Understanding quantitative genetic variation

Effect of sexual recombination on population diversity in aflatoxin production by Aspergillus flavus and evidence for cryptic heterokaryosis

Aspergillus flavus is the major producer of carcinogenic aflatoxins (AFs) in crops worldwide. Natural populations of A. flavus show tremendous variation in AF production, some of which can be attributed to environmental conditions, differential regulation of the AF biosynthetic pathway and deletions or loss-of-function mutations in the AF gene cluster. Understanding the evolutionary processes that generate genetic diversity in A. flavus may also explain quantitative differences in aflatoxigenicity. Several population studies using multilocus genealogical approaches provide indirect evidence of recombination in the genome and specifically in the AF gene cluster. More recently, A. flavus has been shown to be functionally heterothallic and capable of sexual reproduction in laboratory crosses. In the present study, we characterize the progeny from nine A. flavus crosses using toxin phenotype assays, DNA sequence-based markers and array comparative genome hybridization. We show high AF heritability linked to genetic variation in the AF gene cluster, as well as recombination through the independent assortment of chromosomes and through crossing over within the AF cluster that coincides with inferred recombination blocks and hotspots in natural populations. Moreover, the vertical transmission of cryptic alleles indicates that while an A. flavus deletion strain is predominantly homokaryotic, it may harbour AF cluster genes at a low copy number. Results from experimental matings indicate that sexual recombination is driving genetic and functional hyperdiversity in A. flavus. The results of this study have significant implications for managing AF contamination of crops and for improving biocontrol strategies using nonaflatoxigenic strains of A. flavus.

The QTN program and the alleles that matter for evolution: all that's gold does not glitter

The search for the alleles that matter, the quantitative trait nucleotides (QTNs) that underlie heritable variation within populations and divergence among them, is a popular pursuit. But what is the question to which QTNs are the answer? Although their pursuit is often invoked as a means of addressing the molecular basis of phenotypic evolution or of estimating the roles of evolutionary forces, the QTNs that are accessible to experimentalists, QTNs of relatively large effect, may be uninformative about these issues if large-effect variants are unrepresentative of the alleles that matter. Although 20th century evolutionary biology generally viewed large-effect variants as atypical, the field has recently undergone a quiet realignment toward a view of readily discoverable large-effect alleles as the primary molecular substrates for evolution. I argue that neither theory nor data justify this realignment. Models and experimental findings covering broad swaths of evolutionary phenomena suggest that evolution often acts via large numbers of small-effect polygenes, individually undetectable. Moreover, these small-effect variants are different in kind, at the molecular level, from the large-effect alleles accessible to experimentalists. Although discoverable QTNs address some fundamental evolutionary questions, they are essentially misleading about many others.

The molecular epidemiology of parasite infections: tools and applications

Molecular epidemiology, broadly defined, is the application of molecular genetic techniques to the dynamics of disease in a population. In this review, we briefly describe molecular and analytical tools available for molecular epidemiological studies and then provide an overview of how they can be applied to better understand parasitic disease. A range of new molecular tools have been developed in recent years, allowing for the direct examination of parasites from clinical or environmental samples, and providing access to relatively cheap, rapid, high throughput molecular assays. At the same time, new analytical approaches, in particular those derived from coalescent theory, have been developed to provide more robust estimates of evolutionary processes and demographic parameters from multilocus, genotypic data. To date, the primary application of molecular epidemiology has been to provide specific and sensitive identification of parasites and to resolve taxonomic issues, particularly at the species level and below. Population genetic studies have also been used to determine the extent of genetic diversity among populations of parasites and the degree to which this diversity is associated with different host cycles or epidemiologically important phenotypes. Many of these studies have also shed new light on transmission cycles of parasites, particularly the extent to which zoonotic transmission occurs, and on the prevalence and importance of mixed infections with different parasite species or intraspecific variants (polyparasitism). A major challenge, and one which is now being addressed by an increasing number of studies, is to find and utilize genetic markers for complex traits of epidemiological significance, such as drug resistance, zoonotic potential and virulence.

Molecular spandrels: tests of adaptation at the genetic level

Although much progress has been made in identifying the genes (and, in rare cases, mutations) that contribute to phenotypic variation, less is known about the effects that these genes have on fitness. Nonetheless, genes are commonly labelled as 'adaptive' if an allele has been shown to affect a phenotype with known or suspected functional importance or if patterns of nucleotide variation at the locus are consistent with positive selection. In these cases, the 'adaptive' designation may be premature and may lead to incorrect conclusions about the relationships between gene function and fitness. Experiments to test targets and agents of natural selection within a genomic context are necessary for identifying the adaptive consequences of individual alleles.

Comment on "Additive genetic breeding values correlate with the load of partially deleterious mutations"

Tomkins et al. (Reports, 14 May 2010, p. 892) reported a strong negative correlation between breeding values and mutational load in cow-pea weevils. Here, I show that this result can be attributed to a statistical artifact. By testing the observed correlation against an incorrect null hypothesis, they find a negative correlation where one does not exist.

A genome scan for quantitative trait loci influencing carcass, post-natal growth and reproductive traits in commercial Angus cattle

To gain insight into the number of loci of large effect that underlie variation in cattle, a quantitative trait locus (QTL) scan for 14 economically important traits was performed in two commercial Angus populations using 390 microsatellites, 11 single nucleotide polymorphisms (SNPs) and one duplication loci. The first population comprised 1769 registered Angus bulls born between 1955 and 2003, with Expected Progeny Differences computed by the American Angus Association. The second comprised 38 half-sib families containing 1622 steers with six post-natal growth and carcass phenotypes. Linkage analysis was performed by half-sib least squares regression with gridqtl or Bayesian Markov chain Monte Carlo analysis of complex pedigrees with loki. Of the 673 detected QTL, only 118 have previously been reported, reflecting both the conservative approach to QTL reporting in the literature, and the more liberal approach taken in this study. From 33 to 71% of the genetic variance and 35 to 56% of the phenotypic variance in each trait was explained by the detected QTL. To analyse the effects of 11 SNPs and one duplication locus within candidate genes on each trait, a single marker analysis was performed by fitting an additive allele substitution model in both mapping populations. There were 53 associations detected between the SNP/duplication loci and traits with -log(10) P(nominal) ≥ 4.0, where each association explained 0.92% to 4.4% of the genetic variance and 0.01% to 1.86% of the phenotypic variance. Of these associations, only six SNP/duplication loci were located within 8 cM of a QTL peak for the trait, with two being located at the QTL peak: SST_DG156121:c.362A>G for ribeye muscle area and TG_X05380:c.422C>T for calving ease. Strong associations between several SNP/duplication loci and trait variation were obtained in the absence of any detected linked QTL. However, we reject the causality of several commercialized DNA tests, including an association between TG_X05380:c.422C>T and marbling in Angus cattle.

