DISSECTION OF EVOLUTIONARY NETWORKS TO ASSESS THEIR ROLE IN THE EVOLUTION OF ROBUSTNESS,FUNCTION, AND DIVERSIFICATION

Biological systems are remarkably robust in the face of environmental, mutational, and developmental perturbations. Analyses of molecular networks reveal recurrent features, such as modularity, that have been implicated in robustness and evolvability. Multiple theoretical models account for these features, yet few empirical tests of these models exist. Here I develop a set of broadly applicable methodologies to enable expanded empirical evaluation of model predictions. The methodologies focus on the inference and analysis of networks that depict evolutionary correlations among characters. I apply these methodologies to analyze an evolutionary network at a larger scale of organization among 42 stem anatomical and morphological characters of 52 species in the genus Adenia (Passifloraceae). I evaluate a model predicting that modular evolutionary networks will evolve in response to environmental change. The evolutionary network of Adenia is modular and “small‐world,” and the three diagnosed modules correspond roughly to functions of transport, storage, and mechanical support. The phylogenetically informed analyses suggest that the storage module is more impacted by environmental change than expected by chance. These results corroborate the hypothesis that modularity reduces the impact of environmental change, but this result requires further empirical evaluation that can be aided by the proposed methods in additional study systems.     

Beyond topology: coevolution of structure and flux in metabolic networks

Interactions between the structure of a metabolic network and its functional properties underlie its evolutionary diversification, but the mechanism by which such interactions arise remains elusive. Particularly unclear is whether metabolic fluxes that determine the concentrations of compounds produced by a metabolic network, are causally linked to a network's structure or emerge independently of it. A direct empirical study of populations where both structural and functional properties vary among individuals’ metabolic networks is required to establish whether changes in structure affect the distribution of metabolic flux. In a population of house finches (Haemorhous mexicanus), we reconstructed full carotenoid metabolic networks for 442 individuals and uncovered 11 structural variants of this network with different compounds and reactions. We examined the consequences of this structural diversity for the concentrations of plumage‐bound carotenoids produced by flux in these networks. We found that concentrations of metabolically derived, but not dietary carotenoids, depended on network structure. Flux was partitioned similarly among compounds in individuals of the same network structure: within each network, compound concentrations were closely correlated. The highest among‐individual variation in flux occurred in networks with the strongest among‐compound correlations, suggesting that changes in the magnitude, but not the distribution of flux, underlie individual differences in compound concentrations on a static network structure. These findings indicate that the distribution of flux in carotenoid metabolism closely follows network structure. Thus, evolutionary diversification and local adaptations in carotenoid metabolism may depend more on the gain or loss of enzymatic reactions than on changes in flux within a network structure.     

Demographic fluctuations lead to rapid and cyclic shifts in genetic structure among populations of an alpine butterfly,Parnassius smintheus

Many populations, especially in insects, fluctuate in size, and periods of particularly low population size can have strong effects on genetic variation. Effects of demographic bottlenecks on genetic diversity of single populations are widely documented. Effects of bottlenecks on genetic structure among multiple interconnected populations are less studied, as are genetic changes across multiple cycles of demographic collapse and recovery. We take advantage of a long‐term data set comprising demographic, genetic and movement data from a network of populations of the butterfly, Parnassius smintheus, to examine the effects of fluctuating population size on spatial genetic structure. We build on a previous study that documented increased genetic differentiation and loss of spatial genetic patterns (isolation by distance and by intervening forest cover) after a network‐wide bottleneck event. Here, we show that genetic differentiation was reduced again and spatial patterns returned to the system extremely rapidly, within three years (i.e. generations). We also show that a second bottleneck had similar effects to the first, increasing differentiation and erasing spatial patterns. Thus, bottlenecks consistently drive random divergence of allele frequencies among populations in this system, but these effects are rapidly countered by gene flow during demographic recovery. Our results reveal a system in which the relative influence of genetic drift and gene flow continually shift as populations fluctuate in size, leading to cyclic changes in genetic structure. Our results also suggest caution in the interpretation of patterns of spatial genetic structure, and its association with landscape variables, when measured at only a single point in time.     

