Short-term Evolutionary Change Research Articles

Evolution in fossil time series reconciles observations in micro- and macroevolution.

Extrapolating microevolutionary models does not always provide satisfactory explanations for phenotypic diversification on million-year time scales. For example, short-term evolutionary change is often modeled assuming a fixed adaptive landscape, but macroevolutionary changes are likely to involve changes in the adaptive landscape itself. A better understanding of how the adaptive landscape changes across different time intervals and how these changes cause populations to evolve has the potential to narrow the gap between micro- and macroevolution. Here, we analyze two fossil diatom time series of exceptional quality and resolution covering time intervals of a few hundred thousand years using models that account for different behaviors of the adaptive landscape. We find that one of the lineages evolves on a randomly and continuously changing landscape, whereas the other lineage evolves on a landscape that shows a rapid shift in the position of the adaptive peak of a magnitude that is typically associated with species-level differentiation. This suggests phenotypic evolution beyond generational timescales may be a consequence of both gradual and sudden repositioning of adaptive peaks. Both lineages are showing rapid and erratic evolutionary change and are constantly readapting towards the optimal trait state, observations that align with evolutionary dynamics commonly observed in contemporary populations. The inferred trait evolution over a span of a few hundred thousand years in these two lineages is therefore chimeric in the sense that it combines components of trait evolution typically observed on both short and long timescales.

What determines the evolutionary trajectories of wild plant species? Approaches to the study of quantitative fitness-related traits.

Wild plant species provide excellent examples of qualitative traits that evolve in response to environmental challenges (e.g., flower color, heavy metal tolerance, cyanogenesis, and male sterility). In addition to such discrete characters, a dazzling array of continuously distributed, quantitative traits are expressed at every phase of the life cycle. These traits are known or suspected to have evolved by natural selection because they are heritable, differ among populations or closely related taxa occupying distinct habitats, and have individual phenotypes associated with survival and reproductive success. This special issue [American Journal of Botany 109(11)] focuses on the tools and approaches for detecting or inferring the ecological and genetic factors contributing to changes in genetically based variation of quantitative traits within or among populations, or causing their divergence among taxa. The assembled articles use one or more of three primary approaches to detect the process or outcome of natural selection on morphological, life history, reproductive, chemical, and physiological quantitative traits: the analysis of phenotypic or artificially imposed selection to detect direct and indirect selection on traits whose function is well-understood; common garden experiments, including reciprocal transplants and "resurrection" experiments; and quantitative genetic analyses designed to detect and to estimate the environmental and genetic sources of phenotypic variation or to forecast short-term evolutionary change. Together, these articles examine and reveal the adaptive capacity of quantitative traits and the genetically based constraints that may limit their directional evolutionary change, thereby informing and testing inferences, hypotheses, and predictions concerning the evolutionary trajectories of wild plant species.

Population-level deep sequencing reveals the interplay of clonal and sexual reproduction in the fungal wheat pathogen Zymoseptoria tritici.

Pathogens cause significant challenges to global food security. On annual crops, pathogens must re-infect from environmental sources in every growing season. Fungal pathogens have evolved mixed reproductive strategies to cope with the distinct challenges of colonizing growing plants. However, how pathogen diversity evolves during growing seasons remains largely unknown. Here, we performed a deep hierarchical sampling in a single experimental wheat field infected by the major fungal pathogen Zymoseptoria tritici. We analysed whole genome sequences of 177 isolates collected from 12 distinct cultivars replicated in space at three time points of the growing season to maximize capture of genetic diversity. The field population was highly diverse with 37 SNPs per kilobase, a linkage disequilibrium decay within 200–700 bp and a high effective population size. Using experimental infections, we tested a subset of the collected isolates on the dominant cultivar planted in the field. However, we found no significant difference in virulence of isolates collected from the same cultivar compared to isolates collected on other cultivars. About 20 % of the isolate genotypes were grouped into 15 clonal groups. Pairs of clones were disproportionally found at short distances (<5 m), consistent with experimental estimates for per-generation dispersal distances performed in the same field. This confirms predominant leaf-to-leaf transmission during the growing season. Surprisingly, levels of clonality did not increase over time in the field although reproduction is thought to be exclusively asexual during the growing season. Our study shows that the pathogen establishes vast and stable gene pools in single fields. Monitoring short-term evolutionary changes in crop pathogens will inform more durable strategies to contain diseases.

