Evolutionary ecology of dispersal in biodiverse spatially structured systems: what is old and what is new?

Dispersal is a well-recognized driver of ecological and evolutionary dynamics, and simultaneously an evolving trait. Dispersal evolution has traditionally been studied in single-species metapopulations so that it remains unclear how dispersal evolves in metacommunities and metafoodwebs, which are characterized by a multitude of species interactions. Since most natural systems are both species-rich and spatially structured, this knowledge gap should be bridged. Here, we discuss whether knowledge from dispersal evolutionary ecology established in single-species systems holds in metacommunities and metafoodwebs and we highlight generally valid and fundamental principles. Most biotic interactions form the backdrop to the ecological theatre for the evolutionary dispersal play because interactions mediate patterns of fitness expectations across space and time. While this allows for a simple transposition of certain known principles to a multispecies context, other drivers may require more complex transpositions, or might not be transferred. We discuss an important quantitative modulator of dispersal evolution-increased trait dimensionality of biodiverse meta-systems-and an additional driver: co-dispersal. We speculate that scale and selection pressure mismatches owing to co-dispersal, together with increased trait dimensionality, may lead to a slower and more 'diffuse' evolution in biodiverse meta-systems. Open questions and potential consequences in both ecological and evolutionary terms call for more investigation. This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.

Patterns and evolutionary consequences of pleiotropy

Pleiotropy refers to the phenomenon of one gene or one mutation affecting multiple phenotypic traits. While the concept of pleiotropy is as old as Mendelian genetics, functional genomics has finally allowed the first glimpses of the extent of pleiotropy for a large fraction of genes in a genome. After describing conceptual and operational difficulties in quantifying pleiotropy and the pros and cons of various methods for measuring pleiotropy, I review empirical data on pleiotropy, which generally show an L-shaped distribution of the degree of pleiotropy (i.e., the number of traits affected) with most genes having low pleiotropy. I then review the current understanding of the molecular basis of pleiotropy. The rest of the review discusses evolutionary consequences of pleiotropy, focusing on advances in topics including the cost of complexity, regulatory vs. coding evolution, environmental pleiotropy and adaptation, evolution of ageing and other seemingly harmful traits, and evolutionary resolution of pleiotropy.

Adaptation in a heterogeneous environment II: to be three or not to be

We propose a model to describe the adaptation of a phenotypically structured population in a H-patch environment connected by migration, with each patch associated with a different phenotypic optimum, and we perform a rigorous mathematical analysis of this model. We show that the large-time behaviour of the solution (persistence or extinction) depends on the sign of a principal eigenvalue, [Formula: see text], and we study the dependency of [Formula: see text] with respect to H. This analysis sheds new light on the effect of increasing the number of patches on the persistence of a population, which has implications in agroecology and for understanding zoonoses; in such cases we consider a pathogenic population and the patches correspond to different host species. The occurrence of a springboard effect, where the addition of a patch contributes to persistence, or on the contrary the emergence of a detrimental effect by increasing the number of patches on the persistence, depends in a rather complex way on the respective positions in the phenotypic space of the optimal phenotypes associated with each patch. From a mathematical point of view, an important part of the difficulty in dealing with [Formula: see text], compared to [Formula: see text] or [Formula: see text], comes from the lack of symmetry. Our results, which are based on a fixed point theorem, comparison principles, integral estimates, variational arguments, rearrangement techniques, and numerical simulations, provide a better understanding of these dependencies. In particular, we propose a precise characterisation of the situations where the addition of a third patch increases or decreases the chances of persistence, compared to a situation with only two patches.

Pleiotropy drives evolutionary repair of the responsiveness of polarized cell growth to environmental cues

The ability of cells to translate different extracellular cues into different intracellular responses is vital for their survival in unpredictable environments. In Saccharomyces cerevisiae, cell polarity is modulated in response to environmental signals which allows cells to adopt varying morphologies in different external conditions. The responsiveness of cell polarity to extracellular cues depends on the integration of the molecular network that regulates polarity establishment with networks that signal environmental changes. The coupling of molecular networks often leads to pleiotropic interactions that can make it difficult to determine whether the ability to respond to external signals emerges as an evolutionary response to environmental challenges or as a result of pleiotropic interactions between traits. Here, we study how the propensity of the polarity network of S. cerevisiae to evolve toward a state that is responsive to extracellular cues depends on the complexity of the environment. We show that the deletion of two genes, BEM3 and NRP1, disrupts the ability of the polarity network to respond to cues that signal the onset of the diauxic shift. By combining experimental evolution with whole-genome sequencing, we find that the restoration of the responsiveness to these cues correlates with mutations in genes involved in the sphingolipid synthesis pathway and that these mutations frequently settle in evolving populations irrespective of the complexity of the selective environment. We conclude that pleiotropic interactions make a significant contribution to the evolution of networks that are responsive to extracellular cues.

Rate of environmental variation impacts the predictability in evolution

In the two last decades, we have improved our understanding of the adaptive evolution of natural populations under constant and stable environments. For instance, experimental methods from evolutionary biology have allowed us to explore the structure of fitness landscapes and survey how the landscape properties can constrain the adaptation process. However, understanding how environmental changes can affect adaptation remains challenging. Very little progress has been made with respect to time-varying fitness landscapes. Using the adaptive-walk approximation, we survey the evolutionary process of populations under a scenario of environmental variation. In particular, we investigate how the rate of environmental variation influences the predictability in evolution. We observe that the rate of environmental variation not only changes the duration of adaptive walks towards fitness peaks of the fitness landscape, but also affects the degree of repeatability of both outcomes and evolutionary paths. In general, slower environmental variation increases the predictability in evolution. The accessibility of endpoints is greatly influenced by the ecological dynamics. The dependence of these quantities on the genome size and number of traits is also addressed. To our knowledge, this contribution is the first to use the predictive approach to quantify and understand the impact of the speed of environmental variation on the degree of parallelism of the evolutionary process.

