Genetic Algorithms as a method to study adaptive walks in biological landscapes

The metaphor of fitness landscapes is common in evolutionary biology, as a way to visualise the change in allele or phenotypic frequencies of a population under selection. Understanding how different factors in the evolutionary process affect the trajectory of the population across the landscape is of interest to both theoretical and empirical evolutionary biologists. However, fitness landscape studies often have to rely heavily on mathematical methods that are not easy to access by biologically trained researchers. Here, we used a method borrowed from engineering - genetic algorithms - to simulate the evolutionary process and study how different components affect the path taken through a phenotypic fitness landscape. In a simple study, we compare five selection models that reflect different degrees of dependency of fitness on trait quality: this includes strengths of selection, trait-quality dependent reproductive hierarchy and the amount of stochasticity in the reproductive process. We include an analysis of other evolutionary variables such as population size and mutation rate. We analyse a game theory problem, as a test landscape, that lends itself to analysis through a deterministic mathematical simulation, which we use for comparison. Our results show that there are differences in the speed with which different models of selection lead to the fitness optimum.Author summaryEvolution and adaptation in biology occurs in fitness landscapes, multidimensional spaces representing all possible genotypic or phenotypic combinations, where population adapt by following the cline of the fitness dimension. The study of adaptation on complex fitness landscapes has so far been limited by the need for mathematically heavy methods. Here, we present a simulation modelling framework, genetic algorithms, that can be used for evolutionary simulations of a population on a fitness landscape of chosen features and with custom evolutionary parameters.

The onset of ecological diversification 50 years after colonization of a crater lake by haplochromine cichlid fishes

Adaptive radiation research typically relies on the study of evolution in retrospective, leaving the predictive value of the concept hard to evaluate. Several radiations, including the cichlid fishes in the East African Great Lakes, have been studied extensively, yet no study has investigated the onset of the intraspecific processes of niche expansion and differentiation shortly after colonization of an adaptive zone by cichlids. Haplochromine cichlids of one of the two lineages that seeded the Lake Victoria radiation recently arrived in Lake Chala, a lake perfectly suited for within-lake cichlid speciation. Here, we infer the colonization and demographic history, quantify phenotypic, ecological and genomic diversity and diversification, and investigate the selection regime to ask if the population shows signs of diversification resembling the onset of adaptive radiation. We find that since their arrival in the lake, haplochromines have colonized a wide range of depth habitats associated with ecological and morphological expansion and the beginning of phenotypic differentiation and potentially nascent speciation, consistent with the very early onset of an adaptive radiation process. Moreover, we demonstrate evidence of rugged phenotypic fitness surfaces, indicating that current ecological selection may contribute to the phenotypic diversification.

Diminishing returns of inoculum size on the rate of a plant RNA virus evolution

Understanding how genetic drift, mutation and selection interplay in determining the evolutionary fate of populations is one of the central questions of Evolutionary Biology. Theory predicts that by increasing the number of coexisting beneficial alleles in a population beyond some point does not necessarily translates into an acceleration in the rate of evolution. This diminishing-returns effect of beneficial genetic variability in microbial asexual populations is known as clonal interference. Clonal interference has been shown to operate in experimental populations of animal RNA viruses replicating in cell cultures. Here we carried out experiments to test whether a similar diminishing-returns of population size on the rate of adaptation exists for a plant RNA virus infecting real multicellular hosts. We have performed evolution experiments with tobacco etch potyvirus in two hosts, the natural and a novel one, at different inoculation sizes and estimated the rates of evolution for two phenotypic fitness-related traits. Firstly, we found that evolution proceeds faster in the novel than in the original host. Secondly, we found the predicted diminishing-returns effect of inoculum size on the rate of evolution for one of the fitness traits, but not for the other, which suggests that selection operates differently on each trait.

From epigenetic landscape to phenotypic fitness landscape: evolutionary effect of pathogens on host traits

The epigenetic landscape illustrates how cells differentiate into different types through the control of gene regulatory networks. Numerous studies have investigated epigenetic gene regulation but there are limited studies on how the epigenetic landscape and the presence of pathogens influence the evolution of host traits. Here we formulate a multistable decision-switch model involving many possible phenotypes with the antagonistic influence of parasitism. As expected, pathogens can drive dominant (common) phenotypes to become inferior, such as through negative frequency-dependent selection. Furthermore, novel predictions of our model show that parasitism can steer the dynamics of phenotype specification from multistable equilibrium convergence to oscillations. This oscillatory behavior could explain pathogen-mediated epimutations and excessive phenotypic plasticity. The Red Queen dynamics also occur in certain parameter space of the model, which demonstrates winnerless cyclic phenotype-switching in hosts and in pathogens. The results of our simulations elucidate how epigenetic landscape is associated with the phenotypic fitness landscape and how parasitism facilitates non-genetic phenotypic diversity.

Modelling metabolic evolution on phenotypic fitness landscapes: a case study on C4 photosynthesis

How did the complex metabolic systems we observe today evolve through adaptive evolution? The fitness landscape is the theoretical framework to answer this question. Since experimental data on natural fitness landscapes is scarce, computational models are a valuable tool to predict landscape topologies and evolutionary trajectories. Careful assumptions about the genetic and phenotypic features of the system under study can simplify the design of such models significantly. The analysis of C4 photosynthesis evolution provides an example for accurate predictions based on the phenotypic fitness landscape of a complex metabolic trait. The C4 pathway evolved multiple times from the ancestral C3 pathway and models predict a smooth ‘Mount Fuji’ landscape accordingly. The modelled phenotypic landscape implies evolutionary trajectories that agree with data on modern intermediate species, indicating that evolution can be predicted based on the phenotypic fitness landscape. Future directions will have to include structural changes of metabolic fitness landscape structure with changing environments. This will not only answer important evolutionary questions about reversibility of metabolic traits, but also suggest strategies to increase crop yields by engineering the C4 pathway into C3 plants.

Population-specific locomotor phenotypes are displayed by barramundi, Lates calcarifer, in response to thermal stress

We investigated how thermal stress may alter the locomotor phenotype of barramundi, Lates calcarifer , from genetically distinct northern (low latitude) and southern (high latitude) populations in tropical Australia. Following early growth and development under native (25 °C and 30 °C) and non-native (20 °C and 35 °C) temperatures, we observed distinct differences in the swimming performance of northern and southern individuals that were consistent with expectations based on local thermal adaptation. Southern population fish exhibited significantly faster swimming speeds (32.10 ± 0.33 cm·s–1, mass-adjusted mean ± 95% confidence limit) than their northern counterparts (28.58 ± 0.64 cm·s–1) under cold-stress (20 °C) conditions. Conversely, northern population fish performed significantly better (51.63 ± 2.1 cm·s–1) than their southern counterparts (44.18 ± 3.11 cm·s–1) under heat-stress (35 °C) conditions. We conclude that L. calcarifer display locomotor phenotypes thermally adapted to their local environment, with early growth under non-native temperatures leading to significantly reduced phenotypic fitness.