scholarly journals Evolution of clonal populations approaching a fitness peak

2013 ◽  
Vol 9 (1) ◽  
pp. 20120239 ◽  
Author(s):  
Isabel Gordo ◽  
Paulo R. A. Campos
Keyword(s):  
Genetic Background ◽  
Fitness Landscape ◽  
Phenotypic Diversity ◽  
Geometrical Model ◽  
Rate Of Molecular Evolution ◽  
Environmental Variations ◽  
Novel Environments ◽  
Negative Epistasis ◽  
Mean Population Fitness ◽  
New Mutations

Populations facing novel environments are expected to evolve through the accumulation of adaptive substitutions. The dynamics of adaptation depend on the fitness landscape and possibly on the genetic background on which new mutations arise. Here, we model the dynamics of adaptive evolution at the phenotypic and genotypic levels, focusing on a Fisherian landscape characterized by a single peak. We find that Fisher's geometrical model of adaptation, extended to allow for small random environmental variations, is able to explain several features made recently in experimentally evolved populations. Consistent with data on populations evolving under controlled conditions, the model predicts that mean population fitness increases rapidly when populations face novel environments and then achieves a dynamic plateau, the rate of molecular evolution is remarkably constant over long periods of evolution, mutators are expected to invade and patterns of epistasis vary along the adaptive walk. Negative epistasis is expected in the initial steps of adaptation but not at later steps, a prediction that remains to be tested. Furthermore, populations are expected to exhibit high levels of phenotypic diversity at all times during their evolution. This implies that populations are possibly able to adapt rapidly to novel abiotic environments.

scholarly journals On the (un-)predictability of a large intragenic fitness landscape

2016 ◽  
Author(s):  
Claudia Bank ◽  
Sebastian Matuszewski ◽  
Ryan T. Hietpas ◽  
Jeffrey D. Jensen
Keyword(s):  
Amino Acid ◽  
Fitness Landscape ◽  
Fitness Landscapes ◽  
Specific Information ◽  
Theoretical Approaches ◽  
Elevated Salinity ◽  
Theoretical Predictions ◽  
Experimental Approaches ◽  
Deterministic Processes ◽  
Negative Epistasis

AbstractThe study of fitness landscapes, which aims at mapping genotypes to fitness, is receiving ever-increasing attention. Novel experimental approaches combined with NGS methods enable accurate and extensive studies of the fitness effects of mutations – allowing us to test theoretical predictions and improve our understanding of the shape of the true underlying fitness landscape, and its implications for the predictability and repeatability of evolution.Here, we present a uniquely large multi-allelic fitness landscape comprised of 640 engineered mutants that represent all possible combinations of 13 amino-acid changing mutations at six sites in the heat-shock protein Hsp90 in Saccharomyces cerevisiae under elevated salinity. Despite a prevalent pattern of negative epistasis in the landscape, we find that the global fitness peak is reached via four positively epistatic mutations. Combining traditional and extending recently proposed theoretical and statistical approaches, we quantify features of the global multi-allelic fitness landscape. Using subsets of the data, we demonstrate that extrapolation beyond a known part of the landscape is difficult owing to both local ruggedness and amino-acid specific epistatic hotspots, and that inference is additionally confounded by the non-random choice of mutations for experimental fitness landscapes.Author SummaryThe study of fitness landscapes is fundamentally concerned with understanding the relative roles of stochastic and deterministic processes in adaptive evolution. Here, the authors present a uniquely large and complete multi-allelic intragenic fitness landscape of 640 systematically engineered mutations in yeast Hsp90. Using a combination of traditional and recently proposed theoretical approaches, they study the accessibility of the global fitness peak, and the potential for predictability of the fitness landscape topography. They report local ruggedness of the landscape and the existence of epistatic hotspot mutations, which together make extrapolation and hence predictability inherently difficult, if mutation-specific information is not considered.

scholarly journals EPISTASIS BETWEEN NEW MUTATIONS AND GENETIC BACKGROUND AND A TEST OF GENETIC CANALIZATION

Evolution ◽  
2001 ◽  
Vol 55 (9) ◽  
pp. 1746-1752 ◽  
Author(s):  
Santiago F. Elena ◽  
Richard E. Lenski
Keyword(s):  
Genetic Background ◽  
New Mutations

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

2016 ◽  
Author(s):  
Mark Jayson V. Cortez ◽  
Jomar F. Rabajante ◽  
Jerrold M. Tubay ◽  
Ariel L. Babierra
Keyword(s):  
Regulatory Networks ◽  
Fitness Landscape ◽  
Phenotypic Diversity ◽  
Oscillatory Behavior ◽  
Epigenetic Landscape ◽  
Negative Frequency Dependent Selection ◽  
Gene Regulatory ◽  
Epigenetic Gene Regulation ◽  
Phenotypic Fitness ◽  
The Red Queen

AbstractThe 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.

scholarly journals Evolutionary learning of adaptation to varying environments through a transgenerational feedback

2016 ◽  
Vol 113 (40) ◽  
pp. 11266-11271 ◽  
Author(s):  
BingKan Xue ◽  
Stanislas Leibler
Keyword(s):  
Phenotypic Diversity ◽  
Epigenetic Inheritance ◽  
Model Organisms ◽  
Evolutionary Learning ◽  
Bet Hedging ◽  
Learning Mechanism ◽  
Environmental Variations ◽  
Varying Environments ◽  
Varying Environment