On the Fourier transform of a quantitative trait: Implications for compressive sensing

This paper explores the genotype-phenotype relationship. It outlines conditions under which the dependence of a quantitative trait on the genome might be predictable, based on measurement of a limited subset of genotypes. It uses the theory of real-valued Boolean functions in a systematic way to translate trait data into the Fourier domain. Important trait features, such as the roughness of the trait landscape or the modularity of a trait have a simple Fourier interpretation. Roughness at a gene location corresponds to high sensitivity to mutation, while a modular organization of gene activity reduces such sensitivity. Traits where rugged loci are rare will naturally compress gene data in the Fourier domain, leading to a sparse representation of trait data, concentrated in identifiable, low-level coefficients. This Fourier representation of a trait organizes epistasis in a form which is isometric to the trait data. As Fourier matrices are known to be maximally incoherent with the standard basis, this permits employing compressive sensing techniques to work from data sets that are relatively small-sometimes even of polynomial size-compared to the exponentially large sets of possible genomes. This theory provides a theoretical underpinning for systematic use of Boolean function machinery to dissect the dependency of a trait on the genome and environment.

Maintenance of Complex Trait Variation: Classic Theory and Modern Data

Numerous studies have found evidence that GWAS loci experience negative selection, which increases in intensity with the effect size of identified variants. However, there is also accumulating evidence that this selection is not entirely mediated by the focal trait and contains a substantial pleiotropic component. Understanding how selective constraint shapes phenotypic variation requires advancing models capable of balancing these and other components of selection, as well as empirical analyses capable of inferring this balance and how it is generated by the underlying biology. We first review the classic theory connecting phenotypic selection to selection at individual loci as well as approaches and findings from recent analyses of negative selection in GWAS data. We then discuss geometric theories of pleiotropic selection with the potential to guide future modeling efforts. Recent findings revealing the nature of pleiotropic genetic variation provide clues to which genetic relationships are important and should be incorporated into analyses of selection, while findings that effect sizes vary between populations indicate that GWAS measurements could be misleading if effect sizes have also changed throughout human history.

Morphological canalization, integration, and plasticity in response to population density in Abutilon theophrasti: Influences of soil conditions and growth stages

Phenotypic integration and developmental canalization have been hypothesized to constrain the degree of phenotypic plasticity, but little evidence exists, probably due to the lack of studies on the relationships among the three processes, especially for plants under different environments. We conducted a field experiment by subjecting plants of Abutilon theophrasti to three densities, under infertile and fertile soil conditions, and analyzing correlations among canalization, integration, and plasticity in a variety of measured morphological traits after 50 and 70 days, to investigate the relationships among the three variables in response to density and how these responses vary with soil conditions and growth stages. Results showed trait canalization decreased and phenotypic integration and the degree of plasticity (absolute plasticity) in traits increased with density. Phenotypic integration often positively correlated with absolute plasticity, whereas correlations between trait canalization and plasticity were insignificant in most cases, with a few positive ones between canalization and absolute plasticity at low and medium densities. As plants grew, these correlations intensified in infertile soil and attenuated in fertile soil. Our findings suggested the complexity of the relationship between canalization and plasticity: Decreased canalization is more likely to facilitate active plastic responses under more favorable conditions, whereas increased level of integration should mainly be an outcome of plastic responses. Soil conditions and growth stage may affect responses of these correlations to density via modifying plant size, competition strength, and plastic responses in traits. We also predicted that decreased canalization can be advantageous or disadvantageous, and the lack of response to stress may demonstrate a stronger ability of adaptation than passive response, thus should be adaptive plasticity as active response.

Sensitivity to expression levels underlies differential dominance of a putative null allele of the Drosophila tβh gene in behavioral phenotypes

The biogenic amine octopamine (OA) and its precursor tyramine (TA) are involved in controlling a plethora of different physiological and behavioral processes. The tyramine-β-hydroxylase (tβh) gene encodes the enzyme catalyzing the last synthesis step from TA to OA. Here, we report differential dominance (from recessive to overdominant) of the putative null tβh^nM18 allele in 2 behavioral measures in Buridan’s paradigm (walking speed and stripe deviation) and in proboscis extension (sugar sensitivity) in the fruit fly Drosophila melanogaster. The behavioral analysis of transgenic tβh expression experiments in mutant and wild-type flies as well as of OA and TA receptor mutants revealed a complex interaction of both aminergic systems. Our analysis suggests that the different neuronal networks responsible for the 3 phenotypes show differential sensitivity to tβh gene expression levels. The evidence suggests that this sensitivity is brought about by a TA/OA opponent system modulating the involved neuronal circuits. This conclusion has important implications for standard transgenic techniques commonly used in functional genetics.

Differential dominance occurs when genes associated with several phenotypes (pleiotropic genes) show different modes of inheritance (e.g., recessive, dominant or overdominant) depending on the phenotype. This study reveals that differential sensitivity to gene expression levels can mediate differential dominance, which can be a significant challenge for standard transgenic techniques commonly used to elucidate gene function.

Comprehensive study of the genes involved in chlorophyll synthesis and degradation pathways in some monocot and dicot plant species

Chlorophyll (Chl) biosynthesis is one of the most important cellular processes essential for plant photosynthesis. Chl degradation pathway is also important catabolic process occurs during leaf senescence, fruit ripening and under biotic or abiotic stress conditions. Here we have systematically investigated the molecular evolution, gene structure, compositional analysis along with ENc plot, correspondence analysis and codon usage bias of the proteins and encoded genes involved in Chl metabolism from monocots and dicots. The gene and species specific phylogenetic trees using amino acid sequences showed clear clustering formation of the selected species based on monocots and dicots but not supported by 18S rRNA. Nucleotide composition of the encoding genes showed that average GC%, GC1%, GC2% and GC3% were higher in monocots. RSCU analysis depicts that genes from monocots for both pathways and genes for synthesis pathway from dicots only biased to G/C-ending synonymous codons but in degradation pathway most optimal codons (except UUG) in dicots biased to A/U-ending synonymous codons. We found strong evidence of episodic diversifying selection at several amino acid sites in all genes investigated. Conserved domain and gene structures were observed for the genes with varying lengths of introns and exons, involved in Chl metabolism along with some intronless genes within synthesis pathway. ENc and correspondence analyses suggested the mutational or selection constraint on the genes to shape the codon usage. These comprehensive studies may be helpful in further research in molecular phylogenetics and genomics and to better understand the evolutionary dynamics of Chl metabolic pathway.Communicated by Ramaswamy H. Sarma.

