Genotype networks shed light on evolutionary constraints

Multivariate Divergence in Wild Microbes: No Evidence for Evolution along a Genetic Line of Least Resistance

AbstractTrait evolution depends both on the direct fitness effects of specific traits and on indirect selection arising from genetically correlated traits. Although well established in plants and animals, the role of trait correlations in microbial evolution remains a major open question. Here, we tested whether genetic correlations in a suite of metabolic traits are conserved between two sister lineages of fungal endophytes and whether phenotypic divergence between lineages occurred in the direction of the multivariate trait combination containing the most genetic variance within lineages (i.e., the genetic lines of least resistance). We found that while one lineage grew faster across nearly all substrates, lineages differed in their mean response to specific substrates and in their overall multivariate metabolic trait means. The structure of the genetic variance-covariance (G) matrix was conserved between lineages, yet to our surprise divergence in metabolic phenotypes between lineages was nearly orthogonal to the major axis of genetic variation within lineages, indicating that divergence did not occur along the genetic lines of least resistance. Our findings suggest that the evolutionary genetics of trait correlations in microorganisms warrant further research and highlight the extensive functional variation that exists at very fine taxonomic scales in host-associated microbial communities.

The distribution of fitness effects during adaptive walks using a simple genetic network

The tempo and mode of adaptation depends on the availability of beneficial alleles. Genetic interactions arising from gene networks can restrict this availability. However, the extent to which networks affect adaptation remains largely unknown. Current models of evolution consider additive genotype-phenotype relationships while often ignoring the contribution of gene interactions to phenotypic variance. In this study, we model a quantitative trait as the product of a simple gene regulatory network, the negative autoregulation motif. Using forward-time genetic simulations, we measure adaptive walks towards a phenotypic optimum in both additive and network models. A key expectation from adaptive walk theory is that the distribution of fitness effects of new beneficial mutations is exponential. We found that both models instead harbored distributions with fewer large-effect beneficial alleles than expected. The network model also had a complex and bimodal distribution of fitness effects among all mutations, with a considerable density at deleterious selection coefficients. This behavior is reminiscent of the cost of complexity, where correlations among traits constrain adaptation. Our results suggest that the interactions emerging from genetic networks can generate complex and multimodal distributions of fitness effects.

Endless forms of endless formation - The morphogenesis of organisms and scientific objects

The present article proceeds from the premises that living forms and abstract formalization come into being by similar mechanisms (e.g., random variation, selection, conventions) and have similar properties (e.g., semiosis, stasis and complexity). These convergences justify the comparative analysis of form's development, evolution and action in both fields. Here we shall focus on the notion of "endless forms" advanced by Darwin's seminal work in evolutionary biology "On The Origin of Species" to discuss the various ways in which it relates to biological formation. I shall explore the idea of "infinitude of evolved forms" through the lens of the five connotations of the word "endless" provided by the Merriam-Webster Thesaurus dictionary, which are: perpetual; incomputable; manifold; unfinished; steady. From each synonym chosen, a new iteration of dictionary search was made to produce a list of terms that are used in the reviewed literature to describe biological morphogenetic features, which are respectively: reproducible, unpredictable, additive, undetermined, the end of their own formation. In conclusion, I propose a tentative mapping between each of these five connotations and the biological processes at work in their making, which are, respectively: 1) copying organic information; coding organic signs; manufacturing organic meaning 2) natural variation, natural selection, natural conventions; 3) multilevel organization, differentiation/development, complexity; 4) ambiguity, degeneracy, semiotic thresholds; 5) homeostasis, autopoiesis, codepoiesis. The processes discussed here gained salience as developments, additions, or nuances to Darwin's original theory. It must be noted that, even though the discussion is mainly framed by Code Biology as a source of conceptualization, inputs from a wide range of theoretical perspectives will be given emphasis when suitable.

Evolutionary adaptation to juvenile malnutrition impacts adult metabolism and impairs adult fitness in Drosophila

Juvenile undernutrition has lasting effects on adult metabolism of the affected individuals, but it is unclear how adult physiology is shaped over evolutionary time by natural selection driven by juvenile undernutrition. We combined RNAseq, targeted metabolomics, and genomics to study the consequences of evolution under juvenile undernutrition for metabolism of reproductively active adult females of Drosophila melanogaster. Compared to Control populations maintained on standard diet, Selected populations maintained for over 230 generations on a nutrient-poor larval diet evolved major changes in adult gene expression and metabolite abundance, in particular affecting amino acid and purine metabolism. The evolved differences in adult gene expression and metabolite abundance between Selected and Control populations were positively correlated with the corresponding differences previously reported for Selected versus Control larvae. This implies that genetic variants affect both stages similarly. Even when well fed, the metabolic profile of Selected flies resembled that of flies subject to starvation. Finally, Selected flies had lower reproductive output than Controls even when both were raised under the conditions under which the Selected populations evolved. These results imply that evolutionary adaptation to juvenile undernutrition has large pleiotropic consequences for adult metabolism, and that they are costly rather than adaptive for adult fitness. Thus, juvenile and adult metabolism do not appear to evolve independently from each other even in a holometabolous species where the two life stages are separated by a complete metamorphosis.

