Evolving cell models for systems and synthetic biology.

PubMed

Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

2010-03-01

This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.

A model of ecological and evolutionary consequences of color polymorphism.

PubMed

Forsman, Anders; Ahnesjö, Jonas; Caesar, Sofia; Karlsson, Magnus

2008-01-01

We summarize direct and indirect effects on fitness components of animal color pattern and present a synthesis of theories concerning the ecological and evolutionary dynamics of chromatic multiple niche polymorphisms. Previous endeavors have aimed primarily at identifying conditions that promote the evolution and maintenance of polymorphisms. We consider in a conceptual model also the reciprocal influence of color polymorphism on population processes and propose that polymorphism entails selective advantages that may promote the ecological success of polymorphic species. The model begins with an evolutionary branching event from mono- to polymorphic condition that, under the influence of correlational selection, is predicted to promote the evolution of physical integration of coloration and other traits (cf. multi-trait coevolution and complex phenotypes). We propose that the coexistence within a population of alternative ecomorphs with coadapted gene complexes promotes utilization of diverse environmental resources, population stability and persistence, colonization success, and range expansions, and enhances the evolutionary potential and speciation. Conversely, we predict polymorphic populations to be less vulnerable to environmental change and at lower risk of range contractions and extinctions compared with monomorphic populations. We offer brief suggestions as to how these falsifiable predictions may be tested.

Using evolutionary algorithms for fitting high-dimensional models to neuronal data.

PubMed

Svensson, Carl-Magnus; Coombes, Stephen; Peirce, Jonathan Westley

2012-04-01

In the study of neurosciences, and of complex biological systems in general, there is frequently a need to fit mathematical models with large numbers of parameters to highly complex datasets. Here we consider algorithms of two different classes, gradient following (GF) methods and evolutionary algorithms (EA) and examine their performance in fitting a 9-parameter model of a filter-based visual neuron to real data recorded from a sample of 107 neurons in macaque primary visual cortex (V1). Although the GF method converged very rapidly on a solution, it was highly susceptible to the effects of local minima in the error surface and produced relatively poor fits unless the initial estimates of the parameters were already very good. Conversely, although the EA required many more iterations of evaluating the model neuron's response to a series of stimuli, it ultimately found better solutions in nearly all cases and its performance was independent of the starting parameters of the model. Thus, although the fitting process was lengthy in terms of processing time, the relative lack of human intervention in the evolutionary algorithm, and its ability ultimately to generate model fits that could be trusted as being close to optimal, made it far superior in this particular application than the gradient following methods. This is likely to be the case in many further complex systems, as are often found in neuroscience.

(PS)2: protein structure prediction server version 3.0.

PubMed

Huang, Tsun-Tsao; Hwang, Jenn-Kang; Chen, Chu-Huang; Chu, Chih-Sheng; Lee, Chi-Wen; Chen, Chih-Chieh

2015-07-01

Protein complexes are involved in many biological processes. Examining coupling between subunits of a complex would be useful to understand the molecular basis of protein function. Here, our updated (PS)(2) web server predicts the three-dimensional structures of protein complexes based on comparative modeling; furthermore, this server examines the coupling between subunits of the predicted complex by combining structural and evolutionary considerations. The predicted complex structure could be indicated and visualized by Java-based 3D graphics viewers and the structural and evolutionary profiles are shown and compared chain-by-chain. For each subunit, considerations with or without the packing contribution of other subunits cause the differences in similarities between structural and evolutionary profiles, and these differences imply which form, complex or monomeric, is preferred in the biological condition for the subunit. We believe that the (PS)(2) server would be a useful tool for biologists who are interested not only in the structures of protein complexes but also in the coupling between subunits of the complexes. The (PS)(2) is freely available at http://ps2v3.life.nctu.edu.tw/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Games of multicellularity.