Genetic constraints on microevolutionary divergence of sex-biased gene expression

The evolution of sex-specific phenotypes is an important dimension of diversification and local adaptation. The sex-dependent regulation of gene expression is considered a key genomic mechanism facilitating sex-dependent adaptation. In many species, genes with male-biased expression evolve faster in DNA sequence and expression level than genes with female-biased or sexually monomorphic expression. While positive selection may be responsible for rapid DNA sequence evolution, why expression of male-biased genes also evolves rapidly remains unclear. Beyond sex differences in selection, some aspects of the genetic architecture of gene expression could contribute to the rapid evolution of male-biased gene expression. First, male-biased genes might simply have greater standing genetic variance than female-biased genes. Second, male-biased genes could be less constrained by pleiotropy, either within or between sexes. Here, we evaluate these alternative explanations on an intraspecific scale using a series of quantitative genetic experiments conducted on natural variation in male and female gene expression in the fly Drosophila serrata Male-biased genes had significantly higher genetic variance than female-biased genes and were generally more narrowly expressed across tissues, suggesting lower within-individual pleiotropy. However, consistent with stronger constraints due to between-sex pleiotropy, their between-sex genetic correlations, r_MF, were higher than for female-biased genes and more strongly negatively associated with sex bias. Using an extensive clinal dataset, we tested whether sex differences in gene expression divergence among populations have been shaped by pleiotropy. Here too, male-biased gene divergence was more strongly associated with between-sex pleiotropy than was female-biased gene divergence. Systematic differences in genetic variance and pleiotropy may be important factors influencing sex-specific adaptation arising through changes in gene expression.This article is part of the theme issue 'Linking local adaptation with the evolution of sex differences'.

Alleles of a gene differ in pleiotropy, often mediated through currency metabolite production, in E. coli and yeast metabolic simulations

A major obstacle to the mapping of genotype-phenotype relationships is pleiotropy, the tendency of mutations to affect seemingly unrelated traits. Pleiotropy has major implications for evolution, development, ageing, and disease. Except for disease data, pleiotropy is almost exclusively estimated from full gene knockouts. However, most deleterious alleles segregating in natural populations do not fully abolish gene function, and the degree to which a polymorphism reduces protein function may influence the number of traits it affects. Utilizing genome-scale metabolic models for Escherichia coli and Saccharomyces cerevisiae, we show that most fitness-reducing full gene knockouts of metabolic genes in these fast-growing microbes have pleiotropic effects, i.e., they compromise the production of multiple biomass components. Alleles of the same metabolic enzyme-encoding gene with increasingly reduced enzymatic function typically affect an increasing number of biomass components. This increasing pleiotropy is often mediated through effects on the generation of currency metabolites such as ATP or NADPH. We conclude that the physiological effects observed in full gene knockouts of metabolic genes will in most cases not be representative for alleles with only partially reduced enzyme capacity or expression level.

Pathway position constrains the evolution of an ecologically important pathway in aspens (Populus tremula L.)

Many ecological interactions of aspens and their relatives (Populus spp.) are affected by products of the phenylpropanoid pathway synthesizing condensed tannins (CTs), whose production involves trade-offs with other ecologically important compounds and with growth. Genes of this pathway are candidates for investigating the role of selection on ecologically important, polygenic traits. We analysed sequences from 25 genes representing 10 steps of the CT synthesis pathway, which produces CTs used in defence and lignins used for growth, in 12 individuals of European aspen (Populus tremula). We compared these to homologs from P. trichocarpa, to a control set of 77 P. tremula genes, to genome-wide resequencing data and to RNA-seq expression levels, in order to identify signatures of selection distinct from those of demography. In Populus, pathway position exerts a strong influence on the evolution of these genes. Nonsynonymous diversity, divergence and allele frequency shifts (Tajima's D) were much lower than for synonymous measures. Expression levels were higher, and the direction of selection more negative, for upstream genes than for those downstream. Selective constraints act with increasing intensity on upstream genes, despite the presence of multiple paralogs in most gene families. Pleiotropy, expression level, flux control and codon bias appear to interact in determining levels and patterns of variation in genes of this pathway, whose products mediate a wide array of ecological interactions for this widely distributed species.

Gene regulatory network architecture in different developmental contexts influences the genetic basis of morphological evolution

Convergent phenotypic evolution is often caused by recurrent changes at particular nodes in the underlying gene regulatory networks (GRNs). The genes at such evolutionary ‘hotspots’ are thought to maximally affect the phenotype with minimal pleiotropic consequences. This has led to the suggestion that if a GRN is understood in sufficient detail, the path of evolution may be predictable. The repeated evolutionary loss of larval trichomes among Drosophila species is caused by the loss of shavenbaby (svb) expression. svb is also required for development of leg trichomes, but the evolutionary gain of trichomes in the ‘naked valley’ on T2 femurs in Drosophila melanogaster is caused by reduced microRNA-92a (miR-92a) expression rather than changes in svb. We compared the expression and function of components between the larval and leg trichome GRNs to investigate why the genetic basis of trichome pattern evolution differs in these developmental contexts. We found key differences between the two networks in both the genes employed, and in the regulation and function of common genes. These differences in the GRNs reveal why mutations in svb are unlikely to contribute to leg trichome evolution and how instead miR-92a represents the key evolutionary switch in this context. Our work shows that variability in GRNs across different developmental contexts, as well as whether a morphological feature is lost versus gained, influence the nodes at which a GRN evolves to cause morphological change. Therefore, our findings have important implications for understanding the pathways and predictability of evolution.

