Evolvability and genetic constraint in Dalechampia blossoms: components of variance and measures of evolvability

Many evolutionary arguments are based on the assumption that quantitative characters are highly evolvable entities that can be rapidly moulded by changing selection pressures. The empirical evaluation of this assumption depends on having an operational measure of evolvability that reflects the ability of a trait to respond to a given external selection pressure. We suggest short-term evolvability be measured as expected proportional response in a trait to a unit strength of directional selection, where strength of selection is defined independently of character variation and in units of the strength of selection on fitness itself. We show that the additive genetic variance scaled by the square of the trait mean, IA, is such a measure. The heritability, h2, does not measure evolvability in this sense. Based on a diallel analysis, we use IA to assess the evolvability of floral characters in a population of the neotropical vine Dalechampia scandens (Euphorbiaceae). Although we are able to demonstrate that there is additive genetic variation in a number of floral traits, we also find that most of the traits are not expected to change by more than a fraction of a percent per generation. We provide evidence that the degree of among-population divergence of traits is related to their predicted evolvabilities, but not to their heritabilities.     

Phenotypic variability can promote the evolution of adaptive plasticity by reducing the stringency of natural selection

Adaptive phenotypic plasticity is a potent but not ubiquitous solution to environmental heterogeneity, driving interest in what factors promote and limit its evolution. Here, a novel computational model representing stochastic information flow in development is used to explore evolution from a constitutive phenotype to an adaptively plastic response. Results show that populations tend to evolve robustness to developmental stochasticity, but that this evolved robustness limits evolvability; specifically, robust genotypes have less ability to evolve adaptive plasticity when presented with a mix of both the ancestral environment and a new environment. Analytic calculations and computational experiments confirm that this constraint occurs when the initial mutational steps towards plasticity are pleiotropic, such that mutant fitnesses decline in the environment to which their parents are well‐adapted. Greater phenotypic variability improves evolvability in the model by lessening this decline as well as by improving the fitness of partial adaptations to the new environment. By making initial plastic mutations more palatable to natural selection, phenotypic variability can increase the evolvability of an innovative, plastic response without improving evolvability to simpler challenges such as a shifted optimum in a single environment. Populations that evolved robustness by negative feedback between the trait and its rate of change show a particularly strong constraining effect on the evolvability of plasticity, revealing another mechanism by which evolutionary history can limit later innovation. These results document a novel mechanism by which weakening selection could actually stimulate the evolution of a major innovation.     

Independent axes of genetic variation and parallel evolutionary divergence of opercle bone shape in threespine stickleback

Evolution of similar phenotypes in independent populations is often taken as evidence of adaptation to the same fitness optimum. However, the genetic architecture of traits might cause evolution to proceed more often toward particular phenotypes, and less often toward others, independently of the adaptive value of the traits. Freshwater populations of Alaskan threespine stickleback have repeatedly evolved the same distinctive opercle shape after divergence from an oceanic ancestor. Here we demonstrate that this pattern of parallel evolution is widespread, distinguishing oceanic and freshwater populations across the Pacific Coast of North America and Iceland. We test whether this parallel evolution reflects genetic bias by estimating the additive genetic variance-covariance matrix (G) of opercle shape in an Alaskan oceanic (putative ancestral) population. We find significant additive genetic variance for opercle shape and that G has the potential to be biasing, because of the existence of regions of phenotypic space with low additive genetic variation. However, evolution did not occur along major eigenvectors of G, rather it occurred repeatedly in the same directions of high evolvability. We conclude that the parallel opercle evolution is most likely due to selection during adaptation to freshwater habitats, rather than due to biasing effects of opercle genetic architecture.     

