@article{1909, abstract = {Summary: Phenotypes are often environmentally dependent, which requires organisms to track environmental change. The challenge for organisms is to construct phenotypes using the most accurate environmental cue. Here, we use a quantitative genetic model of adaptation by additive genetic variance, within- and transgenerational plasticity via linear reaction norms and indirect genetic effects respectively. We show how the relative influence on the eventual phenotype of these components depends on the predictability of environmental change (fast or slow, sinusoidal or stochastic) and the developmental lag τ between when the environment is perceived and when selection acts. We then decompose expected mean fitness into three components (variance load, adaptation and fluctuation load) to study the fitness costs of within- and transgenerational plasticity. A strongly negative maternal effect coefficient m minimizes the variance load, but a strongly positive m minimises the fluctuation load. The adaptation term is maximized closer to zero, with positive or negative m preferred under different environmental scenarios. Phenotypic plasticity is higher when τ is shorter and when the environment changes frequently between seasonal extremes. Expected mean population fitness is highest away from highest observed levels of phenotypic plasticity. Within- and transgenerational plasticity act in concert to deliver well-adapted phenotypes, which emphasizes the need to study both simultaneously when investigating phenotypic evolution.}, author = {Ezard, Thomas and Prizak, Roshan and Hoyle, Rebecca}, journal = {Functional Ecology}, number = {3}, pages = {693 -- 701}, publisher = {Wiley-Blackwell}, title = {{The fitness costs of adaptation via phenotypic plasticity and maternal effects}}, doi = {10.1111/1365-2435.12207}, volume = {28}, year = {2014}, } @article{1932, abstract = {The existence of complex (multiple-step) genetic adaptations that are "irreducible" (i.e., all partial combinations are less fit than the original genotype) is one of the longest standing problems in evolutionary biology. In standard genetics parlance, these adaptations require the crossing of a wide adaptive valley of deleterious intermediate stages. Here, we demonstrate, using a simple model, that evolution can cross wide valleys to produce "irreducibly complex" adaptations by making use of previously cryptic mutations. When revealed by an evolutionary capacitor, previously cryptic mutants have higher initial frequencies than do new mutations, bringing them closer to a valley-crossing saddle in allele frequency space. Moreover, simple combinatorics implies an enormous number of candidate combinations exist within available cryptic genetic variation. We model the dynamics of crossing of a wide adaptive valley after a capacitance event using both numerical simulations and analytical approximations. Although individual valley crossing events become less likely as valleys widen, by taking the combinatorics of genotype space into account, we see that revealing cryptic variation can cause the frequent evolution of complex adaptations.}, author = {Trotter, Meredith and Weissman, Daniel and Peterson, Grant and Peck, Kayla and Masel, Joanna}, journal = {Evolution}, number = {12}, pages = {3357 -- 3367}, publisher = {Wiley-Blackwell}, title = {{Cryptic genetic variation can make "irreducible complexity" a common mode of adaptation in sexual populations}}, doi = {10.1111/evo.12517}, volume = {68}, year = {2014}, } @article{1936, abstract = {The social intelligence hypothesis states that the need to cope with complexities of social life has driven the evolution of advanced cognitive abilities. It is usually invoked in the context of challenges arising from complex intragroup structures, hierarchies, and alliances. However, a fundamental aspect of group living remains largely unexplored as a driving force in cognitive evolution: the competition between individuals searching for resources (producers) and conspecifics that parasitize their findings (scroungers). In populations of social foragers, abilities that enable scroungers to steal by outsmarting producers, and those allowing producers to prevent theft by outsmarting scroungers, are likely to be beneficial and may fuel a cognitive arms race. Using analytical theory and agent-based simulations, we present a general model for such a race that is driven by the producer-scrounger game and show that the race's plausibility is dramatically affected by the nature of the evolving abilities. If scrounging and scrounging avoidance rely on separate, strategy-specific cognitive abilities, arms races are short-lived and have a limited effect on cognition. However, general cognitive abilities that facilitate both scrounging and scrounging avoidance undergo stable, long-lasting arms races. Thus, ubiquitous foraging interactions may lead to the evolution of general cognitive abilities in social animals, without the requirement of complex intragroup structures.