PubMed

Kaveh, Kamran; Veller, Carl; Nowak, Martin A

2016-08-21

Evolutionary game dynamics are often studied in the context of different population structures. Here we propose a new population structure that is inspired by simple multicellular life forms. In our model, cells reproduce but can stay together after reproduction. They reach complexes of a certain size, n, before producing single cells again. The cells within a complex derive payoff from an evolutionary game by interacting with each other. The reproductive rate of cells is proportional to their payoff. We consider all two-strategy games. We study deterministic evolutionary dynamics with mutations, and derive exact conditions for selection to favor one strategy over another. Our main result has the same symmetry as the well-known sigma condition, which has been proven for stochastic game dynamics and weak selection. For a maximum complex size of n=2 our result holds for any intensity of selection. For n≥3 it holds for weak selection. As specific examples we study the prisoner's dilemma and hawk-dove games. Our model advances theoretical work on multicellularity by allowing for frequency-dependent interactions within groups. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling the influence of parental effects on gene-network evolution.

PubMed

Odorico, Andreas; Rünneburger, Estelle; Le Rouzic, Arnaud

2018-05-01

Understanding the importance of nongenetic heredity in the evolutionary process is a major topic in modern evolutionary biology. We modified a classical gene-network model by allowing parental transmission of gene expression and studied its evolutionary properties through individual-based simulations. We identified ontogenetic time (i.e. the time gene networks have to stabilize before being submitted to natural selection) as a crucial factor in determining the evolutionary impact of this phenotypic inheritance. Indeed, fast-developing organisms display enhanced adaptation and greater robustness to mutations when evolving in presence of nongenetic inheritance (NGI). In contrast, in our model, long development reduces the influence of the inherited state of the gene network. NGI thus had a negligible effect on the evolution of gene networks when the speed at which transcription levels reach equilibrium is not constrained. Nevertheless, simulations show that intergenerational transmission of the gene-network state negatively affects the evolution of robustness to environmental disturbances for either fast- or slow-developing organisms. Therefore, these results suggest that the evolutionary consequences of NGI might not be sought only in the way species respond to selection, but also on the evolution of emergent properties (such as environmental and genetic canalization) in complex genetic architectures. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Development of X-TOOLSS: Preliminary Design of Space Systems Using Evolutionary Computation

NASA Technical Reports Server (NTRS)

Schnell, Andrew R.; Hull, Patrick V.; Turner, Mike L.; Dozier, Gerry; Alverson, Lauren; Garrett, Aaron; Reneau, Jarred

2008-01-01

Evolutionary computational (EC) techniques such as genetic algorithms (GA) have been identified as promising methods to explore the design space of mechanical and electrical systems at the earliest stages of design. In this paper the authors summarize their research in the use of evolutionary computation to develop preliminary designs for various space systems. An evolutionary computational solver developed over the course of the research, X-TOOLSS (Exploration Toolset for the Optimization of Launch and Space Systems) is discussed. With the success of early, low-fidelity example problems, an outline of work involving more computationally complex models is discussed.

Extended evolution: A conceptual framework for integrating regulatory networks and niche construction

PubMed Central

Renn, Jürgen

2015-01-01

ABSTRACT This paper introduces a conceptual framework for the evolution of complex systems based on the integration of regulatory network and niche construction theories. It is designed to apply equally to cases of biological, social and cultural evolution. Within the conceptual framework we focus especially on the transformation of complex networks through the linked processes of externalization and internalization of causal factors between regulatory networks and their corresponding niches and argue that these are an important part of evolutionary explanations. This conceptual framework extends previous evolutionary models and focuses on several challenges, such as the path‐dependent nature of evolutionary change, the dynamics of evolutionary innovation and the expansion of inheritance systems. J. Exp. Zool. (Mol. Dev. Evol.) 324B: 565–577, 2015. © 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution published by Wiley Periodicals, Inc. PMID:26097188

Evolutionary dynamics of group interactions on structured populations: a review

PubMed Central

Perc, Matjaž; Gómez-Gardeñes, Jesús; Szolnoki, Attila; Floría, Luis M.; Moreno, Yamir

