scholarly journals Lexical landscapes as largein silicodata for examining advanced properties of fitness landscapes

2019 ◽  
Author(s):  
Victor A. Meszaros ◽  
Miles D. Miller-Dickson ◽  
C. Brandon Ogbunugafor
Keyword(s):  
Evolutionary Theory ◽  
Empirical Data ◽  
In Silico ◽  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Evolutionary Genetics ◽  
Higher Order ◽  
Fitness Landscapes ◽  
Adaptive Landscape ◽  
Data Sets

In silicoapproaches have served a central role in the development of evolutionary theory for generations. This especially applies to the concept of the fitness landscape, one of the most important abstractions in evolutionary genetics, and one which has benefited from the presence of large empirical data sets only in the last decade or so. In this study, we propose a method that allows us to generate enormous data sets that walk the line betweenin silicoand empirical: word usage frequencies as catalogued by the Google ngram corpora. These data can be codified or analogized in terms of a multidimensional empirical fitness landscape towards the examination of advanced concepts—adaptive landscape by environment interactions, clonal competition, higher-order epistasis and countless others. We argue that the greaterLexical Landscapesapproach can serve as a platform that offers an astronomical number of fitness landscapes for exploration (at least) or theoretical formalism (potentially) in evolutionary biology.

scholarly journals Inferring genetic interactions from comparative fitness data

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Kristina Crona ◽  
Alex Gavryushkin ◽  
Devin Greene ◽  
Niko Beerenwinkel
Keyword(s):  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Higher Order ◽  
Complete Characterization ◽  
Genetic Interactions ◽  
Gene Interactions ◽  
Rank Orders ◽  
Darwinian Fitness ◽  
Parasite Plasmodium

Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax, the fungus Aspergillus niger, and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.

scholarly journals Evolution and development: some insights from evolutionary theory

2001 ◽  
Vol 73 (3) ◽  
pp. 385-395 ◽  
Author(s):  
JEAN R. DAVID
Keyword(s):  
Evolutionary Theory ◽  
Evolutionary Biology ◽  
Evolutionary Genetics ◽  
Developmental Genetics ◽  
Homologous Genes ◽  
Evolution And Development ◽  
Evo Devo ◽  
Why Questions ◽  
The 19Th Century ◽  
Novel Structures

Developmental biology and evolutionary biology are both mature integrative disciplines which started in the 19th century and then followed parallel and independent scientific pathways. Recently, a genetical component has stepped into both disciplines (developmental genetics and evolutionary genetics) pointing out the need for future convergent maturation. Indeed, the Evo-Devo approach is becoming popular among developmental biologists, based on the facts that distant groups share a common ancestry, that precise phylogenies can be worked out and that homologous genes often play similar roles during the development of very different organisms. In this essay, I try to show that the real future of Evo-Devo thinking is still broader. The evolutionary theory is a set of diverse concepts which can and should be used in any biological field. Evolutionary thinking trains to ask « why » questions and to provide logical and plausible answers. It can shed some light on a diversity of general problems such as how to distinguish homologies from analogies, the costs and benefits of multicellularity, the origin of novel structures (e.g. the head), or the evolution of sexual reproduction. In the next decade, we may expect a progressive convergence between developmental genetics and quantitative genetics.

scholarly journals The influence of higher-order epistasis on biological fitness landscape topography

2017 ◽  
Author(s):  
Daniel M. Weinreich ◽  
Yinghong Lan ◽  
Jacob Jaffe ◽  
Robert B. Heckendorn
Keyword(s):  
Natural Selection ◽  
Fitness Landscape ◽  
Higher Order ◽  
Fitness Landscapes ◽  
Epistatic Interactions ◽  
Epistatic Effects

AbstractThe effect of a mutation on the organism often depends on what other mutations are already present in its genome. Geneticists refer to such mutational interactions as epistasis. Pairwise epistatic effects have been recognized for over a century, and their evolutionary implications have received theoretical attention for nearly as long. However, pairwise epistatic interactions themselves can vary with genomic background. This is called higher-order epistasis, and its consequences for evolution are much less well understood. Here, we assess the influence that higher-order epistasis has on the topography of 16 published, biological fitness landscapes. We find that on average, their effects on fitness landscape declines with order, and suggest that notable exceptions to this trend may deserve experimental scrutiny. We explore whether natural selection may have contributed to this finding, and conclude by highlight opportunities for further work dissecting the influence that epistasis of all orders has on the efficiency of natural selection.