}, author = {Arbilly, Michal and Weissman, Daniel and Feldman, Marcus and Grodzinski, Uri}, journal = {Behavioral Ecology}, number = {3}, pages = {487 -- 495}, publisher = {Oxford University Press}, title = {{An arms race between producers and scroungers can drive the evolution of social cognition}}, doi = {10.1093/beheco/aru002}, volume = {25}, year = {2014}, } @article{2168, abstract = {Many species have an essentially continuous distribution in space, in which there are no natural divisions between randomly mating subpopulations. Yet, the standard approach to modelling these populations is to impose an arbitrary grid of demes, adjusting deme sizes and migration rates in an attempt to capture the important features of the population. Such indirect methods are required because of the failure of the classical models of isolation by distance, which have been shown to have major technical flaws. A recently introduced model of extinction and recolonisation in two dimensions solves these technical problems, and provides a rigorous technical foundation for the study of populations evolving in a spatial continuum. The coalescent process for this model is simply stated, but direct simulation is very inefficient for large neighbourhood sizes. We present efficient and exact algorithms to simulate this coalescent process for arbitrary sample sizes and numbers of loci, and analyse these algorithms in detail.}, author = {Kelleher, Jerome and Etheridge, Alison and Barton, Nicholas H}, journal = {Theoretical Population Biology}, pages = {13 -- 23}, publisher = {Academic Press}, title = {{Coalescent simulation in continuous space: Algorithms for large neighbourhood size}}, doi = {10.1016/j.tpb.2014.05.001}, volume = {95}, year = {2014}, } @article{2169, author = {Barton, Nicholas H and Novak, Sebastian and Paixao, Tiago}, journal = {PNAS}, number = {29}, pages = {10398 -- 10399}, publisher = {National Academy of Sciences}, title = {{Diverse forms of selection in evolution and computer science}}, doi = {10.1073/pnas.1410107111}, volume = {111}, year = {2014}, } @article{2170, abstract = { Short-read sequencing technologies have in principle made it feasible to draw detailed inferences about the recent history of any organism. In practice, however, this remains challenging due to the difficulty of genome assembly in most organisms and the lack of statistical methods powerful enough to discriminate between recent, nonequilibrium histories. We address both the assembly and inference challenges. We develop a bioinformatic pipeline for generating outgroup-rooted alignments of orthologous sequence blocks from de novo low-coverage short-read data for a small number of genomes, and show how such sequence blocks can be used to fit explicit models of population divergence and admixture in a likelihood framework. To illustrate our approach, we reconstruct the Pleistocene history of an oak-feeding insect (the oak gallwasp Biorhiza pallida), which, in common with many other taxa, was restricted during Pleistocene ice ages to a longitudinal series of southern refugia spanning the Western Palaearctic. Our analysis of sequence blocks sampled from a single genome from each of three major glacial refugia reveals support for an unexpected history dominated by recent admixture. Despite the fact that 80% of the genome is affected by admixture during the last glacial cycle, we are able to infer the deeper divergence history of these populations. These inferences are robust to variation in block length, mutation model and the sampling location of individual genomes within refugia. This combination of de novo assembly and numerical likelihood calculation provides a powerful framework for estimating recent population history that can be applied to any organism without the need for prior genetic resources.}, author = {Hearn, Jack and Stone, Graham and Bunnefeld, Lynsey and Nicholls, James and Barton, Nicholas H and Lohse, Konrad}, journal = {Molecular Ecology}, number = {1}, pages = {198 -- 211}, publisher = {Wiley-Blackwell}, title = {{Likelihood-based inference of population history from low-coverage de novo genome assemblies}}, doi = {10.1111/mec.12578}, volume = {23}, year = {2014}, } @article{2174, abstract = {When polygenic traits are under stabilizing selection, many different combinations of alleles allow close adaptation to the optimum. If alleles have equal effects, all combinations that result in the same deviation from the optimum are equivalent. Furthermore, the genetic variance that is maintained by mutation-selection balance is 2μ/S per locus, where μ is the mutation rate and S the strength of stabilizing selection. In reality, alleles vary in their effects, making the fitness landscape asymmetric and complicating analysis of the equilibria. We show that