scholarly journals Disentangling eco-evolutionary effects on trait fixation

2018 ◽  
Author(s):  
Peter Czuppon ◽  
Chaitanya S. Gokhale
Keyword(s):  
Evolutionary Dynamics ◽  
Evolutionary Game ◽  
Volterra Model ◽  
Fixation Probability ◽  
Frequency Dependent ◽  
Evolutionary Selection ◽  
Stochastic Fluctuations ◽  
Frequency Independent ◽  
Population Sizes ◽  
Demographic Fluctuations

AbstractIn population genetics, fixation of traits in a demographically changing population under frequency-independent selection has been extensively analysed. In evolutionary game theory, models of fixation have typically focused on fixed population sizes and frequency-dependent selection. A combination of demographic fluctuations with frequency-dependent interactions such as Lotka-Volterra dynamics has received comparatively little attention. We consider a stochastic, competitive Lotka-Volterra model with higher order interactions between two traits. The emerging individual based model allows for stochastic fluctuations in the frequencies of the two traits and the total population size. We calculate the fixation probability of a trait under differing competition coefficients. This fixation probability resembles qualitatively the deterministic evolutionary dynamics. Furthermore, we partially disentangle the selection effects into their ecological and evolutionary components. We find that changing the evolutionary selection strength also changes the population dynamics and vice versa. Thus, a clean separation of the ecological and evolutionary effects is not possible. The entangled eco-evolutionary processes thus cannot be ignored when determining fixation properties in a co-evolutionary system.

scholarly journals How life history can sway the fixation probability of mutants

2016 ◽  
Author(s):  
Xiang-Yi Li ◽  
Shun Kurokawa ◽  
Stefano Giaimo ◽  
Arne Traulsen
Keyword(s):  
Life History ◽  
Age Structure ◽  
Evolutionary Dynamics ◽  
Selective Advantage ◽  
Fixation Probability ◽  
Relative Importance ◽  
Demographic Structure ◽  
Frequency Dependent ◽  
Intermediate Fraction ◽  
Size And Structure

AbstractIn this work, we study the effects of demographic structure on evolutionary dynamics, when selection acts on reproduction, survival, or both. In contrast with the previously discovered pattern that the fixation probability of a neutral mutant decreases while population becomes younger, we show that a mutant with constant selective advantage may have a maximum or a minimum of the fixation probability in populations with an intermediate fraction of young individuals. This highlights the importance of life history and demographic structure in studying evolutionary dynamics. We also illustrate the fundamental differences between selection on reproduction and on survival when age structure is present. In addition, we evaluate the relative importance of size and structure of the population in determining the fixation probability of the mutant. Our work lays the foundation for studying also density and frequency dependent effects in populations when demographic structures cannot be neglected.

scholarly journals Evolutionary dynamics of multiple games

2018 ◽  
Author(s):  
Vandana R. Venkateswaran ◽  
Chaitanya S. Gokhale
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Social Behavior ◽  
Evolutionary Game Theory ◽  
Bacterial Population ◽  
Evolutionary Dynamics ◽  
Evolutionary Game ◽  
Fixation Probability ◽  
Replicator Equation ◽  
Multiple Games

AbstractEvolutionary game theory has been successful in describing phenomena from bacterial population dynamics to the evolution of social behavior. Interactions between individuals are usually captured by a single game. In reality, however, individuals take part in many interactions. Here, we include multiple games and analyze their individual and combined evolutionary dynamics. A typical assumption is that the evolutionary dynamics of individual behavior can be understood by constructing one big comprehensive interactions structure, a single big game. But if any one of the multiple games has more than two strategies, then the combined dynamics cannot be understood by looking only at individual games. Devising a method to study multiple games – where each game could have an arbitrary number of players and strategies – we provide a concise replicator equation, and analyze its resulting dynamics. Moreover, in the case of finite populations, we formulate and calculate a basic and useful property of stochasticity, fixation probability. Our results reveal that even when interactions become incredibly complex, their properties can be captured by relatively simple concepts of evolutionary game(s) theory.

