Genetic analysis of life-history constraint and evolution in a wild ungulate population

Trade-offs among life-history traits are central to evolutionary theory. In quantitative genetic terms, trade-offs may be manifested as negative genetic covariances relative to the direction of selection on phenotypic traits. Although the expression and selection of ecologically important phenotypic variation are fundamentally multivariate phenomena, the in situ quantification of genetic covariances is challenging. Even for life-history traits, where well-developed theory exists with which to relate phenotypic variation to fitness variation, little evidence exists from in situ studies that negative genetic covariances are an important aspect of the genetic architecture of life-history traits. In fact, the majority of reported estimates of genetic covariances among life-history traits are positive. Here we apply theory of the genetics and selection of life histories in organisms with complex life cycles to provide a framework for quantifying the contribution of multivariate genetically based relationships among traits to evolutionary constraint. We use a Bayesian framework to link pedigree-based inference of the genetic basis of variation in life-history traits to evolutionary demography theory regarding how life histories are selected. Our results suggest that genetic covariances may be acting to constrain the evolution of female life-history traits in a wild population of red deer Cervus elaphus: genetic covariances are estimated to reduce the rate of adaptation by about 40%, relative to predicted evolutionary change in the absence of genetic covariances. Furthermore, multivariate phenotypic (rather than genetic) relationships among female life-history traits do not reveal this constraint.     

On the evolution of clonal plant life histories

Clonal plant life histories are special in at least four respects: (1) Clonal plants can also reproduce vegetatively, (2) vegetative reproduction can be realised with short or long spacers, (3) and it may allow to plastically place vegetative offspring in benign patches. (4) Moreover, ramets of clonal plants may remain physically and physiologically integrated. Because of the apparent utility of such traits and because ecological patterns of distribution of clonal and non-clonal plants differ, adaptation is a tempting explanation of observed clonal life-history variation. However, adaptive evolution requires (1) heritable genetic variation and (2) a trait effect on fitness, and (3) it may be constrained if other evolutionary forces are overriding selection or by constraints, costs and trade-offs. (1) The few studies undertaken so far reported broad-sense heritability for clonal traits. Variation in selectively neutral genetic markers appears as pronounced in populations of clonal as non-clonal plants. However, neutral markers may not reflect heritable variation of life-history traits. Moreover, clonal plants may have been sampled at larger spatial scales. Empirical information on the contribution of somatic mutations to heritable variation is lacking. (2) Clonal life-history traits were found to affect fitness. However, much of this evidence stems from artificial rather than natural environments. (3) The relative importance of gene flow, inbreeding, and genetic drift, compared with selection, in the evolution of clonal life histories is hardly explored. Benefits of clonal life-history traits were frequently studied and found. However, there is also evidence for constraints, trade-offs, and costs. In conclusion, though it is very likely, that clonal life-history traits are adaptive, it is neither clear to which degree this is the case, nor which clonal life-history traits constitute adaptations to which environmental factors. Moreover, evolutionary interactions among clonal life-history traits and between clonal and non-clonal ones, such as the mating system, are not well explored. There remains much interesting work to be done in this field – which will be particularly interesting if it is done in the field.     

A knowledge-based method for association studies on complex diseases

Complex disorders are a class of diseases whose phenotypic variance is caused by the interplay of multiple genetic and environmental factors. Analyzing the complexity underlying the genetic architecture of such traits may help develop more efficient diagnostic tests and therapeutic protocols. Despite the continuous advances in revealing the genetic basis of many of complex diseases using genome-wide association studies (GWAS), a major proportion of their genetic variance has remained unexplained, in part because GWAS are unable to reliably detect small individual risk contributions and to capture the underlying genetic heterogeneity. In this paper we describe a hypothesis-based method to analyze the association between multiple genetic factors and a complex phenotype. Starting from sets of markers selected based on preexisting biomedical knowledge, our method generates multi-marker models relevant to the biological process underlying a complex trait for which genotype data is available. We tested the applicability of our method using the WTCCC case-control dataset. Analyzing a number of biological pathways, the method was able to identify several immune system related multi-SNP models significantly associated with Rheumatoid Arthritis (RA) and Crohn's disease (CD). RA-associated multi-SNP models were also replicated in an independent case-control dataset. The method we present provides a framework for capturing joint contributions of genetic factors to complex traits. In contrast to hypothesis-free approaches, its results can be given a direct biological interpretation. The replicated multi-SNP models generated by our analysis may serve as a predictor to estimate the risk of RA development in individuals of Caucasian ancestry.     

