inbred or population. Assuming linkage equilibrium and the absence of epistasis, V _A(i, j) =λV _A(P1, j) +(1−λ) V _A(P2, j) , where λ= parental contribution of P ₁ to i. Similarly, V _T(i, j) = λV _T(P1, j) +(1−λ) V _T(P2, j) . Additive variance in crosses between recombinant inbreds cannot be modelled as a function of  f if, as indicated in the literature, V _A differs among crosses of founder inbreds. If molecular-marker similarity between parents is used as an estimate of f, then a strong linear relationship is likewise not expected between V _A and marker similarity. Differences between the actual and expected λ led to variation in V _A . In applied breeding programs, modelling V _A or V _T in biparental crosses may be feasible with estimates of V _A or V _T in prior crosses and information on λ obtained from molecular-marker data. Received: 23 September 1997 / Accepted: 30 December 1997