Heritability and evolvability of fitness and nonfitness traits: Lessons from livestock

Data from natural populations have suggested a disconnection between trait heritability (variance standardized additive genetic variance, V_A) and evolvability (mean standardized V_A) and emphasized the importance of environmental variation as a determinant of trait heritability but not evolvability. However, these inferences are based on heterogeneous and often small datasets across species from different environments. We surveyed the relationship between evolvability and heritability in >100 traits in farmed cattle, taking advantage of large sample sizes and consistent genetic approaches. Heritability and evolvability estimates were positively correlated (r = 0.37/0.54 on untransformed/log scales) reflecting a substantial impact of V_A on both measures. Furthermore, heritabilities and residual variances were uncorrelated. The differences between this and previously described patterns may reflect lower environmental variation experienced in farmed systems, but also low and heterogeneous quality of data from natural populations. Similar to studies on wild populations, heritabilities for life‐history and behavioral traits were lower than for other traits. Traits having extremely low heritabilities and evolvabilities (17% of the studied traits) were almost exclusively life‐history or behavioral traits, suggesting that evolutionary constraints stemming from lack of genetic variability are likely to be most common for classical “fitness” (cf. life‐history) rather than for “nonfitness” (cf. morphological) traits.     

Conservation and diversity of ancient hemoglobins in Bacteria

A group of single-domain proteins in Bacteria similar to thermoglobin, an oxygen-avid hemoglobin representative of the ancestral form, reveals the primordial structure, function, and evolvability of the family. Conserved residues at specific positions function to bind ligand or participate in hydrophobic packing of the protein core during protein folding. A potential hydrogen bond network consisting of a tyrosine and glutamine residue in the distal ligand-binding site of most hemoglobins suggests that the ancestral protein bound oxygen avidly. Two divergent hemoglobins with mutations at generally conserved positions contain non-canonical ligand-binding sites, illustrating plasticity of the fold. One binds heme in a manner similar to cytochromes and may represent an evolutionary link to the precursor of the hemoglobin fold. Conservation suggests specific biochemical properties of the ancestral protein; diversity suggests an evolvability of this group of hemoglobins tolerant of mutations that perturb conserved biochemical properties for adaptation to novel functions.     

IS EVOLVABILITY INVOLVED IN THE ORIGIN OF MODULAR VARIATION?

Abstract.— Lipson et al. (2002) presented an elegant linear algebraic formalism to define and study the evolution of modularity in an artificial evolving system. They employed simulation data to support their suggestion that modularity arises spontaneously in temporally fluctuating systems in response to selection for enhanced evolvability. We show analytically and by simulation that their correlate of modularity is itself under selection and so is not a reliable indicator of selection for modularity per se. In addition, we question the relation between modularity and evolvability in their simulations, suggesting that this modularity cannot confer enhanced evolvability.     

Evolvability of the Primate Pelvic Girdle

The ilium and ischiopubic bones of the pelvis arise from different regulatory pathways, and as a result, they may be modular in their organization such that features on one bone may be morphologically integrated with each other, but not with features on the other pelvic bone. Modularity at this gross level of organization can act to increase the ability of these structures to respond to selection pressures (i.e., their evolvability). Furthermore, recent work has suggested that the evolution of the human pelvis was facilitated by low levels of integration and high levels of evolvability relative to other African apes. However, the extent of morphological integration and modularity of the bones of the pelvic girdle is not well understood, especially across the entire order of primates. Therefore, the hypothesis that the ilium and ischiopubis constitute separate modules was tested using three-dimensional landmark data that were collected from 752 pelves from 35 primate species. In addition, the hypothesis that the human pelvis demonstrates greatest evolvability was tested by comparing it to all other primates. The results demonstrate that regardless of phylogeny and locomotor function, the primate pelvis as a whole is characterized by low levels of overall integration and high levels of evolvability. In addition, the results support the developmental hypothesis of separate ilium and ischiopubis modular units. Finally, all primates, including humans, apparently share a common pattern of integration, modularity, and evolvability in the pelvis.     