数量性状发育遗传模型及其分析方法的研究进展

发育遗传模型是同时反映性状遗传和发育本质、提供影响遗传变异及调整发育进程的有关因素的信息的模型。建立在群体遗传学基础上的直接效应模型适用于单一基因控制的简单性状。渐成模型将遗传变异分解成直接分量和渐成分量(母体效应和互作效应),能更好地反映有机体遗传和发育的生物学机制。生长轨迹模型有效地综合了复杂性状各分量的发育动态,可获得连续的、综合的、详细的、动态的发育信息。条件遗传分析方法不仅可以估算特定时间段的净效应,且可将净效应分解为不同遗传分量,了解各效应分量的相对贡献。 Abstract：Developmental genetic models and analysis methods for quantitative traits are presented.Developmental genetic models should reflect the genetic and developmental essence,and provide the information of the factors influencing the genetic variation and the developmental process.Direct effect models,which based on the population genetics,may be suitable to analyze simple traits with single gene.Epigenetic models can decompose the whole genetic variation into direct and epigenetic components (maternal effects and epigenetic interaction effects),so that biological mechanism can be better understood.Growth trace models effectively synthesize the developmental dynamics of components of complex traits.With them,continuous,compositive,detailed,and dynamic information of development is available.Conditional analysis method can not only estimate the net effects in a specific time interval,but also depose them into genetic components and help to appreciate the contributions of different effects.     

Reproductive diapause and life-history clines in North American populations of Drosophila melanogaster

Latitudinal clines are widespread in Drosophila melanogaster, and many have been interpreted as adaptive responses to climatic variation. However, the selective mechanisms generating many such patterns remain unresolved, and there is relatively little information regarding how basic life-history components such as fecundity, life span and mortality rates vary across environmental gradients. Here, it is shown that four life-history traits vary predictably with geographic origin of populations sampled along the latitudinal gradient in the eastern United States. Although such patterns are indicative of selection, they cannot distinguish between the direct action of selection on the traits in question or indirect selection by means of underlying genetic correlations. When independent suites of traits covary with geography, it is therefore critical to separate the widespread effects of population source from variation specifically for the traits under investigation. One trait that is associated with variation in life histories and also varies with latitude is the propensity to express reproductive diapause; diapause expression has been hypothesized as a mechanism by which D. melanogaster adults overwinter, and as such may be subject to strong selection in temperate habitats. In this study, recently derived isofemale lines were used to assess the relative contributions of population source and diapause genotype in generating the observed variance for life histories. It is shown that although life span, fecundity and mortality rates varied predictably with geography, diapause genotype explained the majority of the variance for these traits in the sampled populations. Both heat and cold shock resistance were also observed to vary predictably with latitude for the sampled populations. Cold shock tolerance varied between diapause genotypes and the magnitude of this difference varied with geography, whereas heat shock tolerance was affected solely by geographic origin of the populations. These data suggest that a subset of life-history parameters is significantly influenced by the genetic variance for diapause expression in natural populations, and that the observed variance for longevity and fecundity profiles may reflect indirect action of selection on diapause and other correlated traits.     

Sky island bird populations isolated by ancient genetic barriers are characterized by different song traits than those isolated by recent deforestation

