Understanding quantitative genetic variation

A comprehensive SNP-based genetic analysis of inbred mouse strains

Dense genetic maps of mammalian genomes facilitate a variety of biological studies including the mapping of polygenic traits, positional cloning of monogenic traits, mapping of quantitative or qualitative trait loci, marker association, allelic imbalance, speed congenic construction, and evolutionary or phylogenetic comparison. In particular, single nucleotide polymorphisms (SNPs) have proved useful because of their abundance and compatibility with multiple high-throughput technology platforms. SNP genotyping is especially suited for the genetic analysis of model organisms such as the mouse because biallelic markers remain fully informative when used to characterize crosses between inbred strains. Here we report the mapping and genotyping of 673 SNPs (including 519 novel SNPs) in 55 of the most commonly used mouse strains. These data have allowed us to construct a phylogenetic tree that correlates and expands known genealogical relationships and clarifies the origin of strains previously having an uncertain ancestry. All 55 inbred strains are distinguishable genetically using this SNP panel. Our data reveal an uneven SNP distribution consistent with a mosaic pattern of inheritance and provide some insight into the changing dynamics of the physical architecture of the genome. Furthermore, these data represent a valuable resource for the selection of markers and the design of experiments that require the genetic distinction of any pair of mouse inbred strains such as the generation of congenic mice, positional cloning, and the mapping of quantitative or qualitative trait loci.

Complex genetic interactions in a quantitative trait locus

Whether in natural populations or between two unrelated members of a species, most phenotypic variation is quantitative. To analyze such quantitative traits, one must first map the underlying quantitative trait loci. Next, and far more difficult, one must identify the quantitative trait genes (QTGs), characterize QTG interactions, and identify the phenotypically relevant polymorphisms to determine how QTGs contribute to phenotype. In this work, we analyzed three Saccharomyces cerevisiae high-temperature growth (Htg) QTGs (MKT1, END3, and RHO2). We observed a high level of genetic interactions among QTGs and strain background. Interestingly, while the MKT1 and END3 coding polymorphisms contribute to phenotype, it is the RHO2 3′UTR polymorphisms that are phenotypically relevant. Reciprocal hemizygosity analysis of the Htg QTGs in hybrids between S288c and ten unrelated S. cerevisiae strains reveals that the contributions of the Htg QTGs are not conserved in nine other hybrids, which has implications for QTG identification by marker-trait association. Our findings demonstrate the variety and complexity of QTG contributions to phenotype, the impact of genetic background, and the value of quantitative genetic studies in S. cerevisiae.

Most of the differences in phenotype between unrelated members of a species are polygenic in nature. Because of their ubiquity and importance, these polygenic (or quantitative) traits have been intensively studied, and a variety of techniques have been proposed to identify and characterize quantitative trait genes (QTGs). Indeed, the main application of the recently published human HapMap project is to identify the genes responsible for diseases that are quantitative in nature. Using a well-defined Saccharomyces cerevisiae quantitative trait locus containing three QTGs (MKT1, END3, and RHO2), the authors used deletions to analyze the contributions of each gene to phenotype, singly and in combination, and found a variety of interactions. Expression analysis showed no difference in steady-state mRNA levels between alleles of the three genes. Homologous allele replacement identified the phenotypically relevant differences between alleles of each gene, which were single coding polymorphisms for two genes (MKT1 and END3) and the 3′ untranslated region of one gene (RHO2). Finally, analysis of multiple genetic backgrounds showed that the phenotypes conferred by these genetic variants were not conserved. The results show that the techniques proposed to identify QTGs, such as expression analysis and marker-trait association, have profound limitations, and that unbiased genome-wide approaches are needed to dissect quantitative traits. The results also demonstrate the complexity of the genetic interactions that affect quantitative traits and the value of the S. cerevisiae system in studying these traits.