The evolvability of herkogamy: Quantifying the evolutionary potential of a composite trait

Accurate estimates of trait evolvabilities are central to predicting the short‐term evolutionary potential of populations, and hence their ability to adapt to changing environments. We quantify and evaluate the evolvability of herkogamy, the spatial separation of male and female structures in flowers, a key floral trait associated with variation in mating systems. We compiled genetic‐variance estimates for herkogamy and related floral traits, computed evolvabilities, and compared these among trait groups and among species differing in their mating systems. When measured in percentage of its own size, the median evolvability of herkogamy was an order of magnitude greater than the evolvability of other floral size measurements, and was generally not strongly constrained by genetic covariance between its components (pistil and stamen lengths). Median evolvabilities were similar across mating systems, with only a tendency toward reduction in highly selfing taxa. We conclude that herkogamy has the potential to evolve rapidly in response to changing environments. This suggests that the extensive variation in herkogamy commonly observed among closely related populations and species may result from rapid adaptive tracking of fitness optima determined by variation in pollinator communities or other selective factors.     

Epistatic interactions between ancestral genotype and beneficial mutations shape evolvability in Pseudomonas aeruginosa

The idea that interactions between mutations influence adaptation by driving populations to low and high fitness peaks on adaptive landscapes is deeply ingrained in evolutionary theory. Here, we investigate the impact of epistasis on evolvability by challenging populations of two Pseudomonas aeruginosa clones bearing different initial mutations (in rpoB conferring rifampicin resistance, and the type IV pili gene network) to adaptation to a medium containing l ‐serine as the sole carbon source. Despite being initially indistinguishable in fitness, populations founded by the two ancestral genotypes reached different fitness following 300 generations of evolution. Genome sequencing revealed that the difference could not be explained by acquiring mutations in different targets of selection; the majority of clones from both ancestors converged on one of the following two strategies: (1) acquiring mutations in either PA2449 (gcsR, an l ‐serine‐metabolism RpoN enhancer binding protein) or (2) protease genes. Additionally, populations from both ancestors converged on loss‐of‐function mutations in the type IV pili gene network, either due to ancestral or acquired mutations. No compensatory or reversion mutations were observed in RNA polymerase (RNAP) genes, in spite of the large fitness costs typically associated with mutations in rpoB. Although current theory points to sign epistasis as the dominant constraint on evolvability, these results suggest that the role of magnitude epistasis in constraining evolvability may be underappreciated. The contribution of magnitude epistasis is likely to be greatest under the biologically relevant mutation supply rates that make back mutations probabilistically unlikely.     

The mutation matrix and the evolution of evolvability

Evolvability is a key characteristic of any evolving system, and the concept of evolvability serves as a unifying theme in a wide range of disciplines related to evolutionary theory. The field of quantitative genetics provides a framework for the exploration of evolvability with the promise to produce insights of global importance. With respect to the quantitative genetics of biological systems, the parameters most relevant to evolvability are the G-matrix, which describes the standing additive genetic variances and covariances for a suite of traits, and the M-matrix, which describes the effects of new mutations on genetic variances and covariances. A population's immediate response to selection is governed by the G-matrix. However, evolvability is also concerned with the ability of mutational processes to produce adaptive variants, and consequently the M-matrix is a crucial quantitative genetic parameter. Here, we explore the evolution of evolvability by using analytical theory and simulation-based models to examine the evolution of the mutational correlation, r(mu), the key parameter determining the nature of genetic constraints imposed by M. The model uses a diploid, sexually reproducing population of finite size experiencing stabilizing selection on a two-trait phenotype. We assume that the mutational correlation is a third quantitative trait determined by multiple additive loci. An individual's value of the mutational correlation trait determines the correlation between pleiotropic effects of new alleles when they arise in that individual. Our results show that the mutational correlation, despite the fact that it is not involved directly in the specification of an individual's fitness, does evolve in response to selection on the bivariate phenotype. The mutational variance exhibits a weak tendency to evolve to produce alignment of the M-matrix with the adaptive landscape, but is prone to erratic fluctuations as a consequence of genetic drift. The interpretation of this result is that the evolvability of the population is capable of a response to selection, and whether this response results in an increase or decrease in evolvability depends on the way in which the bivariate phenotypic optimum is expected to move. Interestingly, both analytical and simulation results show that the mutational correlation experiences disruptive selection, with local fitness maxima at -1 and +1. Genetic drift counteracts the tendency for the mutational correlation to persist at these extreme values, however. Our results also show that an evolving M-matrix tends to increase stability of the G-matrix under most circumstances. Previous studies of G-matrix stability, which assume nonevolving M-matrices, consequently may overestimate the level of instability of G relative to what might be expected in natural systems. Overall, our results indicate that evolvability can evolve in natural systems in a way that tends to result in alignment of the G-matrix, the M-matrix, and the adaptive landscape, and that such evolution tends to stabilize the G-matrix over evolutionary time.     