2013-01-01

Interactions among living organisms, from bacteria colonies to human societies, are inherently more complex than interactions among particles and non-living matter. Group interactions are a particularly important and widespread class, representative of which is the public goods game. In addition, methods of statistical physics have proved valuable for studying pattern formation, equilibrium selection and self-organization in evolutionary games. Here, we review recent advances in the study of evolutionary dynamics of group interactions on top of structured populations, including lattices, complex networks and coevolutionary models. We also compare these results with those obtained on well-mixed populations. The review particularly highlights that the study of the dynamics of group interactions, like several other important equilibrium and non-equilibrium dynamical processes in biological, economical and social sciences, benefits from the synergy between statistical physics, network science and evolutionary game theory. PMID:23303223

Physical characteristics and evolutionary trends of continental rifts

NASA Technical Reports Server (NTRS)

Ramberg, I. B.; Morgan, P.

1984-01-01

Rifts may be defined as zones beneath which the entire lithosphere has ruptured in extension. They are widespread and occur in a variety of tectonic settings, and range up to 2,600 m.y. in age. The object of this review is to highlight characteristic features of modern and ancient rifts, to emphasize differences and similarities in order to help characterize evolutionary trends, to identify physical conditions favorable for initiation as well as termination of rifting, and to provide constraints for future modeling studies of rifting. Rifts are characterized on the basis of their structural, geomorphic, magmatic and geophysical features and the diverse character of these features and their evolutionary trends through time are discussed. Mechanisms of rifting are critically examined in terms of the physical characteristics and evolutionary trends of rifts, and it is concluded that while simple models can give valuable insight into specific processes of rifting, individual rifts can rarely, if ever, be characterized by well defined trends predicted by these models. More data are required to clearly define evolutionary trends, and the models require development to incorporate the effects of lithospheric heterogeneities and complex geologic histories.

Individual-based modeling of ecological and evolutionary processes

USGS Publications Warehouse

DeAngelis, Donald L.; Mooij, Wolf M.

2005-01-01

Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

Detection of timescales in evolving complex systems

PubMed Central

Darst, Richard K.; Granell, Clara; Arenas, Alex; Gómez, Sergio; Saramäki, Jari; Fortunato, Santo

2016-01-01

Most complex systems are intrinsically dynamic in nature. The evolution of a dynamic complex system is typically represented as a sequence of snapshots, where each snapshot describes the configuration of the system at a particular instant of time. This is often done by using constant intervals but a better approach would be to define dynamic intervals that match the evolution of the system’s configuration. To this end, we propose a method that aims at detecting evolutionary changes in the configuration of a complex system, and generates intervals accordingly. We show that evolutionary timescales can be identified by looking for peaks in the similarity between the sets of events on consecutive time intervals of data. Tests on simple toy models reveal that the technique is able to detect evolutionary timescales of time-varying data both when the evolution is smooth as well as when it changes sharply. This is further corroborated by analyses of several real datasets. Our method is scalable to extremely large datasets and is computationally efficient. This allows a quick, parameter-free detection of multiple timescales in the evolution of a complex system. PMID:28004820

Investigation on Law and Economics Based on Complex Network and Time Series Analysis.

PubMed

Yang, Jian; Qu, Zhao; Chang, Hui

2015-01-01

The research focuses on the cooperative relationship and the strategy tendency among three mutually interactive parties in financing: small enterprises, commercial banks and micro-credit companies. Complex network theory and time series analysis were applied to figure out the quantitative evidence. Moreover, this paper built up a fundamental model describing the particular interaction among them through evolutionary game. Combining the results of data analysis and current situation, it is justifiable to put forward reasonable legislative recommendations for regulations on lending activities among small enterprises, commercial banks and micro-credit companies. The approach in this research provides a framework for constructing mathematical models and applying econometrics and evolutionary game in the issue of corporation financing.

Stabilization of Large Generalized Lotka-Volterra Foodwebs By Evolutionary Feedback

NASA Astrophysics Data System (ADS)

Ackland, G. J.; Gallagher, I. D.