Intraspecific Competitive Divergence and Convergence under Assortative Mating

Ecologically driven sympatric speciation has received much attention recently. We investigate a multilocus model of a quantitative trait that is under frequency-dependent selection caused by intraspecific competition and acts as mating character for assortment. We identify the conditions that lead to the establishment of reproductively isolated clusters. This may be interpreted as evolutionary splitting or sympatric speciation. In our model, there are parameters that independently determine the strength of assortment, the costs for being choosy, and the strength of frequency-dependent natural selection. Sufficiently strong frequency dependence leads to disruptive selection on the phenotypes. The population consists of (sexual) haploid individuals. If frequency dependence is strong enough to induce disruptive selection and costs are absent or low, the result of evolution depends in a distinctive nonlinear way on the strength of assortment: under moderately strong assortment, less genetic variation is maintained than under weak or strong assortment, and sometimes there is none at all. Evolutionary splitting occurs only if frequency dependence and assortment are both strong enough and costs are low. Even then, the evolutionary outcome depends on the genetics and the initial conditions. The roles of the number of loci, of linkage, and of asymmetric selection are also explored.

Genetic architecture of two fitness-related traits in Drosophila melanogaster: ovariole number and thorax length

In Drosophila melanogaster, ovariole number and thorax length are morphological characters thought to be associated with fitness. Maximum daily egg production in females is positively correlated with ovariole number, while thorax length is correlated with male reproductive success and female fecundity. Though both traits are related to fitness, ovariole number is likely to be under stabilizing selection, while thorax length appears to be under directional selection. Current research has focused on examining the sources of variation for ovariole number in relation to fitness, with a view towards elucidating how segregating variation is maintained in natural populations. Here, we utilize a diallel design to explore the genetic architecture of ovariole number and thorax length in nine isogenic lines derived from a natural population. The full diallel design allows the estimation of general combining ability (GCA), specific combining ability (SCA), and also describes variation due to reciprocal effects (RGCA and RSCA). Ovariole number and thorax length differed with respect to their genetic architecture, reflective of the independent selective forces acting on the traits. For ovariole number, GCA accounted for the majority (67.3%) of variation segregating between the lines, with no evidence of reciprocal effects or inbreeding depression; SCA accounted for a small percentage (3.9%) of the variance, suggesting dominance variation; no reciprocal effects were observed. In contrast, for thorax length, the majority of the non-error variance was accounted for by SCA (17.9%), with only one third as much variance (6.2%) due to GCA. Interestingly, RSCA (nuclear-extranuclear interactions) accounted for slightly more variation (7.5%) than GCA in these data. Thus, genetic variation for thorax length is largely in accord with predictions for a fitness trait under directional selection: little additive genetic variation and substantial dominance variation (including a suggestion of inbreeding depression); while the mechanisms underlying the maintenance of variation for ovariole number are more complex.

VERY LOW ADDITIVE GENETIC VARIANCE AND EVOLUTIONARY POTENTIAL IN MULTIPLE POPULATIONS OF TWO RAINFOREST DROSOPHILA SPECIES

Most quantitative traits are thought to exhibit high levels of genetic variance and evolutionary potential. However, this conclusion may be biased by a lack of studies on nonmodel organisms and may not generalize to restricted species. A recent study on a single, southern population of the rainforest-restricted Drosophila birchii failed to find significant additive genetic variance for the desiccation resistance trait; however, it is unclear whether this pattern extends to other D. birchii populations or to other rainforest species. Here we use an animal model design to show very low levels of additive genetic variance for desiccation resistance in multiple populations of two highly sensitive rainforest species of Drosophila from tropical northeastern Australia. In contrast, relatively high levels of genetic variance were found for morphological traits in all populations of the species tested. This indicates limited evolutionary potential for evolving increased desiccation resistance in these rainforest restricted species.

Comparison of quantitative trait loci for adaptive traits between oak and chestnut based on an expressed sequence tag consensus map

A comparative genetic and QTL mapping was performed between Quercus robur L. and Castanea sativa Mill., two major forest tree species belonging to the Fagaceae family. Oak EST-derived markers (STSs) were used to align the 12 linkage groups of the two species. Fifty-one and 45 STSs were mapped in oak and chestnut, respectively. These STSs, added to SSR markers previously mapped in both species, provided a total number of 55 orthologous molecular markers for comparative mapping within the Fagaceae family. Homeologous genomic regions identified between oak and chestnut allowed us to compare QTL positions for three important adaptive traits. Colocation of the QTL controlling the timing of bud burst was significant between the two species. However, conservation of QTL for height growth was not supported by statistical tests. No QTL for carbon isotope discrimination was conserved between the two species. Putative candidate genes for bud burst can be identified on the basis of colocations between EST-derived markers and QTL.