Impact of Frequency Dependence of Gas Labyrinth Seal Rotordynamic Coefficients on Centrifugal Compressor Stability

2010 ◽  
Author(s):  
Giuseppe Vannini ◽  
Manish R. Thorat ◽  
Dara W. Childs ◽  
Mirko Libraschi
Keyword(s):  
Molecular Weight ◽  
Numerical Model ◽  
Control Volume ◽  
Labyrinth Seal ◽  
Labyrinth Seals ◽  
Frequency Dependent ◽  
Rotordynamic Coefficients ◽  
Frequency Independent ◽  
Rotor Surface ◽  
Independent Model

A numerical model developed by Thorat & Childs [1] has indicated that the conventional frequency independent model for labyrinth seals is invalid for rotor surface velocities reaching a significant fraction of Mach 1. A theoretical one-control-volume (1CV) model based on a leakage equation that yields a reasonably good comparison with experimental results is considered in the present analysis. The numerical model yields frequency-dependent rotordynamic coefficients for the seal. Three real centrifugal compressors are analyzed to compare stability predictions with and without frequency-dependent labyrinth seal model. Three different compressor services are selected to have a comprehensive scenario in terms of pressure and molecular weight (MW). The molecular weight is very important for Mach number calculation and consequently for the frequency dependent nature of the coefficients. A hydrogen recycle application with MW around 8, a natural gas application with MW around 18, and finally a propane application with molecular weight around 44 are selected for this comparison. Useful indications on the applicability range of frequency dependent coefficients are given.

scholarly journals Understanding the Evolutionary Games in NSCLC Microenvironment

2020 ◽  
Author(s):  
Ranjini Bhattacharya ◽  
Robert Vander Velde ◽  
Viktoriya Marusyk ◽  
Bina Desai ◽  
Artem Kaznatcheev ◽  
...  
Keyword(s):  
Tumor Cells ◽  
Targeted Therapies ◽  
Evolutionary Dynamics ◽  
Fusion Gene ◽  
Evolutionary Game ◽  
Therapy Resistance ◽  
Resistance Mechanisms ◽  
Intrinsic Resistance ◽  
Frequency Changes

AbstractWhile initially highly successful, targeted therapies eventually fail as populations of tumor cells evolve mechanisms of resistance, leading to resumption of tumor growth. Historically, cell-intrinsic mutational changes have been the major focus of experimental and clinical studies to decipher origins of therapy resistance. While the importance of these mutational changes is undeniable, a growing body of evidence suggests that non-cell autonomous interactions between sub-populations of tumor cells, as well as with non-tumor cells within tumor microenvironment, might have a profound impact on both short term sensitivity of cancer cells to therapies, as well as on the evolutionary dynamics of emergent resistance. In contrast to well established tools to interrogate the functional impact of cell-intrinsic mutational changes, methodologies to understand non-cell autonomous interactions are largely lacking.Evolutionary Game Theory (EGT) is one of the main frameworks to understand the dynamics that drive frequency changes in interacting competing populations with different phenotypic strategies. However, despite a few notable exceptions, the use of EGT to understand evolutionary dynamics in the context of evolving tumors has been largely confined to theoretical studies. In order to apply EGT towards advancing our understanding of evolving tumor populations, we decided to focus on the context of the emergence of resistance to targeted therapies, directed against EML4-ALK fusion gene in lung cancers, as clinical responses to ALK inhibitors represent a poster child of limitations, posed by evolving resistance. To this end, we have examined competitive dynamics between differentially labelled therapy-naïve tumor cells, cells with cell-intrinsic resistance mechanisms, and cells with cell-extrinsic resistance, mediated by paracrine action of hepatocyte growth factor (HGF), within in vitro game assays in the presence or absence of front-line ALK inhibitor alectinib. We found that producers of HGF were the fittest in every pairwise game, while also supporting the proliferation of therapy-naïve cells. Both selective advantage of these producer cells and their impact on total population growth was a linearly increasing function of the initial frequency of producers until eventually reaching a plateau. Resistant cells did not significantly interact with the other two phenotypes. These results provide insights on reconciling selection driven emergence of subpopulations with cell non-cell autonomous resistance mechanisms, with lack of evidence of clonal dominance of these subpopulations. Further, our studies elucidate mechanisms for co-existence of multiple resistance strategies within evolving tumors. This manuscript serves as a technical report and will be followed up with a research paper in a different journal.

scholarly journals Stochastic fluctuations drive non-genetic evolution of proliferation in clonal cancer cell populations

2021 ◽  
Author(s):  
Carmen Ortega-Sabater ◽  
Gabriel Fernandez-Calvo ◽  
Víctor M Pérez-García
Keyword(s):  
Evolutionary Dynamics ◽  
Growth Dynamics ◽  
Driver Mutations ◽  
Organizational Changes ◽  
Tumour Heterogeneity ◽  
Stochastic Fluctuations ◽  
Oncological Patients ◽  
Single Genotype ◽  
History Of ◽  
Broad Variety