Ontogenetic trajectories and early shape differentiation of treehopper pronota (Hemiptera: Membracidae)

Membracids (family: Membracidae), commonly known as treehoppers, are recognizable by their enlarged and often elaborated pronota. Much of the research investigating the development and evolution of this structure has focused on the fifth instar to adult transition, in which the pronotum undergoes the largest transformation as it takes on adult identity. However, little is known about the earlier nymphal stages, the degree to which the pronotum develops at these timepoints, and how development has changed relative to the ancestral state. Here, we studied the nymphal stages and adults of five morphologically distinct membracid species and of Aetalion reticulatum (family: Aetalionidae), the outgroup which was used as an ancestral state proxy. We found that shape differentiation in the pronotum of membracids can start as early as the second instar stage. Most shape differentiation occurs within the nymphal stages and not in the embryo since the shape of the first-instar pronotum did not differ from the outgroup species in all but one species we investigated. We found the anterior–posterior axis of the pronotum elongated at a faster relative rate in membracid species than in A. reticulatum, which contributed to the development of exaggerated pronotal size. Finally, we found differences in the morphogenesis of shape across species. We suggest this is due to the developmental and evolutionary divergence of differential growth patterning of the dorsal surface of the pronotum, not only across species, but also between stages within the same species. This lability may contribute to the evolvability and diversification of the membracid pronotum.     

Sexual Dimorphism Increases Evolvability in a Genetic Regulatory Network

The majority of work on genetic regulatory networks has focused on environmental and mutational robustness, and much less attention has been paid to the conditions under which a network may produce an evolvable phenotype. Sexually dimorphic characters often show rapid rates of change over short evolutionary time scales and while this is thought to be due to the strength of sexual selection acting on the trait, a dimorphic character with an underlying pleiotropic architecture may also influence the evolution of the regulatory network that controls the character and affect evolvability. As evolvability indicates a capacity for phenotypic change and mutational robustness refers to a capacity for phenotypic stasis, increases in evolvability may show a negative relationship with mutational robustness. I tested this with a computational model of a genetic regulatory network and found that, contrary to expectation, sexually dimorphic characters exhibited both higher mutational robustness and higher evolvability. Decomposition of the results revealed that linkage disequilibrium within sex and linkage disequilibrium between sexes, two of the three primary components of additive genetic variance and evolvability in quantitative genetics models, contributed to the differences in evolvability between sexually dimorphic and monomorphic populations. These results indicate that producing two pleiotropically linked characters did not constrain either the production of a robust phenotype or adaptive potential. Instead, the genetic system evolved to maximize both quantities.     

A genetic background with low mutational robustness is associated with increased adaptability to a novel host in an RNA virus

Although mutational robustness is central to many evolutionary processes, its relationship to evolvability remains poorly understood and has been very rarely tested experimentally. Here, we measure the evolvability of Vesicular stomatitis virus in two genetic backgrounds with different levels of mutational robustness. We passaged the viruses into a novel cell type to model a host‐jump episode, quantified changes in infectivity and fitness in the new host, evaluated the cost of adaptation in the original host and analyzed the genetic basis of this adaptation. Lineages evolved from the less robust genetic background demonstrated increased adaptability, paid similar costs of adaptation to the new host and fixed approximately the same number of mutations as their more robust counterparts. Theory predicts that robustness can promote evolvability only in systems where large sets of genotypes are connected by effectively neutral mutations. We argue that this condition might not be fulfilled generally in RNA viruses.     