Selection in backcross programmes

Backcrossing is a well-known and long established breeding scheme where a characteristic is introgressed from a donor parent into the genomic background of a recurrent parent. The various uses of backcrossing in modern genetics, particularly with the help of molecular markers, are reviewed here. Selection in backcross programmes is used to either improve the genetic value of plant and animal populations or fine map quantitative trait loci. Both cases are helpful in our understanding of the genetic bases of quantitative traits variation.

Quantitative trait loci with age-specific effects on fecundity in Drosophila melanogaster

Life-history theory and evolutionary theories of aging assume the existence of alleles with age-specific effects on fitness. While various studies have documented age-related changes in the genetic contribution to variation in fitness components, we know very little about the underlying genetic architecture of such changes. We used a set of recombinant inbred lines to map and characterize the effects of quantitative trait loci (QTL) affecting fecundity of Drosophila melanogaster females at 1 and 4 weeks of age. We identified one QTL on the second chromosome and one or two QTL affecting fecundity on the third chromosome, but these QTL affected fecundity only at 1 week of age. There was more genetic variation for fecundity at 4 weeks of age than at 1 week of age and there was no genetic correlation between early and late-age fecundity. These results suggest that different loci contribute to the variation in fecundity as the organism ages. Our data provide support for the mutation accumulation theory of aging as applied to reproductive senescence. Comparing the results from this study with our previous work on life-span QTL, we also find evidence that antagonistic pleiotropy may contribute to the genetic basis of senescence in these lines as well.

Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris

Comparison of the level of differentiation at neutral molecular markers (estimated as F(ST) or G(ST)) with the level of differentiation at quantitative traits (estimated as Q(ST)) has become a standard tool for inferring that there is differential selection between populations. We estimated Q(ST) of timing of bud set from a latitudinal cline of Pinus sylvestris with a Bayesian hierarchical variance component method utilizing the information on the pre-estimated population structure from neutral molecular markers. Unfortunately, the between-family variances differed substantially between populations that resulted in a bimodal posterior of Q(ST) that could not be compared in any sensible way with the unimodal posterior of the microsatellite F(ST). In order to avoid publishing studies with flawed Q(ST) estimates, we recommend that future studies should present heritability estimates for each trait and population. Moreover, to detect variance heterogeneity in frequentist methods (ANOVA and REML), it is of essential importance to check also that the residuals are normally distributed and do not follow any systematically deviating trends.

Evolution and maintenance of the environmental component of the phenotypic variance: benefit of plastic traits under changing environments

How environmental variances in quantitative traits are influenced by variable environments is an important problem in evolutionary biology. In this study, the evolution and maintenance of phenotypic variance in a plastic trait under stabilizing selection are investigated. The mapping from genotypic value to phenotypic value of the quantitative trait is approximated by a linear reaction norm, with genotypic effects on its phenotypic mean and sensitivity to environment. The environmental deviation is assumed to be decomposed into environmental quality, which interacts with genotypic value, and residual developmental noise, which is independent of genotype. Environmental quality and the optimal phenotype of stabilizing selection are allowed to randomly fluctuate in both space and time, and individuals migrate equally before development and reproduction among different niches. Analyses show that phenotypic plasticity is adaptive within variable environments if correlations have become established between the optimal phenotype and environmental quality in space and/or time. The evolved plasticity increases with variances in optimal phenotypes and correlations between optimal phenotype and environmental quality; this further induces increases in mean fitness and the environmental variance in the trait. Under certain circumstances, however, the environmental variance may decrease with increase in variation in environmental quality.

Tests for the replication of an association between Egfr and natural variation in Drosophila melanogaster wing morphology

Background

Quantitative differences between individuals stem from a combination of genetic and environmental factors, with the heritable variation being shaped by evolutionary forces. Drosophila wing shape has emerged as an attractive system for genetic dissection of multi-dimensional traits. We utilize several experimental genetic methods to validation of the contribution of several polymorphisms in the Epidermal growth factor receptor (Egfr) gene to wing shape and size, that were previously mapped in populations of Drosophila melanogaster from North Carolina (NC) and California (CA). This re-evaluation utilized different genetic testcrosses to generate heterozygous individuals with a variety of genetic backgrounds as well as sampling of new alleles from Kenyan stocks.

Results

Only one variant, in the Egfr promoter, had replicable effects in all new experiments. However, expanded genotyping of the initial sample of inbred lines rendered the association non-significant in the CA population, while it persisted in the NC sample, suggesting population specific modification of the quantitative trait nucleotide QTN effect.

