Journal articles: 'Adaptive or fitness landscapes'

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Zheng, Liming, and Shiqi Luo. "Adaptive Differential Evolution Algorithm Based on Fitness Landscape Characteristic." Mathematics 10, no. 9 (May 1, 2022): 1511. http://dx.doi.org/10.3390/math10091511.

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Differential evolution (DE) is a simple, effective, and robust algorithm, which has demonstrated excellent performance in dealing with global optimization problems. However, different search strategies are designed for different fitness landscape conditions to find the optimal solution, and there is not a single strategy that can be suitable for all fitness landscapes. As a result, developing a strategy to adaptively steer population evolution based on fitness landscape is critical. Motivated by this fact, in this paper, a novel adaptive DE based on fitness landscape (FL-ADE) is proposed, which utilizes the local fitness landscape characteristics in each generation population to (1) adjust the population size adaptively; (2) generate DE/current-to-pcbest mutation strategy. The adaptive mechanism is based on local fitness landscape characteristics of the population and enables to decrease or increase the population size during the search. Due to the adaptive adjustment of population size for different fitness landscapes and evolutionary processes, computational resources can be rationally assigned at different evolutionary stages to satisfy diverse requirements of different fitness landscapes. Besides, the DE/current-to-pcbest mutation strategy, which randomly chooses one of the top p% individuals from the archive cbest of local optimal individuals to be the pcbest, is also an adaptive strategy based on fitness landscape characteristic. Using the individuals that are approximated as local optimums increases the algorithm’s ability to explore complex multimodal functions and avoids stagnation due to the use of individuals with good fitness values. Experiments are conducted on CEC2014 benchmark test suit to demonstrate the performance of the proposed FL-ADE algorithm, and the results show that the proposed FL-ADE algorithm performs better than the other seven highly performing state-of-art DE variants, even the winner of the CEC2014 and CEC2017. In addition, the effectiveness of the adaptive population mechanism and DE/current-to-pcbest mutation strategy based on landscape fitness proposed in this paper are respectively verified.

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Srivastava, Malvika, and Joshua L. Payne. "On the incongruence of genotype-phenotype and fitness landscapes." PLOS Computational Biology 18, no. 9 (September 19, 2022): e1010524. http://dx.doi.org/10.1371/journal.pcbi.1010524.

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The mapping from genotype to phenotype to fitness typically involves multiple nonlinearities that can transform the effects of mutations. For example, mutations may contribute additively to a phenotype, but their effects on fitness may combine non-additively because selection favors a low or intermediate value of that phenotype. This can cause incongruence between the topographical properties of a fitness landscape and its underlying genotype-phenotype landscape. Yet, genotype-phenotype landscapes are often used as a proxy for fitness landscapes to study the dynamics and predictability of evolution. Here, we use theoretical models and empirical data on transcription factor-DNA interactions to systematically study the incongruence of genotype-phenotype and fitness landscapes when selection favors a low or intermediate phenotypic value. Using the theoretical models, we prove a number of fundamental results. For example, selection for low or intermediate phenotypic values does not change simple sign epistasis into reciprocal sign epistasis, implying that genotype-phenotype landscapes with only simple sign epistasis motifs will always give rise to single-peaked fitness landscapes under such selection. More broadly, we show that such selection tends to create fitness landscapes that are more rugged than the underlying genotype-phenotype landscape, but this increased ruggedness typically does not frustrate adaptive evolution because the local adaptive peaks in the fitness landscape tend to be nearly as tall as the global peak. Many of these results carry forward to the empirical genotype-phenotype landscapes, which may help to explain why low- and intermediate-affinity transcription factor-DNA interactions are so prevalent in eukaryotic gene regulation.

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Cervera, Héctor, Jasna Lalić, and Santiago F. Elena. "Effect of Host Species on Topography of the Fitness Landscape for a Plant RNA Virus." Journal of Virology 90, no. 22 (August 31, 2016): 10160–69. http://dx.doi.org/10.1128/jvi.01243-16.

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ABSTRACTAdaptive fitness landscapes are a fundamental concept in evolutionary biology that relate the genotypes of individuals to their fitness. In the end, the evolutionary fate of evolving populations depends on the topography of the landscape, that is, the numbers of accessible mutational pathways and possible fitness peaks (i.e., adaptive solutions). For a long time, fitness landscapes were only theoretical constructions due to a lack of precise information on the mapping between genotypes and phenotypes. In recent years, however, efforts have been devoted to characterizing the properties of empirical fitness landscapes for individual proteins or for microbes adapting to artificial environments. In a previous study, we characterized the properties of the empirical fitness landscape defined by the first five mutations fixed during adaptation of tobacco etch potyvirus (TEV) to a new experimental host,Arabidopsis thaliana. Here we evaluate the topography of this landscape in the ancestral hostNicotiana tabacum. By comparing the topographies of the landscapes for the two hosts, we found that some features remained similar, such as the existence of fitness holes and the prevalence of epistasis, including cases of sign and reciprocal sign epistasis that created rugged, uncorrelated, and highly random topographies. However, we also observed significant differences in the fine-grained details between the two landscapes due to changes in the fitness and epistatic interactions of some genotypes. Our results support the idea that not only fitness tradeoffs between hosts but also topographical incongruences among fitness landscapes in alternative hosts may contribute to virus specialization.IMPORTANCEDespite its importance for understanding virus evolutionary dynamics, very little is known about the topography of virus adaptive fitness landscapes, and even less is known about the effects that different host species and environmental conditions may have on this topography. To bridge this gap, we evaluated the topography of a small fitness landscape formed by all genotypes that result from every possible combination of the first five mutations fixed during adaptation of TEV to the novel hostA. thaliana. To assess the effect that host species may have on this topography, we evaluated the fitness of every genotype in both the ancestral and novel hosts. We found that both landscapes share some macroscopic properties, such as the existence of holes and being highly rugged and uncorrelated, yet they differ in microscopic details due to changes in the magnitude and sign of fitness and epistatic effects.

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Li, Ye, and Claus O. Wilke. "Digital Evolution in Time-Dependent Fitness Landscapes." Artificial Life 10, no. 2 (March 2004): 123–34. http://dx.doi.org/10.1162/106454604773563559.