2004-10-01

Conventional ecological models show that complexity destabilizes foodwebs, suggesting that foodwebs should have neither large numbers of species nor a large number of interactions. However, in nature the opposite appears to be the case. Here we show that if the interactions between species are allowed to evolve within a generalized Lotka-Volterra model such stabilizing feedbacks and weak interactions emerge automatically. Moreover, we show that trophic levels also emerge spontaneously from the evolutionary approach, and the efficiency of the unperturbed ecosystem increases with time. The key to stability in large foodwebs appears to arise not from complexity perse but from evolution at the level of the ecosystem which favors stabilizing (negative) feedbacks.

Stabilization of large generalized Lotka-Volterra foodwebs by evolutionary feedback.

PubMed

Ackland, G J; Gallagher, I D

2004-10-08

Conventional ecological models show that complexity destabilizes foodwebs, suggesting that foodwebs should have neither large numbers of species nor a large number of interactions. However, in nature the opposite appears to be the case. Here we show that if the interactions between species are allowed to evolve within a generalized Lotka-Volterra model such stabilizing feedbacks and weak interactions emerge automatically. Moreover, we show that trophic levels also emerge spontaneously from the evolutionary approach, and the efficiency of the unperturbed ecosystem increases with time. The key to stability in large foodwebs appears to arise not from complexity per se but from evolution at the level of the ecosystem which favors stabilizing (negative) feedbacks.

Identifying predictors of time-inhomogeneous viral evolutionary processes.

PubMed

Bielejec, Filip; Baele, Guy; Rodrigo, Allen G; Suchard, Marc A; Lemey, Philippe

2016-07-01

Various factors determine the rate at which mutations are generated and fixed in viral genomes. Viral evolutionary rates may vary over the course of a single persistent infection and can reflect changes in replication rates and selective dynamics. Dedicated statistical inference approaches are required to understand how the complex interplay of these processes shapes the genetic diversity and divergence in viral populations. Although evolutionary models accommodating a high degree of complexity can now be formalized, adequately informing these models by potentially sparse data, and assessing the association of the resulting estimates with external predictors, remains a major challenge. In this article, we present a novel Bayesian evolutionary inference method, which integrates multiple potential predictors and tests their association with variation in the absolute rates of synonymous and non-synonymous substitutions along the evolutionary history. We consider clinical and virological measures as predictors, but also changes in population size trajectories that are simultaneously inferred using coalescent modelling. We demonstrate the potential of our method in an application to within-host HIV-1 sequence data sampled throughout the infection of multiple patients. While analyses of individual patient populations lack statistical power, we detect significant evidence for an abrupt drop in non-synonymous rates in late stage infection and a more gradual increase in synonymous rates over the course of infection in a joint analysis across all patients. The former is predicted by the immune relaxation hypothesis while the latter may be in line with increasing replicative fitness during the asymptomatic stage.

Multidimensional extended spatial evolutionary games.

PubMed

Krześlak, Michał; Świerniak, Andrzej

2016-02-01

The goal of this paper is to study the classical hawk-dove model using mixed spatial evolutionary games (MSEG). In these games, played on a lattice, an additional spatial layer is introduced for dependence on more complex parameters and simulation of changes in the environment. Furthermore, diverse polymorphic equilibrium points dependent on cell reproduction, model parameters, and their simulation are discussed. Our analysis demonstrates the sensitivity properties of MSEGs and possibilities for further development. We discuss applications of MSEGs, particularly algorithms for modelling cell interactions during the development of tumours. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiscale structure in eco-evolutionary dynamics

NASA Astrophysics Data System (ADS)

Stacey, Blake C.

In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.

Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations

PubMed Central

Beleva Guthrie, Violeta; Masica, David L; Fraser, Andrew; Federico, Joseph; Fan, Yunfan; Camps, Manel; Karchin, Rachel

2018-01-01

Abstract The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure. PMID:29522102

Evolutionary considerations on complex emotions and music-induced emotions. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

NASA Astrophysics Data System (ADS)

Gingras, Bruno; Marin, Manuela M.