Conclusion

Dissection of quantitative trait variation to the nucleotide level can identify sites with replicable effects as small as one percent of the segregating genetic variation. However, the testcross approach to validate QTNs is both labor intensive and time-consuming, and is probably less useful than resampling of large independent sets of outbred individuals.

Fisher's microscope and Haldane's ellipse

Fisher's geometrical model was introduced to study the phenotypic size of mutations contributing to adaptation. However, as pointed out by Haldane, the model involves a simplified picture of the action of natural selection, and this calls into question its generality. In particular, Fisher's model assumes that each trait contributes independently to fitness. Here, we show that Haldane's concerns may be incorporated into Fisher's model solely by allowing the intensity of selection to vary between traits. We further show that this generalization may be achieved by introducing a single, intuitively defined quantity that describes the phenotype prior to adaptation. Comparing the process of adaptation under the original and generalized models, we show that the generalization may bias results toward either larger or smaller mutations. The applicability of Fisher's model is then discussed.

Quantitative trait locus (QTL) isogenic recombinant analysis: a method for high-resolution mapping of QTL within a single population

In the quest for fine mapping quantitative trait loci (QTL) at a subcentimorgan scale, several methods that involve the construction of inbred lines and the generation of large progenies of such inbred lines have been developed (Complex Trait Consortium 2003). Here we present an alternative method that significantly speeds up QTL fine mapping by using one segregating population. As a first step, a rough mapping analysis is performed on a small part of the population. Once the QTL have been mapped to a chromosomal interval by standard procedures, a large population of 1000 plants or more is analyzed with markers flanking the defined QTL to select QTL isogenic recombinants (QIRs). QIRs bear a recombination event in the QTL interval of interest, while other QTL have the same homozygous genotype. Only these QIRs are subsequently phenotyped to fine map the QTL. By focusing at an early stage on the informative individuals in the population only, the efforts in population genotyping and phenotyping are significantly reduced as compared to prior methods. The principles of this approach are demonstrated by fine mapping an erucic acid QTL of rapeseed at a subcentimorgan scale.

Constrained evolution of a quantitative character by pleiotropic mutation

The long-term response to directional selection and its selection limit are derived for a quantitative character that is controlled by pleiotropic mutations with direct deleterious effect on fitness. Directional selection is assumed to be weaker than the selection acting directly on mutations via deleterious effects (purging selection), which renders all mutations to eventual elimination. The analysis embedding this restrictive assumption indicates that the evolutionary response of the character starting from an equilibrium state, in which mutation and purging selection balance but no directional selection is operating, decreases monotonically with time at an exponential rate. And the fading rate of responses is mostly determined by the direct deleterious effect. Contrary to the expectation by the standard selection limit theory based on fixation of extant genetic variation, the present model predicts that the selection limit depends on the intensity of directional selection, the limit being proportional to the ratio of the directional selection intensity to the direct deleterious effect. A slightly larger genetic variance is maintained at the selection limit than would be without directional selection.

Adaptation and speciation: what can Fst tell us?

A useful way of summarizing genetic variability among different populations is through estimates of the inbreeding coefficient, F(st). Several recent studies have tried to use the distribution of estimates of F(st) from individual genetic loci to detect the effects of natural selection. However, the promise of this approach has yet to be fully realized owing to the pervasive dogma that this distribution is highly dependent on demographic history. Here, I review recent theoretical results that indicate that the distribution of estimates of F(st) is generally expected to be robust to the vagaries of demographic history. I suggest that analyses based on it provide a useful first step for identifying candidate genes that might be under selection, and explore the ways in which this information can be used in ecological and evolutionary studies.

Theoretical models of selection and mutation on quantitative traits

Empirical studies of quantitative genetic variation have revealed robust patterns that are observed both across traits and across species. However, these patterns have no compelling explanation, and some of the observations even appear to be mutually incompatible. We review and extend a major class of theoretical models, 'mutation-selection models', that have been proposed to explain quantitative genetic variation. We also briefly review an alternative class of 'balancing selection models'. We consider to what extent the models are compatible with the general observations, and argue that a key issue is understanding and modelling pleiotropy. We discuss some of the thorny issues that arise when formulating models that describe many traits simultaneously.

