Understanding quantitative genetic variation

Antagonistic epistasis for ecophysiological trait differences between Solanum species

Epistasis, the nonadditive interaction between loci, is thought to play a role in many fundamental evolutionary processes, including adaptive differentiation and speciation. Focusing on species differences in ecophysiological traits, we examined the strength and direction of pairwise epistatic interactions between target chromosomal regions from one species, when co-introgressed into the genetic background of a foreign species. A full diallel cross was performed using 15 near-isogenic lines (NILs) constructed between two tomato species (Solanum habrochaites and Solanum lycopersicum) to compare the phenotypic effects of each chromosomal region singly and in combination with each other region. We detected main effect quantitative trait loci (QTLs) for two of our three focal traits. Epistatic effects accounted for c. 25% of detected effects on trait means, depending on the trait. Strikingly, all but two interactions were antagonistic, with the combined effect of chromosomal regions acting in the opposite direction from that of one or both individual chromosomal regions. Our study is one of the few to systematically examine pairwise epistatic effects in a nonmicrobial system. Our results suggest that epistatic interactions can contribute substantially to the genetic basis of traits involved in adaptive species differentiation, especially highly complex, multivariate traits.

The genetics of quantitative traits: challenges and prospects

A major challenge in current biology is to understand the genetic basis of variation for quantitative traits. We review the principles of quantitative trait locus mapping and summarize insights about the genetic architecture of quantitative traits that have been obtained over the past decades. We are currently in the midst of a genomic revolution, which enables us to incorporate genetic variation in transcript abundance and other intermediate molecular phenotypes into a quantitative trait locus mapping framework. This systems genetics approach enables us to understand the biology inside the 'black box' that lies between genotype and phenotype in terms of causal networks of interacting genes.

Simultaneous selection of major and minor genes: use of QTL to increase selection efficiency of coleoptile length of wheat (Triticum aestivum L.)

Plant breeders simultaneously select for qualitative traits controlled by one or a small number of major genes, as well as for polygenic traits controlled by multiple genes that may be detected as quantitative trait loci (QTL). In this study, we applied computer simulation to investigate simultaneous selection for alleles at both major and minor gene (as QTL) loci in breeding populations of two wheat parental lines, HM14BS and Sunstate. Loci targeted for selection included six major genes affecting plant height, disease resistance, and grain quality, plus 6 known and 11 "unidentified" QTL affecting coleoptile length (CL). Parental line HM14BS contributed the target alleles at two of the major gene loci, while parental line Sunstate contributed target alleles at four loci. The parents have similar plant height, but HM14BS has a longer coleoptile, a desirable attribute for deep sowing in rainfed environments. Including the wild-type allele at the major reduced-height locus Rht-D1, HM14BS was assumed to have 13 QTL for increased CL, and Sunstate four; these assumptions being derived from mapping studies and empirical data from an actual HM14BS/Sunstate population. Simulation indicated that compared to backcross populations, a single biparental F(1) cross produced the highest frequency of target genotypes (six desired alleles at major genes plus desired QTL alleles for long CL). From 1,000 simulation runs, an average of 2.4 individuals with the target genotype were present in unselected F(1)-derived doubled haploid (DH) or recombinant inbred line (RIL) populations of size 200. A selection scheme for the six major genes increased the number of target individuals to 19.1, and additional marker-assisted selection (MAS) for CL increased the number to 23.0. Phenotypic selection (PS) of CL outperformed MAS in this study due to the high heritability of CL, incompletely linked markers for known QTL, and the existence of unidentified QTL. However, a selection scheme combining MAS and PS was equally as efficient as PS and would result in net savings in production and time to delivery of long coleoptile wheats containing the six favorable alleles.

IL-2 and its high-affinity receptor: genetic control of immunoregulation and autoimmunity

Type 1 diabetes (T1D) is an organ-specific autoimmune disease featured by destruction of the insulin producing beta-cells of the pancreas by autoreactive T-lymphocytes. Putative environmental triggers conspire with a constellation of genetic elements scattered throughout the genome to elicit a multifactorial autoimmune response involving virtually every cell type of the immune system against pancreatic beta-cells. Recent highly powered genome-wide association studies have confirmed and identified fifteen chromosomal regions harboring several candidate T1D-associated gene loci. Here, we summarize what we know about the genetics of T1D with an emphasis on the contributions of mouse Il2 and human IL2RA polymorphisms and the IL-2-IL-2R pathway to autoimmunity and, more specifically, Treg development and function.