The Modern Synthesis

2018 ◽  
Author(s):  
Vassiliki Betty Smocovitis
Keyword(s):  
Evolutionary Theory ◽  
Evolutionary Biology ◽  
Biological Diversity ◽  
Evolutionary Genetics ◽  
Modern Synthesis ◽  
Evolutionary Synthesis ◽  
General Nature ◽  
Historical Event ◽  
Ernst Mayr ◽  
Synthetic View

The “modern synthesis” generally refers to the early to mid-century formulation of evolutionary theory that reconciled classical Darwinian selection theory with a newer population-oriented view of Mendelian genetics that attempted to explain the origin of biological diversity. It draws on the title of zoologist Julian S. Huxley’s book of 1943 titled Evolution: The Modern Synthesis, a semi-popular account of evolution that ushered in this “modern” synthetic view of evolution. Covering an interval of time approximately between 1920–1950, it also refers to developments in understanding evolution that drew on a range of disciplines that were synthesized or brought to consensus that generally include systematics, paleontology, and botany with a populational view of evolutionary genetics. Whether or not it served to unify the study of evolution, or to unify the disparate biological sciences—and whether or not it led to the emergence of a science of evolutionary biology, as some of its proponents have claimed—remains a topic for discussion. Though they do not refer to precisely the same things or share identical meanings, the phrase “modern synthesis” has overlapped with terms such as the “evolutionary synthesis,” coined and used especially by Ernst Mayr and William B. Provine, to refer to the historical event, as well as terms such as Neo-Darwinian theory or Neo-Darwinism (though criticism has been made regarding the latter term’s applicability to the mid-century developments in evolutionary theory). As Ernst Mayr noted, the term “Neo-Darwinism” was first coined and used by George John Romanes in 1895 to refer to a revision of Charles Darwin’s theory first formulated in 1859, which included Lamarckian inheritance. The extent to which the modern synthesis, and the evolutionary synthesis map with what is also called the synthetic theory, is open for discussion as is specific understanding of the term. For the most part, there is little in the way of consensus or agreement by scientists, philosophers, and historians as to what “the synthesis” (the abbreviated reference) precisely means, and what (if anything) specifically occurred of a general nature in studies of evolution, broadly construed, in the interval of time between 1920–1950.

scholarly journals Recombination and mutational robustness in neutral fitness landscapes

2019 ◽  
Author(s):  
Alexander Klug ◽  
Su-Chan Park ◽  
Joachim Krug
Keyword(s):  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Genetic Recombination ◽  
Fitness Landscapes ◽  
Point Of View ◽  
Genetic Exchange ◽  
Favorable Effect ◽  
Minor Effect ◽  
Moderate Increase ◽  
Mutational Robustness