Why the third way of evolution is necessary.

The Third Way of Evolution was founded in 2014 to make the public aware that contemporary evolution science is not limited to the neo-Darwinian Modern Synthesis of the past century. This was important to do because evolution was challenged as incapable of explaining biological complexity by the Intelligent Design movement. Expounding biological theories like the Modern Synthesis is always subject to limited empirical evidence, fundamental concepts that inevitably change over time, and conceptual preferences that often prove to be misleading. The Modern Synthesis was based on Darwin's preference for the phyletic gradualism necessary to elevate Natural Selection as the sole force determining the direction of evolutionary change. In contradiction to this principle, agricultural crop breeding, direct observation in nature, and genomics have shown that genome change following symbiogenetic cell fusions or interspecific hybridization, not selection, are empirically the most effective methods for originating novel life forms and new species. By asserting that the accumulation of random "slight" variations was the basic mode of both short-term and long-term evolutionary change, the Modern Synthesis also ignored the distinction between (1) microevolutionary change within species by localized mutations and (2) macroevolutionary origination of new species and taxa by genome restructuring. In so doing, the Modern Synthesis failed to recognize the evolutionary importance of cellular capacities to generate large-scale genome changes. By focusing on individual protein-coding genes as the fundamental units of genetic information, the Modern Synthesis did not successfully incorporate either the full non-coding informa tion content in genomes or the major evolutionary potential of mobile DNA elements to generate multisite intragenomic networks necessary for the development of complex organisms. When all of the phenomena overlooked by the Modern Synthesis are taken into consideration, it is not difficult to answer Intelligent Design arguments and show that science is making real progress in understanding the evolution of biological complexity.

Evidence of rapid evolution of an invasive poaceae in response to salinity

Understanding how environmental factors and short-term evolution affect the growth of invasive plants is a central issue in Invasion Biology. For macrophytes, salinity is one of the main factors determining distribution along estuarine environments. Urochola arrecta is a Poaceae with high invasive potential in several freshwater and estuarine ecosystems. In South Brazilian estuaries, this species is found sparsely in mangroves, and invades successfully freshwaters and areas with low salinity. We experimentally described the U. arrecta tolerance to salt. Furthermore, we tested if the response to the saline gradient depends on the population origin, through an experiment with populations inhabiting estuarine and freshwater ecosystems. We designed the experiment with three populations of this species, expecting that estuarine populations were more resistant to salinity. Plants grew in a salinity gradient and after 40 days we measured macrophytes biomass and length. Salinity was highly stressful for U. arrecta independently of its origin. Even so, plant growth differed significantly among populations. Despite higher growth, the population originated from freshwater habitats presented the fastest decrease in performance indicators with increasing salinity. This result indicates short-term evolutionary changes because all populations grew common-garden conditions in our experiment. Furthermore, salinity did not prevent the full establishment of this plant, since almost all propagules developed roots even in the saline treatments. Differences among populations suggest that invasion potential of this species can be higher than predicted by the environmental conditions of current invaded sites. Constant monitoring in estuarine invaded ecosystems is central to manage invasions in critical ecosystems, such as mangroves areas.

Within-Population Genome Size Variation is Mediated by Multiple Genomic Elements That Segregate Independently during Meiosis.

Within-species variation in genome size has been documented in many animals and plants. Despite its importance for understanding eukaryotic genome diversity, there is only sparse knowledge about how individual-level processes mediate genome size variation in populations. Here, we study a natural population of the rotifer Brachionus asplanchnoidis whose members differ up to 1.9-fold in diploid genome size, but were still able to interbreed and produce viable offspring. We show that genome size is highly heritable and can be artificially selected up or down, but not below a certain basal diploid genome size for this species. Analyses of segregation patterns in haploid males reveal that large genomic elements (several megabases in size) provide the substrate of genome size variation. These elements, and their segregation patterns, explain the generation of new genome size variants, the short-term evolutionary potential of genome size change in populations, and some seemingly paradoxical patterns, like an increase in genome size variation among highly inbred lines. Our study suggests that a conceptual model involving only two variables, 1) a basal genome size of the population, and 2) a vector containing information on additional elements that may increase genome size in this population (size, number, and meiotic segregation behavior), can effectively address most scenarios of short-term evolutionary change of genome size in a population.