Competition between recombination and epistasis can cause a transition from allele to genotype selection

Biochemical and regulatory interactions central to biological networks are expected to cause extensive genetic interactions or epistasis affecting the heritability of complex traits and the distribution of genotypes in populations. However, the inference of epistasis from the observed phenotype-genotype correlation is impeded by statistical difficulties, while the theoretical understanding of the effects of epistasis remains limited, in turn limiting our ability to interpret data. Of particular interest is the biologically relevant situation of numerous interacting genetic loci with small individual contributions to fitness. Here, we present a computational model of selection dynamics involving many epistatic loci in a recombining population. We demonstrate that a large number of polymorphic interacting loci can, despite frequent recombination, exhibit cooperative behavior that locks alleles into favorable genotypes leading to a population consisting of a set of competing clones. When the recombination rate exceeds a certain critical value that depends on the strength of epistasis, this "genotype selection" regime disappears in an abrupt transition, giving way to "allele selection"--the regime where different loci are only weakly correlated as expected in sexually reproducing populations. We show that large populations attain highest fitness at a recombination rate just below critical. Clustering of interacting sets of genes on a chromosome leads to the emergence of an intermediate regime, where blocks of cooperating alleles lock into genetic modules. These haplotype blocks disappear in a second transition to pure allele selection. Our results demonstrate that the collective effect of many weak epistatic interactions can have dramatic effects on the population structure.

Haemonchus contortus and Trichostrongylus colubriformis did not adapt to long-term exposure to sheep that were genetically resistant or susceptible to nematode infections

We tested the hypothesis that Haemonchus contortus and Trichostrongylus colubriformis would adapt to long-term exposure to sheep that were either genetically resistant or susceptible to H. contortus. Sheep genotypes were from lines with 10 years prior selection for low (resistant, R) or high (susceptible, S) faecal worm egg count (WEC) following H. contortus infection. Long-term exposure of H. contortus and T.colubriformis to R or S genotypes was achieved using serial passage for up to 30 nematode generations. Thus, we generated four nematode strains; one strain of each species solely exposed to R sheep and one strain of each species solely exposed to S sheep. Considerable host genotype differences in mean WEC during serial passage confirmed adequate nematode selection pressure for both H. contortus (R 4900 eggs per gram (epg), S 19,900 epg) and T. colubriformis (R 5300 epg, S 13,500 epg). Adaptation of nematode strain to host genotype was tested using seven cross-classified tests for H. contortus, and two cross-classified and one outbred genotype test for T. colubriformis. In the cross-classified design, where each strain infects groups of R, S or randomly bred control sheep, parasite adaptation would be indicated by a significant host genotype by nematode strain interaction for traits indicating parasite reproductive success; specifically WEC and, for H. contortus strains, packed cell volume. We found no significant evidence of parasite adaptation to host genotype (P>0.05) for either the H. contortus or T. colubriformis strains. Therefore, we argue that nematodes will not adapt quickly to sheep bred for nematode resistance, where selection is based on low WEC, although selecting sheep using a subset of immune functions may increase adaptation risk. Our results support the hypothesis that nematode resistance is determined by many genes each with relatively small effect. In conclusion, selection of sheep for nematode resistance using WEC should be sustainable in the medium to long-term.

Resistance Gene Replacement in the mosquito Culex pipiens: fitness estimation from long-term cline series

How adaptation appears and is later refined by natural selection has been the object of intense theoretical work. However, the testing of these theories is limited by our ability to estimate the strength of natural selection in nature. Using a long-term cline series, we estimate the selection coefficients acting on different alleles at the same locus to analyze the allele replacement observed in the insecticide resistance gene Ester in the mosquito Culex pipiens in the Montpellier area, southern France. Our method allows us to accurately account for the resistance allele replacement observed in this area since 1986. A first resistance allele appeared early, which was replaced by a second resistance allele providing the same advantage but at a lower cost, itself being replaced by a third resistance allele with both higher advantage and cost. It shows that amelioration of the adaptation (here resistance to insecticide) through allele replacement was successively achieved by selection of first a generalist allele (i.e., with a low fitness variance across environments) and later a specialist allele (i.e., with a large fitness variance across environments). More generally, we discuss how precise estimates of the strength of selection obtained from field data help us understand the process of amelioration of adaptation.

The genetic basis of phenotypic adaptation I: fixation of beneficial mutations in the moving optimum model

We study the genetic basis of adaptation in a moving optimum model, in which the optimal value for a quantitative trait increases over time at a constant rate. We first analyze a one-locus two-allele model with recurrent mutation, for which we derive accurate analytical approximations for (i) the time at which a previously deleterious allele becomes beneficial, (ii) the waiting time for a successful new mutation, and (iii) the time the mutant allele needs to reach fixation. On the basis of these results, we show that the shortest total time to fixation is for alleles with intermediate phenotypic effect. We derive an approximation for this "optimal" effect, and we show that it depends in a simple way on a composite parameter, which integrates the ecological parameters and the genetic architecture of the trait. In a second step, we use stochastic computer simulations of a multilocus model to study the order in which mutant alleles with different effects go to fixation. In agreement with the one-locus results, alleles with intermediate effect tend to become fixed earlier than those with either small or large effects. However, the effect size of the fastest mutations differs from the one predicted in the one-locus model. We show how these differences can be explained by two specific effects of multilocus genetics. Finally, we discuss our results in the light of three relevant timescales acting in the system-the environmental, mutation, and fixation timescales-which define three parameter regimes leading to qualitative differences in the adaptive substitution pattern.

A framework for evolutionary systems biology

BACKGROUND

Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.

RESULTS

Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.

CONCLUSION

EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.