Genomewide landscape of gene–metabolome associations in Escherichia coli

Metabolism is one of the best‐understood cellular processes whose network topology of enzymatic reactions is determined by an organism's genome. The influence of genes on metabolite levels, however, remains largely unknown, particularly for the many genes encoding non‐enzymatic proteins. Serendipitously, genomewide association studies explore the relationship between genetic variants and metabolite levels, but a comprehensive interaction network has remained elusive even for the simplest single‐celled organisms. Here, we systematically mapped the association between > 3,800 single‐gene deletions in the bacterium Escherichia coli and relative concentrations of > 7,000 intracellular metabolite ions. Beyond expected metabolic changes in the proximity to abolished enzyme activities, the association map reveals a largely unknown landscape of gene–metabolite interactions that are not represented in metabolic models. Therefore, the map provides a unique resource for assessing the genetic basis of metabolic changes and conversely hypothesizing metabolic consequences of genetic alterations. We illustrate this by predicting metabolism‐related functions of 72 so far not annotated genes and by identifying key genes mediating the cellular response to environmental perturbations.     

Population genomic footprints of selection and associations with climate in natural populations of Arabidopsis halleri from the Alps

Natural genetic variation is essential for the adaptation of organisms to their local environment and to changing environmental conditions. Here, we examine genomewide patterns of nucleotide variation in natural populations of the outcrossing herb Arabidopsis halleri and associations with climatic variation among populations in the Alps. Using a pooled population sequencing (Pool‐Seq) approach, we discovered more than two million SNPs in five natural populations and identified highly differentiated genomic regions and SNPs using F_ST‐based analyses. We tested only the most strongly differentiated SNPs for associations with a nonredundant set of environmental factors using partial Mantel tests to identify topo‐climatic factors that may underlie the observed footprints of selection. Possible functions of genes showing signatures of selection were identified by Gene Ontology analysis. We found 175 genes to be highly associated with one or more of the five tested topo‐climatic factors. Of these, 23.4% had unknown functions. Genetic variation in four candidate genes was strongly associated with site water balance and solar radiation, and functional annotations were congruent with these environmental factors. Our results provide a genomewide perspective on the distribution of adaptive genetic variation in natural plant populations from a highly diverse and heterogeneous alpine environment.     

Spatial proximity and asynchronous refuge sharing networks both explain patterns of tick genetic relatedness among lizards,but in different years

A major question for understanding the ecology of parasite infections and diseases in wildlife populations concerns the transmission pathways among hosts. Network models are increasingly used to model the transmission of infections among hosts – however, few studies have integrated host behaviour and genetic relatedness of the parasites transmitted between hosts. In a study of the Australian sleepy lizard Tiliqua rugosa and its three‐host ixodid tick (Bothriocroton hydrosauri), we asked if patterns of genetic relatedness among ticks were best explained by spatial proximity or the host transmission network. Using synchronous GPS locations of over 50 adult lizards at 10 min intervals across the three‐month activity period, over 2 years, we developed two alternative parasite transmission networks. One alternative was based on the spatial proximity of lizards (at the centre of their home ranges), and the other was based on the frequency of asynchronous shared refuge use between pairs of lizards. In each year, adult ticks were removed from lizards and their genotypes were determined at four polymorphic microsatellite loci. Adult ticks collected from the same host were more related to each other than ticks from different hosts. Similarly, adult ticks collected from different lizards had a higher relatedness if those lizards had a shorter path length connecting them on each of the two networks we explored. The predictors of tick relatedness differed between years. In the first year, the asynchronous shared refuges network was the stronger predictor of tick relatedness, whereas in year two, the spatial proximity‐based network was the stronger predictor of tick relatedness. We speculate on how changing environmental conditions might change the relative importance of alternative processes driving the transmission of parasites.     