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We study the response of populations of digital organisms that adapt to a time-varying (periodic) fitness landscape of two oscillating peaks. We corroborate in general predictions from quasi-species theory in dynamic landscapes, such as adaptation to the average fitness landscape at small periods (high frequency) and quasistatic adaptation at large periods (low frequency). We also observe adaptive phase shifts (time lags between a change in the fitness landscape and an adaptive change in the population) that indicate a low-pass filter effect, in agreement with existing theory. Finally, we witness long-term adaptation to fluctuating environments not anticipated in previous theoretical work.

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Trujillo, Leonardo, Paul Banse, and Guillaume Beslon. "Getting higher on rugged landscapes: Inversion mutations open access to fitter adaptive peaks in NK fitness landscapes." PLOS Computational Biology 18, no. 10 (October 31, 2022): e1010647. http://dx.doi.org/10.1371/journal.pcbi.1010647.

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Molecular evolution is often conceptualised as adaptive walks on rugged fitness landscapes, driven by mutations and constrained by incremental fitness selection. It is well known that epistasis shapes the ruggedness of the landscape’s surface, outlining their topography (with high-fitness peaks separated by valleys of lower fitness genotypes). However, within the strong selection weak mutation (SSWM) limit, once an adaptive walk reaches a local peak, natural selection restricts passage through downstream paths and hampers any possibility of reaching higher fitness values. Here, in addition to the widely used point mutations, we introduce a minimal model of sequence inversions to simulate adaptive walks. We use the well known NK model to instantiate rugged landscapes. We show that adaptive walks can reach higher fitness values through inversion mutations, which, compared to point mutations, allows the evolutionary process to escape local fitness peaks. To elucidate the effects of this chromosomal rearrangement, we use a graph-theoretical representation of accessible mutants and show how new evolutionary paths are uncovered. The present model suggests a simple mechanistic rationale to analyse escapes from local fitness peaks in molecular evolution driven by (intragenic) structural inversions and reveals some consequences of the limits of point mutations for simulations of molecular evolution.

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Reia, Sandro M., and Paulo R. A. Campos. "Analysis of statistical correlations between properties of adaptive walks in fitness landscapes." Royal Society Open Science 7, no. 1 (January 2020): 192118. http://dx.doi.org/10.1098/rsos.192118.

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The fitness landscape metaphor has been central in our way of thinking about adaptation. In this scenario, adaptive walks are idealized dynamics that mimic the uphill movement of an evolving population towards a fitness peak of the landscape. Recent works in experimental evolution have demonstrated that the constraints imposed by epistasis are responsible for reducing the number of accessible mutational pathways towards fitness peaks. Here, we exhaustively analyse the statistical properties of adaptive walks for two empirical fitness landscapes and theoretical NK landscapes. Some general conclusions can be drawn from our simulation study. Regardless of the dynamics, we observe that the shortest paths are more regularly used. Although the accessibility of a given fitness peak is reasonably correlated to the number of monotonic pathways towards it, the two quantities are not exactly proportional. A negative correlation between predictability and mean path divergence is established, and so the decrease of the number of effective mutational pathways ensures the convergence of the attraction basin of fitness peaks. On the other hand, other features are not conserved among fitness landscapes, such as the relationship between accessibility and predictability.

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Bajić, Djordje, Jean C. C. Vila, Zachary D. Blount, and Alvaro Sánchez. "On the deformability of an empirical fitness landscape by microbial evolution." Proceedings of the National Academy of Sciences 115, no. 44 (October 15, 2018): 11286–91. http://dx.doi.org/10.1073/pnas.1808485115.

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A fitness landscape is a map between the genotype and its reproductive success in a given environment. The topography of fitness landscapes largely governs adaptive dynamics, constraining evolutionary trajectories and the predictability of evolution. Theory suggests that this topography can be deformed by mutations that produce substantial changes to the environment. Despite its importance, the deformability of fitness landscapes has not been systematically studied beyond abstract models, and little is known about its reach and consequences in empirical systems. Here we have systematically characterized the deformability of the genome-wide metabolic fitness landscape of the bacterium Escherichia coli. Deformability is quantified by the noncommutativity of epistatic interactions, which we experimentally demonstrate in mutant strains on the path to an evolutionary innovation. Our analysis shows that the deformation of fitness landscapes by metabolic mutations rarely affects evolutionary trajectories in the short range. However, mutations with large environmental effects produce long-range landscape deformations in distant regions of the genotype space that affect the fitness of later descendants. Our results therefore suggest that, even in situations in which mutations have strong environmental effects, fitness landscapes may retain their power to forecast evolution over small mutational distances despite the potential attenuation of that power over longer evolutionary trajectories. Our methods and results provide an avenue for integrating adaptive and eco-evolutionary dynamics with complex genetics and genomics.

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Bertram, Jason, and Joanna Masel. "Evolution Rapidly Optimizes Stability and Aggregation in Lattice Proteins Despite Pervasive Landscape Valleys and Mazes." Genetics 214, no. 4 (February 27, 2020): 1047–57. http://dx.doi.org/10.1534/genetics.120.302815.

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The “fitness” landscapes of genetic sequences are characterized by high dimensionality and “ruggedness” due to sign epistasis. Ascending from low to high fitness on such landscapes can be difficult because adaptive trajectories get stuck at low-fitness local peaks. Compounding matters, recent theoretical arguments have proposed that extremely long, winding adaptive paths may be required to reach even local peaks: a “maze-like” landscape topography. The extent to which peaks and mazes shape the mode and tempo of evolution is poorly understood, due to empirical limitations and the abstractness of many landscape models. We explore the prevalence, scale, and evolutionary consequences of landscape mazes in a biophysically grounded computational model of protein evolution that captures the “frustration” between “stability” and aggregation propensity. Our stability-aggregation landscape exhibits extensive sign epistasis and local peaks galore. Although this frequently obstructs adaptive ascent to high fitness and virtually eliminates reproducibility of evolutionary outcomes, many adaptive paths do successfully complete the ascent from low to high fitness, with hydrophobicity a critical mediator of success. These successful paths exhibit maze-like properties on a global landscape scale, in which taking an indirect path helps to avoid low-fitness local peaks. This delicate balance of “hard but possible” adaptation could occur more broadly in other biological settings where competing interactions and frustration are important.

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Wilke, Claus O., and Thomas Martinetz. "Adaptive walks on time-dependent fitness landscapes." Physical Review E 60, no. 2 (August 1, 1999): 2154–59. http://dx.doi.org/10.1103/physreve.60.2154.