Ploidally antagonistic selection maintains stable genetic polymorphism

Understanding the maintenance of genetic variation in the face of selection remains a key issue in evolutionary biology. One potential mechanism for the maintenance of genetic variation is opposing selection during the diploid and haploid stages of biphasic life cycles universal among eukaryotic sexual organisms. If haploid and diploid gene expression both occur, selection can act in each phase, potentially in opposing directions. In addition, sex-specific selection during haploid phases is likely simply because male and female gametophytes/gametes tend to have contrasting life histories. We explored the potential for the maintenance of a stable polymorphism under ploidally antagonistic as well as sex-specific selection. Furthermore, we examined the role of the chromosomal location of alleles (autosomal or sex-linked). Our analyses show that the most permissible conditions for the maintenance of polymorphism occur under negative ploidy-by-sex interactions, where stronger selection for an allele in female than male diploids is coupled with weaker selection against the allele in female than male haploids. Such ploidy-by-sex interactions also promote allele frequency differences between the sexes. With constant fitness, ploidally antagonistic selection can maintain stable polymorphisms for autosomal and X-linked genes but not for Y-linked genes. We discuss the implications of our results and outline a number of biological settings where the scenarios modeled may apply.

Replication and explorations of high-order epistasis using a large advanced intercross line pedigree

Dissection of the genetic architecture of complex traits persists as a major challenge in biology; despite considerable efforts, much remains unclear including the role and importance of genetic interactions. This study provides empirical evidence for a strong and persistent contribution of both second- and third-order epistatic interactions to long-term selection response for body weight in two divergently selected chicken lines. We earlier reported a network of interacting loci with large effects on body weight in an F(2) intercross between these high- and low-body weight lines. Here, most pair-wise interactions in the network are replicated in an independent eight-generation advanced intercross line (AIL). The original report showed an important contribution of capacitating epistasis to growth, meaning that the genotype at a hub in the network releases the effects of one or several peripheral loci. After fine-mapping of the loci in the AIL, we show that these interactions were persistent over time. The replication of five of six originally reported epistatic loci, as well as the capacitating epistasis, provides strong empirical evidence that the originally observed epistasis is of biological importance and is a contributor in the genetic architecture of this population. The stability of genetic interaction mechanisms over time indicates a non-transient role of epistasis on phenotypic change. Third-order epistasis was for the first time examined in this study and was shown to make an important contribution to growth, which suggests that the genetic architecture of growth is more complex than can be explained by two-locus interactions only. Our results illustrate the importance of designing studies that facilitate exploration of epistasis in populations for obtaining a comprehensive understanding of the genetics underlying a complex trait.

Genomic and protein structural maps of adaptive evolution of human influenza A virus to increased virulence in the mouse

Adaptive evolution is characterized by positive and parallel, or repeated selection of mutations. Mouse adaptation of influenza A virus (IAV) produces virulent mutants that demonstrate positive and parallel evolution of mutations in the hemagglutinin (HA) receptor and non-structural protein 1 (NS1) interferon antagonist genes. We now present a genomic analysis of all 11 genes of 39 mouse adapted IAV variants from 10 replicate adaptation experiments. Mutations were mapped on the primary and structural maps of each protein and specific mutations were validated with respect to virulence, replication, and RNA polymerase activity. Mouse adapted (MA) variants obtained after 12 or 20–21 serial infections acquired on average 5.8 and 7.9 nonsynonymous mutations per genome of 11 genes, respectively. Among a total of 115 nonsynonymous mutations, 51 demonstrated properties of natural selection including 27 parallel mutations. The greatest degree of parallel evolution occurred in the HA receptor and ribonucleocapsid components, polymerase subunits (PB1, PB2, PA) and NP. Mutations occurred in host nuclear trafficking factor binding sites as well as sites of virus-virus protein subunit interaction for NP, NS1, HA and NA proteins. Adaptive regions included cap binding and endonuclease domains in the PB2 and PA polymerase subunits. Four mutations in NS1 resulted in loss of binding to the host cleavage and polyadenylation specificity factor (CPSF30) suggesting that a reduction in inhibition of host gene expression was being selected. The most prevalent mutations in PB2 and NP were shown to increase virulence but differed in their ability to enhance replication and demonstrated epistatic effects. Several positively selected RNA polymerase mutations demonstrated increased virulence associated with >300% enhanced polymerase activity. Adaptive mutations that control host range and virulence were identified by their repeated selection to comprise a defined model for studying IAV evolution to increased virulence in the mouse.

Quantitative transcriptomic profiling of branching in a glycosphingolipid biosynthetic pathway

Cellular biosynthesis of macromolecules often involves highly branched enzyme pathways, thus cellular regulation of such pathways could be rather difficult. To understand the regulatory mechanism, a systematic approach could be useful. We genetically analyzed a branched biosynthetic pathway for glycosphingolipid (GSL) GM1 using correlation index-based responsible enzyme gene screening (CIRES), a novel quantitative phenotype-genotype correlation analysis. CIRES utilizes transcriptomic profiles obtained from multiple cells. Among a panel of B cell lines, expression of GM1 was negatively correlated with and suppressed by gene expression of CD77 synthase (CD77Syn), whereas no significant positive correlation was found for enzymes actually biosynthesizing GM1. Unexpectedly, a GM1-suppressive phenotype was also observed in the expression of catalytically inactive CD77Syn, ruling out catalytic consumption of lactosylceramide (LacCer) as the main cause for such negative regulation. Rather, CD77Syn seemed to limit other branching reaction(s) by targeting LacCer synthase (LacCerSyn), a proximal enzyme in the pathway, because they were closely localized in the Golgi apparatus and formed a complex. Moreover, turnover of LacCerSyn was accelerated upon CD77Syn expression to globally change the GSL species expressed. Collectively, these data suggest that transcriptomic assessment of macromolecule biosynthetic pathways can disclose a global regulatory mechanism(s) even when unexpected.