that the resulting genetic variance depends on the fraction of alleles near fixation, which contribute by 2μ/S, and on the total mutational effects of alleles that are at intermediate frequency. The inpplayfi between stabilizing selection and mutation leads to a sharp transition: alleles with effects smaller than a threshold value of 2 remain polymorphic, whereas those with larger effects are fixed. The genetic load in equilibrium is less than for traits of equal effects, and the fitness equilibria are more similar. We find p the optimum is displaced, alleles with effects close to the threshold value sweep first, and their rate of increase is bounded by Long-term response leads in general to well-adapted traits, unlike the case of equal effects that often end up at a suboptimal fitness peak. However, the particular peaks to which the populations converge are extremely sensitive to the initial states and to the speed of the shift of the optimum trait value.}, author = {De Vladar, Harold and Barton, Nicholas H}, journal = {Genetics}, number = {2}, pages = {749 -- 767}, publisher = {Genetics Society of America}, title = {{Stability and response of polygenic traits to stabilizing selection and mutation}}, doi = {10.1534/genetics.113.159111}, volume = {197}, year = {2014}, } @article{2252, abstract = {The pattern of inheritance and mechanism of sex determination can have important evolutionary consequences. We studied probabilistic sex determination in the ciliate Tetrahymena thermophila, which was previously shown to cause evolution of skewed sex ratios. We find that the genetic background alters the sex determination patterns of mat alleles in heterozygotes and that allelic interaction can differentially influence the expression probability of the 7 sexes. We quantify the dominance relationships between several mat alleles and find that A-type alleles, which specify sex I, are indeed recessive to B-type alleles, which are unable to specify that sex. Our results provide additional support for the presence of modifier loci and raise implications for the dynamics of sex ratios in populations of T. thermophila.}, author = {Phadke, Sujal and Paixao, Tiago and Pham, Tuan and Pham, Stephanie and Zufall, Rebecca}, issn = {0022-1503}, journal = {Journal of Heredity}, number = {1}, pages = {130 -- 135}, publisher = {Oxford University Press}, title = {{Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila}}, doi = {10.1093/jhered/est063}, volume = {105}, year = {2014}, } @article{537, abstract = {Transgenerational effects are broader than only parental relationships. Despite mounting evidence that multigenerational effects alter phenotypic and life-history traits, our understanding of how they combine to determine fitness is not well developed because of the added complexity necessary to study them. Here, we derive a quantitative genetic model of adaptation to an extraordinary new environment by an additive genetic component, phenotypic plasticity, maternal and grandmaternal effects. We show how, at equilibrium, negative maternal and negative grandmaternal effects maximize expected population mean fitness. We define negative transgenerational effects as those that have a negative effect on trait expression in the subsequent generation, that is, they slow, or potentially reverse, the expected evolutionary dynamic. When maternal effects are positive, negative grandmaternal effects are preferred. As expected under Mendelian inheritance, the grandmaternal effects have a lower impact on fitness than the maternal effects, but this dual inheritance model predicts a more complex relationship between maternal and grandmaternal effects to constrain phenotypic variance and so maximize expected population mean fitness in the offspring.}, author = {Prizak, Roshan and Ezard, Thomas and Hoyle, Rebecca}, journal = {Ecology and Evolution}, number = {15}, pages = {3139 -- 3145}, publisher = {Wiley-Blackwell}, title = {{Fitness consequences of maternal and grandmaternal effects}}, doi = {10.1002/ece3.1150}, volume = {4}, year = {2014}, } @article{2023, abstract = {Understanding the evolution of dispersal is essential for understanding and predicting the dynamics of natural populations. Two main factors are known to influence dispersal evolution: spatio-temporal variation in the environment and relatedness between individuals. However, the relation between these factors is still poorly understood, and they are usually treated separately. In this article, I present a theoretical framework that contains and connects effects of both environmental variation and relatedness, and reproduces and extends their known features. Spatial habitat variation selects for balanced dispersal strategies, whereby the population is kept at an ideal free distribution. Within this class of dispersal strategies, I explain how increased dispersal is promoted by perturbations to the dispersal type frequencies. An explicit formula shows the magnitude of the selective advantage of increased dispersal in terms of the spatial variability in the frequencies of the different dispersal strategies present. These variances are capable of capturing various sources of stochasticity and hence establish a common scale for their effects on the evolution of dispersal. The results furthermore indicate an alternative approach to identifying effects of relatedness on dispersal evolution.