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Hadany, L., and T. Beker. "Fitness-associated recombination on rugged adaptive landscapes." Journal of Evolutionary Biology 16, no. 5 (September 2003): 862–70. http://dx.doi.org/10.1046/j.1420-9101.2003.00586.x.

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Hendry, Andrew P., Peter R. Grant, B. Rosemary Grant, Hugh A. Ford, Mark J. Brewer, and Jeffrey Podos. "Possible human impacts on adaptive radiation: beak size bimodality in Darwin's finches." Proceedings of the Royal Society B: Biological Sciences 273, no. 1596 (May 2, 2006): 1887–94. http://dx.doi.org/10.1098/rspb.2006.3534.

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Adaptive radiation is facilitated by a rugged adaptive landscape, where fitness peaks correspond to trait values that enhance the use of distinct resources. Different species are thought to occupy the different peaks, with hybrids falling into low-fitness valleys between them. We hypothesize that human activities can smooth adaptive landscapes, increase hybrid fitness and hamper evolutionary diversification. We investigated this possibility by analysing beak size data for 1755 Geospiza fortis measured between 1964 and 2005 on the island of Santa Cruz, Galápagos. Some populations of this species can display a resource-based bimodality in beak size, which mirrors the greater beak size differences among species. We first show that an historically bimodal population at one site, Academy Bay, has lost this property in concert with a marked increase in local human population density. We next show that a nearby site with lower human impacts, El Garrapatero, currently manifests strong bimodality. This comparison suggests that bimodality can persist when human densities are low (Academy Bay in the past, El Garrapatero in the present), but not when they are high (Academy Bay in the present). Human activities may negatively impact diversification in ‘young’ adaptive radiations, perhaps by altering adaptive landscapes.

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Cervera, Héctor, Jasna Lalić, and Santiago F. Elena. "Efficient escape from local optima in a highly rugged fitness landscape by evolving RNA virus populations." Proceedings of the Royal Society B: Biological Sciences 283, no. 1836 (August 17, 2016): 20160984. http://dx.doi.org/10.1098/rspb.2016.0984.

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Predicting viral evolution has proven to be a particularly difficult task, mainly owing to our incomplete knowledge of some of the fundamental principles that drive it. Recently, valuable information has been provided about mutation and recombination rates, the role of genetic drift and the distribution of mutational, epistatic and pleiotropic fitness effects. However, information about the topography of virus' adaptive landscapes is still scarce, and to our knowledge no data has been reported so far on how its ruggedness may condition virus' evolvability. Here, we show that populations of an RNA virus move efficiently on a rugged landscape and scape from the basin of attraction of a local optimum. We have evolved a set of Tobacco etch virus genotypes located at increasing distances from a local adaptive optimum in a highly rugged fitness landscape, and we observed that few evolved lineages remained trapped in the local optimum, while many others explored distant regions of the landscape. Most of the diversification in fitness among the evolved lineages was explained by adaptation, while historical contingency and chance events contribution was less important. Our results demonstrate that the ruggedness of adaptive landscapes is not an impediment for RNA viruses to efficiently explore remote parts of it.

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Laughlin, Daniel C., and Julie Messier. "Fitness of multidimensional phenotypes in dynamic adaptive landscapes." Trends in Ecology & Evolution 30, no. 8 (August 2015): 487–96. http://dx.doi.org/10.1016/j.tree.2015.06.003.

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Niklas, Karl J. "Effects of hypothetical developmental barriers and abrupt environmental changes on adaptive walks in a computer-generated domain for early vascular land plants." Paleobiology 23, no. 1 (1997): 63–76. http://dx.doi.org/10.1017/s009483730001664x.

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Computer-generated searches through hypothetical fitness landscapes for progressively more fit variants were used to assess the effects of developmental barriers (mimicked by barring specific types of morphological transformations) and abruptly shifting environmental conditions (mimicked by sudden shifts in how fitness was defined) on the number and accessibility of optimal phenotypes. Relative fitness was defined in terms of maximizing light interception, mechanical stability, or reproductive success, or minimizing surface area, or optimizing the performance of various combinations of these tasks. Developmentally obstructed and unobstructed walks located, on average, equivalent numbers of phenotypic optima. The number of optima identified by both kinds of walks increased in proportion to the number of simultaneously performed tasks used to measure fitness. Walks passing from more complex to less complex fitness landscapes located more optima than walks passing through unchanging, stable landscapes. The model thus suggests that there are no a priori reasons to assume that (1) the morphological options available to adaptive evolution become more restrictive as biological complexity increases, (2) “developmental barriers” necessarily restrain a lineage from evolving well-adapted morphologies, and (3) generalist organisms are less successful than specialists. Also, because the number and accessibility of fitness peaks were proportional to the complexity of fitness landscapes, the model predicts that the probability of cladogenesis will increase as landscape complexity increases, while anagenesis will be encouraged when fitness is defined in terms of performing one or a few tasks simultaneously.

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Wilson, David Sloan, and Alexandra Wells. "Radical Epistasis and the Genotype-Phenotype Relationship." Artificial Life 2, no. 1 (October 1994): 117–28. http://dx.doi.org/10.1162/artl.1994.2.1.117.

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Models of evolution often assume that the offspring of two genotypes, which are genetically intermediate by definition, are also phenotypically intermediate. The continuity between genotype and phenotype interferes with the process of evolution on multipeaked adaptive landscapes because the progeny of genotypes that lie on separate adaptive peaks fall into valleys of low fitness. This problem can be solved by epistasis, which disrupts the continuity between genotype and phenotype. In a five-locus sexual haploid model with maximum epistasis, natural selection in multipeak landscapes evolves a set of genotypes that a) occupy the adaptive peaks and b) give rise to each other by recombination. The epistatic genetic system therefore “molds” the phenotypic distribution to the adaptive landscape, without assortative mating or linkage disequilibrium. If the adaptive landscape is changed, a new set of genotypes quickly evolves that satisfies conditions a and b, above, for the new peaks. Our model may be relevant to a number of recalcitrant problems in biology and also stands in contrast to Kauffman's [3] NK model of evolution on rugged fitness surfaces, in which epistasis and recombination tend to constrain the evolutionary process.

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Pfaender, Jobst, Renny K. Hadiaty, Ulrich K. Schliewen, and Fabian Herder. "Rugged adaptive landscapes shape a complex, sympatric radiation." Proceedings of the Royal Society B: Biological Sciences 283, no. 1822 (January 13, 2016): 20152342. http://dx.doi.org/10.1098/rspb.2015.2342.