A major goal of biology is to identify the genetic causes of organismal diversity. Convergent evolution of traits is often caused by changes in the same genes–evolutionary ‘hotspots’. shavenbaby is a ‘hotspot’ for larval trichome loss in Drosophila, but microRNA-92a underlies the gain of leg trichomes. To understand this difference in the genetics of phenotypic evolution, we compared the expression and function of genes in the underlying regulatory networks. We found that the pathway of evolution is influenced by differences in gene regulatory network architecture in different developmental contexts, as well as by whether a trait is lost or gained. Therefore, hotspots in one context may not readily evolve in a different context. This has important implications for understanding the genetic basis of phenotypic change and the predictability of evolution.

Phylogenetic and Evolutionary Analysis of Plant ARGONAUTES

Comparative sequence analysis is widely used for the reconstruction of phylogeny and for understanding the evolutionary history of gene families. Here, we describe the methodologies to reconstruct the phylogenetic and evolutionary history of a gene family across genomes with a focus on the ARGONAUTE (AGO) family of proteins in plants. The method described here may easily be adapted for studying molecular evolution of a wide variety of gene families. We enlist methods as well as parameters for the collection of molecular data (nucleic acids and peptides), preparation of datasets, and selection of evolutionary models and various methods for the phylogenetic and evolutionary analysis, such as maximum likelihood and Bayesian inference.

Domestication and the storage starch biosynthesis pathway: signatures of selection from a whole sorghum genome sequencing strategy

Next-generation sequencing of complete genomes has given researchers unprecedented levels of information to study the multifaceted evolutionary changes that have shaped elite plant germplasm. In conjunction with population genetic analytical techniques and detailed online databases, we can more accurately capture the effects of domestication on entire biological pathways of agronomic importance. In this study, we explore the genetic diversity and signatures of selection in all predicted gene models of the storage starch synthesis pathway of Sorghum bicolor, utilizing a diversity panel containing lines categorized as either 'Landraces' or 'Wild and Weedy' genotypes. Amongst a total of 114 genes involved in starch synthesis, 71 had at least a single signal of purifying selection and 62 a signal of balancing selection and others a mix of both. This included key genes such as STARCH PHOSPHORYLASE 2 (SbPHO2, under balancing selection), PULLULANASE (SbPUL, under balancing selection) and ADP-glucose pyrophosphorylases (SHRUNKEN2, SbSH2 under purifying selection). Effectively, many genes within the primary starch synthesis pathway had a clear reduction in nucleotide diversity between the Landraces and wild and weedy lines indicating that the ancestral effects of domestication are still clearly identifiable. There was evidence of the positional rate variation within the well-characterized primary starch synthesis pathway of sorghum, particularly in the Landraces, whereby low evolutionary rates upstream and high rates downstream in the metabolic pathway were expected. This observation did not extend to the wild and weedy lines or the minor starch synthesis pathways.

The Nonstationary Dynamics of Fitness Distributions: Asexual Model with Epistasis and Standing Variation

Various models describe asexual evolution by mutation, selection, and drift. Some focus directly on fitness, typically modeling drift but ignoring or simplifying both epistasis and the distribution of mutation effects (traveling wave models). Others follow the dynamics of quantitative traits determining fitness (Fisher's geometric model), imposing a complex but fixed form of mutation effects and epistasis, and often ignoring drift. In all cases, predictions are typically obtained in high or low mutation rate limits and for long-term stationary regimes, thus losing information on transient behaviors and the effect of initial conditions. Here, we connect fitness-based and trait-based models into a single framework, and seek explicit solutions even away from stationarity. The expected fitness distribution is followed over time via its cumulant generating function, using a deterministic approximation that neglects drift. In several cases, explicit trajectories for the full fitness distribution are obtained for arbitrary mutation rates and standing variance. For nonepistatic mutations, especially with beneficial mutations, this approximation fails over the long term but captures the early dynamics, thus complementing stationary stochastic predictions. The approximation also handles several diminishing returns epistasis models (e.g., with an optimal genotype); it can be applied at and away from equilibrium. General results arise at equilibrium, where fitness distributions display a "phase transition" with mutation rate. Beyond this phase transition, in Fisher's geometric model, the full trajectory of fitness and trait distributions takes a simple form; robust to the details of the mutant phenotype distribution. Analytical arguments are explored regarding why and when the deterministic approximation applies.

Epigenetic resolution of the 'curse of complexity' in adaptive evolution of complex traits

The age of most genes exceeds the longevity of their genomic and physiological associations by many orders of magnitude. Such transient contexts modulate the expression of ancient genes to produce currently appropriate and often highly distinct developmental and functional outcomes. The efficacy of such adaptive modulation is diminished by the high dimensionality of complex organisms and associated vast areas of neutrality in their genotypic and developmental networks (and, thus, weak natural selection). Here I explore whether epigenetic effects facilitate adaptive modulation of complex phenotypes by effectively reducing the dimensionality of their deterministic networks and thus delineating their developmental and evolutionary trajectories even under weak selection. Epigenetic effects that link unconnected or widely dispersed elements of genotype space in ecologically relevant time could account for the rapid appearance of functionally integrated adaptive modifications. On an organismal time scale, conceptually similar processes occur during recurrent epigenetic reprogramming of somatic stem cells to produce, recurrently and reversibly, a bewildering array of differentiated and persistent cell lineages, all sharing identical genomic sequences despite strongly distinct phenotypes. I discuss whether close dependency of onset, scope and duration of epigenetic effects on cellular and genomic context in stem cells could provide insights into contingent modulation of conserved genomic material on a much longer evolutionary time scale. I review potential empirical examples of epigenetic bridges that reduce phenotype dimensionality and accomplish rapid adaptive modulation in the evolution of novelties, expression of behavioural types, and stress-induced ossification schedules.