Variation in sleep and metabolic function is associated with latitude and average temperature in Drosophila melanogaster

Regulation of sleep and metabolic homeostasis is critical to an animal's survival and under stringent evolutionary pressure. Animals display remarkable diversity in sleep and metabolic phenotypes; however, an understanding of the ecological forces that select for, and maintain, these phenotypic differences remains poorly understood. The fruit fly, Drosophila melanogaster, is a powerful model for investigating the genetic regulation of sleep and metabolic function, and screening in inbred fly lines has led to the identification of novel genetic regulators of sleep. Nevertheless, little is known about the contributions of naturally occurring genetic differences to sleep, metabolic phenotypes, and their relationship with geographic or environmental gradients. Here, we quantified sleep and metabolic phenotypes in 24 D. melanogaster populations collected from diverse geographic localities. These studies reveal remarkable variation in sleep, starvation resistance, and energy stores. We found that increased sleep duration is associated with proximity to the equator and elevated average annual temperature, suggesting that environmental gradients strongly influence natural variation in sleep. Further, we found variation in metabolic regulation of sleep to be associated with free glucose levels, while starvation resistance associates with glycogen and triglyceride stores. Taken together, these findings reveal robust naturally occurring variation in sleep and metabolic traits in D. melanogaster, providing a model to investigate how evolutionary and ecological history modulate these complex traits.     

Aquatic insects in a sea of desert: population genetic structure is shaped by limited dispersal in a naturally fragmented landscape

Habitat requirements and landscape features can exert strong influences on the population structure of organisms. For aquatic organisms in particular, hydrologic requirements can dictate the extent of available habitat, and thus the degree of genetic connectivity among populations. We used a landscape genetics approach to evaluate hypotheses regarding the influence of landscape features on connectivity among populations of the giant water bug Abedus herberti (Hemiptera: Belostomatidae). Abedus herberti is restricted to naturally‐fragmented, perennial stream habitats in arid regions of North America. This species is exceptional because it is flightless at all life stages. Thus, we hypothesized a high degree of population genetic structure in A. herberti due to hydrologic constraints on habitat and low dispersal ability of the organism. A total of 617 individuals were sampled from 20 populations across southeastern Arizona, USA and genotyped at 10 microsatellite loci. We used a Bayesian clustering method to delineate genetic groups among populations. To determine which of six landscape variables (representing hypotheses of landscape‐level connectivity) has the strongest association with genetic connectivity in A. herberti, we used information‐theoretic model selection. Strong population structure was evident among A. herberti populations, even at small spatial scales. At a larger scale, A. herberti populations were hierarchically structured across the study region, with groups of related populations generally occurring in the same mountain range, rather than in the same major watershed. Surprisingly, stream network connectivity was not important for explaining among‐population patterns. Only the Curvature landscape variable was identified as having an association with genetic connectivity in A. herberti. The Curvature variable hypothesizes that gene flow tends to occur where local topography is concave, such as within stream drainages and dry gullies. Thus, our results suggest that population connectivity may depend on the shape of local overland topography rather than direct connectivity within stream drainage networks.     

Determinants of hierarchical genetic structure in Atlantic salmon populations: environmental factors vs. anthropogenic influences