}, author = {Novak, Sebastian}, journal = {Ecology and Evolution}, number = {24}, pages = {4589 -- 4597}, publisher = {Wiley-Blackwell}, title = {{Habitat heterogeneities versus spatial type frequency variances as driving forces of dispersal evolution}}, doi = {10.1002/ece3.1289}, volume = {4}, year = {2014}, } @inproceedings{2718, abstract = {Even though both population and quantitative genetics, and evolutionary computation, deal with the same questions, they have developed largely independently of each other. I review key results from each field, emphasising those that apply independently of the (usually unknown) relation between genotype and phenotype. The infinitesimal model provides a simple framework for predicting the response of complex traits to selection, which in biology has proved remarkably successful. This allows one to choose the schedule of population sizes and selection intensities that will maximise the response to selection, given that the total number of individuals realised, C = ∑t Nt, is constrained. This argument shows that for an additive trait (i.e., determined by the sum of effects of the genes), the optimum population size and the maximum possible response (i.e., the total change in trait mean) are both proportional to √C.}, author = {Barton, Nicholas H and Paixao, Tiago}, booktitle = {Proceedings of the 15th annual conference on Genetic and evolutionary computation}, location = {Amsterdam, Netherlands}, pages = {1573 -- 1580}, publisher = {ACM}, title = {{Can quantitative and population genetics help us understand evolutionary computation?}}, doi = {10.1145/2463372.2463568}, year = {2013}, } @inproceedings{2719, abstract = {Prediction of the evolutionary process is a long standing problem both in the theory of evolutionary biology and evolutionary computation (EC). It has long been realized that heritable variation is crucial to both the response to selection and the success of genetic algorithms. However, not all variation contributes in the same way to the response. Quantitative genetics has developed a large body of work trying to estimate and understand how different components of the variance in fitness in the population contribute to the response to selection. We illustrate how to apply some concepts of quantitative genetics to the analysis of genetic algorithms. In particular, we derive estimates for the short term prediction of the response to selection and we use variance decomposition to gain insight on local aspects of the landscape. Finally, we propose a new population based genetic algorithm that uses these methods to improve its operation.}, author = {Paixao, Tiago and Barton, Nicholas H}, booktitle = {Proceedings of the 15th annual conference on Genetic and evolutionary computation}, location = {Amsterdam, Netherlands}, pages = {845 -- 852}, publisher = {ACM}, title = {{A variance decomposition approach to the analysis of genetic algorithms}}, doi = {10.1145/2463372.2463470}, year = {2013}, } @article{2720, abstract = {Knowledge of the rate and fitness effects of mutations is essential for understanding the process of evolution. Mutations are inherently difficult to study because they are rare and are frequently eliminated by natural selection. In the ciliate Tetrahymena thermophila, mutations can accumulate in the germline genome without being exposed to selection. We have conducted a mutation accumulation (MA) experiment in this species. Assuming that all mutations are deleterious and have the same effect, we estimate that the deleterious mutation rate per haploid germline genome per generation is U = 0.0047 (95% credible interval: 0.0015, 0.0125), and that germline mutations decrease fitness by s = 11% when expressed in a homozygous state (95% CI: 4.4%, 27%). We also estimate that deleterious mutations are partially recessive on average (h = 0.26; 95% CI: –0.022, 0.62) and that the rate of lethal mutations is <10% of the deleterious mutation rate. Comparisons between the observed evolutionary responses in the germline and somatic genomes and the results from individual-based simulations of MA suggest that the two genomes have similar mutational parameters. These are the first estimates of the deleterious mutation rate and fitness effects from the eukaryotic supergroup Chromalveolata and are within the range of those of other eukaryotes.