Evolution of Vehicle Network on a Highway

One of the challenges related to the investigation of vehicular networks is associated with predicting a network state regarding both short-term and long-term network evolutionary changes. This paper analyzes a case in which vehicles are located on a straight road, and the connectivity state between two consecutive cars is determined by the Markov chain model with two states. The transition probabilities of the considered model are explicitly expressed in terms of known parameters of the network using the Wang-Moayery model. Within the presented model, the network evolution is described in terms of determinative parameters, such as average link duration, average cluster lifetime, and a clusters' existence probability between two fixed moments of time. In support of the theoretically obtained probabilistic distributions, the results of numerical simulations are provided.

Allele frequency dynamics in a pedigreed natural population

A central goal of population genetics is to understand how genetic drift, natural selection, and gene flow shape allele frequencies through time. However, the actual processes underlying these changes-variation in individual survival, reproductive success, and movement-are often difficult to quantify. Fully understanding these processes requires the population pedigree, the set of relationships among all individuals in the population through time. Here, we use extensive pedigree and genomic information from a long-studied natural population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of different evolutionary processes in shaping patterns of genetic variation through time. We performed gene dropping simulations to estimate individual genetic contributions to the population and model drift on the known pedigree. We found that observed allele frequency changes are generally well predicted by accounting for the different genetic contributions of founders. Our results show that the genetic contribution of recent immigrants is substantial, with some large allele frequency shifts that otherwise may have been attributed to selection actually due to gene flow. We identified a few SNPs under directional short-term selection after appropriately accounting for gene flow. Using models that account for changes in population size, we partitioned the proportion of variance in allele frequency change through time. Observed allele frequency changes are primarily due to variation in survival and reproductive success, with gene flow making a smaller contribution. This study provides one of the most complete descriptions of short-term evolutionary change in allele frequencies in a natural population to date.

TETyper: a bioinformatic pipeline for classifying variation and genetic contexts of transposable elements from short-read whole-genome sequencing data.

Much of the worldwide dissemination of antibiotic resistance has been driven by resistance gene associations with mobile genetic elements (MGEs), such as plasmids and transposons. Although increasing, our understanding of resistance spread remains relatively limited, as methods for tracking mobile resistance genes through multiple species, strains and plasmids are lacking. We have developed a bioinformatic pipeline for tracking variation within, and mobility of, specific transposable elements (TEs), such as transposons carrying antibiotic-resistance genes. TETyper takes short-read whole-genome sequencing data as input and identifies single-nucleotide mutations and deletions within the TE of interest, to enable tracking of specific sequence variants, as well as the surrounding genetic context(s), to enable identification of transposition events. A major advantage of TETyper over previous methods is that it does not require a genome reference. To investigate global dissemination of Klebsiella pneumoniae carbapenemase (KPC) and its associated transposon Tn4401, we applied TETyper to a collection of over 3000 publicly available Illumina datasets containing blaKPC. This revealed surprising diversity, with over 200 distinct flanking genetic contexts for Tn4401, indicating high levels of transposition. Integration of sample metadata revealed insights into associations between geographic locations, host species, Tn4401 sequence variants and flanking genetic contexts. To demonstrate the ability of TETyper to cope with high-copy-number TEs and to track specific short-term evolutionary changes, we also applied it to the insertion sequence IS26 within a defined K. pneumoniae outbreak. TETyper is implemented in python and is freely available at https://github.com/aesheppard/TETyper.