Organisms can adapt to a randomly varying environment by creating phenotypic diversity in their population, a phenomenon often referred to as “bet hedging.” The favorable level of phenotypic diversity depends on the statistics of environmental variations over timescales of many generations. Could organisms gather such long-term environmental information to adjust their phenotypic diversity? We show that this process can be achieved through a simple and general learning mechanism based on a transgenerational feedback: The phenotype of the parent is progressively reinforced in the distribution of phenotypes among the offspring. The molecular basis of this learning mechanism could be searched for in model organisms showing epigenetic inheritance.

scholarly journals The Population Genetics of Adaptation: Multiple Substitutions on a Smooth Fitness Landscape

Genetics ◽  
2009 ◽  
Vol 183 (3) ◽  
pp. 1079-1086 ◽  
Author(s):  
Robert L. Unckless ◽  
H. Allen Orr
Keyword(s):  
Population Genetics ◽  
Recent Work ◽  
Adaptive Evolution ◽  
Theoretical Study ◽  
Fitness Landscape ◽  
Selective Advantage ◽  
Analytic Solutions ◽  
Strong Selection ◽  
Genetics Of Adaptation ◽  
New Mutations

Much recent work in the theoretical study of adaptation has focused on the so-called strong selection–weak mutation (SSWM) limit, wherein adaptation is due to new mutations of definite selective advantage. This work, in turn, has focused on the first step (substitution) during adaptive evolution. Here we extend this theory to allow multiple steps during adaptation. We find analytic solutions to the probability that adaptation follows a certain path during evolution as well as the probability that adaptation arrives at a given genotype regardless of the path taken. We also consider the probability of parallel adaptation and the proportion of the total increase in fitness caused by the first substitution. Our key assumption is that there is no epistasis among beneficial mutations.

Interaction of Selection, Mutation, and Drift

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Mutation Rate ◽  
Allele Frequencies ◽  
Deleterious Mutations ◽  
Perfect Adaptation ◽  
Optimal Value ◽  
Selective Effects ◽  
Mean Population Fitness ◽  
New Mutations ◽  
Population Fitness ◽  
As If

This chapter examines the joint impact of selection, mutation, and drift on the allele frequencies at a locus. One key finding is that if the strength of selection is sufficiently weak relative to drift, alleles behave as if they are effectively neutral. Hence, as a population attempts to evolve toward some ideal (optimal) value, the beneficial increment from new mutations eventually becomes sufficiently weak (relative to drift) they are efficiently neutral, implying that perfect adaptation is never possible. This is the notion of the drift barrier. Another key ideal is Haldane's principle: the decline in mean population fitness generated by deleterious mutations is largely independent of their selective effects, but instead is simply a function of their mutation rate.

scholarly journals Compensatory mutations modulate the competitiveness and dynamics of plasmid-mediated colistin resistance in Escherichia coli clones

2020 ◽  
Vol 14 (3) ◽  
pp. 861-865 ◽  
Author(s):  
Qiu E. Yang ◽  
Craig MacLean ◽  
Andrei Papkou ◽  
Manon Pritchard ◽  
Lydia Powell ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Fitness Landscape ◽  
Fitness Cost ◽  
Colistin Resistance ◽  
Bacterial Populations ◽  
Compensatory Evolution ◽  
Neutral Mutations ◽  
The Cost ◽  
Negative Epistasis

AbstractThe emergence of mobile colistin resistance (mcr) threatens to undermine the clinical efficacy of the last antibiotic that can be used to treat serious infections caused by Gram-negative pathogens. Here we measure the fitness cost of a newly discovered MCR-3 using in vitro growth and competition assays. mcr-3 expression confers a lower fitness cost than mcr-1, as determined by competitive ability and cell viability. Consistent with these findings, plasmids carrying mcr-3 have higher stability than mcr-1 plasmids across a range of Escherichia coli strains. Crucially, mcr-3 plasmids can stably persist, even in the absence of colistin. Recent compensatory evolution has helped to offset the cost of mcr-3 expression, as demonstrated by the high fitness of mcr-3.5 as opposed to mcr-3.1. Reconstructing all of the possible evolutionary trajectories from mcr-3.1 to mcr-3.5 reveals a complex fitness landscape shaped by negative epistasis between compensatory and neutral mutations. Our findings highlight the importance of fitness costs and compensatory evolution in driving the dynamics and stability of mobile colistin resistance in bacterial populations, and they highlight the need to understand how processes (other than colistin use) impact mcr dynamics.

scholarly journals Learning Monotonic Genotype-Phenotype Maps

2011 ◽  
Vol 10 (1) ◽  
Author(s):  
Niko Beerenwinkel ◽  
Patrick Knupfer ◽  
Achim Tresch
Keyword(s):  
Immune Responses ◽  
Genetic Background ◽  
Selective Pressure ◽  
Fitness Landscape ◽  
Simulated Data ◽  
Genetic Alterations ◽  
Resistance Mutations ◽  
Medical Interventions ◽  
Resistance Data ◽  
Genetic Events

Evolutionary escape of pathogens from the selective pressure of immune responses and from medical interventions is driven by the accumulation of mutations. We introduce a statistical model for jointly estimating the dynamics and dependencies among genetic alterations and the associated phenotypic changes. The model integrates conjunctive Bayesian networks, which define a partial order on the occurrences of genetic events, with isotonic regression. The resulting genotype-phenotype map is non-decreasing in the lattice of genotypes. It describes evolutionary escape as a directed process following a phenotypic gradient, such as a monotonic fitness landscape. We present efficient algorithms for parameter estimation and model selection. The model is validated using simulated data and applied to HIV drug resistance data. We find that the effect of many resistance mutations is non-linear and depends on the genetic background in which they occur.

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