Genome size drives morphological evolution in organ-specific ways

Morphogenesis is an emergent property of biochemical and cellular interactions during development. Genome size and the correlated trait of cell size can influence these interactions through effects on developmental rate and tissue geometry, ultimately driving the evolution of morphology. We tested whether variation in genome and body size is related to morphological variation in the heart and liver using nine species of the salamander genus Plethodon (genome sizes 29-67 gigabases). Our results show that overall organ size is a function of body size, whereas tissue structure changes dramatically with evolutionary increases in genome size. In the heart, increased genome size is correlated with a reduction of myocardia in the ventricle, yielding proportionally less force-producing mass and greater intertrabecular space. In the liver, increased genome size is correlated with fewer and larger vascular structures, positioning hepatocytes farther from the circulatory vessels that transport key metabolites. Although these structural changes should have obvious impacts on organ function, their effects on organismal performance and fitness may be negligible because low metabolic rates in salamanders relax selective pressure on function of key metabolic organs. Overall, this study suggests large genome and cell size influence the developmental systems involved in heart and liver morphogenesis.

Ehrlich and Raven escape and radiate coevolution hypothesis at different levels of organization: Past and future perspectives

The classic paper by Ehrlich and Raven on coevolution will soon be 60 years old. Although they were not the first to develop the idea of coevolution, their thought-provoking paper certainly popularized this idea and inspired several generations of scientists interested in coevolution. Here, we describe some of their main contributions, quantitatively measure the impact of their seminal paper on different fields of research, and discuss how ideas related to their original paper might push the study of coevolution forward. To guide our discussion, we explore their original hypothesis into three research fields that are associated with distinct scales/levels of organization: (1) the genetic mechanisms underlying coevolutionary interactions; (2) the potential association between coevolutionary diversification and the organization of ecological networks; and (3) the micro- and macroevolutionary mechanisms and expected patterns under their hypothesis. By doing so, we discuss potentially overlooked aspects and future directions for the study of coevolutionary dynamics and diversification.

Dynamic RNA fitness landscapes of a group I ribozyme during changes to the experimental environment

Fitness landscapes of protein and RNA molecules can be studied experimentally using high-throughput techniques to measure the functional effects of numerous combinations of mutations. The rugged topography of these molecular fitness landscapes is important for understanding and predicting natural and experimental evolution. Mutational effects are also dependent upon environmental conditions, but the effects of environmental changes on fitness landscapes remains poorly understood. Here, we investigate the changes to the fitness landscape of a catalytic RNA molecule while changing a single environmental variable that is critical for RNA structure and function. Using high-throughput sequencing of in vitro selections, we mapped a fitness landscape of the Azoarcus group I ribozyme under eight different concentrations of magnesium ions (1–48 mM MgCl₂). The data revealed the magnesium dependence of 16,384 mutational neighbors, and from this, we investigated the magnesium induced changes to the topography of the fitness landscape. The results showed that increasing magnesium concentration improved the relative fitness of sequences at higher mutational distances while also reducing the ruggedness of the mutational trajectories on the landscape. As a result, as magnesium concentration was increased, simulated populations evolved toward higher fitness faster. Curve-fitting of the magnesium dependence of individual ribozymes demonstrated that deep sequencing of in vitro reactions can be used to evaluate the structural stability of thousands of sequences in parallel. Overall, the results highlight how environmental changes that stabilize structures can also alter the ruggedness of fitness landscapes and alter evolutionary processes.

Genotype networks of 80 quantitative Arabidopsis thaliana phenotypes reveal phenotypic evolvability despite pervasive epistasis

We study the genotype-phenotype maps of 80 quantitative phenotypes in the model plant Arabidopsis thaliana, by representing the genotypes affecting each phenotype as a genotype network. In such a network, each vertex or node corresponds to an individual's genotype at all those genomic loci that affect a given phenotype. Two vertices are connected by an edge if the associated genotypes differ in exactly one nucleotide. The 80 genotype networks we analyze are based on data from genome-wide association studies of 199 A. thaliana accessions. They form connected graphs whose topography differs substantially among phenotypes. We focus our analysis on the incidence of epistasis (non-additive interactions among mutations) because a high incidence of epistasis can reduce the accessibility of evolutionary paths towards high or low phenotypic values. We find epistatic interactions in 67 phenotypes, and in 51 phenotypes every pairwise mutant interaction is epistatic. Moreover, we find phenotype-specific differences in the fraction of accessible mutational paths to maximum phenotypic values. However, even though epistasis affects the accessibility of maximum phenotypic values, the relationships between genotypic and phenotypic change of our analyzed phenotypes are sufficiently smooth that some evolutionary paths remain accessible for most phenotypes, even where epistasis is pervasive. The genotype network representation we use can complement existing approaches to understand the genetic architecture of polygenic traits in many different organisms.

Heritable gene expression variability and stochasticity govern clonal heterogeneity in circadian period

A ubiquitous feature of the circadian clock across life forms is its organization as a network of cellular oscillators, with individual cellular oscillators within the network often exhibiting considerable heterogeneity in their intrinsic periods. The interaction of coupling and heterogeneity in circadian clock networks is hypothesized to influence clock’s entrainability, but our knowledge of mechanisms governing period heterogeneity within circadian clock networks remains largely elusive. In this study, we aimed to explore the principles that underlie intercellular period variation in circadian clock networks (clonal period heterogeneity). To this end, we employed a laboratory selection approach and derived a panel of 25 clonal cell populations exhibiting circadian periods ranging from 22 to 28 h. We report that a single parent clone can produce progeny clones with a wide distribution of circadian periods, and this heterogeneity, in addition to being stochastically driven, has a heritable component. By quantifying the expression of 20 circadian clock and clock-associated genes across our clone panel, we found that inheritance of expression patterns in at least three clock genes might govern clonal period heterogeneity in circadian clock networks. Furthermore, we provide evidence suggesting that heritable epigenetic variation in gene expression regulation might underlie period heterogeneity.

How do genetically identical cells exhibit a different circadian phenotype? This study reveals that a single parent clone can produce progeny with a wide distribution of circadian periods and that this heterogeneity, in addition to being stochastically driven, has a heritable component, likely via heritable epigenetic variation in gene expression regulation.