Pathogenic adaptation of intracellular bacteria by rewiring a cis-regulatory input function

The acquisition of DNA by horizontal gene transfer enables bacteria to adapt to previously unexploited ecological niches. Although horizontal gene transfer and mutation of protein-coding sequences are well-recognized forms of pathogen evolution, the evolutionary significance of cis-regulatory mutations in creating phenotypic diversity through altered transcriptional outputs is not known. We show the significance of regulatory mutation for pathogen evolution by mapping and then rewiring a cis-regulatory module controlling a gene required for murine typhoid. Acquisition of a binding site for the Salmonella pathogenicity island-2 regulator, SsrB, enabled the srfN gene, ancestral to the Salmonella genus, to play a role in pathoadaptation of S. typhimurium to a host animal. We identified the evolved cis-regulatory module and quantified the fitness gain that this regulatory output accrues for the bacterium using competitive infections of host animals. Our findings highlight a mechanism of pathogen evolution involving regulatory mutation that is selected because of the fitness advantage the new regulatory output provides the incipient clones.

Association mapping in outbred populations: power and efficiency when genotyping parents and phenotyping progeny

We develop expressions for the power to detect associations between parental genotypes and offspring phenotypes for quantitative traits. Three different "indirect" experimental designs are considered: full-sib, half-sib, and full-sib-half-sib families. We compare the power of these designs to detect genotype-phenotype associations relative to the common, "direct," approach of genotyping and phenotyping the same individuals. When heritability is low, the indirect designs can outperform the direct method. However, the extra power comes at a cost due to an increased phenotyping effort. By developing expressions for optimal experimental designs given the cost of phenotyping relative to genotyping, we show how the extra costs associated with phenotyping a large number of individuals will influence experimental design decisions. Our results suggest that indirect association studies can be a powerful means of detecting allelic associations in outbred populations of species for which genotyping and phenotyping the same individuals is impractical and for life history and behavioral traits that are heavily influenced by environmental variance and therefore best measured on groups of individuals. Indirect association studies are likely to be favored only on purely economical grounds, however, when phenotyping is substantially less expensive than genotyping. A web-based application implementing our expressions has been developed to aid in the design of indirect association studies.

Model of genetic variation in human social networks

Social networks exhibit strikingly systematic patterns across a wide range of human contexts. Although genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here, we show that 3 of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a "mirror network" method to test extant network models and show that none account for observed genetic variation in human social networks. We propose an alternative "Attract and Introduce" model with two simple forms of heterogeneity that generates significant heritability and other important network features. We show that the model is well suited to real social networks in humans. These results suggest that natural selection may have played a role in the evolution of social networks. They also suggest that modeling intrinsic variation in network attributes may be important for understanding the way genes affect human behaviors and the way these behaviors spread from person to person.

Understanding the evolution and stability of the G-matrix

The G-matrix summarizes the inheritance of multiple, phenotypic traits. The stability and evolution of this matrix are important issues because they affect our ability to predict how the phenotypic traits evolve by selection and drift. Despite the centrality of these issues, comparative, experimental, and analytical approaches to understanding the stability and evolution of the G-matrix have met with limited success. Nevertheless, empirical studies often find that certain structural features of the matrix are remarkably constant, suggesting that persistent selection regimes or other factors promote stability. On the theoretical side, no one has been able to derive equations that would relate stability of the G-matrix to selection regimes, population size, migration, or to the details of genetic architecture. Recent simulation studies of evolving G-matrices offer solutions to some of these problems, as well as a deeper, synthetic understanding of both the G-matrix and adaptive radiations.

Reverse engineering the genotype-phenotype map with natural genetic variation

The genetic variation that occurs naturally in a population is a powerful resource for studying how genotype affects phenotype. Each allele is a perturbation of the biological system, and genetic crosses, through the processes of recombination and segregation, randomize the distribution of these alleles among the progeny of a cross. The randomized genetic perturbations affect traits directly and indirectly, and the similarities and differences between traits in their responses to common perturbations allow inferences about whether variation in a trait is a cause of a phenotype (such as disease) or whether the trait variation is, instead, an effect of that phenotype. It is then possible to use this information about causes and effects to build models of probabilistic 'causal networks'. These networks are beginning to define the outlines of the 'genotype-phenotype map'.

Centromere-associated female meiotic drive entails male fitness costs in monkeyflowers

Female meiotic drive, in which paired chromosomes compete for access to the egg, is a potentially powerful but rarely documented evolutionary force. In interspecific monkeyflower (Mimulus) hybrids, a driving M. guttatus allele (D) exhibits a 98:2 transmission advantage via female meiosis. We show that extreme interspecific drive is most likely caused by divergence in centromere-associated repeat domains and document cytogenetic and functional polymorphism for drive within a population of M. guttatus. In conspecific crosses, D had a 58:42 transmission advantage over nondriving alternative alleles. However, individuals homozygous for the driving allele suffered reduced pollen viability. These fitness effects and molecular population genetic data suggest that balancing selection prevents the fixation or loss of D and that selfish chromosomal transmission may affect both individual fitness and population genetic load.