Quantitative trait loci and the study of plant domestication

Plant domestication ranks as one of the most important developments in human history, giving human populations the potential to harness unprecedented quantities of the earth's resources. But domestication has also played a more subtle historical role as the foundation of the modern study of evolution and adaptation. Until recently, however, researchers interested in domestication were limited to studying phenotypic changes or the genetics of simple Mendelian traits, when often the characters of most interest--fruit size, yield, height, flowering time, etc.--are quantitative in nature. The goals of this paper are to review some of the recent work on the quantitative genetics of plant domestication, identify some of the common trends found in this literature, and offer some novel interpretations of the data that is currently available.

Ontogenetics of QTL: the genetic architecture of trichome density over time in Arabidopsis thaliana

Although much is known about the molecular genetic basis of trichome development in Arabidopsis thaliana, less is known about the underlying genetic basis of continuous variation in a trait known to be of adaptive importance: trichome density. The density of leaf trichomes is known to be a major determinant of herbivore damage in natural populations of A. thaliana and herbivores are a significant selective force on genetic variation for trichome density. A number of developmental changes occur during ontogeny in A. thaliana, including changes in trichome density. I used multiple interval mapping (MIM) analysis to identify QTL responsible for trichome density on both juvenile leaves and adult leaves in replicate, independent trials and asked whether those QTL changed with ontogeny. In both juvenile and adult leaves, I detected a single major QTL on chromosome 2 that explained much of the genetic variance. Although additional QTL were detected, there were no consistent differences in the genetic architecture of trichome density measured on juvenile and adult leaves. The finding of a single QTL of major effect for a trait of known adaptive importance suggests that genes of major effect may play an important role in adaptation.

Theories of adaptation: what they do and don't say

Theoretical work on adaptation has lagged behind experimental. But two classes of adaptation model have been partly explored. One is phenotypic and the other DNA sequence based. I briefly consider an example of each--Fisher's geometric model and Gillespie's mutational landscape model, respectively--reviewing recent results. Despite their fundamental differences, these models give rise to several strikingly similar results. I consider possible reasons for this congruence. I also emphasize what predictions do and, as important, do not follow from these models.

Heterozygote advantage and the maintenance of polymorphism for multilocus traits

Explaining how polymorphism is maintained in the face of selection remains a puzzle since selection tends to erode genetic variation. Provided an infinitely large unsubdivided population and no frequency-dependance of selective values, heterozygote advantage is the text book explanation for the maintenance of polymorphism when selection acts at a diallelic locus. Here, we investigate whether this remains true when selection acts at multiple diallelic loci. We use five different definitions of heterozygote advantage that largely cover this concept for multiple loci. Using extensive numerical simulations, we found no clear associations between the presence of any of the five definitions of heterozygote advantage and the maintenance of polymorphism at all loci. The strength of the association decreases as the number of loci increases or as recombination decreases. We conclude that heterozygote advantage cannot be a general mechanism for the maintenance of genetic polymorphism at multiple loci. These findings suggest that a correlation between the number of heterozygote loci and fitness is not warranted on theoretical ground.

Generating phenotypic variation: prospects from "evo-devo" research on Bicyclus anynana wing patterns

Understanding the generation of phenotypic variation is an important challenge for modern evolutionary biology, and butterfly wing patterns are an exciting system that can shed some light on this issue. Here, we report on recent advances in the genetics of Bicyclus anynana butterflies. This system provides the potential for a fully integrated study of the evolutionary and developmental processes underlying diversity in morphology.

The genetic architecture of response to long-term artificial selection for oil concentration in the maize kernel

In one of the longest-running experiments in biology, researchers at the University of Illinois have selected for altered composition of the maize kernel since 1896. Here we use an association study to infer the genetic basis of dramatic changes that occurred in response to selection for changes in oil concentration. The study population was produced by a cross between the high- and low-selection lines at generation 70, followed by 10 generations of random mating and the derivation of 500 lines by selfing. These lines were genotyped for 488 genetic markers and the oil concentration was evaluated in replicated field trials. Three methods of analysis were tested in simulations for ability to detect quantitative trait loci (QTL). The most effective method was model selection in multiple regression. This method detected approximately 50 QTL accounting for approximately 50% of the genetic variance, suggesting that >50 QTL are involved. The QTL effect estimates are small and largely additive. About 20% of the QTL have negative effects (i.e., not predicted by the parental difference), which is consistent with hitchhiking and small population size during selection. The large number of QTL detected accounts for the smooth and sustained response to selection throughout the twentieth century.