Aligning functional network constraint to evolutionary outcomes

BACKGROUND

Functional constraint through genomic architecture is suggested to be an important dimension of genome evolution, but quantitative evidence for this idea is rare. In this contribution, existing evidence and discussions on genomic architecture as constraint for convergent evolution, rapid adaptation, and genic adaptation are summarized into alternative, testable hypotheses. Network architecture statistics from protein-protein interaction networks are then used to calculate differences in evolutionary outcomes on the example of genomic evolution in yeast, and the results are used to evaluate statistical support for these longstanding hypotheses.

RESULTS

A discriminant function analysis lent statistical support to classifying the yeast interactome into hub, intermediate and peripheral nodes based on network neighborhood connectivity, betweenness centrality, and average shortest path length. Quantitative support for the existence of genomic architecture as a mechanistic basis for evolutionary constraint is then revealed through utilizing these statistical parameters of the protein-protein interaction network in combination with estimators of protein evolution.

CONCLUSIONS

As functional genetic networks are becoming increasingly available, it will now be possible to evaluate functional genetic network constraint against variables describing complex phenotypes and environments, for better understanding of commonly observed deterministic patterns of evolution in non-model organisms. The hypothesis framework and methodological approach outlined herein may help to quantify the extrinsic versus intrinsic dimensions of evolutionary constraint, and result in a better understanding of how fast, effectively, or deterministically organisms adapt.

Genotype network intersections promote evolutionary innovation

Evolutionary innovations are qualitatively novel traits that emerge through evolution and increase biodiversity. The genetic mechanisms of innovation remain poorly understood. A systems view of innovation requires the analysis of genotype networks—the vast networks of genetic variants that produce the same phenotype. Innovations can occur at the intersection of two different genotype networks. However, the experimental characterization of genotype networks has been hindered by the vast number of genetic variants that need to be functionally analyzed. Here, we use high-throughput sequencing to study the fitness landscape at the intersection of the genotype networks of two catalytic RNA molecules (ribozymes). We determined the ability of numerous neighboring RNA sequences to catalyze two different chemical reactions, and we use these data as a proxy for a genotype to fitness map where two functions come in close proximity. We find extensive functional overlap, and numerous genotypes can catalyze both functions. We demonstrate through evolutionary simulations that these numerous points of intersection facilitate the discovery of a new function. However, the rate of adaptation of the new function depends upon the local ruggedness around the starting location in the genotype network. As a consequence, one direction of adaptation is more rapid than the other. We find that periods of neutral evolution increase rates of adaptation to the new function by allowing populations to spread out in their genotype network. Our study reveals the properties of a fitness landscape where genotype networks intersect and the consequences for evolutionary innovations. Our results suggest that historic innovations in natural systems may have been facilitated by overlapping genotype networks.

The determination of the empirical fitness landscape at the genotypic intersection between two different catalytic RNA (ribozyme) functions reveals details about how novel traits can emerge through evolutionary innovation.

Evolutionary constraints on disparity of ericaceous pollen grains

BACKGROUND AND AIMS

Flowering plants show a high diversity of pollen morphology, assumed to reflect not only variations in the underlying design, but also stress imposed by ecological conditions related to pollen survival and germination. Both components are expected to constrain the accumulation of pollen disparity. However, this assumption has rarely been tested using empirical data.

METHODS

This study is designed to test this hypothesis by inferring the accumulation of pollen disparity in Ericaceae, a large eudicot family with recent, ongoing radiations, with focus on three functionally significant pollen characters using a dated phylogeny.

KEY RESULTS

Multiple lines of evidence supported the hypothesis that pollen disparity in Ericaceae did not evolve steadily but rather pulsed over time, clearly decoupling from the relative constant rate pattern of species diversification inferred. In a 3-D pollen morphospace, most major clades appear to occupy distinct neighbouring regions, whereas the subfamily Epacridoideae overlaps extensively with other subfamilies. No evidence for correlations was found between dimension of pollen disparity and species diversity at either the subfamily or generic level. Furthermore, the distribution of species in present pollen morphospace showed a strong central tendency, with the core compartment containing a large number of species from species-rich genera.

CONCLUSIONS

The recovered evidence fits well with the expectations of limitations on available pollen morphological disparity, and suggests that innovation of pollen germination traits may have little effect on species diversification.

Chaperones, Canalization, and Evolution of Animal Forms

Over half a century ago, British developmental biologist Conrad Hal Waddington proposed the idea of canalization, that is, homeostasis in development. Since the breakthrough that was made by Rutherford and Lindquist (1998), who proposed a role of Hsp90 in developmental buffering, chaperones have gained much attention in the study of canalization. However, recent studies have revealed that a number of other molecules are also potentially involved in canalization. Here, I introduce the emerging role of DnaJ chaperones in canalization. I also discuss how the expression levels of such buffering molecules can be altered, thereby altering organismal development. Since developmental robustness is maternally inherited in various organisms, I propose that dynamic bet hedging, an increase in within-clutch variation in offspring phenotypes that is caused by unpredictable environmental challenges to the mothers, plays a key role in altering the expression levels of buffering molecules. Investigating dynamic bet hedging at the molecular level and how it impacts upon morphological phenotypes will help our understanding of the molecular mechanisms of canalization and evolutionary processes.