Statistical mechanics and the evolution of polygenic quantitative traits

The evolution of quantitative characters depends on the frequencies of the alleles involved, yet these frequencies cannot usually be measured. Previous groups have proposed an approximation to the dynamics of quantitative traits, based on an analogy with statistical mechanics. We present a modified version of that approach, which makes the analogy more precise and applies quite generally to describe the evolution of allele frequencies. We calculate explicitly how the macroscopic quantities (i.e., quantities that depend on the quantitative trait) depend on evolutionary forces, in a way that is independent of the microscopic details. We first show that the stationary distribution of allele frequencies under drift, selection, and mutation maximizes a certain measure of entropy, subject to constraints on the expectation of observable quantities. We then approximate the dynamical changes in these expectations, assuming that the distribution of allele frequencies always maximizes entropy, conditional on the expected values. When applied to directional selection on an additive trait, this gives a very good approximation to the evolution of the trait mean and the genetic variance, when the number of mutations per generation is sufficiently high (4Nmicro > 1). We show how the method can be modified for small mutation rates (4Nmicro --> 0). We outline how this method describes epistatic interactions as, for example, with stabilizing selection.

The Evolutionary Persistence of Genes That Increase Mental Disorders Risk

Natural selection constantly removes those genetic variants (alleles) that even slightly decrease average reproductive success. Yet, given the high heritabilities and prevalence rates of severe mental disorders, human populations seem to be awash in deleterious alleles. Evolutionary genetics offers an illuminating framework for understanding why mental disorder risk alleles have persisted despite natural selection, and this framework can help guide future research in behavioral and psychiatric genetics.

Stringent mating-type-regulated auxotrophy increases the accuracy of systematic genetic interaction screens with Saccharomyces cerevisiae mutant arrays

A genomic collection of haploid Saccharomyces cerevisiae deletion strains provides a unique resource for systematic analysis of gene interactions. Double-mutant haploid strains can be constructed by the synthetic genetic array (SGA) method, wherein a query mutation is introduced by mating to mutant arrays, selection of diploid double mutants, induction of meiosis, and selection of recombinant haploid double-mutant progeny. The mechanism of haploid selection is mating-type-regulated auxotrophy (MRA), by which prototrophy is restricted to a particular haploid genotype generated only as a result of meiosis. MRA escape leads to false-negative genetic interaction results because postmeiotic haploids that are supposed to be under negative selection instead proliferate and mate, forming diploids that are heterozygous at interacting loci, masking phenotypes that would be observed in a pure haploid double-mutant culture. This work identified factors that reduce MRA escape, including insertion of terminator and repressor sequences upstream of the MRA cassette, deletion of silent mating-type loci, and utilization of alpha-type instead of a-type MRA. Modifications engineered to reduce haploid MRA escape reduced false negative results in SGA-type analysis, resulting in >95% sensitivity for detecting gene-gene interactions.

Effects of selection and drift on G matrix evolution in a heterogeneous environment: a multivariate Qst-Fst Test with the freshwater snail Galba truncatula

Unraveling the effect of selection vs. drift on the evolution of quantitative traits is commonly achieved by one of two methods. Either one contrasts population differentiation estimates for genetic markers and quantitative traits (the Q(st)-F(st) contrast) or multivariate methods are used to study the covariance between sets of traits. In particular, many studies have focused on the genetic variance-covariance matrix (the G matrix). However, both drift and selection can cause changes in G. To understand their joint effects, we recently combined the two methods into a single test (accompanying article by Martin et al.), which we apply here to a network of 16 natural populations of the freshwater snail Galba truncatula. Using this new neutrality test, extended to hierarchical population structures, we studied the multivariate equivalent of the Q(st)-F(st) contrast for several life-history traits of G. truncatula. We found strong evidence of selection acting on multivariate phenotypes. Selection was homogeneous among populations within each habitat and heterogeneous between habitats. We found that the G matrices were relatively stable within each habitat, with proportionality between the among-populations (D) and the within-populations (G) covariance matrices. The effect of habitat heterogeneity is to break this proportionality because of selection for habitat-dependent optima. Individual-based simulations mimicking our empirical system confirmed that these patterns are expected under the selective regime inferred. We show that homogenizing selection can mimic some effect of drift on the G matrix (G and D almost proportional), but that incorporating information from molecular markers (multivariate Q(st)-F(st)) allows disentangling the two effects.

Selective sweep at a quantitative trait locus in the presence of background genetic variation

We model selection at a locus affecting a quantitative trait (QTL) in the presence of genetic variance due to other loci. The dynamics at the QTL are related to the initial genotypic value and to the background genetic variance of the trait, assuming that background genetic values are normally distributed, under three different forms of selection on the trait. Approximate dynamics are derived under the assumption of small mutation effect. For similar strengths of selection on the trait (i.e, gradient of directional selection beta) the way background variation affects the dynamics at the QTL critically depends on the shape of the fitness function. It generally causes the strength of selection on the QTL to decrease with time. The resulting neutral heterozygosity pattern resembles that of a selective sweep with a constant selection coefficient corresponding to the early conditions. The signature of selection may also be blurred by mutation and recombination in the later part of the sweep. We also study the race between the QTL and its genetic background toward a new optimum and find the conditions for a complete sweep. Overall, our results suggest that phenotypic traits exhibiting clear-cut molecular signatures of selection may represent a biased subset of all adaptive traits.