Approaches to determine clinical significance of genetic variants

The clinical significance of genetic variants (single nucleotide polymorphisms, SNPs) has implications for risk assessment and also for predicting the outcome of a disease process, especially in response to intervention. Approaches to determine the clinical significance of genetic polymorphisms are now beginning to be developed. The technology tools and procedures currently available have significant potential in identifying and validating polymorphisms associated with environmentally sensitive phenotypes. Numerous concepts can now provide the methodology to selectively identify SNPs with the potential for impacting gene function. These include computational algorithms, biochemical assays, yeast mutagenicity assays, and epidemiological studies, either as a stand-alone screen, or in various combinations depending on the gene of interest. Proof of principle will ultimately depend on large-scale epidemiological and clinical studies, but will require intensive resources. Therefore, the use of the mouse as a preclinical biological model is paramount in helping screen valid SNPs or combinations of SNPs for human studies. But more importantly, mouse modeling will help answer the question of what role gene variants play in sensitivity or resistance to a wide variety of environmental insults ranging from toxic chemicals and carcinogens to more mundane and routine exposure items, such as dietary factors, air quality, over the counter and prescription medications, and ultraviolet light. Our focus on SNPs that result in an amino acid change is a matter of expediency because these variants are more amenable to the prescreening approaches currently available that are expected to help identify SNPs that affect protein function. The mouse models generated to evaluate the environmental relevance of selected SNPs will be extremely valuable biological tools to validate gene variant and environment interaction in a variety of settings. Informative mouse models will also provide the basis of pursuing relevant SNPs in epidemiological and clinical investigations.

Quantitative trait locus mapping in natural populations: progress, caveats and future directions

Over the last 15 years quantitative trait locus (QTL) mapping has become a popular method for understanding the genetic basis of continuous variation in a variety of systems. For example, the technique is now an integral tool in medical genetics, livestock production, plant breeding and population genetics of model organisms. Ten years ago, it was suggested that the method could be used to understand continuous variation in natural populations. In this review I: (i) clarify what is meant by natural population in the QTL context, (ii) discuss whether evolutionary biologists have successfully mapped QTL in natural populations, (iii) highlight some of the questions that have been addressed by QTL mapping in natural populations, (iv) describe how QTL mapping can be conducted in unmanipulated natural populations, (v) highlight some of the limitations of QTL mapping and (vi) try to predict some future directions for QTL mapping in natural populations.

The genetic basis of male fertility in relation to haplodiploid reproduction in Leptopilina clavipes (Hymenoptera: Figitidae)

Traits under relaxed selection are expected to become reduced or disappear completely, a process called vestigialization. In parthenogenetic populations, traits historically involved in sexual reproduction are no longer under selection and potentially subject to such reduction. In Leptopilina clavipes, thelytokous (parthenogenetic) populations are infected by Wolbachia bacteria. Arrhenotokous populations do not harbor Wolbachia. When antibiotics are applied to infected females, they are cured from their infection and males arise. Such males are capable of producing offspring with uninfected females, but with lower fertilization success than sexual males. This can be attributed to the lack of selection on male fertility in thelytokous lines. In this study we used this variation in L. clavipes male fertility to determine the genetic basis of this trait. Males from cured thelytokous populations were crossed to females from uninfected populations. Using AFLP markers, a genetic linkage map was generated, consisting of five linkage groups and spanning a total distance of 219.9 cM. A single QTL of large effect (explaining 46.5% of the phenotypic variance) was identified for male fertility, which we call male fertility factor (mff). We discuss possible mechanisms underlying the effect of mff, as well as mechanisms involved in vestigialization of traits involved in sexual reproduction.

Replication of an Egfr-wing shape association in a wild-caught cohort of Drosophila melanogaster

Linkage disequilibrium mapping has been used extensively in medical and evolutionary genetics to map causal polymorphisms within genes associated with disease status or phenotypic variation for a trait. However, the initial findings of most nonhuman studies have not been replicated in subsequent studies, due in part to false positives, as well as additional factors that can render true positives unreplicable. These factors may be more severe when the initial study is performed using an experimental population of organisms reared under controlled lab conditions. We demonstrate that despite considerable phenotypic differences for wing shape between a lab-reared experimental population and a wild-caught cohort of Drosophila melanogaster, an association between a putative regulatory polymorphism in Egfr and wing shape can be replicated. These results are discussed both within the framework of future association-mapping studies and within the context of the evolutionary dynamics of alleles in populations.