Disentangling the effects of natural environmental features and anthropogenic factors on the genetic structure of endangered populations is an important challenge for conservation biology. Here, we investigated the combined influences of major environmental features and stocking with non‐native fish on the genetic structure and local adaptation of Atlantic salmon (Salmo salar) populations. We used 17 microsatellite loci to genotype 975 individuals originating from 34 French rivers. Bayesian analyses revealed a hierarchical genetic structure into five geographically distinct clusters. Coastal distance, geological substrate and river length were strong predictors of population structure. Gene flow was higher among rivers with similar geologies, suggesting local adaptation to geological substrate. The effect of river length was mainly owing to one highly differentiated population that has the farthest spawning grounds off the river mouth (up to 900 km) and the largest fish, suggesting local adaptation to river length. We detected high levels of admixture in stocked populations but also in neighbouring ones, implying large‐scale impacts of stocking through dispersal of non‐native individuals. However, we found relatively few admixed individuals suggesting a lower fitness of stocked fish and/or some reproductive isolation between wild and stocked individuals. When excluding stocked populations, genetic structure increased as did its correlation with environmental factors. This study overall indicates that geological substrate and river length are major environmental factors influencing gene flow and potential local adaptation among Atlantic salmon populations but that stocking with non‐native individuals may ultimately disrupt these natural patterns of gene flow among locally adapted populations.     

Metabolic control analysis under uncertainty: framework development and case studies

Information about the enzyme kinetics in a metabolic network will enable understanding of the function of the network and quantitative prediction of the network responses to genetic and environmental perturbations. Despite recent advances in experimental techniques, such information is limited and existing experimental data show extensive variation and they are based on in vitro experiments. In this article, we present a computational framework based on the well-established (log)linear formalism of metabolic control analysis. The framework employs a Monte Carlo sampling procedure to simulate the uncertainty in the kinetic data and applies statistical tools for the identification of the rate-limiting steps in metabolic networks. We applied the proposed framework to a branched biosynthetic pathway and the yeast glycolysis pathway. Analysis of the results allowed us to interpret and predict the responses of metabolic networks to genetic and environmental changes, and to gain insights on how uncertainty in the kinetic mechanisms and kinetic parameters propagate into the uncertainty in predicting network responses. Some of the practical applications of the proposed approach include the identification of drug targets for metabolic diseases and the guidance for design strategies in metabolic engineering for the purposeful manipulation of the metabolism of industrial organisms.     

A kinetic model describes metabolic response to perturbations and distribution of flux control in the benzenoid network of Petunia hybrida

In recent years there has been much interest in the genetic enhancement of plant metabolism; however, attempts at genetic modification are often unsuccessful due to an incomplete understanding of network dynamics and their regulatory properties. Kinetic modeling of plant metabolic networks can provide predictive information on network control and response to genetic perturbations, which allow estimation of flux at any concentration of intermediate or enzyme in the system. In this research, a kinetic model of the benzenoid network was developed to simulate whole network responses to different concentrations of supplied phenylalanine (Phe) in petunia flowers and capture flux redistributions caused by genetic manipulations. Kinetic parameters were obtained by network decomposition and non‐linear least squares optimization of data from petunia flowers supplied with either 75 or 150 mm ²H₅‐Phe. A single set of kinetic parameters simultaneously accommodated labeling and pool size data obtained for all endogenous and emitted volatiles at the two concentrations of supplied ²H₅‐Phe. The generated kinetic model was validated using flowers from transgenic petunia plants in which benzyl CoA:benzyl alcohol/phenylethanol benzoyltransferase (BPBT) was down‐regulated via RNAi. The determined in vivo kinetic parameters were used for metabolic control analysis, in which flux control coefficients were calculated for fluxes around the key branch point at Phe and revealed that phenylacetaldehyde synthase activity is the primary controlling factor for the phenylacetaldehyde branch of the benzenoid network. In contrast, control of flux through the β‐oxidative and non‐β‐oxidative pathways is highly distributed.     