AbstractMutational robustness quantifies the effect of random mutations on fitness. When mutational robustness is high, most mutations do not change fitness or have only a minor effect on it. From the point of view of fitness landscapes, robust genotypes form neutral networks of almost equal fitness. Using deterministic population models it has been shown that selection favors genotypes inside such networks, which results in increased mutational robustness. Here we demonstrate that this effect is massively enhanced by recombination. Our results are based on a detailed analysis of mesa-shaped fitness landscapes, where we derive precise expressions for the dependence of the robustness on the landscape parameters for recombining and non-recombining populations. In addition, we carry out numerical simulations on different types of random holey landscapes as well as on an empirical fitness landscape. We show that the mutational robustness of a genotype generally correlates with its recombination weight, a new measure that quantifies the likelihood for the genotype to arise from recombination. We argue that the favorable effect of recombination on mutational robustness is a highly universal feature that may have played an important role in the emergence and maintenance of mechanisms of genetic exchange.Author summaryTwo long-standing and seemingly unrelated puzzles in evolutionary biology concern the ubiquity of sexual reproduction and the robustness of organisms against genetic perturbations. Using a theoretical approach based on the concept of a fitness landscape, in this article we argue that the two phenomena may in fact be closely related. In our setting the hereditary information of an organism is encoded in its genotype, which determines it to be either viable or non-viable, and robustness is defined as the fraction of mutations that maintain viability. Previous work has demonstrated that the purging of non-viable genotypes from the population by natural selection leads to a moderate increase in robustness. Here we show that genetic recombination acting in combination with selection massively enhances this effect, an observation that is largely independent of how genotypes are connected by mutations. This suggests that the increase of robustness may be a major driver underlying the evolution of sexual recombination and other forms of genetic exchange throughout the living world.

scholarly journals Genotypic context modulates fitness landscapes: Effects on the speed and direction of evolution for antimicrobial resistance

2018 ◽  
Author(s):  
C. Brandon Ogbunugafor ◽  
Rafael F. Guerrero ◽  
Margaret J. Eppstein
Keyword(s):  
Public Health ◽  
Drug Resistance ◽  
Antimicrobial Resistance ◽  
Adaptive Evolution ◽  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Genetic Differences ◽  
Fitness Landscapes ◽  
Bacterial Enzyme ◽  
Pathogen Populations

AbstractUnderstanding the forces that drive the dynamics of adaptive evolution is a goal of many subfields within evolutionary biology. The fitness landscape analogy has served as a useful abstraction for addressing these topics across many systems, and recent treatments have revealed how different environments can frame the particulars of adaptive evolution by changing the topography of fitness landscapes. In this study, we examine how the larger, ambient genotypic context in which the fitness landscape being modeled is embedded affects fitness landscape topography and subsequent evolution. Using simulations on empirical fitness landscapes, we discover that genotypic context, defined by genetic variability in regions outside of the locus under study (in this case, an essential bacterial enzyme target of antibiotics), influences the speed and direction of evolution in several surprising ways. These findings have implications for how we study the evolution of drug resistance in nature, and for presumptions about how biological evolution might be expected to occur in genetically-modified organisms. More generally, the findings speak to theory surrounding how “difference can beget difference” in adaptive evolution: that small genetic differences between organisms can greatly alter the specifics of how evolution occurs, which can rapidly drive even slightly diverged populations further apart.Author summaryTechnological advances enable scientists to engineer individual mutations at specific sites within an organism’s genome with increasing ease. These breakthroughs have provided scientists with tools to study how different engineered mutations affect the function of a given gene or protein, yielding useful insight into genotype-phenotype mapping and evolution. In this study, we use engineered strains of bacteria to show how the dynamics (speed and direction) of evolution of drug resistance in an enzyme depends on the species-type of that bacterial enzyme, and on the presence/absence of mutations in other genes in the bacterial genome. These findings have broad implications for public health, genetic engineering, and theories of speciation. In the context of public health and biomedicine, our results suggest that future efforts in managing antimicrobial resistance must consider genetic makeup of different pathogen populations before predicting how resistance will occur, rather than assuming that the same resistance pathways will appear in different pathogen populations. With regard to broader theory in evolutionary biology, our results show how even small genetic differences between organisms can alter how future evolution occurs, potentially causing closely-related populations to quickly diverge.

scholarly journals Effect of Host Species on Topography of the Fitness Landscape for a Plant RNA Virus

2016 ◽  
Vol 90 (22) ◽  
pp. 10160-10169 ◽  
Author(s):  
Héctor Cervera ◽  
Jasna Lalić ◽  
Santiago F. Elena
Keyword(s):  
Host Species ◽  
Evolutionary Biology ◽  
Evolutionary Dynamics ◽  
Fitness Landscape ◽  
Rna Virus ◽  
Fitness Landscapes ◽  
Content Type ◽  
Fine Grained ◽  
Novel Host ◽  
Fitness Tradeoffs