2015-06-01

Recent efforts to uncover the neural underpinnings of emotional experiences have provided a foundation for novel neurophysiological theories of emotions, adding to the existing body of psychophysiological, motivational, and evolutionary theories. Besides explicitly modeling human-specific emotions and considering the interactions between emotions and language, Koelsch et al.'s original contribution to this challenging endeavor is to identify four brain areas as distinct "affect systems" which differ in terms of emotional qualia and evolutionary pathways [1]. Here, we comment on some features of this promising Quartet Theory of Emotions, focusing particularly on evolutionary and biological aspects related to the four affect systems and their relation to prevailing emotion theories, as well as on the role of music-induced emotions.

Fitness landscapes, heuristics and technological paradigms: A critique on random search models in evolutionary economics

NASA Astrophysics Data System (ADS)

Frenken, Koen

2001-06-01

The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.

Threat-detection in child development: an evolutionary perspective.

PubMed

Boyer, Pascal; Bergstrom, Brian

2011-03-01

Evidence for developmental aspects of fear-targets and anxiety suggests a complex but stable pattern whereby specific kinds of fears emerge at different periods of development. This developmental schedule seems appropriate to dangers encountered repeatedly during human evolution. Also consistent with evolutionary perspective, the threat-detection systems are domain-specific, comprising different kinds of cues to do with predation, intraspecific violence, contamination-contagion and status loss. Proper evolutionary models may also be relevant to outstanding issues in the domain, notably the connections between typical development and pathology. Copyright © 2010 Elsevier Ltd. All rights reserved.

Investigation on Law and Economics Based on Complex Network and Time Series Analysis

PubMed Central

Yang, Jian; Qu, Zhao; Chang, Hui

2015-01-01

The research focuses on the cooperative relationship and the strategy tendency among three mutually interactive parties in financing: small enterprises, commercial banks and micro-credit companies. Complex network theory and time series analysis were applied to figure out the quantitative evidence. Moreover, this paper built up a fundamental model describing the particular interaction among them through evolutionary game. Combining the results of data analysis and current situation, it is justifiable to put forward reasonable legislative recommendations for regulations on lending activities among small enterprises, commercial banks and micro-credit companies. The approach in this research provides a framework for constructing mathematical models and applying econometrics and evolutionary game in the issue of corporation financing. PMID:26076460

Adaptive evolution of complex innovations through stepwise metabolic niche expansion.

PubMed

Szappanos, Balázs; Fritzemeier, Jonathan; Csörgő, Bálint; Lázár, Viktória; Lu, Xiaowen; Fekete, Gergely; Bálint, Balázs; Herczeg, Róbert; Nagy, István; Notebaart, Richard A; Lercher, Martin J; Pál, Csaba; Papp, Balázs

2016-05-20

A central challenge in evolutionary biology concerns the mechanisms by which complex metabolic innovations requiring multiple mutations arise. Here, we propose that metabolic innovations accessible through the addition of a single reaction serve as stepping stones towards the later establishment of complex metabolic features in another environment. We demonstrate the feasibility of this hypothesis through three complementary analyses. First, using genome-scale metabolic modelling, we show that complex metabolic innovations in Escherichia coli can arise via changing nutrient conditions. Second, using phylogenetic approaches, we demonstrate that the acquisition patterns of complex metabolic pathways during the evolutionary history of bacterial genomes support the hypothesis. Third, we show how adaptation of laboratory populations of E. coli to one carbon source facilitates the later adaptation to another carbon source. Our work demonstrates how complex innovations can evolve through series of adaptive steps without the need to invoke non-adaptive processes.