The evolution of the evolvability properties of the yeast prion [PSI+

Abstract.— Saccharomyces cerevisiae's ability to form the prion [PSI⁺] may increase the rate of evolvability, defined as the rate of appearance of heritable and potentially adaptive phenotypic variants. The increase in evolvability occurs when the appearance of the prion causes read-through translation and reveals hidden variation in untranslated regions. Eventually the portion of the phenotypic variation that is adaptive loses its dependence on the revealing mechanism. The mechanism is reversible, so the restoration of normal translation termination conceals the revealed deleterious variation, leaving the yeast without a permanent handicap. Given that the ability to form [PSI⁺] is known to be fixed and conserved in yeast, we construct a mathematical model to calculate whether this ability is more likely to have become fixed due to chance alone or due to its evolvability characteristics. We find that evolvability is a more likely explanation, as long as environmental change makes partial read-through of stop codons adaptive at a frequency of at least once every million years.     

PERSPECTIVE: COMPLEX ADAPTATIONS AND THE EVOLUTION OF EVOLVABILITY

The problem of complex adaptations is studied in two largely disconnected research traditions: evolutionary biology and evolutionary computer science. This paper summarizes the results from both areas and compares their implications. In evolutionary computer science it was found that the Darwinian process of mutation, recombination and selection is not universally effective in improving complex systems like computer programs or chip designs. For adaptation to occur, these systems must possess “evolvability,” i.e., the ability of random variations to sometimes produce improvement. It was found that evolvability critically depends on the way genetic variation maps onto phenotypic variation, an issue known as the representation problem. The genotype-phenotype map determines the variability of characters, which is the propensity to vary. Variability needs to be distinguished from variations, which are the actually realized differences between individuals. The genotype-phenotype map is the common theme underlying such varied biological phenomena as genetic canalization, developmental constraints, biological versatility, developmental dissociability, and morphological integration. For evolutionary biology the representation problem has important implications: how is it that extant species acquired a genotype-phenotype map which allows improvement by mutation and selection? Is the genotype-phenotype map able to change in evolution? What are the selective forces, if any, that shape the genotype-phenotype map? We propose that the genotype-phenotype map can evolve by two main routes: epistatic mutations, or the creation of new genes. A common result for organismic design is modularity. By modularity we mean a genotype-phenotype map in which there are few pleiotropic effects among characters serving different functions, with pleiotropic effects falling mainly among characters that are part of a single functional complex. Such a design is expected to improve evolvability by limiting the interference between the adaptation of different functions. Several population genetic models are reviewed that are intended to explain the evolutionary origin of a modular design. While our current knowledge is insufficient to assess the plausibility of these models, they form the beginning of a framework for understanding the evolution of the genotype-phenotype map.     

Enzyme promiscuity: evolutionary and mechanistic aspects

The past few years have seen significant advances in research related to the 'latent skills' of enzymes - namely, their capacity to promiscuously catalyze reactions other than the ones they evolved for. These advances regard (i) the mechanism of catalytic promiscuity - how enzymes, that generally exert exquisite specificity, promiscuously catalyze other, and sometimes barely related, reactions; (ii) the evolvability of promiscuous functions - namely, how latent activities evolve further, and in particular, how promiscuous activities can firstly evolve without severely compromising the original activity. These findings have interesting implications on our understanding of how new enzymes evolve. They support the key role of catalytic promiscuity in the natural history of enzymes, and suggest that today's enzymes diverged from ancestral proteins catalyzing a whole range of activities at low levels, to create families and superfamilies of potent and highly specialized enzymes.     