Evolutionary dynamics allows to understand many changes happening in a broad variety of biological systems, ranging from individuals to complete ecosystems. It is also behind a number of remarkable organizational changes that happen during the natural history of cancers. These reflect tumour heterogeneity, which is present at all cellular levels, including the genome, proteome and phenome, shaping its development and interrelation with its environment. An intriguing observation in different cohorts of oncological patients is that tumours exhibit an increased proliferation as the disease progresses, while the timescales involved are apparently too short for the fixation of sufficient driver mutations to promote an explosive growth. In this paper we discuss how phenotypic plasticity, emerging from a single genotype, may play a key role and provide a ground for a continuous acceleration of the proliferation rate of clonal populations with time. Here we address this question by means of stochastic and deterministic mathematical models that capture proliferation trait heterogeneity in clonal populations and elucidate the contribution of phenotypic transitions on tumour growth dynamics.

scholarly journals Evolution to alternative levels of stable diversity leaves areas of niche space unexplored

2021 ◽  
Author(s):  
Ilan N. Rubin ◽  
Iaroslav Ispolatov ◽  
Michael Doebeli
Keyword(s):  
Evolutionary Dynamics ◽  
Natural Populations ◽  
Metastable States ◽  
Community Diversity ◽  
Limited Resources ◽  
Niche Space ◽  
Stable States ◽  
Low Diversity ◽  
Population Sizes ◽  
Adaptive Radiations

AbstractOne of the oldest and most persistent questions in ecology and evolution is whether natural communities tend to evolve toward saturation and maximal diversity. Robert MacArthur’s classical theory of niche packing and the theory of adaptive radiations both imply that populations will diversify and fully partition any available niche space. However, the saturation of natural populations is still very much an open area of debate and investigation. Additionally, recent evolutionary theory suggests the existence of alternative evolutionary stable states (ESSs), which implies that some stable communities may not be fully saturated. Using models with classical Lokta-Volterra ecological dynamics and three formulations of evolutionary dynamics (a model using adaptive dynamics, an individual-based model, and a partial differential equation model), we show that following an adaptive radiation, communities can often get stuck in low diversity states when limited by mutations of small phenotypic effect. These low diversity metastable states can also be maintained by limited resources and finite population sizes. When small mutations and finite populations are considered together, it is clear that despite the presence of higher-diversity stable states, natural populations are likely not fully saturating their environment and leaving potential niche space unfilled. Additionally, within-species variation can further reduce community diversity from levels predicted by models that assume species-level homogeneity.Author summaryUnderstanding if and when communities evolve to saturate their local environments is imperative to our understanding of natural populations. Using computer simulations of classical evolutionary models, we study whether adaptive radiations tend to lead toward saturated communities in which no new species can invade or remain trapped in alternative, lower diversity stable states. We show that with asymmetric competition and small effect mutations, evolutionary Red Queen dynamics can trap communities in low diversity metastable states. Moreover, limited resources not only reduces community population sizes, but also reduces community diversity, denying the formation of saturated communities and stabilizing low diversity, non-stationary evolutionary dynamics. Our results are directly relevant to the longstanding questions important to both ecological empiricists and theoreticians on the species packing and saturation of natural environments. Also, by showing the ease evolution can trap communities in low diversity metastable stats, we demonstrate the potential harm in relying solely on ESSs to answer questions of biodiversity.

scholarly journals Negative frequency-dependent selection maintains coexisting genotypes during fluctuating selection

2019 ◽  
Author(s):  
Caroline B. Turner ◽  
Sean W. Buskirk ◽  
Katrina B. Harris ◽  
Vaughn S. Cooper
Keyword(s):  
Evolutionary Dynamics ◽  
Burkholderia Cenocepacia ◽  
Natural Environments ◽  
Fluctuating Selection ◽  
Frequency Dependent ◽  
Frequency Dependent Selection ◽  
Fluctuating Environment ◽  
Fluctuating Environments ◽  
Negative Frequency Dependent Selection ◽  
Selection For