Adaptive evolution of complex innovations through stepwise metabolic niche expansion

PubMed Central

Szappanos, Balázs; Fritzemeier, Jonathan; Csörgő, Bálint; Lázár, Viktória; Lu, Xiaowen; Fekete, Gergely; Bálint, Balázs; Herczeg, Róbert; Nagy, István; Notebaart, Richard A.; Lercher, Martin J.; Pál, Csaba; Papp, Balázs

2016-01-01

A central challenge in evolutionary biology concerns the mechanisms by which complex metabolic innovations requiring multiple mutations arise. Here, we propose that metabolic innovations accessible through the addition of a single reaction serve as stepping stones towards the later establishment of complex metabolic features in another environment. We demonstrate the feasibility of this hypothesis through three complementary analyses. First, using genome-scale metabolic modelling, we show that complex metabolic innovations in Escherichia coli can arise via changing nutrient conditions. Second, using phylogenetic approaches, we demonstrate that the acquisition patterns of complex metabolic pathways during the evolutionary history of bacterial genomes support the hypothesis. Third, we show how adaptation of laboratory populations of E. coli to one carbon source facilitates the later adaptation to another carbon source. Our work demonstrates how complex innovations can evolve through series of adaptive steps without the need to invoke non-adaptive processes. PMID:27197754

Evolutionary Development of the Simulation by Logical Modeling System (SIBYL)

NASA Technical Reports Server (NTRS)

Wu, Helen

1995-01-01

Through the evolutionary development of the Simulation by Logical Modeling System (SIBYL) we have re-engineered the expensive and complex IBM mainframe based Long-term Hardware Projection Model (LHPM) to a robust cost-effective computer based mode that is easy to use. We achieved significant cost reductions and improved productivity in preparing long-term forecasts of Space Shuttle Main Engine (SSME) hardware. The LHPM for the SSME is a stochastic simulation model that projects the hardware requirements over 10 years. SIBYL is now the primary modeling tool for developing SSME logistics proposals and Program Operating Plan (POP) for NASA and divisional marketing studies.

A hybrid neural learning algorithm using evolutionary learning and derivative free local search method.

PubMed

Ghosh, Ranadhir; Yearwood, John; Ghosh, Moumita; Bagirov, Adil

2006-06-01

In this paper we investigate a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient method has the advantage of being able to jump over many local minima and find very deep local minima. However, earlier research has shown that a good starting point for the discrete gradient method can improve the quality of the solution point. Evolutionary algorithms are best suited for global optimisation problems. Nevertheless they are cursed with longer training times and often unsuitable for real world application. For optimisation problems such as weight optimisation for ANNs in real world applications the dimensions are large and time complexity is critical. Hence the idea of a hybrid model can be a suitable option. In this paper we propose different fusion strategies for hybrid models combining the evolutionary strategy with the discrete gradient method to obtain an optimal solution much quicker. Three different fusion strategies are discussed: a linear hybrid model, an iterative hybrid model and a restricted local search hybrid model. Comparative results on a range of standard datasets are provided for different fusion hybrid models.

Colour spaces in ecology and evolutionary biology.

PubMed

Renoult, Julien P; Kelber, Almut; Schaefer, H Martin

2017-02-01

The recognition that animals sense the world in a different way than we do has unlocked important lines of research in ecology and evolutionary biology. In practice, the subjective study of natural stimuli has been permitted by perceptual spaces, which are graphical models of how stimuli are perceived by a given animal. Because colour vision is arguably the best-known sensory modality in most animals, a diversity of colour spaces are now available to visual ecologists, ranging from generalist and basic models allowing rough but robust predictions on colour perception, to species-specific, more complex models giving accurate but context-dependent predictions. Selecting among these models is most often influenced by historical contingencies that have associated models to specific questions and organisms; however, these associations are not always optimal. The aim of this review is to provide visual ecologists with a critical perspective on how models of colour space are built, how well they perform and where their main limitations are with regard to their most frequent uses in ecology and evolutionary biology. We propose a classification of models based on their complexity, defined as whether and how they model the mechanisms of chromatic adaptation and receptor opponency, the nonlinear association between the stimulus and its perception, and whether or not models have been fitted to experimental data. Then, we review the effect of modelling these mechanisms on predictions of colour detection and discrimination, colour conspicuousness, colour diversity and diversification, and for comparing the perception of colour traits between distinct perceivers. While a few rules emerge (e.g. opponent log-linear models should be preferred when analysing very distinct colours), in general model parameters still have poorly known effects. Colour spaces have nonetheless permitted significant advances in ecology and evolutionary biology, and more progress is expected if ecologists compare results between models and perform behavioural experiments more routinely. Such an approach would further contribute to a better understanding of colour vision and its links to the behavioural ecology of animals. While visual ecology is essentially a transfer of knowledge from visual sciences to evolutionary ecology, we hope that the discipline will benefit both fields more evenly in the future. © 2015 Cambridge Philosophical Society.