A modelling framework for the analysis of artificial-selection time series

Artificial-selection experiments constitute an important source of empirical information for breeders, geneticists and evolutionary biologists. Selected characters can generally be shifted far from their initial state, sometimes beyond what is usually considered as typical inter-specific divergence. A careful analysis of the data collected during such experiments may thus reveal the dynamical properties of the genetic architecture that underlies the trait under selection. Here, we propose a statistical framework describing the dynamics of selection-response time series. We highlight how both phenomenological models (which do not make assumptions on the nature of genetic phenomena) and mechanistic models (explaining the temporal trends in terms of e.g. mutations, epistasis or canalization) can be used to understand and interpret artificial-selection data. The practical use of the models and their implementation in a software package are demonstrated through the analysis of a selection experiment on the shape of the wing in Drosophila melanogaster.

A high-resolution linkage map for comparative genome analysis and QTL fine mapping in Asian seabass, Lates calcarifer

Background

High density linkage maps are essential for comparative analysis of synteny, fine mapping of quantitative trait loci (QTL), searching for candidate genes and facilitating genome sequence assembly. However, in most foodfish species, marker density is still low. We previously reported a first generation linkage map with 240 DNA markers and its application to preliminarily map QTL for growth traits in Asian seabass (Lates calcarifer). Here, we report a high-resolution linkage map with 790 microsatellites and SNPs, comparative analysis of synteny, fine-mapping of QTL and the identification of potential candidate genes for growth traits.

Results

A second generation linkage map of Asian seabass was developed with 790 microsatellite and SNP markers. The map spanned a genetic length of 2411.5 cM, with an average intermarker distance of 3.4 cM or 1.1 Mb. This high density map allowed for comparison of the map with Tetraodon nigroviridis genome, which revealed 16 synteny regions between the two species. Moreover, by employing this map we refined QTL to regions of 1.4 and 0.2 cM (or 400 and 50 kb) in linkage groups 2 and 3 in a population containing 380 progeny; potential candidate genes for growth traits in QTL regions were further identified using comparative genome analysis, whose effects on growth traits were investigated. Interestingly, a QTL cluster at Lca371 underlying growth traits of Asian seabass showed similarity to the cathepsin D gene of human, which is related to cancer and Alzheimer's disease.

Conclusions

We constructed a high resolution linkage map, carried out comparative mapping, refined the positions of QTL, identified candidate genes for growth traits and analyzed their effects on growth. Our study developed a framework that will be indispensable for further identification of genes and analysis of molecular variation within the refined QTL to enhance understanding of the molecular basis of growth and speed up genetic improvement of growth performance, and it also provides critical resource for future genome sequence assembly and comparative genomics studies on the evolution of fish genomes.

Intersubspecific subcongenic mouse strain analysis reveals closely linked QTLs with opposite effects on body weight

A previous genome-wide QTL study revealed many QTLs affecting postnatal body weight and growth in an intersubspecific backcross mouse population between the C57BL/6J (B6) strain and wild Mus musculus castaneus mice captured in the Philippines. Subsequently, several closely linked QTLs for body composition traits were revealed in an F(2) intercross population between B6 and B6.Cg-Pbwg1, a congenic strain on the B6 genetic background carrying the growth QTL Pbwg1 on proximal chromosome 2. However, no QTL affecting body weight has been duplicated in the F(2) population, except for mapping an overdominant QTL that causes heterosis of body weight. In this study, we developed 17 intersubspecific subcongenic strains with overlapping and nonoverlapping castaneus regions from the B6.Cg-Pbwg1 congenic strain in order to search for and genetically dissect QTLs affecting body weight into distinct closely linked loci. Phenotypic comparisons of several developed subcongenic strains with the B6 strain revealed that two closely linked but distinct QTLs that regulate body weight, named Pbwg1.11 and Pbwg1.12, are located on an 8.9-Mb region between D2Mit270 and D2Mit472 and on the next 3.6-Mb region between D2Mit205 and D2Mit182, respectively. Further analyses using F(2) segregating populations obtained from intercrosses between B6 and each of the two selected subcongenic strains confirmed the presence of these two body weight QTLs. Pbwg1.11 had an additive effect on body weight at 6, 10, and 13 weeks of age, and its castaneus allele decreased it. In contrast, the castaneus allele at Pbwg1.12 acted in a dominant fashion and surprisingly increased body weight at 6, 10, and 13 weeks of age despite the body weight of wild castaneus mice being 60% of that of B6 mice. These findings illustrate the complex genetic nature of body weight regulation and support the importance of subcongenic mouse analysis to dissect closely linked loci.

The maintenance of genetic variation for oviposition rate in two-spotted spider mites: inferences from artificial selection

Despite the directional selection acting on life-history traits, substantial amounts of standing variation for these traits have frequently been found. This variation may result from balancing selection (e.g., through genetic trade-offs) or from mutation-selection balance. These mechanisms affect allele frequencies in different ways: Under balancing selection alleles are maintained at intermediate frequencies, whereas under mutation-selection balance variation is generated by deleterious mutations and removed by directional selection, which leads to asymmetry in the distribution of allele frequencies. To investigate the importance of these two mechanisms in maintaining heritable variation in oviposition rate of the two-spotted spider mite, we analyzed the response to artificial selection. In three replicate experiments, we selected for higher and lower oviposition rate, compared to control lines. A response to selection only occurred in the downward direction. Selection for lower oviposition rate did not lead to an increase in any other component of fitness, but led to a decline in female juvenile survival. The results suggest standing variation for oviposition rate in this population consists largely of deleterious alleles, as in a mutation-selection balance. Consequently, the standing variation for this trait does not appear to be indicative of its adaptive potential.