Genetic analysis of differentiation among breeding ponds reveals a candidate gene for local adaptation in Rana arvalis

One of the main questions in evolutionary and conservation biology is how geographical and environmental features of the landscape shape neutral and adaptive genetic variation in natural populations. The identification of genomic polymorphisms that account for adaptive variation can aid in finding candidate loci for local adaptation. Consequently, a comparison of spatial patterns in neutral markers and loci under selection may help disentangle the effects of gene flow, genetic drift and selection at the landscape scale. Many amphibians breed in wetlands, which differ in environmental conditions and in the degree of isolation, enhancing the potential for local adaptation. We used microsatellite markers to measure genetic differentiation among 17 local populations of Rana arvalis breeding in a network of wetlands. We found that locus RC08604 deviated from neutral expectations, suggesting that it is a good candidate for directional selection. We used a genetic network analysis to show that the allele distribution in this locus is correlated with habitat characteristics, whereas this was not the case at neutral markers that displayed a different allele distribution and population network in the study area. The graph approach illustrated the genomic heterogeneity (neutral loci vs. the candidate locus for directional selection) of gene exchange and genetic divergence among populations under directional selection. Limited gene flow between wetlands was only observed at the candidate genomic region under directional selection. RC08604 is partially located inside an up‐regulated thyroid‐hormone receptor (TRβ) gene coordinating the expression of other genes during metamorphosis and appears to be linked with variation in larval life‐history traits found among R. arvalis populations. We suggest that directional selection on genes coding larval life‐history traits is strong enough to maintain the divergence in these genomic regions, reducing the effective recombination of locally adapted alleles but not in other regions of the genome. Integrating this knowledge into conservation plans at the landscape scale will improve the design of management strategies to preserve adaptive genetic diversity in wetland networks.     

Directional selection reduces developmental canalization against genetic and environmental perturbations in Drosophila wings

Natural selection may enhance or weaken the robustness of phenotypes against genetic or environmental perturbations. However, important aspects of the relationship between adaptive evolution and canalization remain unclear. Recent work showed that the evolution of larger wing size in a high altitude natural population of Drosophila melanogaster was accompanied by decanalized wing development–‐specifically a loss of robustness to genetic perturbation. But this study did not address environmental robustness, and it compared populations that may have numerous biological differences. Here, we perform artificial selection on this same trait in D. melanogaster (larger wing length) and directly test whether this directional selection resulted in decanalization. We find that in general, size‐selected replicates show greater frequencies of wing defects than control replicates both after mutagenesis (genetic perturbation) and when subjected to high temperature stress (environmental perturbation), although the increase in defect frequency varies importantly among replicates. These results support the hypothesis that directional selection may result in the loss of both genetic and environmental robustness–offering a rare window into the relationship between adaptation and canalization.     

Spatial predictors of genomic and phenotypic variation differ in a lowland Middle American bird (Icterus gularis)

Spatial patterns of intraspecific variation are shaped by geographical distance among populations, historical changes in gene flow and interactions with local environments. Although these factors are not mutually exclusive and operate on both genomic and phenotypic variation, it is unclear how they affect these two axes of variation. We address this question by exploring the predictors of genomic and phenotypic divergence in Icterus gularis, a broadly distributed Middle American bird that exhibits marked geographical variation in body size across its range. We combined a comprehensive single nucleotide polymorphism and phenotypic data set to test whether genome‐wide genetic and phenotypic differentiation are best explained by (i) isolation by distance, (ii) isolation by history or (iii) isolation by environment. We find that the pronounced genetic and phenotypic variation in I. gularis are only partially correlated and differ regarding spatial predictors. Whereas genomic variation is largely explained by historical barriers to gene flow, phenotypic diversity can be best predicted by contemporary environmental heterogeneity. Our genomic analyses reveal strong phylogeographical structure coinciding with the Chivela Pass at the Isthmus of Tehuantepec that was formed during the Pleistocene, when populations were isolated in north–south refugia. In contrast, we found a strong association between body size and environmental variables, such as temperature and precipitation. The relationship between body size and local climate is consistent with a pattern produced by either natural selection or environmental plasticity. Overall, these results provide empirical evidence for why phenotypic and genomic data are often in conflict in taxonomic and phylogeographical studies.     