A combinatorial approach to detecting gene-gene and gene-environment interactions in family studies

Widespread multifactor interactions present a significant challenge in determining risk factors of complex diseases. Several combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have emerged as a promising tool for better detecting gene-gene (G x G) and gene-environment (G x E) interactions. We recently developed a general combinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, which can entertain both qualitative and quantitative phenotypes and allows for both discrete and continuous covariates to detect G x G and G x E interactions in a sample of unrelated individuals. In this article, we report the development of an algorithm that can be used to study G x G and G x E interactions for family-based designs, called pedigree-based GMDR (PGMDR). Compared to the available method, our proposed method has several major improvements, including allowing for covariate adjustments and being applicable to arbitrary phenotypes, arbitrary pedigree structures, and arbitrary patterns of missing marker genotypes. Our Monte Carlo simulations provide evidence that the PGMDR method is superior in performance to identify epistatic loci compared to the MDR-pedigree disequilibrium test (PDT). Finally, we applied our proposed approach to a genetic data set on tobacco dependence and found a significant interaction between two taste receptor genes (i.e., TAS2R16 and TAS2R38) in affecting nicotine dependence.

Interactions between markers can be caused by the dominance effect of quantitative trait loci

F(2) populations are commonly used in genetic studies of animals and plants. For simplicity, most quantitative trait locus or loci (QTL) mapping methods have been developed on the basis of populations having two distinct genotypes at each polymorphic marker or gene locus. In this study, we demonstrate that dominance can cause the interactions between markers and propose an inclusive linear model that includes marker variables and marker interactions so as to completely control both additive and dominance effects of QTL. The proposed linear model is the theoretical basis for inclusive composite-interval QTL mapping (ICIM) for F(2) populations, which consists of two steps: first, the best regression model is selected by stepwise regression, which approximately identifies markers and marker interactions explaining both additive and dominance variations; second, the interval mapping approach is applied to the phenotypic values adjusted by the regression model selected in the first step. Due to the limited mapping population size, the large number of variables, and multicollinearity between variables, coefficients in the inclusive linear model cannot be accurately determined in the first step. Interval mapping is necessary in the second step to fine tune the QTL to their true positions. The efficiency of including marker interactions in mapping additive and dominance QTL was demonstrated by extensive simulations using three QTL distribution models with two population sizes and an actual rice F(2) population.

Genetics of drought adaptation in Arabidopsis thaliana II. QTL analysis of a new mapping population, KAS-1 x TSU-1

Despite compelling evidence that adaptation to local climate is common in plant populations, little is known about the evolutionary genetics of traits that contribute to climatic adaptation. A screen of natural accessions of Arabidopsis thaliana revealed Tsu-1 and Kas-1 to be opposite extremes for water-use efficiency and climate at collection sites for these accessions differs greatly. To provide a tool to understand the genetic basis of this putative adaptation, Kas-1 and Tsu-1 were reciprocally crossed to create a new mapping population. Analysis of F(3) families showed segregating variation in both delta(13)C and transpiration rate, and as expected these traits had a negative genetic correlation (r(g)=- 0.3). 346 RILs, 148 with Kas-1 cytoplasm and 198 with Tsu-1 cytoplasm, were advanced to the F(9) and genotyped using 48 microsatellites and 55 SNPs for a total of 103 markers. This mapping population was used for QTL analysis of delta(13)C using F(9) RIL means. Analysis of this reciprocal cross showed a large effect of cytoplasmic background, as well as two QTL for delta(13)C. The Kas-1 x Tsu-1 mapping population provides a powerful new resource for mapping QTL underlying natural variation and for dissecting the genetic basis of water-use efficiency differences.

Sequential elimination of major-effect contributors identifies additional quantitative trait loci conditioning high-temperature growth in yeast

Several quantitative trait loci (QTL) mapping strategies can successfully identify major-effect loci, but often have poor success detecting loci with minor effects, potentially due to the confounding effects of major loci, epistasis, and limited sample sizes. To overcome such difficulties, we used a targeted backcross mapping strategy that genetically eliminated the effect of a previously identified major QTL underlying high-temperature growth (Htg) in yeast. This strategy facilitated the mapping of three novel QTL contributing to Htg of a clinically derived yeast strain. One QTL, which is linked to the previously identified major-effect QTL, was dissected, and NCS2 was identified as the causative gene. The interaction of the NCS2 QTL with the first major-effect QTL was background dependent, revealing a complex QTL architecture spanning these two linked loci. Such complex architecture suggests that more genes than can be predicted are likely to contribute to quantitative traits. The targeted backcrossing approach overcomes the difficulties posed by sample size, genetic linkage, and epistatic effects and facilitates identification of additional alleles with smaller contributions to complex traits.