Various mechanisms of isolation can structure populations and result in cultural and genetic differentiation. Similar to genetic markers, for songbirds, culturally transmitted sexual signals such as breeding song can be used as a measure of differentiation as songs can also be impacted by geographic isolation resulting in population‐level differences in song structure. Several studies have found differences in song structure either across ancient geographic barriers or across contemporary habitat barriers owing to deforestation. However, very few studies have examined the effect of both ancient barriers and recent deforestation in the same system. In this study, we examined the geographic variation in song structure across six populations of the White‐bellied Shortwing, a threatened and endemic songbird species complex found on isolated mountaintops or “sky islands” of the Western Ghats. While some sky islands in the system are isolated by ancient valleys, others are separated by deforestation. We examined 14 frequency and temporal spectral traits and two syntax traits from 835 songs of 38 individuals across the six populations. We identified three major song clusters based on a discriminant model of spectral traits, degree of similarity of syntax features, as well as responses of birds to opportunistic playback. However, some traits like complex vocal mechanisms (CVM), relating to the use of syrinxes, clearly differentiated both ancient and recently fragmented populations. We suggest that CVMs may have a cultural basis and can be used to identify culturally isolated populations that cannot be differentiated using genetic markers or commonly used frequency‐based song traits. Our results demonstrate the use of bird songs to reconstruct phylogenetic groups and impacts of habitat fragmentation even in complex scenarios of historic and contemporary isolation.     

Evolution of Rotifer Life Histories

When compared to most other multicellular animals, rotifers are all relatively small, short-lived and fast-reproducing organisms. However among and within different rotifer species there is a large variation in life history patterns. This review accounts for such variation in rotifers, with a strong focus on monogonont rotifers. As the life cycle of monogonont rotifers involves both asexual and sexual reproduction, life history patterns can be examined on the level of the genetic individual, which includes all asexual females, sexual females and males that originated from one resting egg. This concept has been applied successfully in many areas, for example in predicting optimal levels of mictic reproduction or sex allocation theory. The benefits and implications of the view of the genetic individual are discussed in detail. Rotifer life histories can also be viewed on the level of physiological individuals. A large part of this review deals with the life histories of individual amictic females and addresses life history traits like body size, egg size and resource allocation patterns. It asks which trade-offs exist among those traits, how these traits change under the influence of environmental factors like food availability or temperature, and whether these changes can be interpreted as adaptive.     

Insulin-like growth factor-1 is associated with life-history variation across Mammalia

Despite the diversity of mammalian life histories, persistent patterns of covariation have been identified, such as the ‘fast–slow’ axis of life-history covariation. Smaller species generally exhibit ‘faster’ life histories, developing and reproducing rapidly, but dying young. Hormonal mechanisms with pleiotropic effects may mediate such broad patterns of life-history variation. Insulin-like growth factor 1 (IGF-1) is one such mechanism because heightened IGF-1 activity is related to traits associated with faster life histories, such as increased growth and reproduction, but decreased lifespan. Using comparative methods, we show that among 41 mammalian species, increased plasma IGF-1 concentrations are associated with fast life histories and altricial reproductive patterns. Interspecific path analyses show that the effects of IGF-1 on these broad patterns of life-history variation are through its direct effects on some individual life-history traits (adult body size, growth rate, basal metabolic rate) and through its indirect effects on the remaining life-history traits. Our results suggest that the role of IGF-1 as a mechanism mediating life-history variation is conserved over the evolutionary time period defining mammalian diversification, that hormone–trait linkages can evolve as a unit, and that suites of life-history traits could be adjusted in response to selection through changes in plasma IGF-1.     

Positive genetic correlations among major life-history traits related to ecological success in the aphid Myzus persicae

Life-history theory is based on the assumption that evolution is constrained by trade-offs among different traits that contribute to fitness. Such trade-offs should be evident from negative genetic correlations among major life-history traits. However, this expectation is not always met. Here I report the results of a life-table experiment designed to measure the broad-sense heritabilities of life-history traits and their genetic correlations in 19 different clones of the aphid Myzus persicae from Victoria, Australia. Most individual traits, as well as fitness calculated as the finite rate of increase from the life table, exhibited highly significant heritabilities. The pattern of genetic correlations revealed absolutely no evidence for life-history trade-offs. Rather, life histories were arranged along an axis from better to worse. Clones with shorter development times tended to have larger body sizes, higher fecundities, and larger offspring. The fitness of clones estimated from the life table in the laboratory tended to be positively associated with their abundance in the field. Fitness also increased significantly with heterozygosity at the seven microsatellite loci that were used to distinguish clones and estimate their frequencies in the field. I discuss these findings in light of a recent proposition that positive genetic correlations among life-history traits for which trade-offs are expected can be explained by genetic variation for resource acquisition ability that is maintained in populations by a cost of acquisition, and I propose ways to test for such a cost in M. persicae.     