Smaller, scale-free gene networks increase quantitative trait heritability and result in faster population recovery

One of the goals of biology is to bridge levels of organization. Recent technological advances are enabling us to span from genetic sequence to traits, and then from traits to ecological dynamics. The quantitative genetics parameter heritability describes how quickly a trait can evolve, and in turn describes how quickly a population can recover from an environmental change. Here I propose that we can link the details of the genetic architecture of a quantitative trait--i.e., the number of underlying genes and their relationships in a network--to population recovery rates by way of heritability. I test this hypothesis using a set of agent-based models in which individuals possess one of two network topologies or a linear genotype-phenotype map, 16-256 genes underlying the trait, and a variety of mutation and recombination rates and degrees of environmental change. I find that the network architectures introduce extensive directional epistasis that systematically hides and reveals additive genetic variance and affects heritability: network size, topology, and recombination explain 81% of the variance in average heritability in a stable environment. Network size and topology, the width of the fitness function, pre-change additive variance, and certain interactions account for ∼75% of the variance in population recovery times after a sudden environmental change. These results suggest that not only the amount of additive variance, but importantly the number of loci across which it is distributed, is important in regulating the rate at which a trait can evolve and populations can recover. Taken in conjunction with previous research focused on differences in degree of network connectivity, these results provide a set of theoretical expectations and testable hypotheses for biologists working to span levels of organization from the genotype to the phenotype, and from the phenotype to the environment.

Progress and promise of genome-wide association studies for human complex trait genetics

Enormous progress in mapping complex traits in humans has been made in the last 5 yr. There has been early success for prevalent diseases with complex phenotypes. These studies have demonstrated clearly that, while complex traits differ in their underlying genetic architectures, for many common disorders the predominant pattern is that of many loci, individually with small effects on phenotype. For some traits, loci of large effect have been identified. For almost all complex traits studied in humans, the sum of the identified genetic effects comprises only a portion, generally less than half, of the estimated trait heritability. A variety of hypotheses have been proposed to explain why this might be the case, including untested rare variants, and gene-gene and gene-environment interaction. Effort is currently being directed toward implementation of novel analytic approaches and testing rare variants for association with complex traits using imputed variants from the publicly available 1000 Genomes Project resequencing data and from direct resequencing of clinical samples. Through integration with annotations and functional genomic data as well as by in vitro and in vivo experimentation, mapping studies continue to characterize functional variants associated with complex traits and address fundamental issues such as epistasis and pleiotropy. This review focuses primarily on the ways in which genome-wide association studies (GWASs) have revolutionized the field of human quantitative genetics.

Assessing the complex architecture of polygenic traits in diverged yeast populations

Phenotypic variation arising from populations adapting to different niches has a complex underlying genetic architecture. A major challenge in modern biology is to identify the causative variants driving phenotypic variation. Recently, the baker's yeast, Saccharomyces cerevisiae has emerged as a powerful model for dissecting complex traits. However, past studies using a laboratory strain were unable to reveal the complete architecture of polygenic traits. Here, we present a linkage study using 576 recombinant strains obtained from crosses of isolates representative of the major lineages. The meiotic recombinational landscape appears largely conserved between populations; however, strain-specific hotspots were also detected. Quantitative measurements of growth in 23 distinct ecologically relevant environments show that our recombinant population recapitulates most of the standing phenotypic variation described in the species. Linkage analysis detected an average of 6.3 distinct QTLs for each condition tested in all crosses, explaining on average 39% of the phenotypic variation. The QTLs detected are not constrained to a small number of loci, and the majority are specific to a single cross-combination and to a specific environment. Moreover, crosses between strains of similar phenotypes generate greater variation in the offspring, suggesting the presence of many antagonistic alleles and epistatic interactions. We found that subtelomeric regions play a key role in defining individual quantitative variation, emphasizing the importance of the adaptive nature of these regions in natural populations. This set of recombinant strains is a powerful tool for investigating the complex architecture of polygenic traits.

Genome-wide association study SNPs in the human genome diversity project populations: does selection affect unlinked SNPs with shared trait associations?

Genome-wide association studies (GWAS) have identified more than 2,000 trait-SNP associations, and the number continues to increase. GWAS have focused on traits with potential consequences for human fitness, including many immunological, metabolic, cardiovascular, and behavioral phenotypes. Given the polygenic nature of complex traits, selection may exert its influence on them by altering allele frequencies at many associated loci, a possibility which has yet to be explored empirically. Here we use 38 different measures of allele frequency variation and 8 iHS scores to characterize over 1,300 GWAS SNPs in 53 globally distributed human populations. We apply these same techniques to evaluate SNPs grouped by trait association. We find that groups of SNPs associated with pigmentation, blood pressure, infectious disease, and autoimmune disease traits exhibit unusual allele frequency patterns and elevated iHS scores in certain geographical locations. We also find that GWAS SNPs have generally elevated scores for measures of allele frequency variation and for iHS in Eurasia and East Asia. Overall, we believe that our results provide evidence for selection on several complex traits that has caused changes in allele frequencies and/or elevated iHS scores at a number of associated loci. Since GWAS SNPs collectively exhibit elevated allele frequency measures and iHS scores, selection on complex traits may be quite widespread. Our findings are most consistent with this selection being either positive or negative, although the relative contributions of the two are difficult to discern. Our results also suggest that trait-SNP associations identified in Eurasian samples may not be present in Africa, Oceania, and the Americas, possibly due to differences in linkage disequilibrium patterns. This observation suggests that non-Eurasian and non-East Asian sample populations should be included in future GWAS.

Carbohydrate metabolic pathway genes associated with quantitative trait loci (QTL) for obesity and type 2 diabetes: identification by data mining

Increasing consumption of refined carbohydrates is now being recognized as a primary contributor to the development of nutritionally related chronic diseases such as obesity and type 2 diabetes mellitus (T2DM). A data mining approach was used to evaluate the role of carbohydrate metabolic pathway genes in the development of obesity and T2DM. Data from public databases were used to map the position of the carbohydrate metabolic pathway genes to known quantitative trait loci (QTL) for obesity and T2DM and for examining the pathway genes for the presence of sequence and structural genetic variants such as single nucleotide polymorphisms (SNPs) and copy number variants (CNS), respectively. The results demonstrated that a majority of the genes of the carbohydrate metabolic pathways are associated with QTL for obesity and many for T2DM. In addition, some key genes of the pathways also encode non-synonymous SNPs that exhibit significant differences in population frequencies. This study emphasizes the significance of the metabolic pathways genes in the development of disease phenotypes, its differential occurrence across populations and between individuals, and a strategy for interpreting an individuals' risk for disease.