Mapping of Hieracium (Asteraceae) chromosomes with genus-specific satDNA elements derived from next-generation sequencing data

The highly repetitive DNA fraction of the eukaryotic genome is considered a mobile, rapidly changing entity, thus reflecting trajectories of short-term evolutionary change. It consists of several large classes in which transposable elements and satellite DNA (satDNA) predominate. Despite a growing awareness of its structure and functional significance, the evolutionary dynamics of repetitive elements and, particularly, satDNA remain poorly characterized. Next-generation sequencing (NGS) has opened up new possibilities for high-throughput genome analysis. Here, we applied satDNA repeatome elements derived from NGS data as probes for fluorescence in situ hybridization to characterize the karyotypes of three diploid hawkweed species of the predominantly polyploid apomictic genus Hieracium, namely H. intybaceum, H. prenanthoides and H. alpinum. Three cluster-distributed, genus-specific satDNA elements that are not present in the sister genus Pilosella were identified; notably, one element spans the functional centromeres. Each of the investigated diploids possessed a species-specific assortment of detected repeats. Their utilization as molecular-cytogenetic markers, in combination with ribosomal DNA loci, allowed for the development of a system to identify the individual chromosomes of the Hieracium species, thus providing a basis for the future investigation of karyotype evolution in diploid hawkweeds and for exploring satDNA dynamics in hybrids and apomicts of allopolyploid origin.

Human-aided admixture may fuel ecosystem transformation during biological invasions: theoretical and experimental evidence.

Biological invasions can transform our understanding of how the interplay of historical isolation and contemporary (human-aided) dispersal affects the structure of intraspecific diversity in functional traits, and in turn, how changes in functional traits affect other scales of biological organization such as communities and ecosystems. Because biological invasions frequently involve the admixture of previously isolated lineages as a result of human-aided dispersal, studies of invasive populations can reveal how admixture results in novel genotypes and shifts in functional trait variation within populations. Further, because invasive species can be ecosystem engineers within invaded ecosystems, admixture-induced shifts in the functional traits of invaders can affect the composition of native biodiversity and alter the flow of resources through the system. Thus, invasions represent promising yet under-investigated examples of how the effects of short-term evolutionary changes can cascade across biological scales of diversity. Here, we propose a conceptual framework that admixture between divergent source populations during biological invasions can reorganize the genetic variation underlying key functional traits, leading to shifts in the mean and variance of functional traits within invasive populations. Changes in the mean or variance of key traits can initiate new ecological feedback mechanisms that result in a critical transition from a native ecosystem to a novel invasive ecosystem. We illustrate the application of this framework with reference to a well-studied plant model system in invasion biology and show how a combination of quantitative genetic experiments, functional trait studies, whole ecosystem field studies and modeling can be used to explore the dynamics predicted to trigger these critical transitions.

Hamilton's rule in multi-level selection models

Hamilton's rule is regarded as a useful tool in the understanding of social evolution, but it relies on restrictive, overly simple assumptions. Here we model more realistic situations, in which the traditional Hamilton's rule generally fails to predict the direction of selection. We offer modifications that allow accurate predictions, but also show that these Hamilton's rule type inequalities do not predict long-term outcomes. To illustrate these issues we propose a two-level selection model for the evolution of cooperation. The model describes the dynamics of a population of groups of cooperators and defectors of various sizes and compositions and contains birth–death processes at both the individual level and the group level. We derive Hamilton-like inequalities that accurately predict short-term evolutionary change, but do not reliably predict long-term evolutionary dynamics. Over evolutionary time, cooperators and defectors can repeatedly change roles as the favored type, because the amount of assortment between cooperators changes in complicated ways due to both individual-level and group-level processes. The equation that governs the dynamics of cooperator/defector assortment is a certain partial differential equation, which can be solved numerically, but whose behaviour cannot be predicted by Hamilton's rules, because Hamilton's rules only contain first-derivative information. In addition, Hamilton's rules are sensitive to demographic fitness effects such as local crowding, and hence models that assume constant group sizes are not equivalent to models like ours that relax that assumption. In the long-run, the group distribution typically reaches an equilibrium, in which case Hamilton's rules necessarily become equalities.