Synthetic circuits reveal how mechanisms of gene regulatory networks constrain evolution

Phenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation found in organismal development is biased towards certain phenotypes, but the molecular mechanisms behind such biases are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most pertinent evidence is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed in Escherichia coli that produce a gene expression stripe-a pivotal pattern in embryonic development. The two parental circuits produce the same phenotype, but create it through different regulatory mechanisms. We show that mutations cause distinct novel phenotypes in the two networks and use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our results reveal that the regulatory mechanisms of networks restrict the possible phenotypic variation upon mutation. Consequently, seemingly equivalent networks can indeed be distinct in how they constrain the outcome of further evolution.

Distribution of genotype network sizes in sequence-to-structure genotype-phenotype maps

An essential quantity to ensure evolvability of populations is the navigability of the genotype space. Navigability, understood as the ease with which alternative phenotypes are reached, relies on the existence of sufficiently large and mutually attainable genotype networks. The size of genotype networks (e.g. the number of RNA sequences folding into a particular secondary structure or the number of DNA sequences coding for the same protein structure) is astronomically large in all functional molecules investigated: an exhaustive experimental or computational study of all RNA folds or all protein structures becomes impossible even for moderately long sequences. Here, we analytically derive the distribution of genotype network sizes for a hierarchy of models which successively incorporate features of increasingly realistic sequence-to-structure genotype-phenotype maps. The main feature of these models relies on the characterization of each phenotype through a prototypical sequence whose sites admit a variable fraction of letters of the alphabet. Our models interpolate between two limit distributions: a power-law distribution, when the ordering of sites in the prototypical sequence is strongly constrained, and a lognormal distribution, as suggested for RNA, when different orderings of the same set of sites yield different phenotypes. Our main result is the qualitative and quantitative identification of those features of sequence-to-structure maps that lead to different distributions of genotype network sizes.

Regulatory network structure determines patterns of intermolecular epistasis

Most phenotypes are determined by molecular systems composed of specifically interacting molecules. However, unlike for individual components, little is known about the distributions of mutational effects of molecular systems as a whole. We ask how the distribution of mutational effects of a transcriptional regulatory system differs from the distributions of its components, by first independently, and then simultaneously, mutating a transcription factor and the associated promoter it represses. We find that the system distribution exhibits increased phenotypic variation compared to individual component distributions - an effect arising from intermolecular epistasis between the transcription factor and its DNA-binding site. In large part, this epistasis can be qualitatively attributed to the structure of the transcriptional regulatory system and could therefore be a common feature in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the constraints of individual components, thereby increasing phenotypic variation that selection could act on and facilitating adaptive evolution.

Constraint and Contingency Pervade the Emergence of Novel Phenotypes in Complex Metabolic Systems

An evolutionary constraint is a bias or limitation in phenotypic variation that a biological system produces. We know examples of such constraints, but we have no systematic understanding about their extent and causes for any one biological system. We here study metabolisms, genomically encoded complex networks of enzyme-catalyzed biochemical reactions, and the constraints they experience in bringing forth novel phenotypes that allow survival on novel carbon sources. Our computational approach does not limit us to analyzing constrained variation in any one organism, but allows us to quantify constraints experienced by any metabolism. Specifically, we study metabolisms that are viable on one of 50 different carbon sources, and quantify how readily alterations of their chemical reactions create the ability to survive on a novel carbon source. We find that some metabolic phenotypes are much less likely to originate than others. For example, metabolisms viable on D-glucose are 1835 times more likely to give rise to metabolisms viable on D-fructose than on acetate. Likewise, we observe that some novel metabolic phenotypes are more contingent on parental phenotypes than others. Biochemical similarities among carbon sources can help explain the causes of these constraints. In addition, we study metabolisms that can be produced by recombination among 55 metabolisms of different bacterial strains or species, and show that their novel phenotypes are also contingent on and constrained by parental genotypes. To our knowledge, our analysis is the first to systematically quantify the incidence of constrained evolution in a broad class of biological system that is central to life and its evolution.

The Underlying Ecological Processes of Gut Microbiota Among Cohabitating Retarded, Overgrown and Normal Shrimp

Increasing evidence of tight links among the gut microbiota, obesity, and host health has emerged, but knowledge of the ecological processes that shape the variation in microbial assemblages across growth rates remains elusive. Moreover, inadequately control for differences in factors that profoundly affect the gut microbial community, hampers evaluation of the gut microbiota roles in regulating growth rates. To address this gap, we evaluated the composition and ecological processes of the gut bacterial community in cohabitating retarded, overgrown, and normal shrimps from identically managed ponds. Gut bacterial community structures were distinct (P = 0.0006) among the shrimp categories. Using a structural equation modeling (SEM), we found that changes in the gut bacterial community were positively related to digestive activities, which subsequently affected shrimp growth rate. This association was further supported by intensified interspecies interaction and enriched lineages with high nutrient intake efficiencies in overgrown shrimps. However, the less phylogenetic clustering of gut microbiota in overgrown and retarded subjects may offer empty niches for pathogens invasion, as evidenced by higher abundances of predicted functional pathways involved in disease infection. Given no differences in biotic and abiotic factors among the cohabitating shrimps, we speculated that the distinct gut community assembly could be attributed to random colonization in larval shrimp (e.g., priority effects) and that an altered microbiota could be a causative factor in overgrowth or retardation in shrimp. To our knowledge, this is the first study to provide an integrated overview of the direct roles of gut microbiota in shaping shrimp growth rate and the underlying ecological mechanisms.