The statistical mechanics of a polygenic character under stabilizing selection, mutation and drift

By exploiting an analogy between population genetics and statistical mechanics, we study the evolution of a polygenic trait under stabilizing selection, mutation and genetic drift. This requires us to track only four macroscopic variables, instead of the distribution of all the allele frequencies that influence the trait. These macroscopic variables are the expectations of: the trait mean and its square, the genetic variance, and of a measure of heterozygosity, and are derived from a generating function that is in turn derived by maximizing an entropy measure. These four macroscopics are enough to accurately describe the dynamics of the trait mean and of its genetic variance (and in principle of any other quantity). Unlike previous approaches that were based on an infinite series of moments or cumulants, which had to be truncated arbitrarily, our calculations provide a well-defined approximation procedure. We apply the framework to abrupt and gradual changes in the optimum, as well as to changes in the strength of stabilizing selection. Our approximations are surprisingly accurate, even for systems with as few as five loci. We find that when the effects of drift are included, the expected genetic variance is hardly altered by directional selection, even though it fluctuates in any particular instance. We also find hysteresis, showing that even after averaging over the microscopic variables, the macroscopic trajectories retain a memory of the underlying genetic states.

An evolutionary framework for association testing in resequencing studies

Sequencing technologies are becoming cheap enough to apply to large numbers of study participants and promise to provide new insights into human phenotypes by bringing to light rare and previously unknown genetic variants. We develop a new framework for the analysis of sequence data that incorporates all of the major features of previously proposed approaches, including those focused on allele counts and allele burden, but is both more general and more powerful. We harness population genetic theory to provide prior information on effect sizes and to create a pooling strategy for information from rare variants. Our method, EMMPAT (Evolutionary Mixed Model for Pooled Association Testing), generates a single test per gene (substantially reducing multiple testing concerns), facilitates graphical summaries, and improves the interpretation of results by allowing calculation of attributable variance. Simulations show that, relative to previously used approaches, our method increases the power to detect genes that affect phenotype when natural selection has kept alleles with large effect sizes rare. We demonstrate our approach on a population-based re-sequencing study of association between serum triglycerides and variation in ANGPTL4.

Genetic architecture of a feeding adaptation: garter snake (Thamnophis) resistance to tetrodotoxin bearing prey

Detailing the genetic basis of adaptive variation in natural populations is a first step towards understanding the process of adaptive evolution, yet few ecologically relevant traits have been characterized at the genetic level in wild populations. Traits that mediate coevolutionary interactions between species are ideal for studying adaptation because of the intensity of selection and the well-characterized ecological context. We have previously described the ecological context, evolutionary history and partial genetic basis of tetrodotoxin (TTX) resistance in garter snakes (Thamnophis). Derived mutations in a voltage-gated sodium channel gene (Na(v)1.4) in three garter snake species are associated with resistance to TTX, the lethal neurotoxin found in their newt prey (Taricha). Here we evaluate the contribution of Na(v)1.4 alleles to TTX resistance in two of those species from central coastal California. We measured the phenotypes (TTX resistance) and genotypes (Na(v)1.4 and microsatellites) in a local sample of Thamnophis atratus and Thamnophis sirtalis. Allelic variation in Na(v)1.4 explains 23 per cent of the variation in TTX resistance in T. atratus while variation in a haphazard sample of the genome (neutral microsatellite markers) shows no association with the phenotype. Similarly, allelic variation in Na(v)1.4 correlates almost perfectly with TTX resistance in T. sirtalis, but neutral variation does not. These strong correlations suggest that Na(v)1.4 is a major effect locus. The simple genetic architecture of TTX resistance in garter snakes may significantly impact the dynamics of phenotypic coevolution. Fixation of a few alleles of major effect in some garter snake populations may have led to the evolution of extreme phenotypes and an 'escape' from the arms race with newts.

Variation in acoustic signalling traits exhibits footprints of sexual selection

Phenotypic variation is ubiquitous in nature and a precondition for adaptive evolution. However, theory predicts that the extent of phenotypic variation should decrease with increasing strength of selection on a trait. Comparative analyses of trait variability have repeatedly used this expectation to infer the type or strength of selection. Yet, the suggested influence of selection on trait variability has rarely been tested empirically. In the present study, I compare estimates of sexual selection strength and trait variability from published data. I constricted the analysis to acoustic courtship traits in amphibians and insects with known variability and corresponding results of female binary choice experiments on these traits. Trait variability and strength of sexual selection were significantly correlated, and both were correlated with signal duration. Because traits under stronger selection had lower variation even after the effect of signal duration was eliminated, I conclude that traces of the strength of selection can be observed with respect to variation of acoustic signaling traits in insects and amphibians. The analysis also shows that traits under stabilizing selection have significantly lower phenotypic variability than traits under directional selection.

Effects of missing marker and segregation distortion on QTL mapping in F2 populations

Missing marker and segregation distortion are commonly encountered in actual quantitative trait locus (QTL) mapping populations. Our objective in this study was to investigate the impact of the two factors on QTL mapping through computer simulations. Results indicate that detection power decreases with increasing levels of missing markers, and the false discovery rate increases. Missing markers have greater effects on smaller effect QTL and smaller size populations. The effect of missing markers can be quantified by a population with a reduced size similar to the marker missing rate. As for segregation distortion, if the distorted marker is not closely linked with any QTL, it will not have significant impact on QTL mapping; otherwise, the impact of the distortion will depend on the degree of dominance of QTL, frequencies of the three marker types, the linkage distance between the distorted marker and QTL, and the mapping population size. Sometimes, the distortion can result in a higher genetic variance than that of non-distortion, and therefore benefits the detection of linked QTL. A formula of the ratio of genetic variance explained by QTL under distortion and non-distortion was given in this study, so as to easily determine whether the segregation distortion marker (SDM) increases or decreases the QTL detection power. The effect of SDM decreases rapidly as its linkage relationship with QTL becomes looser. In general, distorted markers will not have a great effect on the position and effect estimations of QTL, and their effects can be ignored in large-size mapping populations.

Melanin coloration has temperature-dependent effects on breeding performance that may maintain phenotypic variation in a passerine bird

Fluctuating selection pressure may maintain phenotypic variation because of different types of individuals being adapted to different environmental conditions. We show that the extensive variation in the coloration of male pied flycatchers (Ficedula hypoleuca) can be maintained through differences in the reproductive success of male phenotypes under different conditions. The effects of weather conditions on the relative success of different male phenotypes varied between different phases of breeding. The reproductive output of black males was the highest when it was cold during egg-laying but warm during the nestling period, whereas the fledgling production of brown males was highest when it was continuously warm. In addition, male forehead and wing patch sizes had context-dependent effects on timing of breeding and nestling mortality, respectively. These results indicate that environmental heterogeneity plays a role in maintaining phenotypic variation. As melanin-based coloration is heritable, climate change may alter phenotype frequencies depending on the patterns of warming.