AbstractNatural environments are rarely static; rather selection can fluctuate on time scales ranging from hours to centuries. However, it is unclear how adaptation to fluctuating environments differs from adaptation to constant environments at the genetic level. For bacteria, one key axis of environmental variation is selection for planktonic or biofilm modes of growth. We conducted an evolution experiment with Burkholderia cenocepacia, comparing the evolutionary dynamics of populations evolving under constant selection for either biofilm formation or planktonic growth with populations in which selection fluctuated between the two environments on a weekly basis. Populations evolved in the fluctuating environment shared many of the same genetic targets of selection as those evolved in constant biofilm selection, but were genetically distinct from the constant planktonic populations. In the fluctuating environment, mutations in the biofilm-regulating genes wspA and rpfR rose to high frequency in all replicate populations. A mutation in wspA first rose rapidly and nearly fixed during the initial biofilm phase but was subsequently displaced by a collection of rpfR mutants upon the shift to the planktonic phase. The wspA and rpfR genotypes coexisted via negative frequency-dependent selection around an equilibrium frequency that shifted between the environments. The maintenance of coexisting genotypes in the fluctuating environment was unexpected. Under temporally fluctuating environments coexistence of two genotypes is only predicted under a narrow range of conditions, but the frequency-dependent interactions we observed provide a mechanism that can increase the likelihood of coexistence in fluctuating environments.

scholarly journals A Blind Calibration Model for I/Q Imbalances of Wideband Zero-IF Receivers

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1868
Author(s):  
Xiaoye Peng ◽  
Zhiyu Wang ◽  
Jiongjiong Mo ◽  
Chenge Wang ◽  
Jiarui Liu ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Finite Impulse Response ◽  
Low Cost ◽  
Classification Rule ◽  
Statistical Characteristics ◽  
High Signal ◽  
Calibration Model ◽  
Frequency Dependent ◽  
Frequency Independent ◽  
Blind Calibration

Frequency-dependent I/Q imbalance and frequency-independent I/Q imbalance are the major impairments in wideband zero-IF receivers, and they both cannot be ignored. In this paper, a blind calibration model is designed for compensating these I/Q imbalances. In order to accurately estimate the imbalance parameters with low cost, a classification rule is proposed according to the frequency-domain statistical characteristics of the received signal. The calibration points in the frequency-domain are divided into two groups. Then, the amplitude imbalance and the frequency-dependent phase imbalance are derived from the group of signal points and, separately, the frequency-independent phase imbalance is calculated from the group of noise points. In the derivation of the frequency-dependent phase imbalance, a general fitting model suitable for all signal points is proposed, which does not require special calculations for either DC point or fs/2 point. Then, a finite impulse response (FIR) real-valued filter is designed to correct the impairments of received signal. The performances of the proposed calibration model are evaluated through both simulations and experiments. The simulation results show the image rejection ratio (IRR) improvement to around 35–45 dBc at high signal-to-noise ratio (SNR). Based on the mismatched data of the ADRV9009 evaluation board, the experimental results exhibit the IRR improvement of both multi-tone and wideband signals to about 30 dBc.

scholarly journals EMERGENT NETWORK STRUCTURE, EVOLVABLE ROBUSTNESS, AND NONLINEAR EFFECTS OF POINT MUTATIONS IN AN ARTIFICIAL GENOME MODEL

2009 ◽  
Vol 12 (03) ◽  
pp. 293-310 ◽  
Author(s):  
THIMO ROHLF ◽  
CHRISTOPHER R. WINKLER
Keyword(s):  
Evolutionary Dynamics ◽  
Genetic Regulation ◽  
Point Mutations ◽  
Nonlinear Effects ◽  
High Rate ◽  
Stabilizing Selection ◽  
Clear Understanding ◽  
Stochastic Fluctuations ◽  
Neutral Mutations ◽  
Genome Model

Genetic regulation is a key component in development, but a clear understanding of the structure and dynamics of genetic networks is not yet at hand. In this paper we investigate these properties within an artificial genome model originally introduced by Reil [Proc. 5th European Conf. Artificial Life (Springer, 1999), pp. 457–466]. We analyze statistical properties of randomly generated genomes both on the sequence and network level, and show that this model correctly predicts the frequency of genes in genomes as found in experimental data. Using an evolutionary algorithm based on stabilizing selection for a phenotype, we show that dynamical robustness against single base mutations, as against random changes in initial states of regulatory dynamics that mimic stochastic fluctuations in environmental conditions, can emerge in parallel. Point mutations at the sequence level can have strongly nonlinear effects on network wiring, including structurally neutral mutations and simultaneous rewiring of multiple connections, which occasionally lead to strong reorganization of the attractor landscape and metastability of evolutionary dynamics. Similar to real genomes, evolved artificial genomes exhibit both highly conserved regions, as well as regions that are characterized by a high rate of accepted base substitutions.

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