Differences in the selection response of serially repeated color pattern characters: Standing variation, development, and evolution

BackgroundThere is spectacular morphological diversity in nature but lineages typically display a limited range of phenotypes. Because developmental processes generate the phenotypic variation that fuels natural selection, they are a likely source of evolutionary biases, facilitating some changes and limiting others. Although shifts in developmental regulation are associated with morphological differences between taxa, it is unclear how underlying mechanisms affect the rate and direction of evolutionary change within populations under selection.Here we focus on two ecologically relevant features of butterfly wing color patterns, eyespot size and color composition, which are similarly and strongly correlated across the serially repeated eyespots. Though these two characters show similar patterns of standing variation and covariation within a population, they differ in key features of their underlying development. We targeted pairs of eyespots with artificial selection for coordinated (concerted selection) versus independent (antagonistic selection) change in their color composition and size and compared evolutionary responses of the two color pattern characters.ResultsThe two characters respond to selection in strikingly different ways despite initially similar patterns of variation in all directions present in the starting population. Size (determined by local properties of a diffusing inductive signal) evolves flexibly in all selected directions. However, color composition (determined by a tissue-level response to the signal concentration gradient) evolves only in the direction of coordinated change. There was no independent evolutionary change in the color composition of two eyespots in response to antagonistic selection. Moreover, these differences in the directions of short-term evolutionary change in eyespot size and color composition within a single species are consistent with the observed wing pattern diversity in the genus.ConclusionBoth characters respond rapidly to selection for coordinated change, but there are striking differences in their response to selection for antagonistic, independent change across eyespots. While many additional factors may contribute to both short- and long-term evolutionary response, we argue that the compartmentalization of developmental processes can influence the diversification of serial repeats such as butterfly eyespots, even under strong selection.

The evolutionary genetics of egg size plasticity in a butterfly

Abstract The evolution of phenotypic plasticity requires that it is adaptive, genetically determined, and exhibits sufficient genetic variation. For the tropical butterfly Bicyclus anynana there is evidence that temperature-mediated plasticity in egg size is an adaptation to predictable seasonal change. Here we set out to investigate heritability in egg size and genetic variation in the plastic response to temperature in this species, using a half-sib breeding design. Egg size of individual females was first measured at a high temperature 4 days after eclosion. Females were then transferred to a low temperature and egg size was measured after acclimation periods of 6 and 12 days respectively. Overall, additive genetic variance explained only 3-11% of the total phenotypic variance, whereas maternal effects were more pronounced. Genotype-environment interactions and cross-environmental correlations of less than unity suggest that there is potential for short-term evolutionary change. Our findings strengthen the support for the adaptive nature of temperature-mediated plasticity in egg size.

Population Thinking, Price’s Equation and the Analysis of Economic Evolution

In this paper it is argued that evolutionary economics needs general statistical tools for performing the analysis of the aggregate effects of evolution in terms of the underlying population dynamics. These tools have been developed within biometrics, and they have recently become directly applicable to economic evolution due to the development of what may be called a general evometrics. Central to this evometrics is a method for partitioning evolutionary change developed by George Price into the selection effect and what may be called the innovation effect. This method serves surprisingly well as a means of accounting for evolution and as a starting point for the explanation of evolution. The applications of Price’s equation cover the partitioning and analysis of relatively short-term evolutionary change within individual industries as well as the study of more complexly structured populations of firms. By extrapolating these applications of Price’s evometrics, the paper suggests that his approach may play a central role in the emerging evolutionary econometrics.

Variability in the 28-kDa Surface Antigen Protein Multigene Locus of Isolates of the Emerging Disease Agent Ehrlichia chaffeensis Suggests That It Plays a Role in Immune Evasion

Infections caused by rickettsial pathogens persist in vertebrate hosts for long periods of time, despite the active host immune response. We recently described the multigene locus encoding 28 kDa surface antigen proteins (28 kDa SAPs) for two closely related rickettsials, Ehrlichia chaffeensis and Ehrlichia canis (Reddy, G. R., et al. (1998) Biochem. Biophys. Res. Commun. 247, 636–643), that share extensive structural homology to antigenic variant surface protein genes of Neisseria and Borrelia species. In this study, we describe motifs for recombinase binding sites and a high frequency of repeat elements in the cloned 28 kDa SAP genes. The locus for two newly established E. chaffeensis isolates also was characterized, and immunological specificity of the 28 kDa SAPs was investigated. The study identified variant forms of the 28 kDa SAPs and extensive restriction fragment length polymorphisms among isolates. The molecular data suggest that the locus is influenced by short-term evolutionary changes such as genetic recombinations leading to the generation of antigenic variants. Antigenic variation could contribute to the mechanism of immune evasion and the emergence of new diseases.