Adaptation - not by sweeps alone

There has been recent progress in identifying selective sweeps underlying a range of adaptations. Jonathan Pritchard and Anna Di Rienzo argue that many adaptive events in natural populations may occur by polygenic adaptation, which would largely go undetected by conventional methods for detecting selection.

Adaptations to sexual selection and sexual conflict: insights from experimental evolution and artificial selection

Artificial selection and experimental evolution document natural selection under controlled conditions. Collectively, these techniques are continuing to provide fresh and important insights into the genetic basis of evolutionary change, and are now being employed to investigate mating behaviour. Here, we focus on how selection techniques can reveal the genetic basis of post-mating adaptations to sexual selection and sexual conflict. Alteration of the operational sex ratio of adult Drosophila over just a few tens of generations can lead to altered ejaculate allocation patterns and the evolution of resistance in females to the costly effects of elevated mating rates. We provide new data to show how male responses to the presence of rivals can evolve. For several traits, the way in which males responded to rivals was opposite in lines selected for male-biased, as opposed to female-biased, adult sex ratio. This shows that the manipulation of the relative intensity of intra- and inter-sexual selection can lead to replicable and repeatable effects on mating systems, and reveals the potential for significant contemporary evolutionary change. Such studies, with important safeguards, have potential utility for understanding sexual selection and sexual conflict across many taxa. We discuss how artificial selection studies combined with genomics will continue to deepen our knowledge of the evolutionary principles first laid down by Darwin 150 years ago.

A genome-wide association study of Cloninger's temperament scales: implications for the evolutionary genetics of personality

Variation in personality traits is 30-60% attributed to genetic influences. Attempts to unravel these genetic influences at the molecular level have, so far, been inconclusive. We performed the first genome-wide association study of Cloninger's temperament scales in a sample of 5117 individuals, in order to identify common genetic variants underlying variation in personality. Participants' scores on Harm Avoidance, Novelty Seeking, Reward Dependence, and Persistence were tested for association with 1,252,387 genetic markers. We also performed gene-based association tests and biological pathway analyses. No genetic variants that significantly contribute to personality variation were identified, while our sample provides over 90% power to detect variants that explain only 1% of the trait variance. This indicates that individual common genetic variants of this size or greater do not contribute to personality trait variation, which has important implications regarding the genetic architecture of personality and the evolutionary mechanisms by which heritable variation is maintained.

Mutations and quantitative genetic variation: lessons from Drosophila

A central issue in evolutionary quantitative genetics is to understand how genetic variation for quantitative traits is maintained in natural populations. Estimates of genetic variation and of genetic correlations and pleiotropy among multiple traits, inbreeding depression, mutation rates for fitness and quantitative traits and of the strength and nature of selection are all required to evaluate theoretical models of the maintenance of genetic variation. Studies in Drosophila melanogaster have shown that a substantial fraction of segregating variation for fitness-related traits in Drosophila is due to rare deleterious alleles maintained by mutation-selection balance, with a smaller but significant fraction attributable to intermediate frequency alleles maintained by alleles with antagonistic pleiotropic effects, and late-age-specific effects. However, the nature of segregating variation for traits under stabilizing selection is less clear and requires more detailed knowledge of the loci, mutation rates, allelic effects and frequencies of molecular polymorphisms affecting variation in suites of pleiotropically connected traits. Recent studies in D. melanogaster have revealed unexpectedly complex genetic architectures of many quantitative traits, with large numbers of pleiotropic genes and alleles with sex-, environment- and genetic background-specific effects. Future genome wide association analyses of many quantitative traits on a common panel of fully sequenced Drosophila strains will provide much needed empirical data on the molecular genetic basis of quantitative traits.

On epistasis: why it is unimportant in polygenic directional selection

There is a difference in viewpoint of developmental and evo-devo geneticists versus breeders and students of quantitative evolution. The former are interested in understanding the developmental process; the emphasis is on identifying genes and studying their action and interaction. Typically, the genes have individually large effects and usually show substantial dominance and epistasis. The latter group are interested in quantitative phenotypes rather than individual genes. Quantitative traits are typically determined by many genes, usually with little dominance or epistasis. Furthermore, epistatic variance has minimum effect, since the selected population soon arrives at a state in which the rate of change is given by the additive variance or covariance. Thus, the breeder's custom of ignoring epistasis usually gives a more accurate prediction than if epistatic variance were included in the formulae.

Ecological opportunity and the origin of adaptive radiations

Ecological opportunity--through entry into a new environment, the origin of a key innovation or extinction of antagonists--is widely thought to link ecological population dynamics to evolutionary diversification. The population-level processes arising from ecological opportunity are well documented under the concept of ecological release. However, there is little consensus as to how these processes promote phenotypic diversification, rapid speciation and adaptive radiation. We propose that ecological opportunity could promote adaptive radiation by generating specific changes to the selective regimes acting on natural populations, both by relaxing effective stabilizing selection and by creating conditions that ultimately generate diversifying selection. We assess theoretical and empirical evidence for these effects of ecological opportunity and review emerging phylogenetic approaches that attempt to detect the signature of ecological opportunity across geological time. Finally, we evaluate the evidence for the evolutionary effects of ecological opportunity in the diversification of Caribbean Anolis lizards. Some of the processes that could link ecological opportunity to adaptive radiation are well documented, but others remain unsupported. We suggest that more study is required to characterize the form of natural selection acting on natural populations and to better describe the relationship between ecological opportunity and speciation rates.

The genetics of human adaptation: hard sweeps, soft sweeps, and polygenic adaptation

There has long been interest in understanding the genetic basis of human adaptation. To what extent are phenotypic differences among human populations driven by natural selection? With the recent arrival of large genome-wide data sets on human variation, there is now unprecedented opportunity for progress on this type of question. Several lines of evidence argue for an important role of positive selection in shaping human variation and differences among populations. These include studies of comparative morphology and physiology, as well as population genetic studies of candidate loci and genome-wide data. However, the data also suggest that it is unusual for strong selection to drive new mutations rapidly to fixation in particular populations (the 'hard sweep' model). We argue, instead, for alternatives to the hard sweep model: in particular, polygenic adaptation could allow rapid adaptation while not producing classical signatures of selective sweeps. We close by discussing some of the likely opportunities for progress in the field.