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Strong disruptive ecological selection can initiate speciation, even in the absence of physical isolation of diverging populations. Species evolving under disruptive ecological selection are expected to be ecologically distinct but, at least initially, genetically weakly differentiated. Strong selection and the associated fitness advantages of narrowly adapted individuals, coupled with assortative mating, are predicted to overcome the homogenizing effects of gene flow. Theoretical plausibility is, however, contrasted by limited evidence for the existence of rugged adaptive landscapes in nature. We found evidence for multiple, disruptive ecological selection regimes that have promoted divergence in the sympatric, incipient radiation of ‘sharpfin’ sailfin silverside fishes in ancient Lake Matano (Sulawesi, Indonesia). Various modes of ecological specialization have led to adaptive morphological differences between the species, and differently adapted morphs display significant but incomplete reproductive isolation. Individual fitness and variation in morphological key characters show that disruptive selection shapes a rugged adaptive landscape in this small but complex incipient lake fish radiation.

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Heckmann, David. "Modelling metabolic evolution on phenotypic fitness landscapes: a case study on C4 photosynthesis." Biochemical Society Transactions 43, no. 6 (November 27, 2015): 1172–76. http://dx.doi.org/10.1042/bst20150148.

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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.

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Arias, Mónica, Yann le Poul, Mathieu Chouteau, Romain Boisseau, Neil Rosser, Marc Théry, and Violaine Llaurens. "Crossing fitness valleys: empirical estimation of a fitness landscape associated with polymorphic mimicry." Proceedings of the Royal Society B: Biological Sciences 283, no. 1829 (April 27, 2016): 20160391. http://dx.doi.org/10.1098/rspb.2016.0391.

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Characterizing fitness landscapes associated with polymorphic adaptive traits enables investigation of mechanisms allowing transitions between fitness peaks. Here, we explore how natural selection can promote genetic mechanisms preventing heterozygous phenotypes from falling into non-adaptive valleys. Polymorphic mimicry is an ideal system to investigate such fitness landscapes, because the direction of selection acting on complex mimetic colour patterns can be predicted by the local mimetic community composition. Using more than 5000 artificial butterflies displaying colour patterns exhibited by the polymorphic Müllerian mimic Heliconius numata , we directly tested the role of wild predators in shaping fitness landscapes. We compared predation rates on mimetic phenotypes (homozygotes at the supergene controlling colour pattern), intermediate phenotypes (heterozygotes), exotic morphs (absent from the local community) and palatable cryptic phenotypes. Exotic morphs were significantly more attacked than local morphs, highlighting predators' discriminatory capacities. Overall, intermediates were attacked twice as much as local homozygotes, suggesting the existence of deep fitness valleys promoting strict dominance and reduced recombination between supergene alleles. By including information on predators' colour perception, we also showed that protection on intermediates strongly depends on their phenotypic similarity to homozygous phenotypes and that ridges exist between similar phenotypes, which may facilitate divergence in colour patterns.

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de Lima Filho, J. A., F. G. B. Moreira, P. R. A. Campos, and Viviane M. de Oliveira. "Adaptive walks on correlated fitness landscapes with heterogeneous connectivities." Journal of Statistical Mechanics: Theory and Experiment 2012, no. 02 (February 21, 2012): P02014. http://dx.doi.org/10.1088/1742-5468/2012/02/p02014.

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Campos, Paulo R. A., Christoph Adami, and Claus O. Wilke. "Optimal adaptive performance and delocalization in NK fitness landscapes." Physica A: Statistical Mechanics and its Applications 304, no. 3-4 (February 2002): 495–506. http://dx.doi.org/10.1016/s0378-4371(01)00572-6.

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Rubin, Ilan N., Yaroslav Ispolatov, and Michael Doebeli. "Adaptive diversification and niche packing on rugged fitness landscapes." Journal of Theoretical Biology 562 (April 2023): 111421. http://dx.doi.org/10.1016/j.jtbi.2023.111421.

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Geard, Nicholas, and Janet Wiles. "LinMap: Visualizing Complexity Gradients in Evolutionary Landscapes." Artificial Life 14, no. 3 (July 2008): 277–97. http://dx.doi.org/10.1162/artl.2008.14.3.14304.

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This article describes an interactive visualization tool, LinMap, for exploring the structure of complexity gradients in evolutionary landscapes. LinMap is a computationally efficient and intuitive tool for visualizing and exploring multidimensional parameter spaces. An artificial cell lineage model is presented that allows complexity to be quantified according to several different developmental and phenotypic metrics. LinMap is applied to the evolutionary landscapes generated by this model to demonstrate that different definitions of complexity produce different gradients across the same landscape; that landscapes are characterized by a phase transition between proliferating and quiescent cell lineages where both complexity and diversity are maximized; and that landscapes defined by adaptive fitness and complexity can display different topographical features.

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Østman, Bjørn, Arend Hintze, and Christoph Adami. "Impact of epistasis and pleiotropy on evolutionary adaptation." Proceedings of the Royal Society B: Biological Sciences 279, no. 1727 (June 22, 2011): 247–56. http://dx.doi.org/10.1098/rspb.2011.0870.

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Evolutionary adaptation is often likened to climbing a hill or peak. While this process is simple for fitness landscapes where mutations are independent, the interaction between mutations (epistasis) as well as mutations at loci that affect more than one trait (pleiotropy) are crucial in complex and realistic fitness landscapes. We investigate the impact of epistasis and pleiotropy on adaptive evolution by studying the evolution of a population of asexual haploid organisms (haplotypes) in a model of N interacting loci, where each locus interacts with K other loci. We use a quantitative measure of the magnitude of epistatic interactions between substitutions, and find that it is an increasing function of K . When haplotypes adapt at high mutation rates, more epistatic pairs of substitutions are observed on the line of descent than expected. The highest fitness is attained in landscapes with an intermediate amount of ruggedness that balance the higher fitness potential of interacting genes with their concomitant decreased evolvability. Our findings imply that the synergism between loci that interact epistatically is crucial for evolving genetic modules with high fitness, while too much ruggedness stalls the adaptive process.

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Niklas, Karl J. "Adaptive walks through fitness landscapes for early vascular land plants." American Journal of Botany 84, no. 1 (January 1997): 16–25. http://dx.doi.org/10.2307/2445878.