Gene co-expression network connectivity is an important determinant of selective constraint

While several studies have investigated general properties of the genetic architecture of natural variation in gene expression, few of these have considered natural, outbreeding populations. In parallel, systems biology has established that a general feature of biological networks is that they are scale-free, rendering them buffered against random mutations. To date, few studies have attempted to examine the relationship between the selective processes acting to maintain natural variation of gene expression and the associated co-expression network structure. Here we utilised RNA-Sequencing to assay gene expression in winter buds undergoing bud flush in a natural population of Populus tremula, an outbreeding forest tree species. We performed expression Quantitative Trait Locus (eQTL) mapping and identified 164,290 significant eQTLs associating 6,241 unique genes (eGenes) with 147,419 unique SNPs (eSNPs). We found approximately four times as many local as distant eQTLs, with local eQTLs having significantly higher effect sizes. eQTLs were primarily located in regulatory regions of genes (UTRs or flanking regions), regardless of whether they were local or distant. We used the gene expression data to infer a co-expression network and investigated the relationship between network topology, the genetic architecture of gene expression and signatures of selection. Within the co-expression network, eGenes were underrepresented in network module cores (hubs) and overrepresented in the periphery of the network, with a negative correlation between eQTL effect size and network connectivity. We additionally found that module core genes have experienced stronger selective constraint on coding and non-coding sequence, with connectivity associated with signatures of selection. Our integrated genetics and genomics results suggest that purifying selection is the primary mechanism underlying the genetic architecture of natural variation in gene expression assayed in flushing leaf buds of P. tremula and that connectivity within the co-expression network is linked to the strength of purifying selection.

Parallel or convergent evolution in human population genomic data revealed by genotype networks

BACKGROUND

Genotype networks are representations of genetic variation data that are complementary to phylogenetic trees. A genotype network is a graph whose nodes are genotypes (DNA sequences) with the same broadly defined phenotype. Two nodes are connected if they differ in some minimal way, e.g., in a single nucleotide.

RESULTS

We analyze human genome variation data from the 1,000 genomes project, and construct haploid genotype (haplotype) networks for 12,235 protein coding genes. The structure of these networks varies widely among genes, indicating different patterns of variation despite a shared evolutionary history. We focus on those genes whose genotype networks show many cycles, which can indicate homoplasy, i.e., parallel or convergent evolution, on the sequence level.

CONCLUSION

For 42 genes, the observed number of cycles is so large that it cannot be explained by either chance homoplasy or recombination. When analyzing possible explanations, we discovered evidence for positive selection in 21 of these genes and, in addition, a potential role for constrained variation and purifying selection. Balancing selection plays at most a small role. The 42 genes with excess cycles are enriched in functions related to immunity and response to pathogens. Genotype networks are representations of genetic variation data that can help understand unusual patterns of genomic variation.

Evolutionary escape on complex genotype-phenotype networks

We study the problem of evolutionary escape that is the process whereby a population under sudden changes in the selective pressures acting upon it try to evade extinction by evolving from previously well-adapted phenotypes to those that are favoured by the new selective pressure. We perform a comparative analysis between results obtained by modelling genotype space as a regular hypercube (H-graphs), which is the scenario considered in previous work on the subject, to those corresponding to a complex genotype-phenotype network (B-graphs). In order to analyse the properties of the escape process on both these graphs, we apply a general theory based on multi-type branching processes to compute the evolutionary dynamics and probability of escape. We show that the distribution of distances between phenotypes in B-graphs exhibits a much larger degree of heterogeneity than in H-graphs. This property, one of the main structural differences between both types of graphs, causes heterogeneous behaviour in all results associated to the escape problem. We further show that, due to the heterogeneity characterising escape on B-graphs, escape probability can be underestimated by assuming a regular hypercube genotype network, even if we compare phenotypes at the same distance in H-graphs. Similarly, it appears that the complex structure of B-graphs slows down the rate of escape.

Evolutionary stasis in pollen morphogenesis due to natural selection

The contribution of developmental constraints and selective forces to the determination of evolutionary patterns is an important and unsolved question. We test whether the long-term evolutionary stasis observed for pollen morphogenesis (microsporogenesis) in eudicots is due to developmental constraints or to selection on a morphological trait shaped by microsporogenesis: the equatorial aperture pattern. Most eudicots have three equatorial apertures but several taxa have independently lost the equatorial pattern and have microsporogenesis decoupled from aperture pattern determination. If selection on the equatorial pattern limits variation, we expect to see increased variation in microsporogenesis in the nonequatorial clades. Variation of microsporogenesis was studied using phylogenetic comparative analyses in 83 species dispersed throughout eudicots including species with and without equatorial apertures. The species that have lost the equatorial pattern have highly variable microsporogenesis at the intra-individual and inter-specific levels regardless of their pollen morphology, whereas microsporogenesis remains stable in species with the equatorial pattern. The observed burst of variation upon loss of equatorial apertures shows that there are no strong developmental constraints precluding variation in microsporogenesis, and that the stasis is likely to be due principally to selective pressure acting on pollen morphogenesis because of its implication in the determination of the equatorial aperture pattern.

The Relationship between Gene Network Structure and Expression Variation among Individuals and Species

Variation among individuals is a prerequisite of evolution by natural selection. As such, identifying the origins of variation is a fundamental goal of biology. We investigated the link between gene interactions and variation in gene expression among individuals and species using the mammalian limb as a model system. We first built interaction networks for key genes regulating early (outgrowth; E9.5-11) and late (expansion and elongation; E11-13) limb development in mouse. This resulted in an Early (ESN) and Late (LSN) Stage Network. Computational perturbations of these networks suggest that the ESN is more robust. We then quantified levels of the same key genes among mouse individuals and found that they vary less at earlier limb stages and that variation in gene expression is heritable. Finally, we quantified variation in gene expression levels among four mammals with divergent limbs (bat, opossum, mouse and pig) and found that levels vary less among species at earlier limb stages. We also found that variation in gene expression levels among individuals and species are correlated for earlier and later limb development. In conclusion, results are consistent with the robustness of the ESN buffering among-individual variation in gene expression levels early in mammalian limb development, and constraining the evolution of early limb development among mammalian species.