Additive genetic breeding values correlate with the load of partially deleterious mutations

The mutation-selection-balance model predicts most additive genetic variation to arise from numerous mildly deleterious mutations of small effect. Correspondingly, "good genes" models of sexual selection and recent models for the evolution of sex are built on the assumption that mutational loads and breeding values for fitness-related traits are correlated. In support of this concept, inbreeding depression was negatively genetically correlated with breeding values for traits under natural and sexual selection in the weevil Callosobruchus maculatus. The correlations were stronger in males and strongest for condition. These results confirm the role of existing, partially recessive mutations in maintaining additive genetic variation in outbred populations, reveal the nature of good genes under sexual selection, and show how sexual selection can offset the cost of sex.

Retention of low-fitness genotypes over six decades of admixture between native and introduced tiger salamanders

BACKGROUND

Introductions of non-native tiger salamanders into the range of California tiger salamanders have provided a rare opportunity to study the early stages of secondary contact and hybridization. We produced first- and second-generation hybrid salamanders in the lab and measured viability among these early-generation hybrid crosses to determine the strength of the initial barrier to gene exchange. We also created contemporary-generation hybrids in the lab and evaluated the extent to which selection has affected fitness over approximately 20 generations of admixture. Additionally, we examined the inheritance of quantitative phenotypic variation to better understand how evolution has progressed since secondary contact.

RESULTS

We found significant variation in the fitness of hybrids, with non-native backcrosses experiencing the highest survival and F2 hybrids the lowest. Contemporary-generation hybrids had similar survival to that of F2 families, contrary to our expectation that 20 generations of selection in the wild would eliminate unfit genotypes and increase survival. Hybrid survival clearly exhibited effects of epistasis, whereas size and growth showed mostly additive genetic variance, and time to metamorphosis showed substantial dominance.

CONCLUSIONS

Based on first- and second- generation cross types, our results suggest that the initial barrier to gene flow between these two species was relatively weak, and subsequent evolution has been generally slow. The persistence of low-viability recombinant hybrid genotypes in some contemporary populations illustrates that while hybridization can provide a potent source of genetic variation upon which natural selection can act, the sorting of fit from unfit gene combinations might be inefficient in highly admixed populations. Spatio-temporal fluctuation in selection or complex genetics has perhaps stalled adaptive evolution in this system despite selection for admixed genotypes within generations.

Something old and something new: wedding recombinant inbred lines with traditional line cross analysis increases power to describe gene interactions

In this paper we present a novel approach to quantifying genetic architecture that combines recombinant inbred lines (RIL) with line cross analysis (LCA). LCA is a method of quantifying directional genetic effects (i.e. summed effects of all loci) that differentiate two parental lines. Directional genetic effects are thought to be critical components of genetic architecture for the long term response to selection and as a cause of inbreeding depression. LCA typically begins with two inbred parental lines that are crossed to produce several generations such as F1, F2, and backcrosses to each parent. When a RIL population (founded from the same P1 and P2 as was used to found the line cross population) is added to the LCA, the sampling variance of several nonadditive genetic effect estimates is greatly reduced. Specifically, estimates of directional dominance, additive x additive, and dominance x dominance epistatic effects are reduced by 92%, 94%, and 56% respectively. The RIL population can be simultaneously used for QTL identification, thus uncovering the effects of specific loci or genomic regions as elements of genetic architecture. LCA and QTL mapping with RIL provide two qualitatively different measures of genetic architecture with the potential to overcome weaknesses of each approach alone. This approach provides cross-validation of the estimates of additive and additive x additive effects, much smaller confidence intervals on dominance, additive x additive and dominance x dominance estimates, qualitatively different measures of genetic architecture, and the potential when used together to balance the weaknesses of LCA or RIL QTL analyses when used alone.

Fluctuating selection: the perpetual renewal of adaptation in variable environments

Darwin insisted that evolutionary change occurs very slowly over long periods of time, and this gradualist view was accepted by his supporters and incorporated into the infinitesimal model of quantitative genetics developed by R. A. Fisher and others. It dominated the first century of evolutionary biology, but has been challenged in more recent years both by field surveys demonstrating strong selection in natural populations and by quantitative trait loci and genomic studies, indicating that adaptation is often attributable to mutations in a few genes. The prevalence of strong selection seems inconsistent, however, with the high heritability often observed in natural populations, and with the claim that the amount of morphological change in contemporary and fossil lineages is independent of elapsed time. I argue that these discrepancies are resolved by realistic accounts of environmental and evolutionary changes. First, the physical and biotic environment varies on all time-scales, leading to an indefinite increase in environmental variance over time. Secondly, the intensity and direction of natural selection are also likely to fluctuate over time, leading to an indefinite increase in phenotypic variance in any given evolving lineage. Finally, detailed long-term studies of selection in natural populations demonstrate that selection often changes in direction. I conclude that the traditional gradualist scheme of weak selection acting on polygenic variation should be supplemented by the view that adaptation is often based on oligogenic variation exposed to commonplace, strong, fluctuating natural selection.

Major and minor QTL and epistasis contribute to fatty acid compositions and oil concentration in high-oil maize

High-oil maize is a useful genetic resource for genomic investigation in plants. To determine the genetic basis of oil concentration and composition in maize grain, a recombinant inbred population derived from a cross between normal line B73 and high-oil line By804 was phenotyped using gas chromatography, and genotyped with 228 molecular markers. A total of 42 individual QTL, associated with fatty acid compositions and oil concentration, were detected in 21 genomic regions. Five major QTL were identified for measured traits, one each of which explained 42.0% of phenotypic variance for palmitic acid, 15.0% for stearic acid, 27.7% for oleic acid, 48.3% for linoleic acid, and 15.7% for oil concentration in the RIL population. Thirty-six loci were involved in 24 molecular marker pairs of epistatic interactions across all traits, which explained phenotypic variances ranging from 0.4 to 6.1%. Seven of 18 mapping candidate genes related to lipid metabolism were localized within or were close to identified individual QTL, explaining 0.7-13.2% of the population variance. These results demonstrated that a few major QTL with large additive effects could play an important role in attending fatty acid compositions and increasing oil concentration in used germplasm. A larger number of minor QTL and a certain number of epistatic QTL, both with additive effects, also contributed to fatty acid compositions and oil concentration.