Adaptation of Escherichia coli to glucose promotes evolvability in lactose

The selective history of a population can influence its subsequent evolution, an effect known as historical contingency. We previously observed that five of six replicate populations that were evolved in a glucose‐limited environment for 2000 generations, then switched to lactose for 1000 generations, had higher fitness increases in lactose than populations started directly from the ancestor. To test if selection in glucose systematically increased lactose evolvability, we started 12 replay populations—six from a population subsample and six from a single randomly selected clone—from each of the six glucose‐evolved founder populations. These replay populations and 18 ancestral populations were evolved for 1000 generations in a lactose‐limited environment. We found that replay populations were initially slightly less fit in lactose than the ancestor, but were more evolvable, in that they increased in fitness at a faster rate and to higher levels. This result indicates that evolution in the glucose environment resulted in genetic changes that increased the potential of genotypes to adapt to lactose. Genome sequencing identified four genes—iclR, nadR, spoT, and rbs—that were mutated in most glucose‐evolved clones and are candidates for mediating increased evolvability. Our results demonstrate that short‐term selective costs during selection in one environment can lead to changes in evolvability that confer longer term benefits.     

Correlated Flexible Molecular Coding and Molecular Evolvability

Evolvability of biopolymers is based on molecular coding. The molecular coding is represented by biopolymer function vs monomeric sequence relationship, that is, a proper fitness landscape on the sequence space. On the other hand, molecular coding is mostly realized by monomeric sequence vs biopolymer structure relationship. We suggest the evolution of evolvability based on flexible or multiplex coding originating from flexible or polymorphic conformation of evolving biopolymers. We report a finding supporting that the amino acid landscape of the standard genetic code for an amino acid property which is more important to the protein function gives higher value of an evolvability measure. We developed a promising molecular construct which realized genotype-phenotype linking in order to study the in vitroprotein evolution to clarify above mentioned protein evolvability.     

Populations adapt to fluctuating selection using derived and ancestral allelic diversity

Populations can adapt to changing environments by using allelic diversity, yet whether diversity is recently derived or ancestral is often debated. Although evolution could productively use both types of diversity in a changing environment, their relative frequency has not been quantified. We address this question experimentally using budding yeast strains that harbor a tandem repeat containing URA3 gene, which we expose to cyclical selection and counterselection. We characterize and quantify the dynamics of frameshift events in the URA3 gene in eight populations over 12 cycles of selection and find that ancestral alleles account for 10–20% of all adaptive events. Using a general model of fluctuating selection, we determine how these results depend on mutation rates, population sizes, and fluctuation timescales. We quantify the contribution of derived alleles to the adaptation process using the de novo mutation rate along the population's ancestral lineage, a novel measure that is applicable in a wide range of settings. We find that the adaptive dynamics undergoes a sharp transition from selection on ancestral alleles to selection on derived alleles as fluctuation timescales increase. Our results demonstrate that fluctuations can select between different modes of adaptation over evolutionary timescales.     

The effect of mutational robustness on the evolvability of multicellular organisms and eukaryotic cells

Canalization involves mutational robustness, the lack of phenotypic change as a result of genetic mutations. Given the large divergence in phenotype across species, understanding the relationship between high robustness and evolvability has been of interest to both theorists and experimentalists. Although canalization was originally proposed in the context of multicellular organisms, the effect of multicellularity and other classes of hierarchical organization on evolvability has not been considered by theoreticians. We address this issue using a Boolean population model with explicit representation of an environment in which individuals with explicit genotype and a hierarchical phenotype representing multicellularity evolve. Robustness is described by a single real number between zero and one which emerges from the genotype–phenotype map. We find that high robustness is favoured in constant environments, and lower robustness is favoured after environmental change. Multicellularity and hierarchical organization severely constrain robustness: peak evolvability occurs at an absolute level of robustness of about 0.99 compared with values of about 0.5 in a classical neutral network model. These constraints result in a sharp peak of evolvability in which the maximum is set by the fact that the fixation of adaptive mutations becomes more improbable as robustness decreases. When robustness is put under genetic control, robustness levels leading to maximum evolvability are selected for, but maximal relative fitness appears to require recombination.