Is the F(ST) a good predictor of extinction?

The organization of neutral genetic variation has long been used as a diagnostic tool to infer demographic properties of populations, and recently it has been shown that this information can also be used to estimate the magnitude of genetic deterioration in small or fragmented populations. A further step of this research is to assess whether neutral genetic indicators can serve to predict and compare the viabilities of endangered species. I use modeling to explore how ecological metapopulation settings are related to neutral genetic indicators (such as the fixation index [F(ST)]), changes in genetic load, and metapopulation viability. The analysis indicates that genetic indicators are generally strongly and consistently correlated with the genetic load, population size and structure, and time of extinction but identifies two potential limitations for their use in viability assessments. First, the regime of environmental perturbations is not accurately reflected by neutral indicators, so that their predictive power may be reduced in variable environments. Second, many species are threatened by recent human-induced changes of their habitat configuration. In most cases, genetic indicators may not have reached their equilibrium value in the altered habitat, which limits their ability to compare species with heterogeneous histories and life-history traits.     

Systems biology strategy to study lipotoxicity and the metabolic syndrome

Systems biology views and studies the biological systems in the context of complex interactions between their building blocks and processes. Given its multi-level complexity, metabolic syndrome (MetS) makes a strong case for adopting the systems biology approach. Despite many MetS traits being highly heritable, it is becoming evident that the genetic contribution to these traits is mediated via gene–gene and gene–environment interactions across several spatial and temporal scales, and that some of these traits such as lipotoxicity may even be a product of long-term dynamic changes of the underlying genetic and molecular networks. This presents several conceptual as well as methodological challenges and may demand a paradigm shift in how we study the undeniably strong genetic component of complex diseases such as MetS. The argument is made here that for adopting systems biology approaches to MetS an integrative framework is needed which glues the biological processes of MetS with specific physiological mechanisms and principles and that lipotoxicity is one such framework. The metabolic phenotypes, molecular and genetic networks can be modeled within the context of such integrative framework and the underlying physiology.     

Vicious circles: positive feedback in major evolutionary and ecological transitions

Evolutionary biologists and ecologists often focus on equilibrium states that are subject to forms of negative feedback, such as optima for phenotypic traits or regulation of population sizes. However, recent theoretical and empirical studies show how positive feedback can be instrumental in driving many of the most important and spectacular processes in evolutionary ecology, including the evolution of sex and genetic systems, mating systems, life histories, complex cooperation in insects and humans, ecological specialization, species diversity, species ranges, speciation and extinction. Taken together, this work suggests that positive feedback is more common than is generally appreciated, and that its self-reinforcing dynamics generate the conditions for changes that might otherwise be difficult or impossible for selection or other mechanisms to achieve. Testing for positive feedback requires analysing each causal link in feedback loops, tracking genetic, character and population-dynamic changes across generations, and elucidating the conditions that can result in self-reinforcing change.     

Parameters in dynamic models of complex traits are containers of missing heritability

Polymorphisms identified in genome-wide association studies of human traits rarely explain more than a small proportion of the heritable variation, and improving this situation within the current paradigm appears daunting. Given a well-validated dynamic model of a complex physiological trait, a substantial part of the underlying genetic variation must manifest as variation in model parameters. These parameters are themselves phenotypic traits. By linking whole-cell phenotypic variation to genetic variation in a computational model of a single heart cell, incorporating genotype-to-parameter maps, we show that genome-wide association studies on parameters reveal much more genetic variation than when using higher-level cellular phenotypes. The results suggest that letting such studies be guided by computational physiology may facilitate a causal understanding of the genotype-to-phenotype map of complex traits, with strong implications for the development of phenomics technology.     