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DeWitt, Thomas J., and Jin Yoshimura. "The fitness threshold model: Random environmental change alters adaptive landscapes." Evolutionary Ecology 12, no. 5 (July 1998): 615–26. http://dx.doi.org/10.1023/a:1006564911480.

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Rendel, Mark D. "Adaptive evolutionary walks require neutral intermediates in RNA fitness landscapes." Theoretical Population Biology 79, no. 1-2 (February 2011): 12–18. http://dx.doi.org/10.1016/j.tpb.2010.10.001.

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Rozen, Daniel E., Michelle G. J. L. Habets, Andreas Handel, and J. Arjan G. M. de Visser. "Heterogeneous Adaptive Trajectories of Small Populations on Complex Fitness Landscapes." PLoS ONE 3, no. 3 (March 5, 2008): e1715. http://dx.doi.org/10.1371/journal.pone.0001715.

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Burch, Christina L., and Lin Chao. "Evolution by Small Steps and Rugged Landscapes in the RNA Virus ϕ6." Genetics 151, no. 3 (March 1, 1999): 921–27. http://dx.doi.org/10.1093/genetics/151.3.921.

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Abstract Fisher’s geometric model of adaptive evolution argues that adaptive evolution should generally result from the substitution of many mutations of small effect because advantageous mutations of small effect should be more common than those of large effect. However, evidence for both evolution by small steps and for Fisher’s model has been mixed. Here we report supporting results from a new experimental test of the model. We subjected the bacteriophage ϕ6 to intensified genetic drift in small populations and caused viral fitness to decline through the accumulation of a deleterious mutation. We then propagated the mutated virus at a range of larger population sizes and allowed fitness to recover by natural selection. Although fitness declined in one large step, it was usually recovered in smaller steps. More importantly, step size during recovery was smaller with decreasing size of the recovery population. These results confirm Fisher’s main prediction that advantageous mutations of small effect should be more common. We also show that the advantageous mutations of small effect are compensatory mutations whose advantage is conditional (epistatic) on the presence of the deleterious mutation, in which case the adaptive landscape of ϕ6 is likely to be very rugged.

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Erwin, Douglas H. "The topology of evolutionary novelty and innovation in macroevolution." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1735 (October 23, 2017): 20160422. http://dx.doi.org/10.1098/rstb.2016.0422.

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Sewall Wright's fitness landscape introduced the concept of evolutionary spaces in 1932. George Gaylord Simpson modified this to an adaptive, phenotypic landscape in 1944 and since then evolutionary spaces have played an important role in evolutionary theory through fitness and adaptive landscapes, phenotypic and functional trait spaces, morphospaces and related concepts. Although the topology of such spaces is highly variable, from locally Euclidean to pre-topological, evolutionary change has often been interpreted as a search through a pre-existing space of possibilities, with novelty arising by accessing previously inaccessible or difficult to reach regions of a space. Here I discuss the nature of evolutionary novelty and innovation within the context of evolutionary spaces, and argue that the primacy of search as a conceptual metaphor ignores the generation of new spaces as well as other changes that have played important evolutionary roles. This article is part of the themed issue ‘Process and pattern in innovations from cells to societies’.

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Jordan, Lyndon A., and Michael J. Ryan. "The sensory ecology of adaptive landscapes." Biology Letters 11, no. 5 (May 2015): 20141054. http://dx.doi.org/10.1098/rsbl.2014.1054.

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In complex environments, behavioural plasticity depends on the ability of an animal to integrate numerous sensory stimuli. The multidimensionality of factors interacting to shape plastic behaviour means it is difficult for both organisms and researchers to predict what constitutes an adaptive response to a given set of conditions. Although researchers may be able to map the fitness pay-offs of different behavioural strategies in changing environments, there is no guarantee that the study species will be able to perceive these pay-offs. We thus risk a disconnect between our own predictions about adaptive behaviour and what is behaviourally achievable given the umwelt of the animal being studied. This may lead to erroneous conclusions about maladaptive behaviour in circumstances when the behaviour exhibited is the most adaptive possible given sensory limitations. With advances in the computational resources available to behavioural ecologists, we can now measure vast numbers of interactions among behaviours and environments to create adaptive behavioural surfaces. These surfaces have massive heuristic, predictive and analytical potential in understanding adaptive animal behaviour, but researchers using them are destined to fail if they ignore the sensory ecology of the species they study. Here, we advocate the continued use of these approaches while directly linking them to perceptual space to ensure that the topology of the generated adaptive landscape matches the perceptual reality of the animal it intends to study. Doing so will allow predictive models of animal behaviour to reflect the reality faced by the agents on adaptive surfaces, vastly improving our ability to determine what constitutes an adaptive response for the animal in question.

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Campos, P. R. A., C. Adami, and C. O. Wilke. "Erratum to “Optimal adaptive performance and delocalization in NK fitness landscapes”." Physica A: Statistical Mechanics and its Applications 318, no. 3-4 (February 2003): 637. http://dx.doi.org/10.1016/s0378-4371(02)01554-6.

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Hayden, Eric J., and Andreas Wagner. "Environmental change exposes beneficial epistatic interactions in a catalytic RNA." Proceedings of the Royal Society B: Biological Sciences 279, no. 1742 (June 20, 2012): 3418–25. http://dx.doi.org/10.1098/rspb.2012.0956.

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Natural selection drives populations of individuals towards local peaks in a fitness landscape. These peaks are created by the interactions between individual mutations. Fitness landscapes may change as an environment changes. In a previous contribution, we discovered a variant of the Azoarcus group I ribozyme that represents a local peak in the RNA fitness landscape. The genotype at this peak is distinguished from the wild-type by four point mutations. We here report ribozyme fitness data derived from constructing all possible combinations of these point mutations. We find that these mutations interact epistatically. Importantly, we show that these epistatic interactions change qualitatively in the three different environments that we studied. We find examples where the relative fitness of a ribozyme can change from neutral or negative in one environment, to positive in another. We also show that the fitness effect of a specific GC–AU base pair switch is dependent on both the environment and the genetic context. Moreover, the mutations that we study improve activity at the cost of decreased structural stability. Environmental change is ubiquitous in nature. Our results suggest that such change can facilitate adaptive evolution by exposing new peaks of a fitness landscape. They highlight a prominent role for genotype–environment interactions in doing so.