The enigma of frequency-dependent selection

Frequency-dependent selection is so fundamental to modern evolutionary thinking that everyone `knows' the concept. Yet the term is used to refer to different types of selection. The concept is well defined in the original context of population genetics theory, which focuses on short-term evolutionary change. The original concept becomes ambiguous, however, when used in the context of long-term evolution, where density dependence becomes essential. Weak and strong frequency dependence, as distinguished in this article, refer to two very different forms of selection.

SHORT-TERM EVOLUTION IN THE SIZE AND SHAPE OF PEA APHIDS.

Phenotypic evolution in contemporary populations can generally be witnessed only when novel selective forces produce rapid evolution. Examples of conditions that have led to rapid evolution include drastic environmental change, invasion of a new predator, or a host-range expansion. In cyclical parthenogens, however, yearly cycles of phenotypic evolution may occur due to the loss of adaptation during recombination in the sexual phase (genetic slippage), permitting an opportunity to observe adaptive evolutionary change in contemporary populations that are not necessarily subject to new patterns of natural selection. In insect herbivores, comparative studies suggest that morphological features that aid individuals in remaining on the plant or exploiting it as a food source are likely targets for selection. Here, we estimated the genetic variability of morphological traits in a cyclical parthenogen, the pea aphid (Acyrthosiphon pisum), to determine the potential for their evolution and we tested the hypothesis that size and/or shape evolves by clonal selection during one season of parthenogenetic reproduction. Genetic variation in a set of morphological traits was estimated using laboratory-reared descendents of clones collected from a single alfalfa field in May 1988 and April 1989 (henceforth, the "early" collections). In both years, there was significant clonal heritability early in the season both for overall morphology and for several individual aspects of size and shape. Because the course of short-term evolutionary change in the multivariate phenotype is a function of patterns of genetic covariance among characters, genetic correlations between size and 12 shape variables were also estimated for these early collections. A comparison between the mean phenotype of each early collection and that of a corresponding "late" collection made from the same field seven to eight clonal generations later in the same years revealed qualitatively similar changes in the average multivariate morphological phenotypes between the time periods in both years, although the difference was only significant for the 1989 samples. The pattern of genetic correlations that we estimated early in the 1989 season between overall size and various shape variables suggests that the observed short-term evolutionary changes in shape could have been due to natural selection acting only to increase overall size. We tested this hypothesis by estimating selection on size using a separate data set in which both demographic and morphological variables were measured on individuals reared under field conditions. Highly significant regressions of individual relative fitness on size were found for two major fitness components. Thus, it is likely that the evolutionary change in morphology that we observed is attributable to natural selection, possibly acting primarily through body size. A shift back to smaller size between the late 1988 and early 1989 collections from the same field suggests that either a cost of recombination or opposing selective forces during overwintering may produce persistent yearly cycles of morphological evolution in this cyclically parthenogenetic species.

Rapid evolution of the visual system: a cellular assay of the retina and dorsal lateral geniculate nucleus of the Spanish wildcat and the domestic cat

The large Spanish wildcat, Felis silvestris tartessia, has retained features of the Pleistocene ancestor of the modern domestic cat, F. catus. To gauge the direction and magnitude of short-term evolutionary change in this lineage, we have compared the retina, the optic nerve, and the dorsal lateral geniculate nucleus (LGN) of Spanish wildcats and their domestic relatives. Retinas of the two species have the same area. However, densities of cone photoreceptors are higher in wildcat--over 100% higher in the area centralis--whereas rod densities are as high, or higher, in the domestic lineage. Densities of retinal ganglion cells are typically 20-100% higher across the wildcat retina, and the total ganglion cell population is nearly 70% higher than in the domestic cat. These differences are confined to the populations of beta and gamma retinal ganglion cells. In contrast, the population of alpha cells is almost precisely the same in both species. The wildcat LGN is much larger than that of the domestic cat and contains approximately 50% more neurons. However, cell size does not differ appreciably in either the retina or LGN of these species. The differences in total numbers of ganglion cells and LGN neurons correspond neatly to the overall decline in brain size in the domestic lineage and to allometric predictions based on average species differences in body size. We suggest that an increase in the severity of naturally occurring cell death is the most plausible mechanism that can account for the rapid evolutionary reduction in cell populations in this feline lineage.