Surviving evolutionary escape on complex genotype-phenotype networks

We study the problem of evolutionary escape and survival of cell populations with a genotype-phenotype structure. We refer to evolutionary escape as the process where a cell of a given ill-adapted population to reach a well-adapted phenotype. Similarly, survival refers to the dynamics of the population once the escape phenotype has been reached. The aim of this paper is to analyse the influence of topological properties associated to robustness and evolvability on the probability of escape and on the probability of survival. In order to explore these issues, we formulate a population dynamics model, consisting of a multi-type time-continuous branching process, where types are associated to genotypes and their birth and death probabilities depend on the associated phenotype (non-escape or escape). We exploit the separation of time scales introduced by the the difference in reproductive ratios between the ill-adapted phenotypes and the escape phenotype. Two dynamical regimes emerge: a fast-decaying regime associated to the escape process itself, and a slow regime which corresponds to the survival dynamics of the population once the escape phenotype has been reached. We exploit this separation of time scales to analyse the topological factors which determine escape and survival probabilities. We show that, while the escape probability depends on the degree of escape phenotype, the probability of survival is essentially determined by its robustness, measured in terms of a weighted clustering coefficient.

The origins of mutational robustness

Biological systems are resistant to genetic changes; a property known as mutational robustness, the origin of which remains an open question. In recent years, researchers have explored emergent properties of biological systems and mechanisms of genetic redundancy to reveal how mutational robustness emerges and persists. Several mechanisms have been proposed to explain the origin of mutational robustness, including molecular chaperones and gene duplication. The latter has received much attention, but its role in robustness remains controversial. Here, I examine recent findings linking genetic redundancy through gene duplication and mutational robustness. Experimental evolution and genome resequencing have made it possible to test the role of gene duplication in tolerating mutations at both the coding and regulatory levels. This evidence as well as previous findings on regulatory reprogramming of duplicates support the role of gene duplication in the origin of robustness.

A Philosophical Perspective on Evolutionary Systems Biology

Evolutionary systems biology (ESB) is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB's progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology.

toyLIFE: a computational framework to study the multi-level organisation of the genotype-phenotype map

The genotype-phenotype map is an essential object to understand organismal complexity and adaptability. However, its experimental characterisation is a daunting task. Thus, simple models have been proposed and investigated. They have revealed that genotypes differ in their robustness to mutations; phenotypes are represented by a broadly varying number of genotypes, and simple point mutations suffice to navigate the space of genotypes while maintaining a phenotype. Nonetheless, most current models focus only on one level of the map (folded molecules, gene regulatory networks, or networks of metabolic reactions), so that many relevant questions cannot be addressed. Here we introduce toyLIFE, a multi-level model for the genotype-phenotype map based on simple genomes and interaction rules from which a complex behaviour at upper levels emerges -remarkably plastic gene regulatory networks and metabolism. toyLIFE is a tool that permits the investigation of how different levels are coupled, in particular how and where mutations affect phenotype or how the presence of certain metabolites determines the dynamics of toyLIFE gene regulatory networks. The model can easily incorporate evolution through more complex mutations, recombination, or gene duplication and deletion, thus opening an avenue to explore extended genotype-phenotype maps.

Using genomics to characterize evolutionary potential for conservation of wild populations

Genomics promises exciting advances towards the important conservation goal of maximizing evolutionary potential, notwithstanding associated challenges. Here, we explore some of the complexity of adaptation genetics and discuss the strengths and limitations of genomics as a tool for characterizing evolutionary potential in the context of conservation management. Many traits are polygenic and can be strongly influenced by minor differences in regulatory networks and by epigenetic variation not visible in DNA sequence. Much of this critical complexity is difficult to detect using methods commonly used to identify adaptive variation, and this needs appropriate consideration when planning genomic screens, and when basing management decisions on genomic data. When the genomic basis of adaptation and future threats are well understood, it may be appropriate to focus management on particular adaptive traits. For more typical conservations scenarios, we argue that screening genome-wide variation should be a sensible approach that may provide a generalized measure of evolutionary potential that accounts for the contributions of small-effect loci and cryptic variation and is robust to uncertainty about future change and required adaptive response(s). The best conservation outcomes should be achieved when genomic estimates of evolutionary potential are used within an adaptive management framework.

The topology of robustness and evolvability in evolutionary systems with genotype-phenotype map

In this paper we formulate a topological definition of the concepts of robustness and evolvability. We start our investigation by formulating a multiscale model of the evolutionary dynamics of a population of cells. Our cells are characterised by a genotype-phenotype map: their chances of survival under selective pressure are determined by their phenotypes, whereas the latter are determined their genotypes. According to our multiscale dynamics, the population dynamics generates the evolution of a genotype-phenotype network. Our representation of the genotype-phenotype network is similar to previously described ones, but has a novel element, namely, our network contains two types of nodes: genotype and phenotype nodes. This network representation allows us to characterise robustness and evolvability in terms of its topological properties: phenotypic robustness by means of the clustering coefficient of the phenotype nodes, and evolvability as the emergence of giant connected component which allows navigation between phenotypes. This topological definition of evolvability allows us to characterise the so-called robustness of evolvability, which is defined in terms of the robustness against attack (i.e. edge removal) of the giant connected component. An investigation of the factors that affect the robustness of evolvability shows that phenotypic robustness and the cryptic genetic variation are key to the integrity of the ability to innovate. These results fit within the framework of a number of models which point out that robustness favours rather than hindering evolvability. We further show that the corresponding phenotype network, defined as the one-component projection of the whole genotype-phenotype network, exhibits the small-world phenomenon, which implies that in this type of evolutionary system the rate of adaptability is enhanced.