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Taylor, Mark A., Amity M. Wilczek, Judith L. Roe, Stephen M. Welch, Daniel E. Runcie, Martha D. Cooper, and Johanna Schmitt. "Large-effect flowering time mutations reveal conditionally adaptive paths through fitness landscapes in Arabidopsis thaliana." Proceedings of the National Academy of Sciences 116, no. 36 (August 16, 2019): 17890–99. http://dx.doi.org/10.1073/pnas.1902731116.

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Contrary to previous assumptions that most mutations are deleterious, there is increasing evidence for persistence of large-effect mutations in natural populations. A possible explanation for these observations is that mutant phenotypes and fitness may depend upon the specific environmental conditions to which a mutant is exposed. Here, we tested this hypothesis by growing large-effect flowering time mutants of Arabidopsis thaliana in multiple field sites and seasons to quantify their fitness effects in realistic natural conditions. By constructing environment-specific fitness landscapes based on flowering time and branching architecture, we observed that a subset of mutations increased fitness, but only in specific environments. These mutations increased fitness via different paths: through shifting flowering time, branching, or both. Branching was under stronger selection, but flowering time was more genetically variable, pointing to the importance of indirect selection on mutations through their pleiotropic effects on multiple phenotypes. Finally, mutations in hub genes with greater connectedness in their regulatory networks had greater effects on both phenotypes and fitness. Together, these findings indicate that large-effect mutations may persist in populations because they influence traits that are adaptive only under specific environmental conditions. Understanding their evolutionary dynamics therefore requires measuring their effects in multiple natural environments.

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Otwinowski, Jakub, Colin H. LaMont, and Armita Nourmohammad. "Information-Geometric Optimization with Natural Selection." Entropy 22, no. 9 (August 31, 2020): 967. http://dx.doi.org/10.3390/e22090967.

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Evolutionary algorithms, inspired by natural evolution, aim to optimize difficult objective functions without computing derivatives. Here we detail the relationship between classical population genetics of quantitative traits and evolutionary optimization, and formulate a new evolutionary algorithm. Optimization of a continuous objective function is analogous to searching for high fitness phenotypes on a fitness landscape. We describe how natural selection moves a population along the non-Euclidean gradient that is induced by the population on the fitness landscape (the natural gradient). We show how selection is related to Newton’s method in optimization under quadratic fitness landscapes, and how selection increases fitness at the cost of reducing diversity. We describe the generation of new phenotypes and introduce an operator that recombines the whole population to generate variants. Finally, we introduce a proof-of-principle algorithm that combines natural selection, our recombination operator, and an adaptive method to increase selection and find the optimum. The algorithm is extremely simple in implementation; it has no matrix inversion or factorization, does not require storing a covariance matrix, and may form the basis of more general model-based optimization algorithms with natural gradient updates.

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Nowak, Stefan, and Joachim Krug. "Analysis of adaptive walks on NK fitness landscapes with different interaction schemes." Journal of Statistical Mechanics: Theory and Experiment 2015, no. 6 (June 10, 2015): P06014. http://dx.doi.org/10.1088/1742-5468/2015/06/p06014.

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Kumai, William. "Adaptive Walks and Fitness Peak Climbing: Language Learning as Inducing Adaptive Change in L2 Systems." Nagoya JALT Journal 1, no. 1 (June 29, 2020): 29–42. http://dx.doi.org/10.37546/jaltchap.nagoya1.1-2.

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This paper adopts the perspective of students, groups, and entire classes as being complex adaptive systems, or CAS. Two important concepts from complexity theory, adaptive walks and fitness landscapes, can be used to create optimal language learning conditions for producing changes in students’ L2 systems. Every configuration of L2 traits a student might have can be assigned a fitness value, that is, an L2 competence level. The set of all such values creates an abstract landscape, the fitness landscape. By changing traits, the position on the landscape changes, meaning a student can take a journey on the landscape, known as an adaptive walk, in the search for higher peaks, that is, higher competence. The goal becomes establishing conditions in which adaptive walks are encouraged. Several L2 activities are introduced as applications of these ideas. 学生、グループ、およびクラス全体は、複雑系適応システムと考えられる。複雑系理論における2つの概念、アダプティブ・ウォーク(適応型歩行)とフィットネス・ランドスケープは、言語学習に最適な条件を創り出す一助となる。それぞれの学生は皆、文法や発音など異なるレベルのL2 スキルを保有している。これらのスキルを組み合わせることで全体的な L2 能力すなわちフィットネス・バリューを生み出すことが可能となる。このような異なるレベルの組み合わせによる全てのユニットとそれに伴うフィットネス・バリューはフィットネス・ランドスケーブ(適応度地形)を創りだす。ある L2 スキルが向上または低下する時、フィットネス・バリューは変化する。それによってランドスケープ上の位置が変化する。スキルのレベル変化を通じて学生はアダプティブ・ウォークとして知られるランドスケープを旅する。旅の到達目標は、アダプティブ・ウォークを奨励してランドスケープ上の高位のフィットネルピークを見出すことである。これらの理念の応用としていくつかの L2 アクティビティを導入する。

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Kauffman, Stuart A. "Cambrian explosion and Permian quiescence: implications of rugged fitness landscapes." Paleontological Society Special Publications 6 (1992): 160. http://dx.doi.org/10.1017/s2475262200007206.

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The Cambrian explosion witnessed the formation of a large number of the higher taxa extant today. The higher taxa are said to have “filled in” from the top down, with species that found phyla giving rise to daughter species which found classes, then orders, and so on. During the Permian extinction, in contrast, 96% of all species go extinct. During the rebound, a large number of new families are created, a few new orders are created, but no new phyla are created. The higher taxa are said to have “filled in” from the bottom up. The profound asymmetry between the Cambrian and Permian has been a deep puzzle. I shall suggest that this asymmetry is a nearly inevitable consequence of adaptive evolution on rugged, multipeaked fitness landscapes.

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Camus, M. Florencia, Kevin Fowler, Matthew W. D. Piper, and Max Reuter. "Sex and genotype effects on nutrient-dependent fitness landscapes in Drosophila melanogaster." Proceedings of the Royal Society B: Biological Sciences 284, no. 1869 (December 20, 2017): 20172237. http://dx.doi.org/10.1098/rspb.2017.2237.