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.

scholarly journals Field manipulation of competition among hybrids reveals dynamic and highly stable features of a complex fitness landscape driving adaptive radiation

2019 ◽  
Author(s):  
Christopher H. Martin ◽  
Katelyn Gould
Keyword(s):  
Adaptive Radiation ◽  
Prey Capture ◽  
Fitness Landscape ◽  
Fitness Landscapes ◽  
Competitive Environment ◽  
Adaptive Landscape ◽  
Dynamic Features ◽  
Environmental Variance ◽  
San Salvador ◽  
Independent Field

AbstractThe effect of the environment on fitness in natural populations is a fundamental question in evolutionary biology. However, experimental manipulations of environment and phenotype are rare. Thus, the relative importance of the competitive environment versus intrinsic organismal performance in shaping the location, height, and fluidity of fitness peaks and valleys remains largely unknown. We experimentally tested the effect of competitive environment on the fitness landscape driving the evolution of novelty in a sympatric adaptive radiation of a generalist and two trophic specialist pupfishes, a scale-eater and molluscivore, endemic to San Salvador Island, Bahamas. We manipulated phenotypes, by generating 2,611 F4/F5 lab-reared hybrids, and competitive environment, by altering frequencies of rare phenotypes between high- and low-frequency field enclosures, then tracked hybrid survival in two natural lake populations on San Salvador. We found no evidence of frequency-dependent effects on survival fitness landscapes, indicating robustness to the competitive environment. Although survival surfaces favored alternate phenotypes between lakes, joint fitness estimation across lake environments supported multiple fitness peaks for generalist and molluscivore phenotypes and a large fitness valley isolating the most divergent scale-eater phenotype, strikingly similar to a previous independent field experiment. The consistency of this complex fitness landscape across competitive environments, multivariate trait axes, and spatiotemporal heterogeneity provides surprising evidence of stasis in major features of fitness landscapes despite substantial environmental variance, possibly due to absolute biomechanical constraints on diverse prey capture strategies within this radiation. These results challenge competitive speciation theory and highlight the interplay between organism and environment underlying static and dynamic features of the adaptive landscape.

scholarly journals Inferring Genetic Interactions From Comparative Fitness Data

2017 ◽  
Author(s):  
Kristina Crona ◽  
Alex Gavryushkin ◽  
Devin Greene ◽  
Niko Beerenwinkel
Keyword(s):  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Higher Order ◽  
Complete Characterization ◽  
Genetic Interactions ◽  
Gene Interactions ◽  
Rank Orders ◽  
Darwinian Fitness ◽  
Hiv 1

AbstractDarwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax, the fungus Aspergillus niger, and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.

New Evolutionary Theory Via Simulation

2021 ◽  
pp. 75-96
Author(s):  
Gino Cattani ◽  
Mariano Mastrogiorgio
Keyword(s):  
Technological Innovation ◽  
Evolutionary Theory ◽  
Fitness Landscape ◽  
Simulation Modelling ◽  
Fitness Landscapes ◽  
Number Of Components ◽  
Nk Model ◽  
Technological Adaptation ◽  
Nk Landscapes ◽  
History Friendly Models

Simulation modelling is very common in evolutionary approaches to economics, strategy, and technological innovation. A well-established simulation framework is the NK model of fitness landscapes, which is particularly useful for modelling the processes of technological adaptation, whose difficulty is reflected into how a fitness landscape behaves as a function of the number of components and internal interdependencies of a technology. However, classical NK models become problematic when modelling different types of processes, such as technological exaptation, unless a broader family of NK models is considered. After reviewing the classical NK model, this chapter explores the potential of ‘generalized’ NK landscapes, followed by a review of other important simulation frameworks in evolutionary theory, such as holey landscapes, quantum-like approaches, and history-friendly models.

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