}, author = {Long, Hongan and Paixao, Tiago and Azevedo, Ricardo and Zufall, Rebecca}, journal = {Genetics}, number = {2}, pages = {527--540}, publisher = {Genetics Society of America}, title = {{Accumulation of spontaneous mutations in the ciliate Tetrahymena thermophila}}, doi = {10.1534/genetics.113.153536}, volume = {195}, year = {2013}, } @article{2817, abstract = {The basic idea of evolutionary game theory is that payoff determines reproductive rate. Successful individuals have a higher payoff and produce more offspring. But in evolutionary and ecological situations there is not only reproductive rate but also carrying capacity. Individuals may differ in their exposure to density limiting effects. Here we explore an alternative approach to evolutionary game theory by assuming that the payoff from the game determines the carrying capacity of individual phenotypes. Successful strategies are less affected by density limitation (crowding) and reach higher equilibrium abundance. We demonstrate similarities and differences between our framework and the standard replicator equation. Our equation is defined on the positive orthant, instead of the simplex, but has the same equilibrium points as the replicator equation. Linear stability analysis produces the classical conditions for asymptotic stability of pure strategies, but the stability properties of internal equilibria can differ in the two frameworks. For example, in a two-strategy game with an internal equilibrium that is always stable under the replicator equation, the corresponding equilibrium can be unstable in the new framework resulting in a limit cycle.}, author = {Novak, Sebastian and Chatterjee, Krishnendu and Nowak, Martin}, journal = {Journal of Theoretical Biology}, pages = {26 -- 34}, publisher = {Elsevier}, title = {{Density games}}, doi = {10.1016/j.jtbi.2013.05.029}, volume = {334}, year = {2013}, } @article{2823, abstract = {The primary goal of restoration is to create self-sustaining ecological communities that are resilient to periodic disturbance. Currently, little is known about how restored communities respond to disturbance events such as fire and how this response compares to remnant vegetation. Following the 2003 fires in south-eastern Australia we examined the post-fire response of revegetation plantings and compared this to remnant vegetation. Ten burnt and 10 unburnt (control) sites were assessed for each of three types of vegetation (direct seeding revegetation, revegetation using nursery seedlings (tubestock) and remnant woodland). Sixty sampling sites were surveyed 6months after fire to quantify the initial survival of mid- and overstorey plant species in each type of vegetation. Three and 5years after fire all sites were resurveyed to assess vegetation structure, species diversity and vigour, as well as indicators of soil function. Overall, revegetation showed high (>60%) post-fire survival, but this varied among species depending on regeneration strategy (obligate seeder or resprouter). The native ground cover, mid- and overstorey in both types of plantings showed rapid recovery of vegetation structure and cover within 3years of fire. This recovery was similar to the burnt remnant woodlands. Non-native (exotic) ground cover initially increased after fire, but was no different in burnt and unburnt sites 5years after fire. Fire had no effect on species richness, but burnt direct seeding sites had reduced species diversity (Simpson's Diversity Index) while diversity was higher in burnt remnant woodlands. Indices of soil function in all types of vegetation had recovered to levels found in unburnt sites 5years after fire. These results indicate that even young revegetation (stands <10years old) showed substantial recovery from disturbance by fire. This suggests that revegetation can provide an important basis for restoring woodland communities in the fire-prone Australian environment.}, author = {Pickup, Melinda and Wilson, Susie and Freudenberger, David and Nicholls, Nick and Gould, Lori and Hnatiuk, Sarah and Delandre, Jeni}, journal = {Austral Ecology}, number = {3}, pages = {300 -- 312}, publisher = {Wiley-Blackwell}, title = {{Post-fire recovery of revegetated woodland communities in south-eastern Australia}}, doi = {10.1111/j.1442-9993.2012.02404.x}, volume = {38}, year = {2013}, } @article{2842, abstract = {We outline two approaches to inference of neighbourhood size, N, and dispersal rate, σ2, based on either allele frequencies or on the lengths of sequence blocks that are shared between genomes. Over intermediate timescales (10-100 generations, say), populations that live in two dimensions approach a quasi-equilibrium that is independent of both their local structure and their deeper history. Over such scales, the standardised covariance of allele frequencies (i.e. pairwise FS T) falls with the logarithm of distance, and depends only on neighbourhood size, N, and a 'local scale', κ; the rate of gene flow, σ2, cannot be inferred. We show how spatial correlations