Properties of selected mutations and genotypic landscapes under Fisher's geometric model

The fitness landscape-the mapping between genotypes and fitness-determines properties of the process of adaptation. Several small genotypic fitness landscapes have recently been built by selecting a handful of beneficial mutations and measuring fitness of all combinations of these mutations. Here, we generate several testable predictions for the properties of these small genotypic landscapes under Fisher's geometric model of adaptation. When the ancestral strain is far from the fitness optimum, we analytically compute the fitness effect of selected mutations and their epistatic interactions. Epistasis may be negative or positive on average depending on the distance of the ancestral genotype to the optimum and whether mutations were independently selected, or coselected in an adaptive walk. Simulations show that genotypic landscapes built from Fisher's model are very close to an additive landscape when the ancestral strain is far from the optimum. However, when it is close to the optimum, a large diversity of landscape with substantial roughness and sign epistasis emerged. Strikingly, small genotypic landscapes built from several replicate adaptive walks on the same underlying landscape were highly variable, suggesting that several realizations of small genotypic landscapes are needed to gain information about the underlying architecture of the fitness landscape.

The Utility of Fisher's Geometric Model in Evolutionary Genetics

The accumulation of data on the genomic bases of adaptation has triggered renewed interest in theoretical models of adaptation. Among these models, Fisher Geometric Model (FGM) has received a lot of attention over the last two decades. FGM is based on a continuous multidimensional phenotypic landscape, but it is for the emerging properties of individual mutation effects that it is mostly used. Despite an apparent simplicity and a limited number of parameters, FGM integrates a full model of mutation and epistatic interactions that allows the study of both beneficial and deleterious mutations, and subsequently the fate of evolving populations. In this review, I present the different properties of FGM and the qualitative and quantitative support they have received from experimental evolution data. I later discuss how to estimate the different parameters of the model and outline some future directions to connect FGM and the molecular determinants of adaptation.

On the effect of phenotypic dimensionality on adaptation and optimality

What proportion of the traits of individuals has been optimally shaped by natural selection and what has not? Here, we estimate the maximal number of those traits using a mathematical model for natural selection in multitrait organisms. The model represents the most ideal conditions for natural selection: a simple genotype-phenotype map and independent variation between traits. The model is also used to disentangle the influence of fitness functions and the number of traits, n, per se on the efficiency of natural selection. We also allow n to evolve. Our simulations show that, for all fitness functions and even in the best conditions optimal phenotypes are rarely encountered, only for n = 1, and that a large proportion of traits are always far from their optimum, specially for large n. This happens to different degrees depending on the fitness functions (additive linear, additive nonlinear, Gaussian and multiplicative). The traits that arise earlier in evolution account for a larger proportion of the absolute fitness of individuals. Thus, complex phenotypes have, in proportion, more traits that are far from optimal and the closeness to the optimum correlates with the age of the trait. Based on estimated population sizes, mutation rates and selection coefficients, we provide an upper estimation of the number of traits that can become and remain adapted by direct natural selection.

Pleiotropy can be effectively estimated without counting phenotypes through the rank of a genotype-phenotype map

Although pleiotropy, the capability of a gene to affect multiple phenotypes, has been well known as one of the common gene properties, a quantitative estimation remains a great challenge, simply because of the phenotype complexity. Not surprisingly, it is hard for general readers to understand how, without counting phenotypes, gene pleiotropy can be effectively estimated from the genetics data. In this article we extensively discuss the Gu-2007 method that estimated pleiotropy from the protein sequence analysis. We show that this method is actually to estimate the rank (K) of genotype-phenotype mapping that can be concisely written as K = min(r, Pmin), where Pmin is the minimum pleiotropy among all legitimate measures including the fitness components, and r is the rank of mutational effects of an amino acid site. Together, the effective gene pleiotropy (Ke) estimated by the Gu-2007 method has the following meanings: (i) Ke is an estimate of K = min(r, Pmin), the rank of a genotype-phenotype map; (ii) Ke is an estimate for the minimum pleiotropy Pmin only if Pmin < r; (iii) the Gu-2007 method attempted to estimate the pleiotropy of amino acid sites, a conserved proxy to the true gene pleiotropy; (iv) with a sufficiently large phylogeny such that the rank of mutational effects at an amino acid site is r → 19, one can estimate Pmin between 1 and 19; and (v) Ke is a conserved estimate of K because those slightly affected components in fitness have been effectively removed by the estimation procedure. In addition, we conclude that mutational pleiotropy (number of traits affected by a single mutation) cannot be estimated without knowing the phenotypes.

Allelic variation in genes contributing to glycoalkaloid biosynthesis in a diploid interspecific population of potato

Variation for allelic state within genes of both primary and secondary metabolism influences the quantity and quality of steroidal glycoalkaloids produced in potato leaves. Genetic factors associated with the biosynthesis and accumulation of steroidal glycoalkaloids (SGAs) in potato were addressed by a candidate gene approach and whole genome single nucleotide polymorphism (SNP) genotyping. Allelic sequences spanning coding regions of four candidate genes [3-hydroxy-3-methylglutaryl coenzyme A reductase 2 (HMG2); 2,3-squalene epoxidase; solanidine galactosyltransferase; and solanidine glucosyltransferase (SGT2)] were obtained from two potato species differing in SGA composition: Solanum chacoense (chc 80-1) and Solanum tuberosum group Phureja (phu DH). An F2 population was genotyped and foliar SGAs quantified. The concentrations of α-solanine, α-chaconine, leptine I, leptine II and total SGAs varied broadly among F2 individuals. F2 plants with chc 80-1 alleles for HMG2 or SGT2 accumulated significantly greater leptines and total SGAs compared to plants with phu DH alleles. Plants with chc 80-1 alleles at both loci expressed the greatest levels of total SGAs, α-solanine and α-chaconine. A significant positive correlation was found between α-solanine and α-chaconine accumulation as well as between leptine I and leptine II. A whole genome SNP genotyping analysis of an F2 subsample verified the importance of chc 80-1 alleles at HMG2 and SGT2 for SGA synthesis and accumulation and suggested additional candidate genes including some previously associated with SGA production. Loci on five and seven potato pseudochromosomes were associated with synthesis and accumulation of SGAs, respectively. Two loci, on pseudochromosomes 1 and 6, explained phenotypic segregation of α-solanine and α-chaconine synthesis. Knowledge of the genetic factors influencing SGA production in potato may assist breeding for pest resistance.