Testing hypotheses regarding the genetics of adaptation

Many of the hypotheses regarding the genetics of adaptation require that one know specific details about the genetic basis of complex traits, such as the number and effects of the loci involved. Developments in molecular biology have made it possible to create relatively dense maps of markers that can potentially be used to map genes underlying specific traits. However, there are a number of reasons to doubt that such mapping will provide the level of resolution necessary to specifically address many evolutionary questions. Moreover, evolutionary change is built upon the substitution of individual mutations, many of which may now be cosegregating in the same allele. In order for this developing area not to become a mirage that traps the efforts of an entire field, the genetic dissection of adaptive traits should be conducted within a strict hypothesis-testing framework and within systems that promise a reasonable chance of identifying the specific genetic changes of interest. Continuing advances in molecular technology may lead the way here, but some form of genetic testing is likely to be forever required.     

Cross-species gene transfer; implications for a new theory of evolution

It has been established that genes can be transferred and expressed among procaryotes of different species. I am hypothesizing--and there is mounting evidence for this conclusion--that genes are transferred and expressed among all species, and that such exchange is facilitated by, and can help account for, the existence of the biological unities, from the uniform genetic code to the cross-species similarity of the stages of embryological development. If this idea is correct, the uniformity of the genetic code would allow organisms to decipher and use genes transposed from chromosomes of foreign species, and the shared sequence of embryological development within each phylum would allow the organism to integrate these genes, particularly when the genes affect complex morphological traits. The cross-species gene transfer model could help explain many observations which have puzzled evolutionists, such as rapid bursts in evolution and the widespread occurrence of parallelism in the fossil record.     

Population genetics of genomics-based crop improvement methods

Many genome-wide association studies (GWAS) in humans are concluding that, even with very large sample sizes and high marker densities, most of the genetic basis of complex traits may remain unexplained. At the same time, recent research in plant GWAS is showing much greater success with fewer resources. Both GWAS and genomic selection (GS), a method for predicting phenotypes by the use of genome-wide marker data, are receiving considerable attention among plant breeders. In this review we explore how differences in population genetic histories, as well as past selection for traits of interest, have produced trait architectures and patterns of linkage disequilibrium (LD) that frequently differ dramatically between domesticated plants and humans, making detection of quantitative trait loci (QTL) effects in crops more rewarding and less costly than in humans.     

A potential resolution to the lek paradox through indirect genetic effects

Females often prefer males with elaborate traits, even when they receive no direct benefits from their choice. In such situations, mate discrimination presumably has genetic advantages; selective females will produce offspring of higher genetic quality. Over time, persistent female preferences for elaborate secondary-sexual traits in males should erode genetic variance in these traits, eventually eliminating any benefit to the preferences. Yet, strong female preferences persist in many taxa. This puzzle is called the lek paradox and raises two primary questions: do females obtain genetic benefits for offspring by selecting males with elaborate secondary-sexual characteristics and, if so, how is the genetic variation in these male traits maintained? We suggest that indirect genetic effects may help to resolve the lek paradox. Maternal phenotypes, such as habitat selection behaviours and offspring provisioning, often influence the condition and the expression of secondary-sexual traits in sons. These maternal influences are commonly genetic based (i.e. they are indirect genetic effects). Females choosing mates with elaborate traits may receive ‘good genes’ for daughters in the form of effective maternal characteristics. Recognizing the significance of indirect genetic effects may be important to our understanding of the process and consequences of sexual selection.     

Quantitative trait locus analysis of longitudinal quantitative trait data in complex pedigrees

There is currently considerable interest in genetic analysis of quantitative traits such as blood pressure and body mass index. Despite the fact that these traits change throughout life they are commonly analyzed only at a single time point. The genetic basis of such traits can be better understood by collecting and effectively analyzing longitudinal data. Analyses of these data are complicated by the need to incorporate information from complex pedigree structures and genetic markers. We propose conducting longitudinal quantitative trait locus (QTL) analyses on such data sets by using a flexible random regression estimation technique. The relationship between genetic effects at different ages is efficiently modeled using covariance functions (CFs). Using simulated data we show that the change in genetic effects over time can be well characterized using CFs and that including parameters to model the change in effect with age can provide substantial increases in power to detect QTL compared with repeated measure or univariate techniques. The asymptotic distributions of the methods used are investigated and methods for overcoming the practical difficulties in fitting CFs are discussed. The CF-based techniques should allow efficient multivariate analyses of many data sets in human and natural population genetics.