Clades reach highest morphological disparity early in their evolution

There are few putative macroevolutionary trends or rules that withstand scrutiny. Here, we test and verify the purported tendency for animal clades to reach their maximum morphological variety relatively early in their evolutionary histories (early high disparity). We present a meta-analysis of 98 metazoan clades radiating throughout the Phanerozoic. The disparity profiles of groups through time are summarized in terms of their center of gravity (CG), with values above and below 0.50 indicating top- and bottom-heaviness, respectively. Clades that terminate at one of the "big five" mass extinction events tend to have truncated trajectories, with a significantly top-heavy CG distribution overall. The remaining 63 clades show the opposite tendency, with a significantly bottom-heavy mean CG (relatively early high disparity). Resampling tests are used to identify groups with a CG significantly above or below 0.50; clades not terminating at a mass extinction are three times more likely to be significantly bottom-heavy than top-heavy. Overall, there is no clear temporal trend in disparity profile shapes from the Cambrian to the Recent, and early high disparity is the predominant pattern throughout the Phanerozoic. Our results do not allow us to distinguish between ecological and developmental explanations for this phenomenon. To the extent that ecology has a role, however, the paucity of bottom-heavy clades radiating in the immediate wake of mass extinctions suggests that early high disparity more probably results from the evolution of key apomorphies at the base of clades rather than from physical drivers or catastrophic ecospace clearing.

Switching between apparently redundant iron-uptake mechanisms benefits bacteria in changeable environments

Bacteria often possess multiple siderophore-based iron uptake systems for scavenging this vital resource from their environment. However, some siderophores seem redundant, because they have limited iron-binding efficiency and are seldom expressed under iron limitation. Here, we investigate the conundrum of why selection does not eliminate this apparent redundancy. We focus on Pseudomonas aeruginosa, a bacterium that can produce two siderophores-the highly efficient but metabolically expensive pyoverdine, and the inefficient but metabolically cheap pyochelin. We found that the bacteria possess molecular mechanisms to phenotypically switch from mainly producing pyoverdine under severe iron limitation to mainly producing pyochelin when iron is only moderately limited. We further show that strains exclusively producing pyochelin grew significantly better than strains exclusively producing pyoverdine under moderate iron limitation, whereas the inverse was seen under severe iron limitation. This suggests that pyochelin is not redundant, but that switching between siderophore strategies might be beneficial to trade off efficiencies versus costs of siderophores. Indeed, simulations parameterized from our data confirmed that strains retaining the capacity to switch between siderophores significantly outcompeted strains defective for one or the other siderophore under fluctuating iron availabilities. Finally, we discuss how siderophore switching can be viewed as a form of collective decision-making, whereby a coordinated shift in behaviour at the group level emerges as a result of positive and negative feedback loops operating among individuals at the local scale.

Sexual selection and the evolution of secondary sexual traits: sex comb evolution in Drosophila

Sexual selection can drive rapid evolutionary change in reproductive behaviour, morphology and physiology. This often leads to the evolution of sexual dimorphism, and continued exaggerated expression of dimorphic sexual characteristics, although a variety of other alternative selection scenarios exist. Here, we examined the evolutionary significance of a rapidly evolving, sexually dimorphic trait, sex comb tooth number, in two Drosophila species. The presence of the sex comb in both D. melanogaster and D. pseudoobscura is known to be positively related to mating success, although little is yet known about the sexually selected benefits of sex comb structure. In this study, we used experimental evolution to test the idea that enhancing or eliminating sexual selection would lead to variation in sex comb tooth number. However, the results showed no effect of either enforced monogamy or elevated promiscuity on this trait. We discuss several hypotheses to explain the lack of divergence, focussing on sexually antagonistic coevolution, stabilizing selection via species recognition and nonlinear selection. We discuss how these are important, but relatively ignored, alternatives in understanding the evolution of rapidly evolving sexually dimorphic traits.

Compensatory evolution and the origins of innovations

Cryptic genetic sequences have attenuated effects on phenotypes. In the classic view, relaxed selection allows cryptic genetic diversity to build up across individuals in a population, providing alleles that may later contribute to adaptation when co-opted--e.g., following a mutation increasing expression from a low, attenuated baseline. This view is described, for example, by the metaphor of the spread of a population across a neutral network in genotype space. As an alternative view, consider the fact that most phenotypic traits are affected by multiple sequences, including cryptic ones. Even in a strictly clonal population, the co-option of cryptic sequences at different loci may have different phenotypic effects and offer the population multiple adaptive possibilities. Here, we model the evolution of quantitative phenotypic characters encoded by cryptic sequences and compare the relative contributions of genetic diversity and of variation across sites to the phenotypic potential of a population. We show that most of the phenotypic variation accessible through co-option would exist even in populations with no polymorphism. This is made possible by a history of compensatory evolution, whereby the phenotypic effect of a cryptic mutation at one site was balanced by mutations elsewhere in the genome, leading to a diversity of cryptic effect sizes across sites rather than across individuals. Cryptic sequences might accelerate adaptation and facilitate large phenotypic changes even in the absence of genetic diversity, as traditionally defined in terms of alternative alleles.