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The sexes perform different reproductive roles and have evolved sometimes strikingly different phenotypes. One focal point of adaptive divergence occurs in the context of diet and metabolism, and males and females of a range of species have been shown to require different nutrients to maximize their fitness. Biochemical analyses in Drosophila melanogaster have confirmed that dimorphism in dietary requirements is associated with molecular sex differences in metabolite titres. In addition, they also showed significant within-sex genetic variation in the metabolome. To date however, it is unknown whether this metabolic variation translates into differences in reproductive fitness. The answer to this question is crucial to establish whether genetic variation is selectively neutral or indicative of constraints on sex-specific physiological adaptation and optimization. Here we assay genetic variation in consumption and metabolic fitness effects by screening male and female fitness of thirty D. melanogaster genotypes across four protein-to-carbohydrate ratios. In addition to confirming sexual dimorphism in consumption and fitness, we find significant genetic variation in male and female dietary requirements. Importantly, these differences are not explained by feeding responses and probably reflect metabolic variation that, in turn, suggests the presence of genetic constraints on metabolic dimorphism.

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Agarwala, Atish, and Daniel S. Fisher. "Adaptive walks on high-dimensional fitness landscapes and seascapes with distance-dependent statistics." Theoretical Population Biology 130 (December 2019): 13–49. http://dx.doi.org/10.1016/j.tpb.2019.09.011.

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Capblancq, Thibaut, Matthew C. Fitzpatrick, Rachael A. Bay, Moises Exposito-Alonso, and Stephen R. Keller. "Genomic Prediction of (Mal)Adaptation Across Current and Future Climatic Landscapes." Annual Review of Ecology, Evolution, and Systematics 51, no. 1 (November 2, 2020): 245–69. http://dx.doi.org/10.1146/annurev-ecolsys-020720-042553.

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Signals of local adaptation have been found in many plants and animals, highlighting the heterogeneity in the distribution of adaptive genetic variation throughout species ranges. In the coming decades, global climate change is expected to induce shifts in the selective pressures that shape this adaptive variation. These changes in selective pressures will likely result in varying degrees of local climate maladaptation and spatial reshuffling of the underlying distributions of adaptive alleles. There is a growing interest in using population genomic data to help predict future disruptions to locally adaptive gene-environment associations. One motivation behind such work is to better understand how the effects of changing climate on populations’ short-term fitness could vary spatially across species ranges. Here we review the current use of genomic data to predict the disruption of local adaptation across current and future climates. After assessing goals and motivationsunderlying the approach, we review the main steps and associated statistical methods currently in use and explore our current understanding of the limits and future potential of using genomics to predict climate change (mal)adaptation.

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Reiss, John O. "Relative Fitness, Teleology, and the Adaptive Landscape." Evolutionary Biology 34, no. 1-2 (July 14, 2007): 4–27. http://dx.doi.org/10.1007/s11692-007-9000-9.

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Leprêtre, Florian, Cyril Fonlupt, Sébastien Verel, Virginie Marion, Rolando Armas, Hernán Aguirre, and Kiyoshi Tanaka. "Fitness landscapes analysis and adaptive algorithms design for traffic lights optimization on SIALAC benchmark." Applied Soft Computing 85 (December 2019): 105869. http://dx.doi.org/10.1016/j.asoc.2019.105869.

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Hartman, Stefan. "Towards adaptive tourism areas: using fitness landscapes for managing and futureproofing tourism area development." Journal of Tourism Futures 4, no. 2 (June 2018): 152–62. http://dx.doi.org/10.1108/jtf-03-2018-0009.

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Leushkin, Evgeny V., Georgii A. Bazykin, and Alexey S. Kondrashov. "Insertions and deletions trigger adaptive walks in Drosophila proteins." Proceedings of the Royal Society B: Biological Sciences 279, no. 1740 (March 28, 2012): 3075–82. http://dx.doi.org/10.1098/rspb.2011.2571.

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Maps that relate all possible genotypes or phenotypes to fitness—fitness landscapes—are central to the evolution of life, but remain poorly known. An insertion or a deletion (indel) of one or several amino acids constitutes a substantial leap of a protein within the space of amino acid sequences, and it is unlikely that after such a leap the new sequence corresponds precisely to a fitness peak. Thus, one can expect an indel in the protein-coding sequence that gets fixed in a population to be followed by some number of adaptive amino acid substitutions, which move the new sequence towards a nearby fitness peak. Here, we study substitutions that occur after a frame-preserving indel in evolving proteins of Drosophila . An insertion triggers 1.03 ± 0.75 amino acid substitutions within the protein region centred at the site of insertion, and a deletion triggers 4.77 ± 1.03 substitutions within such a region. The difference between these values is probably owing to a higher fraction of effectively neutral insertions. Almost all of the triggered amino acid substitutions can be attributed to positive selection, and most of them occur relatively soon after the triggering indel and take place upstream of its site. A high fraction of substitutions that follow an indel occur at previously conserved sites, suggesting that an indel substantially changes selection that shapes the protein region around it. Thus, an indel is often followed by an adaptive walk of length that is in agreement with the theory of molecular adaptation.

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Park, Su-Chan, Johannes Neidhart, and Joachim Krug. "Greedy adaptive walks on a correlated fitness landscape." Journal of Theoretical Biology 397 (May 2016): 89–102. http://dx.doi.org/10.1016/j.jtbi.2016.02.035.

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Barton, N. H., and Michael Turelli. "Adaptive landscapes, genetic distance and the evolution of quantitative characters." Genetical Research 49, no. 2 (April 1987): 157–73. http://dx.doi.org/10.1017/s0016672300026951.

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SummaryThe maintenance of polygenic variability by a balance between mutation and stabilizing selection has been analysed using two approximations: the ‘Gaussian’ and the ‘house of cards’. These lead to qualitatively different relationships between the equilibrium genetic variance and the parameters describing selection and mutation. Here we generalize these approximations to describe the dynamics of genetic means and variances under arbitrary patterns of selection and mutation. We incorporate genetic drift into the same mathematical framework.The effects of frequency-independent selection and genetic drift can be determined from the gradient of log mean fitness and a covariance matrix that depends on genotype frequencies. These equations describe an ‘adaptive landscape’, with a natural metric of genetic distance set by the covariance matrix. From this representation we can change coordinates to derive equations describing the dynamics of an additive polygenic character in terms of the moments (means, variances, …) of allelic effects at individual loci. Only under certain simplifying conditions, such as those derived from the Gaussian and house-of-cards approximations, do these general recursions lead to tractable equations for the first few phenotypic moments. The alternative approximations differ in the constraints they impose on the distributions of allelic effects at individual loci. The Gaussian-based prediction that evolution of the phenotypic mean does not change the genetic variance is shown to be a consequence of the assumption that the allelic distributions are never skewed. We present both analytical and numerical results delimiting the parameter values consistent with our approximations.