The effects of the genetic background on herbicide resistance fitness cost and its associated dominance in Arabidopsis thaliana

The advantage of the resistance conferred by a mutation can sometimes be offset by a high fitness-cost penalty. This balance will affect possible fate of the resistance allele. Few studies have explored the impact of the genetic background on the expression of the resistance fitness cost and none has attempted to measure the variation in fitness-cost dominance. However, both the fitness penalty and its dominance may modify evolutionary trajectory and outcome. Here the impact of Arabidopsis thaliana intraspecific genetic diversity on fitness cost and its associated dominance was investigated by analysing 12 quantitative traits in crosses between a mutant conferring resistance to the herbicide 2,4-D and nine different natural genetic backgrounds. Fitness cost values were found to be more affected by intraspecific genetic diversity than fitness cost dominance, even though this effect depends on the quantitative trait measured. This observation has implications for the choice of the best strategy for preventing herbicide resistance development. In addition, our results pinpoint a potential compensatory improvement of the resistance fitness cost and its associated dominance by the genetic diversity locally present within a species.

Evolutionary implications of the form of predator generalization for aposematic signals and mimicry in prey

Generalization is at the heart of many aspects of behavioral ecology; for foragers it can be seen as an essential feature of learning about potential prey, because natural populations of prey are unlikely to be perfectly homogenous. Aposematic signals are considered to aid predators in learning to avoid a class of defended prey. Predators do this by generalizing between the appearance of prey they have previously sampled and the appearance of prey they subsequently encounter. Mimicry arises when such generalization occurs between individuals of different species. Our aim here is to explore whether the specific shape of the generalization curve can be expected to be important for theoretical predictions relating to the evolution of aposematism and mimicry. We do this by a reanalysis and development of the models provided in two recent papers. We argue that the shape of the generalization curve, in combination with the nature of genetic and phenotypic variation in prey traits, can have evolutionary significance under certain delineated circumstances. We also demonstrate that the process of gradual evolution of Müllerian mimicry proposed by Fisher is particularly efficient in populations with a rich supply of standing genetic variation in mimetic traits.

Genetic tools for studying adaptation and the evolution of behavior

The rapid expansion of genomic and molecular genetic techniques in model organisms, and the application of these techniques to organisms that are less well studied genetically, make it possible to understand the genetic control of many behavioral phenotypes. However, many behavioral ecologists are uncertain about the value of including a genetic component in their studies. In this article, we review how genetic analyses of behavior are central to topics ranging from understanding past selection and predicting future evolution to explaining the neural and hormonal control of behavior. Furthermore, we review both new and old techniques for studying evolutionary behavior genetics and highlight how the choice of approach depends on both the question and the organism. Topics discussed include genetic architecture, detecting the past history of selection, and genotype-by-environment interactions. We show how these questions are being addressed with techniques including statistical genetics, QTL analyses, transgenic analyses, and microarrays. Many of the techniques were first applied to the behavior of genetic model organisms such as laboratory mice and flies. Two recent developments serve to expand the relevance of such studies to behavioral ecology. The first is to use model organisms for studies of the genetic basis of evolutionarily relevant behavior and the second is to apply methods developed in model genetic systems to species that have not previously been examined genetically. These conceptual advances, along with the rapid diversification of genetic tools and the recognition of widespread genetic homology, suggest a bright outlook for evolutionary genetic studies. This review provides access to tools through references to the recent literature and shows the great promise for evolutionary behavioral genetics.

Increase in quantitative variation after exposure to environmental stresses and/or introduction of a major mutation: G x E interaction and epistasis or canalization?

Why does phenotypic variation increase upon exposure of the population to environmental stresses or introduction of a major mutation? It has usually been interpreted as evidence of canalization (or robustness) of the wild-type genotype; but an alternative population genetic theory has been suggested by J. Hermisson and G. Wagner: "the release of hidden genetic variation is a generic property of models with epistasis or genotype-environment interaction." In this note we expand their model to include a pleiotropic fitness effect and a direct effect on residual variance of mutant alleles. We show that both the genetic and environmental variances increase after the genetic or environmental change, but these increases could be very limited if there is strong pleiotropic selection. On the basis of more realistic selection models, our analysis lends further support to the genetic theory of Hermisson and Wagner as an interpretation of hidden variance.

The anomalous effects of biased mutation revisited: mean-optimum deviation and apparent directional selection under stabilizing selection

Empirical evidence indicates that the distribution of the effects of mutations on quantitative traits is not symmetric about zero. Under stabilizing selection in infinite populations with normally distributed mutant effects having a nonzero mean, Waxman and Peck showed that the deviation of the population mean from the optimum is expected to be small. We show by simulation that genetic drift, leptokurtosis of mutational effects, and pleiotropy can increase the mean-optimum deviation greatly, however, and that the apparent directional selection thereby caused can be substantial.

Genetic variation affecting host-parasite interactions: major-effect quantitative trait loci affect the transmission of sigma virus in Drosophila melanogaster

In natural populations, genetic variation affects resistance to disease. Whether that genetic variation comprises lots of small-effect polymorphisms or a small number of large-effect polymorphisms has implications for adaptation, selection and how genetic variation is maintained in populations. Furthermore, how much genetic variation there is, and the genes that underlie this variation, affects models of co-evolution between parasites and their hosts. We are studying the genetic variation that affects the resistance of Drosophila melanogaster to its natural pathogen--the vertically transmitted sigma virus. We have carried out three separate quantitative trait locus mapping analyses to map gene variants on the second chromosome that cause variation in the rate at which males transmit the infection to their offspring. All three crosses identified a locus in a similar chromosomal location that causes a large drop in the rate at which the virus is transmitted. We also found evidence for an additional smaller-effect quantitative trait locus elsewhere on the chromosome. Our data, together with previous experiments on the sigma virus and parasitoid wasps, indicate that the resistance of D. melanogaster to co-evolved pathogens is controlled by a limited number of major-effect polymorphisms.