Non-local competition drives both rapid divergence and prolonged stasis in a model of speciation in populations with degenerate resource consumption

The theory of speciation is dominated by adaptationist thinking, with less attention to mechanisms that do not affect species adaptation. Degeneracy – the imperfect specificity of interactions between diverse elements of biological systems and their environments – is key to the adaptability of populations. A mathematical model was explored in which population and resource were distributed one-dimensionally according to trait value. Resource consumption was degenerate – neither strictly location-specific nor location-independent. As a result, the competition for resources among the elements of the population was non-local. Two modeling approaches, a modified differential-integral Verhulstian equation and a cellular automata model, showed similar results: narrower degeneracy led to divergent dynamics with suppression of intermediate forms, whereas broader degeneracy led to suppression of diversifying forms, resulting in population stasis with increasing phenotypic homogeneity. Such behaviors did not increase overall adaptation because they continued after the model populations achieved maximal resource consumption rates, suggesting that degeneracy-driven distributed competition for resources rather than selective pressure toward more efficient resource exploitation was the driving force. The solutions were stable in the presence of limited environmental stochastic variability or heritable phenotypic variability. A conclusion was made that both dynamic diversification and static homogeneity of populations may be outcomes of the same process – distributed competition for resource not affecting the overall adaptation – with the difference between them defined by the spread of trait degeneracy in a given environment. Thus, biological degeneracy is a driving force of both speciation and stasis in biology, which, by themselves, are not necessarily adaptive in nature.

Phylogenetic niche conservatism: what are the underlying evolutionary and ecological causes?

Phylogenetic niche conservatism (PNC) is the tendency of lineages to retain their niche-related traits through speciation events. A recent surge in the availability of well-sampled molecular phylogenies has stimulated phylogenetic approaches to understanding ecological processes at large geographical scales and through macroevolutionary time. We stress that PNC is a pattern, not a process, and is found only in some traits and some lineages. At the simplest level, a pattern of PNC is an inevitable consequence of evolution - descent with modification and divergence of lineages - but several intrinsic causes, including physicochemical, developmental and genetic constraints, can lead directly to a marked pattern of PNC. A pattern of PNC can also be caused indirectly, as a by-product of other causes, such as extinction, dispersal limitation, competition and predation. Recognition of patterns of PNC can contribute to understanding macroevolutionary processes: for example, release from constraint in traits has been hypothesized to trigger adaptive radiations such as that of the angiosperms. Given the multiple causes of patterns of PNC, tests should address explicit questions about hypothesized processes. We conclude that PNC is a scientifically useful concept with applications to the practice of ecological research.

The role of robustness in phenotypic adaptation and innovation

Phenotypes that vary in response to DNA mutations are essential for evolutionary adaptation and innovation. Therefore, it seems that robustness, a lack of phenotypic variability, must hinder adaptation. The main purpose of this review is to show why this is not necessarily correct. There are two reasons. The first is that robustness causes the existence of genotype networks--large connected sets of genotypes with the same phenotype. I discuss why genotype networks facilitate phenotypic variability. The second reason emerges from the evolutionary dynamics of evolving populations on genotype networks. I discuss how these dynamics can render highly robust phenotypes more variable, using examples from protein and RNA macromolecules. In addition, robustness can help avoid an important evolutionary conflict between the interests of individuals and populations-a conflict that can impede evolutionary adaptation.

Strain Variation in the Transcriptome of the Dengue Fever Vector, Aedes aegypti

Studies of transcriptome dynamics provide a basis for understanding functional elements of the genome and the complexity of gene regulation. The dengue vector mosquito, Aedes aegypti, exhibits great adaptability to diverse ecological conditions, is phenotypically polymorphic, and shows variation in vectorial capacity to arboviruses. Previous genome sequencing showed richness in repetitive DNA and transposable elements that can contribute to genome plasticity. Population genetic studies revealed a varying degree of worldwide genetic polymorphism. However, the extent of functional genetic polymorphism across strains is unknown. The transcriptomes of three Ae. aegypti strains, Chetumal (CTM), Rexville D-Puerto Rico (Rex-D) and Liverpool (LVP), were compared. CTM is more susceptible than Rex- D to infection by dengue virus serotype 2. A total of 4188 transcripts exhibit either no or small variation (<2-fold) among sugar-fed samples of the three strains and between sugar- and blood-fed samples within each strain, corresponding most likely to genes encoding products necessary for vital functions. Transcripts enriched in blood-fed mosquitoes encode proteins associated with catalytic activities, molecular transport, metabolism of lipids, carbohydrates and amino acids, and functions related to blood digestion and the progression of the gonotropic cycle. Significant qualitative and quantitative differences were found in individual transcripts among strains including differential representation of paralogous gene products. The majority of immunity-associated transcripts decreased in accumulation after a bloodmeal and the results are discussed in relation to the different susceptibility of CTM and Rex-D mosquitoes to DENV2 infection.

Evolutionary systems biology: historical and philosophical perspectives on an emerging synthesis

Systems biology (SB) is at least a decade old now and maturing rapidly. A more recent field, evolutionary systems biology (ESB), is in the process of further developing system-level approaches through the expansion of their explanatory and potentially predictive scope. This chapter will outline the varieties of ESB existing today by tracing the diverse roots and fusions that make up this integrative project. My approach is philosophical and historical. As well as examining the recent origins of ESB, I will reflect on its central features and the different clusters of research it comprises. In its broadest interpretation, ESB consists of five overlapping approaches: comparative and correlational ESB; network architecture ESB; network property ESB; population genetics ESB; and finally, standard evolutionary questions answered with SB methods. After outlining each approach with examples, I will examine some strong general claims about ESB, particularly that it can be viewed as the next step toward a fuller modern synthesis of evolutionary biology (EB), and that it is also the way forward for evolutionary and systems medicine. I will conclude with a discussion of whether the emerging field of ESB has the capacity to combine an even broader scope of research aims and efforts than it presently does.