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EBELING, W., and A. SCHARNHORST. "DYNAMICS OF ECONOMIC AND TECHNOLOGICAL SEARCH PROCESSES IN COMPLEX ADAPTIVE LANDSCAPES." Advances in Complex Systems 04, no. 01 (March 2001): 71–88. http://dx.doi.org/10.1142/s0219525901000139.

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We investigate the dynamics of economic evolution and technological change as hill-climbing in an adaptive landscape over a continuous characteristics space. A technology/firm is described by a large number of attributes or characteristics representing technology-inherent aspects, financial, organizational and economic features. These parameters span a characteristics space, which is a real Euclidean vector space, in analogy to the phenotype space in biology. Further we define a real-valued multimodal fitness function/functional and a population density over the characteristics space. The evolutionary dynamics including competition and mutations/innovations is modeled by reaction-diffusion equations of Fisher–Eigen or Lotka–Volterra type. We demonstrate the potential of such models, which in certain aspects go beyond the widespread applications of discrete replicator dynamics. Concerning technological change the emergence of technological populations as the result of a search process in an adaptive landscape will be investigated. In particular, the relation between incremental and radical innovations will be considered, especially the apparent paradox of a discrete continuum of technological change. Further, an application of the developed framework to the assessment of firms in the stock market is discussed.

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Gorton, Amanda J., David A. Moeller, and Peter Tiffin. "Little plant, big city: a test of adaptation to urban environments in common ragweed ( Ambrosia artemisiifolia )." Proceedings of the Royal Society B: Biological Sciences 285, no. 1881 (June 27, 2018): 20180968. http://dx.doi.org/10.1098/rspb.2018.0968.

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A full understanding of how cities shape adaptation requires characterizing genetically-based phenotypic and fitness differences between urban and rural populations under field conditions. We used a reciprocal transplant experiment with the native plant common ragweed, ( Ambrosia artemisiifolia ), and found that urban and rural populations have diverged in flowering time, a trait that strongly affects fitness. Although urban populations flowered earlier than rural populations, plants growing in urban field sites flowered later than plants in rural field sites. This counter-gradient variation is consistent adaptive divergence between urban and rural populations. Also consistent with local adaptation, both urban and rural genotypes experienced stronger net selection in the foreign than in the local habitat, but this pattern was not significant for male fitness. Despite the evidence for local adaptation, rural populations had higher lifetime fitness at all sites, suggesting that selection has been stronger or more uniform in rural than urban populations. We also found that inter-population differences in both flowering time and fitness tended to be greater among urban than rural populations, which is consistent with greater drift or spatial variation in selection within urban environments. In summary, our results are consistent with adaptive divergence of urban and rural populations, but also suggest there may be greater environmental heterogeneity in urban environments which also affects evolution in urban landscapes.

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Nahum, Joshua R., Peter Godfrey-Smith, Brittany N. Harding, Joseph H. Marcus, Jared Carlson-Stevermer, and Benjamin Kerr. "A tortoise–hare pattern seen in adapting structured and unstructured populations suggests a rugged fitness landscape in bacteria." Proceedings of the National Academy of Sciences 112, no. 24 (May 11, 2015): 7530–35. http://dx.doi.org/10.1073/pnas.1410631112.

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In the context of Wright’s adaptive landscape, genetic epistasis can yield a multipeaked or “rugged” topography. In an unstructured population, a lineage with selective access to multiple peaks is expected to fix rapidly on one, which may not be the highest peak. In a spatially structured population, on the other hand, beneficial mutations take longer to spread. This slowdown allows distant parts of the population to explore the landscape semiindependently. Such a population can simultaneously discover multiple peaks, and the genotype at the highest discovered peak is expected to dominate eventually. Thus, structured populations sacrifice initial speed of adaptation for breadth of search. As in the fable of the tortoise and the hare, the structured population (tortoise) starts relatively slow but eventually surpasses the unstructured population (hare) in average fitness. In contrast, on single-peak landscapes that lack epistasis, all uphill paths converge. Given such “smooth” topography, breadth of search is devalued and a structured population only lags behind an unstructured population in average fitness (ultimately converging). Thus, the tortoise–hare pattern is an indicator of ruggedness. After verifying these predictions in simulated populations where ruggedness is manipulable, we explore average fitness in metapopulations of Escherichia coli. Consistent with a rugged landscape topography, we find a tortoise–hare pattern. Further, we find that structured populations accumulate more mutations, suggesting that distant peaks are higher. This approach can be used to unveil landscape topography in other systems, and we discuss its application for antibiotic resistance, engineering problems, and elements of Wright’s shifting balance process.

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Geoghegan, Jemma L., Alistair M. Senior, and Edward C. Holmes. "Pathogen population bottlenecks and adaptive landscapes: overcoming the barriers to disease emergence." Proceedings of the Royal Society B: Biological Sciences 283, no. 1837 (August 31, 2016): 20160727. http://dx.doi.org/10.1098/rspb.2016.0727.

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Emerging diseases are a major challenge to public health. Revealing the evolutionary processes that allow novel pathogens to adapt to new hosts, also the potential barriers to host adaptation, is central to understanding the drivers of disease emergence. In particular, it is unclear how the genetics and ecology of pathogens interact to shape the likelihood of successful cross-species transmission. To better understand the determinants of host adaptation and emergence, we modelled key aspects of pathogen evolutionary dynamics at both intra- and inter-host scales, using parameter values similar to those observed in influenza virus. We considered the possibility of acquiring the necessary host adaptive mutations both before (‘off-the-shelf’ emergence) and after (‘tailor-made’ emergence) a virus is transmitted from a donor to a new recipient species. Under both scenarios, population bottlenecks at inter-host transmission act as a major barrier to host adaptation, greatly limiting the number of adaptive mutations that are able to cross the species barrier. In addition, virus emergence is hindered if the fitness valley between the donor and recipient hosts is either too steep or too shallow. Overall, our results reveal where in evolutionary parameter space a virus could adapt to and become transmissible in a new species.

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Journal articles on the topic 'Adaptive or fitness landscapes'

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