Present and future applications of DNA technologies to improve beef production

Substantial improvements in production efficiency and quality of beef and dairy products have been made possible through manipulation of bovine genetics. The advent of modern breeds in the last two centuries, the institution of phenotypic selection practices and quantitative genetics, even the process of domestication in the distant past, have all represented means to make use of naturally occurring variation in the genome to tailor the animal for a desired outcome. We discuss the history of genome research in cattle and recent technological advances that promise a leap forward in the use of DNA sequence to facilitate selection, in which a detailed genome-level view for individual animals may provide comprehensive and relatively accurate assessment of the consequences, both desired and unintended, of genetic selection for livestock production.

Emerging of Stochastic Dynamical Equalities and Steady State Thermodynamics from Darwinian Dynamics

The evolutionary dynamics first conceived by Darwin and Wallace, referring to as Darwinian dynamics in the present paper, has been found to be universally valid in biology. The statistical mechanics and thermodynamics, while enormous successful in physics, have been in an awkward situation of wanting a consistent dynamical understanding. Here we present from a formal point of view an exploration of the connection between thermodynamics and Darwinian dynamics and a few related topics. We first show that the stochasticity in Darwinian dynamics implies the existence temperature, hence the canonical distribution of Boltzmann-Gibbs type. In term of relative entropy the Second Law of thermodynamics is dynamically demonstrated without detailed balance condition, and is valid regardless of size of the system. In particular, the dynamical component responsible for breaking detailed balance condition does not contribute to the change of the relative entropy. Two types of stochastic dynamical equalities of current interest are explicitly discussed in the present approach: One is based on Feynman-Kac formula and another is a generalization of Einstein relation. Both are directly accessible to experimental tests. Our demonstration indicates that Darwinian dynamics represents logically a simple and straightforward starting point for statistical mechanics and thermodynamics and is complementary to and consistent with conservative dynamics that dominates the physical sciences. Present exploration suggests the existence of a unified stochastic dynamical framework both near and far from equilibrium.

Heritability in the genomics era--concepts and misconceptions

Heritability allows a comparison of the relative importance of genes and environment to the variation of traits within and across populations. The concept of heritability and its definition as an estimable, dimensionless population parameter was introduced by Sewall Wright and Ronald Fisher nearly a century ago. Despite continuous misunderstandings and controversies over its use and application, heritability remains key to the response to selection in evolutionary biology and agriculture, and to the prediction of disease risk in medicine. Recent reports of substantial heritability for gene expression and new estimation methods using marker data highlight the relevance of heritability in the genomics era.

Heat shock protein 101 effects in A. thaliana: genetic variation, fitness and pleiotropy in controlled temperature conditions

The Hsp100/ClpB heat shock protein family is ancient and required for high temperature survival, but natural variation in expression and its phenotypic effects is unexplored in plants. In controlled environment experiments, we examined the effects of variation in the Arabidopsis cytosolic AtHsp101 (hereafter Hsp101). Ten wild-collected ecotypes differed in Hsp101 expression responses across a 22 to 40 degrees C gradient. Genotypes from low latitudes expressed the least Hsp101. We tested fitness and pleiotropic consequences of varying Hsp101 expression in 'control' vs. mild thermal stress treatments (15/25 degrees C D/N vs. 15/25 degrees D/N plus 3 h at 35 degrees C 3 days/week). Comparing wild type and null mutants, wt Columbia (Col) produced approximately 33% more fruits compared to its Hsp101 homozygous null mutant. There was no difference between Landsberg erecta null mutant NIL (Ler) and wt Ler; wt Ler showed very low Hsp101 expression. In an assay of six genotypes, fecundity was a saturating function of Hsp101 content, in both experimental treatments. Thus, in addition to its essential role in acquired thermal tolerance, Hsp101 provides a substantial fitness benefit under normal growth conditions. Knocking out Hsp101 decreased fruit production, days to germination and days to bolting, total dry mass, and number of inflorescences; it increased transpiration rate and allocation to root mass. Root : total mass ratio decayed exponentially with Hsp101 content. This study shows that Hsp101 expression is evolvable in natural populations. Our results further suggest that Hsp101 is primarily an emergency high-temperature tolerance mechanism, since expression levels are lower in low-latitude populations from warmer climates. Hsp101 expression appears to carry an important trade-off in reduced root growth. This trade-off may select for suppressed expression under chronically high temperatures.