Epistasis, pleiotropy, and the mutation load in sexual and asexual populations

Mutation may impose a substantial load on populations, which varies according to the reproductive mode of organisms. Over the past years, various authors used adaptive landscape models to predict the long-term effect of mutation on mean fitness; however, many of these studies assumed very weak mutation rates, so that at most one mutation segregates in the population. In this article, we derive several simple approximations (confirmed by simulations) for the mutation load at high mutation rate (U), using a general model that allows us to play with the number of selected traits (n), the degree of pleiotropy of mutations, and the shape of the fitness function (which affects the average sign and magnitude of epistasis among mutations). When mutations have strong fitness effects, the equilibrium fitness W¯ of sexuals and asexuals is close to e(-U); under weaker mutational effects, sexuals reach a different regime where W¯ is a simple function of U and of a parameter describing the shape of the fitness function. Contrarily to weak mutation results showing that W¯ is an increasing function of population size and a decreasing function of n, these parameters may have opposite effects in sexual populations at high mutation rate.

Pleiotropy of FRIGIDA enhances the potential for multivariate adaptation

An evolutionary response to selection requires genetic variation; however, even if it exists, then the genetic details of the variation can constrain adaptation. In the simplest case, unlinked loci and uncorrelated phenotypes respond directly to multivariate selection and permit unrestricted paths to adaptive peaks. By contrast, 'antagonistic' pleiotropic loci may constrain adaptation by affecting variation of many traits and limiting the direction of trait correlations to vectors that are not favoured by selection. However, certain pleiotropic configurations may improve the conditions for adaptive evolution. Here, we present evidence that the Arabidopsis thaliana gene FRI (FRIGIDA) exhibits 'adaptive' pleiotropy, producing trait correlations along an axis that results in two adaptive strategies. Derived, low expression FRI alleles confer a 'drought escape' strategy owing to fast growth, low water use efficiency and early flowering. By contrast, a dehydration avoidance strategy is conferred by the ancestral phenotype of late flowering, slow growth and efficient water use during photosynthesis. The dehydration avoidant phenotype was recovered when genotypes with null FRI alleles were transformed with functional alleles. Our findings indicate that the well-documented effects of FRI on phenology result from differences in physiology, not only a simple developmental switch.

Investigating the Relationship between Topology and Evolution in a Dynamic Nematode Odor Genetic Network

The relationship between biological network architectures and evolution is unclear. Within the phylum nematoda olfaction represents a critical survival tool. For nematodes, olfaction contributes to multiple processes including the finding of food, hosts, and reproductive partners, making developmental decisions, and evading predators. Here we examine a dynamic nematode odor genetic network to investigate how divergence, diversity, and contribution are shaped by network topology. Our findings describe connectivity frameworks and characteristics that correlate with molecular evolution and contribution across the olfactory network. Our data helps guide the development of a robust evolutionary description of the nematode odor network that may eventually aid in the prediction of interactive and functional qualities of novel nodes.

Intralocus sexual conflict for fitness: sexually antagonistic alleles for testosterone

Intralocus sexual conflict occurs when a trait encoded by the same genetic locus in the two sexes has different optima in males and females. Such conflict is widespread across taxa, however, the shared phenotypic traits that mediate the conflict are largely unknown. We examined whether the sex hormone, testosterone (T), that controls sexual differentiation, contributes to sexually antagonistic fitness variation in the bank vole, Myodes glareolus. We compared (opposite-sex) sibling reproductive fitness in the bank vole after creating divergent selection lines for T. This study shows that selection for T was differentially associated with son versus daughter reproductive success, causing a negative correlation in fitness between full siblings. Our results demonstrate the presence of intralocus sexual conflict for fitness in this small mammal and that sexually antagonistic selection is acting on T. We also found a negative correlation in fitness between parents and their opposite-sex progeny (e.g. father-daughter), highlighting a dilemma for females, as the indirect genetic benefits of selecting reproductively successful males (high T) are lost with daughters. We discuss mechanisms that may mitigate this disparity between progeny quality.

Targets of selection in a disease resistance network in wild tomatoes

Studies combining comparative genomics and information on biochemical pathways have revealed that protein evolution can be affected by the amount of pleiotropy associated with a particular gene. The amount of pleiotropy, in turn, can be a function of the position at which a gene operates in a pathway and the pathway structure. Genes that serve as convergence points and have several partners (so-called hubs) often show the greatest constraint and hence the slowest rate of protein evolution. In this article, we have studied five genes (Pto, Fen, Rin4, Prf and Pfi) in a defence signalling network in a wild tomato species, Solanum peruvianum. These proteins operate together and contribute to bacterial resistance in tomato. We predicted that Prf (and possibly Pfi), which serves as a convergence point for upstream signals, should show greater evolutionary constraint. However, we found instead that two of the genes which potentially interact with pathogen ligands, Rin4 and Fen, have evolved under strong evolutionary constraint, whereas Prf and Pfi, which probably function further downstream in the network, show evidence of balancing selection. This counterintuitive observation may be probable in pathogen defence networks, because pathogens may target positions throughout resistance networks to manipulate or nullify host resistance, thereby leaving a molecular signature of host-parasite co-evolution throughout a single network.