can be accounted for, assuming a Gaussian distribution of allele frequencies, giving maximum likelihood estimates of N and κ. Alternatively, inferences can be based on the distribution of the lengths of sequence that are identical between blocks of genomes: long blocks (>0.1 cM, say) tell us about intermediate timescales, over which we assume a quasi-equilibrium. For large neighbourhood size, the distribution of long blocks is given directly by the classical Wright-Malécot formula; this relationship can be used to infer both N and σ2. With small neighbourhood size, there is an appreciable chance that recombinant lineages will coalesce back before escaping into the distant past. For this case, we show that if genomes are sampled from some distance apart, then the distribution of lengths of blocks that are identical in state is geometric, with a mean that depends on N and σ2.}, author = {Barton, Nicholas H and Etheridge, Alison and Kelleher, Jerome and Véber, Amandine}, journal = {Theoretical Population Biology}, number = {1}, pages = {105 -- 119}, publisher = {Elsevier}, title = {{Inference in two dimensions: Allele frequencies versus lengths of shared sequence blocks}}, doi = {10.1016/j.tpb.2013.03.001}, volume = {87}, year = {2013}, } @inbook{2907, abstract = {Sex and recombination are among the most striking features of the living world, and they play a crucial role in allowing the evolution of complex adaptation. The sharing of genomes through the sexual union of different individuals requires elaborate behavioral and physiological adaptations. At the molecular level, the alignment of two DNA double helices, followed by their precise cutting and rejoining, is an extraordinary feat. Sex and recombination have diverse—and often surprising—evolutionary consequences: distinct sexes, elaborate mating displays, selfish genetic elements, and so on.}, author = {Barton, Nicholas H}, booktitle = {The Princeton Guide to Evolution}, isbn = {9780691149776}, pages = {328 -- 333}, publisher = {Princeton University Press}, title = {{Recombination and sex}}, year = {2013}, } @article{2908, abstract = {Hybridization is an almost inevitable component of speciation, and its study can tell us much about that process. However, hybridization itself may have a negligible influence on the origin of species: on the one hand, universally favoured alleles spread readily across hybrid zones, whilst on the other, spatially heterogeneous selection causes divergence despite gene flow. Thus, narrow hybrid zones or occasional hybridisation may hardly affect the process of divergence.}, author = {Barton, Nicholas H}, journal = {Journal of Evolutionary Biology}, number = {2}, pages = {267 -- 269}, publisher = {Wiley-Blackwell}, title = {{Does hybridisation influence speciation? }}, doi = {10.1111/jeb.12015}, volume = {26}, year = {2013}, } @article{2909, abstract = {We survey a class of models for spatially structured populations which we have called spatial Λ-Fleming–Viot processes. They arise from a flexible framework for modelling in which the key innovation is that random genetic drift is driven by a Poisson point process of spatial ‘events’. We demonstrate how this overcomes some of the obstructions to modelling populations which evolve in two- (and higher-) dimensional spatial continua, how its predictions match phenomena observed in data and how it fits with classical models. Finally we outline some directions for future research.}, author = {Barton, Nicholas H and Etheridge, Alison and Véber, Amandine}, journal = {Journal of Statistical Mechanics Theory and Experiment}, number = {1}, publisher = {IOP Publishing}, title = {{Modelling evolution in a spatial continuum}}, doi = {10.1088/1742-5468/2013/01/P01002}, volume = {2013}, year = {2013}, } @article{2910, abstract = {Coalescent simulation has become an indispensable tool in population genetics and many complex evolutionary scenarios have been incorporated into the basic algorithm. Despite many years of intense interest in spatial structure, however, there are no available methods to simulate the ancestry of a sample of genes that occupy a spatial continuum. This is mainly due to the severe technical problems encountered by the classical model of isolation by distance. A recently introduced model solves these technical problems and provides a solid theoretical basis for the study of populations evolving in continuous space. We present a detailed algorithm to simulate the coalescent process in this model, and provide an efficient implementation of a generalised version of this algorithm as a freely available Python module.}, author = {Kelleher, Jerome and Barton, Nicholas H and Etheridge, Alison}, journal = {Bioinformatics}, number = {7}, pages = {955 -- 956}, publisher = {Oxford University Press}, title = {{Coalescent simulation in continuous space}}, doi = {10.1093/bioinformatics/btt067}, volume = {29}, year = {2013}, }