Data and theory point to mainly additive genetic variance for complex traits

The relative proportion of additive and non-additive variation for complex traits is important in evolutionary biology, medicine, and agriculture. We address a long-standing controversy and paradox about the contribution of non-additive genetic variation, namely that knowledge about biological pathways and gene networks imply that epistasis is important. Yet empirical data across a range of traits and species imply that most genetic variance is additive. We evaluate the evidence from empirical studies of genetic variance components and find that additive variance typically accounts for over half, and often close to 100%, of the total genetic variance. We present new theoretical results, based upon the distribution of allele frequencies under neutral and other population genetic models, that show why this is the case even if there are non-additive effects at the level of gene action. We conclude that interactions at the level of genes are not likely to generate much interaction at the level of variance.

Genetic variation in quantitative or complex traits can be partitioned into many components due to additive, dominance, and interaction effects of genes. The most important is the additive genetic variance because it determines most of the correlation of relatives and the opportunities for genetic change by natural or artificial selection. From reviews of the literature and presentation of a summary analysis of human twin data, we show that a high proportion, typically over half, of the total genetic variance is additive. This is surprising as there are many potential interactions of gene effects within and between loci, some revealed in recent QTL analyses. We demonstrate that under the standard model of neutral mutation, which leads to a U-shaped distribution of gene frequencies with most near 0 or 1, a high proportion of additive variance would be expected regardless of the amount of dominance or epistasis at the individual loci. We also show that the model is compatible with observations in populations undergoing selection and results of QTL analyses on F2 populations.

Cranial bone morphometric study among mouse strains

BACKGROUND

Little is known about the molecular mechanism which regulates how the whole cranium is shaped. Mouse models currently available for genetic research include several hundreds of unique inbred strains and genetically engineered mutants. By cross comparing their genomic structures, we can elucidate the cause of any differences in the phenotype between two strains. The craniometry of subspecies, or closely related species, of mice provide a good systemic model to study the relationship between genetic variance and cranial shape evolution. The lack of a quantified framework for comparing and analyzing mouse cranial shape has been a problem. For this reason, we performed quantitative analysis of cranial shape morphology between several mouse strains.

RESULTS

This article reports on a craniometric assay of seven mouse strains: four inbred strains (C57BL/6J, BALB/cA, C3H/HeJ, and CBA/JNCr) from Mus musculus domesticus (M. m. domesticus); one closed colony strain (ICR) from M. m. domesticus; one inbred strain (MSM/Ms) from Mus musculus molossinus; and, Mus spretus as a strain from a species other than M. m. domesticus. We performed linear measurements and geometric morphometrics. Geometric morphometrics revealed that the cranial characteristics of each strains were clearly distinguishable. We obtained mean scores for each species using the tpsRelw Program and plotted them.

CONCLUSION

Geometric morphometrics proved to be useful for identifying and classifying variations in form, and it revealed that M. spretus has a slender cranium when compared with our other strains. The mean cranial shape of C3H or CBA was more similar to MSM/Ms, which is derived from M. m. molossinus, than to either C57BL/6J, BALB, or ICR which are derived from M. m. domesticus. Future work in this field will aid in elucidating the mechanism of whole cranial shape regulation.

Insight into the genetic bases of climatic adaptation in experimentally evolving wheat populations

Experimental populations evolving under natural selection represent an interesting tool to study genetic bases of adaptation. Evolution of genes possibly involved in adaptive response can be followed together with the corresponding phenotypic traits. Using experimental populations of hexaploid wheat, we studied the evolution of flowering time, a major adaptive trait that synchronizes the initiation of reproduction and the occurrence of favourable environmental conditions. During 12 generations, three populations were grown in contrasted environments (Vervins North France, Le Moulon near Paris, Toulouse South France) under the influence of natural selection, drift, mutation and recombination. Evolution of diversity at the major gene VRN-1 involved in wheat vernalization response has been analysed jointly with earliness estimated in controlled conditions. Whatever the population, rapid phenotypic changes as well as parallel genotypic variations were observed in the first seven generations, probably as the result of selection acting on this major gene which explains 80% of the trait variation overall. Different allelic combinations at physically unlinked copies of VRN-1 located on distinct genomes (A, B and D) were selected between populations. As theoretically expected, due to population differentiation, a high level of genetic diversity was maintained overall in generation 12. Surprisingly, in two populations out of three, the emergence of new alleles by mutation or migration, coupled with temporal variable selection or frequency-dependent selection, allowed to maintain within-population diversity despite local genetic drift and natural selection. This result may plead for an evolutionary approach of wheat genetic resource conservation.

Sex-ratio evolution in nuclear-cytoplasmic gynodioecy when restoration is a threshold trait

Gynodioecious plant species, which have populations consisting of female and hermaphrodite individuals, usually have complex sex determination involving cytoplasmic male sterility (CMS) alleles interacting with nuclear restorers of fertility. In response to recent evidence, we present a model of sex-ratio evolution in which restoration of male fertility is a threshold trait. We find that females are maintained at low frequencies for all biologically relevant parameter values. Furthermore, this model predicts periodically high female frequencies (>50%) under conditions of lower female seed fecundity advantages (compensation, x = 5%) and pleiotropic fitness effects associated with restorers of fertility (costs of restoration, y = 20%) than in other models. This model explains the maintenance of females in species that have previously experienced invasions of CMS alleles and the evolution of multiple restorers. Sensitivity of the model to small changes in cost and compensation values and to initial conditions may explain why populations of the same species vary widely for sex ratio.