Impact of founder population, drift and selection on the genetic diversity of a recently translocated tree population

Recently established, temperate tree populations combine a high level of differentiation for adaptive traits, suggesting rapid genetic evolution, with a high level of genetic diversity within population, suggesting a limited impact of genetic drift and purifying selection. To study experimentally the evolutionary forces in a recently established population, we assessed the spatial and temporal patterns of genetic diversity within a disjunct population of Cedrus atlantica established 140 years ago in south-eastern France from a North African source. The population is expanding through natural regeneration. Three generations were sampled, including founder trees. We analysed 12 isozyme loci, three of which were previously found in tight association with selected genes, and quantitative traits. No bottleneck effect was detected in the founder generation, but a simple test of allelic association revealed an initial disequilibrium which disappeared in the following generations. The impact of genetic drift during secondary evolution was limited, as suggested by the weak temporal differentiation. The genetic load was not reduced after 3 generations, and the quantitative variation for adaptive traits did not change either. Thus, initial genetic changes first proceed from a rapid re-organisation of the diversity through mating and recombination, whereas genetic erosion through drift and selection is delayed due to temporal and spatial stochasticity. Two life-history traits of trees contribute to slowing down the processes of genetic erosion: perenniality and large spatial scale. Thus, one would expect recently established tree populations to have a higher diversity than older ones, which seems in accordance with experimental surveys.

Genome-wide association studies: theoretical and practical concerns

To fully understand the allelic variation that underlies common diseases, complete genome sequencing for many individuals with and without disease is required. This is still not technically feasible. However, recently it has become possible to carry out partial surveys of the genome by genotyping large numbers of common SNPs in genome-wide association studies. Here, we outline the main factors - including models of the allelic architecture of common diseases, sample size, map density and sample-collection biases - that need to be taken into account in order to optimize the cost efficiency of identifying genuine disease-susceptibility loci.

Mapping quantitative trait loci in multiple populations of Arabidopsis thaliana identifies natural allelic variation for trichome density

The majority of biological traits are genetically complex. Mapping the quantitative trait loci (QTL) that determine these phenotypes is a powerful means for estimating many parameters of the genetic architecture for a trait and potentially identifying the genes responsible for natural variation. Typically, such experiments are conducted in a single mapping population and, therefore, have only the potential to reveal genomic regions that are polymorphic between the progenitors of the population. What remains unclear is how well the QTL identified in any one mapping experiment characterize the genetics that underlie natural variation in traits. Here we provide QTL mapping data for trichome density from four recombinant inbred mapping populations of Arabidopsis thaliana. By aligning the linkage maps for these four populations onto a common physical map, the results from each experiment were directly compared. Seven of the nine QTL identified are population specific while two were mapped in all four populations. Our results show that many lineage-specific alleles that either increase or decrease trichome density persist in natural populations and that most of this genetic variation is additive. More generally, these findings suggest that the use of multiple populations holds great promise for better understanding the genetic architecture of natural variation.

Redistribution of gene frequency and changes of genetic variation following a bottleneck in population size

Although the distribution of frequencies of genes influencing quantitative traits is important to our understanding of their genetic basis and their evolution, direct information from laboratory experiments is very limited. In theory, different models of selection and mutation generate different predictions of frequency distributions. When a large population at mutation-selection balance passes through a rapid bottleneck in size, the frequency distribution of genes is dramatically altered, causing changes in observable quantities such as the mean and variance of quantitative traits. We investigate the gene frequency distribution of a population at mutation-selection balance under a joint-effect model of real stabilizing and pleiotropic selection and its redistribution and thus changes of the genetic properties of metric and fitness traits after the population passes a rapid bottleneck and expands in size. If all genes that affect the trait are neutral with respect to fitness, the additive genetic variance (VA) is always reduced by a bottleneck in population size, regardless of their degree of dominance. For genes that have been under selection, VA increases following a bottleneck if they are (partially) recessive, while the dominance variance increases substantially for any degree of dominance. With typical estimates of mutation parameters, the joint-effect model can explain data from laboratory experiments on the effect of bottlenecking on fitness and morphological traits, providing further support for it as a plausible mechanism for maintenance of quantitative genetic variation.