Standing variation and new mutations both contribute to a fast response to selection for flowering time in maize inbreds

BACKGROUND

In order to investigate the rate and limits of the response to selection from highly inbred genetic material and evaluate the respective contribution of standing variation and new mutations, we conducted a divergent selection experiment from maize inbred lines in open-field conditions during 7 years. Two maize commercial seed lots considered as inbred lines, F252 and MBS847, constituted two biological replicates of the experiment. In each replicate, we derived an Early and a Late population by selecting and selfing the earliest and the latest individuals, respectively, to produce the next generation.

RESULTS

All populations, except the Early MBS847, responded to selection despite a short number of generations and a small effective population size. Part of the response can be attributed to standing genetic variation in the initial seed lot. Indeed, we identified one polymorphism initially segregating in the F252 seed lot at a candidate locus for flowering time, which explained 35% of the trait variation within the Late F252 population. However, the model that best explained our data takes into account both residual polymorphism in the initial seed lots and a constant input of heritable genetic variation by new (epi)mutations. Under this model, values of mutational heritability range from 0.013 to 0.025, and stand as an upper bound compare to what is reported in other species.

CONCLUSIONS

Our study reports a long-term divergent selection experiment for a complex trait, flowering time, conducted on maize in open-field conditions. Starting from a highly inbred material, we created within a few generations populations that strikingly differ from the initial seed lot for flowering time while preserving most of the phenotypic characteristics of the initial inbred. Such material is unique for studying the dynamics of the response to selection and its determinants. In addition to the fixation of a standing beneficial mutation associated with a large phenotypic effect, a constant input of genetic variance by new mutations has likely contributed to the response. We discuss our results in the context of the evolution and mutational dynamics of populations characterized by a small effective population size.

Genome-Wide Association Studies of Hypertension: Light at the End of the Tunnel

Despite its significant genetic component, the study of hypertension by genome-wide association presents more challenges than other common complex diseases. Its high prevalence, heterogeneity, and somewhat unclear definition are the challenges that need to be overcome on one hand. On the other hand, there are issues of small effect sizes and pleiotropism that are not specific to hypertension alone but nonetheless magnify the problems of genetic dissection when coupled with phenotypic misclassification. We discuss issues of study design and summarise published genome-wide association studies (GWASs) of hypertension and blood pressure. With careful study design and analysis success is possible, as demonstrated by the recent large-scale studies. Following these, there is still further scope to advance the field through high fidelity phenotyping and deep sequencing.

Genetic regulation of canine skeletal traits: trade-offs between the hind limbs and forelimbs in the fox and dog

Genetic variation in functionally integrated skeletal traits can be maintained over 10 million years despite bottlenecks and stringent selection. Here, we describe an analysis of the genetic architecture of the canid axial skeleton using populations of the Portuguese Water Dog Canis familiaris) and silver fox (Vulpes vulpes). Twenty-one skeletal metrics taken from radiographs of the forelimbs and hind limbs of the fox and dog were used to construct separate anatomical principal component (PC) matrices of the two species. In both species, 15 of the 21 PCs exhibited significant heritability, ranging from 25% to 70%. The second PC, in both species, represents a trade-off in which limb-bone width is inversely correlated with limb-bone length. PC2 accounts for approximately 15% of the observed skeletal variation, approximately 30% of the variation in shape. Many of the other significant PCs affect very small amounts of variation (e.g., 0.2-2%) along trade-off axes that partition function between the forelimbs and hind limbs. These PCs represent shape axes in which an increase in size of an element of the forelimb is associated with a decrease in size of an element of the hind limb and vice versa. In most cases, these trade-offs are heritable in both species and genetic loci have been identified in the Portuguese Water Dog for many of these. These PCs, present in both the dog and the fox, include ones that affect lengths of the forelimb versus the hind limb, length of the forefoot versus that of the hind foot, muscle moment (i.e., lever) arms of the forelimb versus hind limb, and cortical thickness of the bones of the forelimb versus hind limb. These inverse relationships suggest that genetic regulation of the axial skeleton results, in part, from the action of genes that influence suites of functionally integrated traits. Their presence in both dogs and foxes suggests that the genes controlling the regulation of these PCs of the forelimb versus hind limb may be found in other tetrapod taxa.

Evolutionary-thinking in agricultural weed management

Agricultural weeds evolve in response to crop cultivation. Nevertheless, the central importance of evolutionary ecology for understanding weed invasion, persistence and management in agroecosystems is not widely acknowledged. This paper calls for more evolutionarily-enlightened weed management, in which management principles are informed by evolutionary biology to prevent or minimize weed adaptation and spread. As a first step, a greater knowledge of the extent, structure and significance of genetic variation within and between weed populations is required to fully assess the potential for weed adaptation. The evolution of resistance to herbicides is a classic example of weed adaptation. Even here, most research focuses on describing the physiological and molecular basis of resistance, rather than conducting studies to better understand the evolutionary dynamics of selection for resistance. We suggest approaches to increase the application of evolutionary-thinking to herbicide resistance research. Weed population dynamics models are increasingly important tools in weed management, yet these models often ignore intrapopulation and interpopulation variability, neglecting the potential for weed adaptation in response to management. Future agricultural weed management can benefit from greater integration of ecological and evolutionary principles to predict the long-term responses of weed populations to changing weed management, agricultural environments and global climate.

Evolution of biomolecular networks: lessons from metabolic and protein interactions

Despite only becoming popular at the beginning of this decade, biomolecular networks are now frameworks that facilitate many discoveries in molecular biology. The nodes of these networks are usually proteins (specifically enzymes in metabolic networks), whereas the links (or edges) are their interactions with other molecules. These networks are made up of protein-protein interactions or enzyme-enzyme interactions through shared metabolites in the case of metabolic networks. Evolutionary analysis has revealed that changes in the nodes and links in protein-protein interaction and metabolic networks are subject to different selection pressures owing to distinct topological features. However, many evolutionary constraints can be uncovered only if temporal and spatial aspects are included in the network analysis.