The pleiotropic structure of the genotype-phenotype map: the evolvability of complex organisms

It was first noticed 100 years ago that mutations tend to affect more than one phenotypic characteristic, a phenomenon that was called 'pleiotropy'. Because pleiotropy was found so frequently, the notion arose that pleiotropy is 'universal'. However, quantitative estimates of pleiotropy have not been available until recently. These estimates show that pleiotropy is highly restricted and are more in line with the notion of variational modularity than with universal pleiotropy. This finding has major implications for the evolvability of complex organisms and the mapping of disease-causing mutations.

One hundred years of pleiotropy: a retrospective

Pleiotropy is defined as the phenomenon in which a single locus affects two or more distinct phenotypic traits. The term was formally introduced into the literature by the German geneticist Ludwig Plate in 1910, 100 years ago. Pleiotropy has had an important influence on the fields of physiological and medical genetics as well as on evolutionary biology. Different approaches to the study of pleiotropy have led to incongruence in the way that it is perceived and discussed among researchers in these fields. Furthermore, our understanding of the term has changed quite a bit since 1910, particularly in light of modern molecular data. This review traces the history of the term "pleiotropy" and reevaluates its current place in the field of genetics.

Genomic patterns of pleiotropy and the evolution of complexity

Pleiotropy refers to the phenomenon of a single mutation or gene affecting multiple distinct phenotypic traits and has broad implications in many areas of biology. Due to its central importance, pleiotropy has also been extensively modeled, albeit with virtually no empirical basis. Analyzing phenotypes of large numbers of yeast, nematode, and mouse mutants, we here describe the genomic patterns of pleiotropy. We show that the fraction of traits altered appreciably by the deletion of a gene is minute for most genes and the gene-trait relationship is highly modular. The standardized size of the phenotypic effect of a gene on a trait is approximately normally distributed with variable SDs for different genes, which gives rise to the surprising observation of a larger per-trait effect for genes affecting more traits. This scaling property counteracts the pleiotropy-associated reduction in adaptation rate (i.e., the "cost of complexity") in a nonlinear fashion, resulting in the highest adaptation rate for organisms of intermediate complexity rather than low complexity. Intriguingly, the observed scaling exponent falls in a narrow range that maximizes the optimal complexity. Together, the genome-wide observations of overall low pleiotropy, high modularity, and larger per-trait effects from genes of higher pleiotropy necessitate major revisions of theoretical models of pleiotropy and suggest that pleiotropy has not only allowed but also promoted the evolution of complexity.

A preliminary analysis of gene pleiotropy estimated from protein sequences

Biologists have long recognized the importance of gene pleiotropy, that is, single genes affect multiple traits, which is one of the most commonly observed attributes of genes. Yet the extent of gene pleiotropy has been seriously under-explored. Theoretically, Fisher's model assumed a universal pleiotropy, that is, a mutation can potentially affect all phenotypic traits. On the other hand, experimental assays of a gene usually showed a few distinct phenotypes. Our recent work provides a new approach by estimating the degree of pleiotropy effectively from the phylogenetic sequence analysis. In this article, we estimated the effective gene pleiotropy for 321 vertebrate genes, and found that a gene typically affects 6-7 molecular phenotypes that correspond to the components of organismal fitness, respectively. The positive correlation of gene pleiotropy with the number of Gene Ontology biological processes, as well as the expression broadness provides a biological basis for the sequence-based estimation of gene pleiotropy. On the other hand, the degree of gene pleiotropy has been restricted to a digital number of molecular phenotypes, indicating that some cautions are needed for theoretical analysis of gene pleiotropy based on the assumption of universal pleiotropy.

Co-ordination of osmotic stress responses through osmosensing and signal transduction events in fishes

This review centres upon the molecular regulation of osmotic stress responses in fishes, focusing on how osmosensing and signal transduction events co-ordinate changes in the activity and abundance of effector proteins during osmotic stress and how these events integrate into osmotic stress responses of varying magnitude. The concluding sections discuss the relevance of osmosensory signal transduction to the evolution of euryhalinity and present experimental approaches that may best stimulate future research. Iterating the importance of osmosensing and signal transduction during fish osmoregulation may be pertinent amidst the increased use of genomic technologies that typically focus solely on changes in the abundances of gene products, and may limit insight into critical upstream events that occur mainly through post-translational mechanisms.

Toward a population genetic framework of developmental evolution: the costs, limits, and consequences of phenotypic plasticity

Adaptive phenotypic plasticity allows organisms to cope with environmental variability, and yet, despite its adaptive significance, phenotypic plasticity is neither ubiquitous nor infinite. In this review, we merge developmental and population genetic perspectives to explore costs and limits on the evolution of plasticity. Specifically, we focus on the role of modularity in developmental genetic networks as a mechanism underlying phenotypic plasticity, and apply to it lessons learned from population genetic theory on the interplay between relaxed selection and mutation accumulation. We argue that the environmental specificity of gene expression and the associated reduction in pleiotropic constraints drive a fundamental tradeoff between the range of plasticity that can be accommodated and mutation accumulation in alternative developmental networks. This tradeoff has broad implications for understanding the origin and maintenance of plasticity and may contribute to a better understanding of the role of plasticity in the origin, diversification, and loss of phenotypic diversity.

Explorations in topology-delving underneath the surface of genetic interaction maps

High throughput assays, as well as advances in computational approaches, have recently allowed the acquisition of vast amounts of genetic interaction (GI) data in several organisms. Since GIs are a functional measure that reports on the effect of a mutation in one gene on the phenotype of a mutation in another, they can serve as a powerful tool to study both the function of individual genes and the wiring of biological networks. Therefore, these data hold much promise for advancing our understanding of cellular systems. In this review we focus on the methodologies currently available for using and interpreting large datasets of GIs for functional gene groups (GI maps), and elaborate on the challenges ahead. In addition, we discuss potential applications for the study of evolution and disease mechanisms, and highlight the need for comprehensive integrative analysis to extract the wealth of information found in these maps.