Origin and Evolutionary Alteration of the Mitochondrial Import System in Eukaryotic Lineages

PubMed Central

Fukasawa, Yoshinori; Oda, Toshiyuki; Tomii, Kentaro

2017-01-01

Abstract Protein transport systems are fundamentally important for maintaining mitochondrial function. Nevertheless, mitochondrial protein translocases such as the kinetoplastid ATOM complex have recently been shown to vary in eukaryotic lineages. Various evolutionary hypotheses have been formulated to explain this diversity. To resolve any contradiction, estimating the primitive state and clarifying changes from that state are necessary. Here, we present more likely primitive models of mitochondrial translocases, specifically the translocase of the outer membrane (TOM) and translocase of the inner membrane (TIM) complexes, using scrutinized phylogenetic profiles. We then analyzed the translocases’ evolution in eukaryotic lineages. Based on those results, we propose a novel evolutionary scenario for diversification of the mitochondrial transport system. Our results indicate that presequence transport machinery was mostly established in the last eukaryotic common ancestor, and that primitive translocases already had a pathway for transporting presequence-containing proteins. Moreover, secondary changes including convergent and migrational gains of a presequence receptor in TOM and TIM complexes, respectively, likely resulted from constrained evolution. The nature of a targeting signal can constrain alteration to the protein transport complex. PMID:28369657

Darwinian evolution in the light of genomics

PubMed Central

Koonin, Eugene V.

2009-01-01

Comparative genomics and systems biology offer unprecedented opportunities for testing central tenets of evolutionary biology formulated by Darwin in the Origin of Species in 1859 and expanded in the Modern Synthesis 100 years later. Evolutionary-genomic studies show that natural selection is only one of the forces that shape genome evolution and is not quantitatively dominant, whereas non-adaptive processes are much more prominent than previously suspected. Major contributions of horizontal gene transfer and diverse selfish genetic elements to genome evolution undermine the Tree of Life concept. An adequate depiction of evolution requires the more complex concept of a network or ‘forest’ of life. There is no consistent tendency of evolution towards increased genomic complexity, and when complexity increases, this appears to be a non-adaptive consequence of evolution under weak purifying selection rather than an adaptation. Several universals of genome evolution were discovered including the invariant distributions of evolutionary rates among orthologous genes from diverse genomes and of paralogous gene family sizes, and the negative correlation between gene expression level and sequence evolution rate. Simple, non-adaptive models of evolution explain some of these universals, suggesting that a new synthesis of evolutionary biology might become feasible in a not so remote future. PMID:19213802

Evolutionary Models of Irregular Warfare

DTIC Science & Technology

2013-03-01

repro- duction. These adaptations include both physiological and behavioral strategies ranging from armour and immunity to complex nervous sys- tems...evolutionary principles to the level of grand strategy and international politics. This has given rise to some unexpected results: for example, work...forces, while only needing a small number of parameters to do so. Furthermore, they allow one to explore the effect of alternative strategies —whether

Evolutionary fields can explain patterns of high-dimensional complexity in ecology

NASA Astrophysics Data System (ADS)

Wilsenach, James; Landi, Pietro; Hui, Cang

2017-04-01

One of the properties that make ecological systems so unique is the range of complex behavioral patterns that can be exhibited by even the simplest communities with only a few species. Much of this complexity is commonly attributed to stochastic factors that have very high-degrees of freedom. Orthodox study of the evolution of these simple networks has generally been limited in its ability to explain complexity, since it restricts evolutionary adaptation to an inertia-free process with few degrees of freedom in which only gradual, moderately complex behaviors are possible. We propose a model inspired by particle-mediated field phenomena in classical physics in combination with fundamental concepts in adaptation, which suggests that small but high-dimensional chaotic dynamics near to the adaptive trait optimum could help explain complex properties shared by most ecological datasets, such as aperiodicity and pink, fractal noise spectra. By examining a simple predator-prey model and appealing to real ecological data, we show that this type of complexity could be easily confused for or confounded by stochasticity, especially when spurred on or amplified by stochastic factors that share variational and spectral properties with the underlying dynamics.