Historical human activities reshape evolutionary trajectories across both native and introduced ranges

The same vectors that introduce species to new ranges could move them among native populations, but how human‐mediated dispersal impacts native ranges has been difficult to address because human‐mediated dispersal and natural dispersal can simultaneously shape patterns of gene flow. Here, we disentangle human‐mediated dispersal from natural dispersal by exploiting a system where the primary vector was once extensive but has since ceased. From 10th to 19th Centuries, ships in the North Atlantic exchanged sediments dredged from the intertidal for ballast, which ended when seawater ballast tanks were adopted. We investigate genetic patterns from RADseq‐derived SNPs in the amphipod Corophium volutator (n = 121; 4,870 SNPs) and the annelid Hediste diversicolor (n = 78; 3,820 SNPs), which were introduced from Europe to North America, have limited natural dispersal capabilities, are abundant in intertidal sediments, but not commonly found in modern water ballast tanks. We detect similar levels of genetic subdivision among introduced North American populations and among native European populations. Phylogenetic networks and clustering analyses reveal population structure between sites, a high degree of phylogenetic reticulation within ranges, and phylogenetic splits between European and North American populations. These patterns are inconsistent with phylogeographic structure expected to arise from natural dispersal alone, suggesting human activity eroded ancestral phylogeographic structure between native populations, but was insufficient to overcome divergent processes between naturalized populations and their sources. Our results suggest human activity may alter species' evolutionary trajectories on a broad geographic scale via regional homogenization and global diversification, in some cases precluding historical inference from genetic data.     

Environmental effects on fine‐scale spatial genetic structure in four Alpine keystone forest tree species

Genetic responses to environmental changes take place at different spatial scales. While the effect of environment on the distribution of species' genetic diversity at large geographical scales has been the focus of several recent studies, its potential effects on genetic structure at local scales are understudied. Environmental effects on fine‐scale spatial genetic structure (FSGS) were investigated in four Alpine conifer species (five to eight populations per species) from the eastern Italian Alps. Significant FSGS was found for 11 of 25 populations. Interestingly, we found no significant differences in FSGS across species but great variation among populations within species, highlighting the importance of local environmental factors. Interannual variability in spring temperature had a small but significant effect on FSGS of Larix decidua, probably related to species‐specific life history traits. For Abies alba, Picea abies and Pinus cembra, linear models identified spring precipitation as a potentially relevant climate factor associated with differences in FSGS across populations; however, models had low explanatory power and were strongly influenced by a P. cembra outlier population from a very dry site. Overall, the direction of the identified effects is according to expectations, with drier and more variable environments increasing FSGS. Underlying mechanisms may include climate‐related changes in the variance of reproductive success and/or environmental selection of specific families. This study provides new insights on potential changes in local genetic structure of four Alpine conifers in the face of environmental changes, suggesting that new climates, through altering FSGS, may also have relevant impacts on plant microevolution.     

Testing population differentiation in plant species – how important are environmental maternal effects

The maternal environment may contribute to population differentiation in offspring traits if growing conditions of mother plants are different. However, the magnitude of such environmental maternal effects compared with genetic differentiation is often not clear. We tested the importance of environmental maternal effects by comparing population differentiation in parental seed directly collected in the field and in F₁ seed grown under homogeneous conditions. The F₁ seeds were obtained by random crosses within populations. We used five populations in each of four plant species to analyse seed mass and growth chamber germination of both generations at the same time. In two species, we additionally tested offspring performance in the field. We found a significant population differentiation in all species and for nearly all measured traits. Population‐by‐generation interactions indicating environmental maternal effects were significant for germination (three species) and for seed mass (two species) but not for growth and reproduction. The significant interaction was partly due to a reduction of among‐population differentiation from the parental to the F₁ generation that can be explained by a decrease of maternal provisioning effects. However, in some species by trait combinations a change in population ranking and not a decrease of variation was responsible for significant population‐by‐generation interactions indicating environmental maternal effects beyond maternal provisioning. Fitting of seed mass as covariate was not successful in reducing environmental maternal effects on population differentiation in germination. We discuss alternative methods to account for environmental maternal effects in studies on genetic differentiation among populations.