The correlation of evolutionary rate with pathway position in plant terpenoid biosynthesis

Genes are expected to face stronger selective constraint and to evolve more slowly if they encode enzymes upstream as opposed to downstream in metabolic pathways, because upstream genes are more pleiotropic, being required for a wider range of end products. However, few clear examples of this trend in evolutionary rate variation exist. We examined whether genes involved in plant terpenoid biosynthesis exhibit such a pattern, using data for 40 genes from five fully sequenced angiosperms, Oryza, Vitis, Arabidopsis, Populus, and Ricinus. Our results show that d(N)/d(S) does in fact correlate with pathway position along pathways converting glucose to the terpenoid phytohormones abscissic acid, gibberellic acid (GA), and brassinosteroids. Upstream versus downstream rate variation is particularly strong in the GA pathway. In contrast, we found no or little apparent variation in d(N)/d(S) with gene copy number. We also introduce a new measure of pathway position, the Pathway Pleiotropy Index (PPI), which counts groups of enzymes between pathway branch points. We found that this measure is superior to pathway position in explaining variation in d(N)/d(S) along each pathway. Although at least 8 of the 40 genes showed evidence of positive selection, correlations of d(N)/d(S) with PPI remain significant when these genes are removed. Therefore, our results are consistent with the prediction that selective constraint is progressively relaxed along metabolic pathways.

Network-level molecular evolutionary analysis of the insulin/TOR signal transduction pathway across 12 Drosophila genomes

Biological function is based on complex networks consisting of large numbers of interacting molecules. The evolutionary properties of molecular networks and, in particular, the impact of network architecture on the sequence evolution of its individual components are, nonetheless, still poorly understood. Here, we conducted a fine-scale network-level molecular evolutionary analysis of the insulin/TOR pathway across 12 species of Drosophila. We found that the insulin/TOR pathway components are completely conserved across these species and that two genes located at major network branch points show evidence for positive selection. Remarkably, we detected a gradient in the strength of purifying selection along the pathway, increasing from the upstream to the downstream genes. We also found that physically interacting proteins tend to have more similar levels of selective constraint, even though this feature might represent a byproduct of the correlation between selective constraint and the pathway position. Our results clearly indicate that the levels of functional constraint do depend on the position of the proteins in the pathway and, consequently, the architecture of the pathway constrains gene sequence evolution.

The loci of evolution: how predictable is genetic evolution?

Is genetic evolution predictable? Evolutionary developmental biologists have argued that, at least for morphological traits, the answer is a resounding yes. Most mutations causing morphological variation are expected to reside in the cis-regulatory, rather than the coding, regions of developmental genes. This "cis-regulatory hypothesis" has recently come under attack. In this review, we first describe and critique the arguments that have been proposed in support of the cis-regulatory hypothesis. We then test the empirical support for the cis-regulatory hypothesis with a comprehensive survey of mutations responsible for phenotypic evolution in multicellular organisms. Cis-regulatory mutations currently represent approximately 22% of 331 identified genetic changes although the number of cis-regulatory changes published annually is rapidly increasing. Above the species level, cis-regulatory mutations altering morphology are more common than coding changes. Also, above the species level cis-regulatory mutations predominate for genes not involved in terminal differentiation. These patterns imply that the simple question "Do coding or cis-regulatory mutations cause more phenotypic evolution?" hides more interesting phenomena. Evolution in different kinds of populations and over different durations may result in selection of different kinds of mutations. Predicting the genetic basis of evolution requires a comprehensive synthesis of molecular developmental biology and population genetics.

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.

Pleiotropic constraint hampers the resolution of sexual antagonism in vertebrate gene expression

The numerous physiological and phenotypic differences between the sexes, as well as the disparity between male and female reproductive interests, result in sexual conflicts, which are often manifested at the genomic level. Sexually antagonistic genes benefit one sex at the expense of the other and experience strong pressure to evolve male- and female-specific expression patterns to resolve sexual conflicts and maximize fitness for both sexes. Sex-biased gene expression has recently been demonstrated for much of the metazoan transcriptome, suggesting that many loci are sexually antagonistic. However, many coding regions function in multiple processes throughout the organism. This pleiotropy increases the complexity of selection for any given gene, which in turn may obscure sex-specific selective pressures and hamper the evolution of sex-biased gene expression. Here we use microarray gene expression data, in conjunction with data on transcript abundance from expressed sequence tag libraries, to demonstrate that loci with sex-biased gene expression are significantly less pleiotropic than unbiased genes. This relationship was independent of sex chromosome gene dosage effects, and the results were concordant across two study organisms, chicken and mouse. These results suggest that the resolution of sexually antagonistic gene expression is determined by the evolutionary constraints acting on any given antagonistic locus.

Rapid evolution of female-biased, but not male-biased, genes expressed in the avian brain

The powerful pressures of sexual and natural selection associated with species recognition and reproduction are thought to manifest in a faster rate of evolution in sex-biased genes, an effect that has been documented particularly for male-biased genes expressed in the reproductive tract. However, little is known about the rate of evolution for genes involved in sexually dimorphic behaviors, which often form the neurological basis of intrasexual competition and mate choice. We used microarray data, designed to uncover sex-biased expression patterns in embryonic chicken brain, in conjunction with data on the rate of sequence evolution for >4,000 coding regions aligned between chicken and zebra finch in order to study the role of selection in governing the molecular evolution for sex-biased and unbiased genes. Surprisingly, we found that female-biased genes, defined across a range of cutoff values, show a higher rate of functional evolution than both male-biased and unbiased genes. Autosomal male-biased genes evolve at a similar rate as unbiased genes. Sex-specific genomic properties, such as heterogeneity in genomic distribution and GC content, and codon usage bias for sex-biased classes fail to explain this surprising result, suggesting that selective pressures may be acting differently on the male and female brain.