The genetic theory of adaptation: a brief history

Theoretical studies of adaptation have exploded over the past decade. This work has been inspired by recent, surprising findings in the experimental study of adaptation. For example, morphological evolution sometimes involves a modest number of genetic changes, with some individual changes having a large effect on the phenotype or fitness. Here I survey the history of adaptation theory, focusing on the rise and fall of various views over the past century and the reasons for the slow development of a mature theory of adaptation. I also discuss the challenges that face contemporary theories of adaptation.

The human genome project and the discovery of genetic determinants of cancer susceptibility

The Human Genome Project has recently provided a great deal of information on the sequence that comprises the human genome. We are now in the process of structuring and deciphering the 3 x 10(9) base sequence in order to gain insights into its functional role. Several efforts are focusing on the search for DNA sequence variations underlying common/complex diseases that constitute a real burden in terms of public health measures. As expected, the genetic architecture of these complex traits, shows tremendous complexity, and the discovery and characterisation of susceptibility alleles constitute a real challenge for the geneticist. Conceptual and experimental genetic approaches aimed at dissecting the molecular features of susceptibility genes, in particular those predisposing to cancer, are outlined and discussed in this review.

Many amino acid substitution variants identified in DNA repair genes during human population screenings are predicted to impact protein function

Over 520 different amino acid substitution variants have been previously identified in the systematic screening of 91 human DNA repair genes for sequence variation. Two algorithms were employed to predict the impact of these amino acid substitutions on protein activity. Sorting Intolerant from Tolerant (SIFT) classified 226 of 508 variants (44%) as "Intolerant." Polymorphism Phenotyping (PolyPhen) classed 165 of 489 amino acid substitutions (34%) as "Probably or possibly damaging." Another 9-15% of the variants were classed as "Potentially intolerant or damaging." The results from the two algorithms are highly associated, with concordance in predicted impact observed for approximately 62% of the variants. Twenty-one to thirty-one percent of the variant proteins are predicted to exhibit reduced activity by both algorithms. These variants occur at slightly lower individual allele frequency than do the variants classified as "Tolerant" or "Benign." Both algorithms correctly predicted the impact of 26 functionally characterized amino acid substitutions in the APE1 protein on biochemical activity, with one exception. It is concluded that a substantial fraction of the missense variants observed in the general human population are functionally relevant. These variants are expected to be the molecular genetic and biochemical basis for the associations of reduced DNA repair capacity phenotypes with elevated cancer risk.

The nk model and population genetics

The nk model of fitness interactions is examined. This model has been used by previous authors to investigate the effects of fitness epistasis on substitution dynamics in molecular evolution, and to make broader claims about the importance of epistasis. To examine these claims, an infinite-allele approximation is introduced. In this limit, it is shown that the nk model is, at an appropriate level of description, formally identical to the non-epistatic House-of-Cards model--a well-studied model in theoretical population genetics. It is further shown that in many parameter regimes, the analytical results obtained from this infinite-allele approximation are very close to results from the full nk model (with a finite number of alleles per locus). The findings presented shed light on a number of previous results.

Predictions of patterns of response to artificial selection in lines derived from natural populations

The pattern of response to artificial selection on quantitative traits in laboratory populations can tell us something of the genetic architecture in the natural population from which they were derived. We modeled artificial selection in samples drawn from natural populations in which variation had been maintained by recurrent mutation, with genes having an effect on the trait, which was subject to real stabilizing selection, and a pleitropic effect on fitness (the joint-effect model). Natural selection leads to an inverse correlation between effects and frequencies of genes, such that the frequency distribution of genes increasing the trait has an extreme U-shape. In contrast to the classical infinitesimal model, an early accelerated response and a larger variance of response among replicates were predicted. However, these are reduced if the base population has been maintained in the laboratory for some generations by random sampling prior to artificial selection. When multiple loci and linkage are also taken into account, the gametic disequilibria generated by the Bulmer and Hill-Robertson effects are such that little or no increase in variance and acceleration of response in early generations of artificial selection are predicted; further, the patterns of predicted responses for the joint-effect model now become close to those of the infinitesimal model. Comparison with data from laboratory selection experiments shows that, overall, the analysis did not provide clear support for the joint-effect model or a clear case for rejection.