An evolutionary perspective on gradual formation of superego in the primal horde

PubMed Central

Pulcu, Erdem

2014-01-01

Freud proposed that the processes which occurred in the primal horde are essential for understanding superego formation and therefore, the successful dissolution of the Oedipus complex. However, Freud theorized superego formation in the primal horde as if it is an instant, all-or-none achievement. The present paper proposes an alternative model aiming to explain gradual development of superego in the primitive man. The proposed model is built on knowledge from evolutionary and neural sciences as well as anthropology, and it particularly focuses on the evolutionary significance of the acquisition of fire by hominids in the Pleistocene period in the light of up-to-date archaeological findings. Acquisition of fire is discussed as a form of sublimation which might have helped Prehistoric man to maximize the utility of limited evolutionary biological resources, potentially contributing to the rate and extent of bodily evolution. The limitations of both Freud's original conceptualization and the present model are discussed accordingly in an interdisciplinary framework. PMID:24478740

Restart Operator Meta-heuristics for a Problem-Oriented Evolutionary Strategies Algorithm in Inverse Mathematical MISO Modelling Problem Solving

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.

2017-02-01

This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.

The nearly neutral and selection theories of molecular evolution under the fisher geometrical framework: substitution rate, population size, and complexity.

PubMed

Razeto-Barry, Pablo; Díaz, Javier; Vásquez, Rodrigo A

2012-06-01

The general theories of molecular evolution depend on relatively arbitrary assumptions about the relative distribution and rate of advantageous, deleterious, neutral, and nearly neutral mutations. The Fisher geometrical model (FGM) has been used to make distributions of mutations biologically interpretable. We explored an FGM-based molecular model to represent molecular evolutionary processes typically studied by nearly neutral and selection models, but in which distributions and relative rates of mutations with different selection coefficients are a consequence of biologically interpretable parameters, such as the average size of the phenotypic effect of mutations and the number of traits (complexity) of organisms. A variant of the FGM-based model that we called the static regime (SR) represents evolution as a nearly neutral process in which substitution rates are determined by a dynamic substitution process in which the population's phenotype remains around a suboptimum equilibrium fitness produced by a balance between slightly deleterious and slightly advantageous compensatory substitutions. As in previous nearly neutral models, the SR predicts a negative relationship between molecular evolutionary rate and population size; however, SR does not have the unrealistic properties of previous nearly neutral models such as the narrow window of selection strengths in which they work. In addition, the SR suggests that compensatory mutations cannot explain the high rate of fixations driven by positive selection currently found in DNA sequences, contrary to what has been previously suggested. We also developed a generalization of SR in which the optimum phenotype can change stochastically due to environmental or physiological shifts, which we called the variable regime (VR). VR models evolution as an interplay between adaptive processes and nearly neutral steady-state processes. When strong environmental fluctuations are incorporated, the process becomes a selection model in which evolutionary rate does not depend on population size, but is critically dependent on the complexity of organisms and mutation size. For SR as well as VR we found that key parameters of molecular evolution are linked by biological factors, and we showed that they cannot be fixed independently by arbitrary criteria, as has usually been assumed in previous molecular evolutionary models.

The Nearly Neutral and Selection Theories of Molecular Evolution Under the Fisher Geometrical Framework: Substitution Rate, Population Size, and Complexity

PubMed Central

Razeto-Barry, Pablo; Díaz, Javier; Vásquez, Rodrigo A.

2012-01-01

The general theories of molecular evolution depend on relatively arbitrary assumptions about the relative distribution and rate of advantageous, deleterious, neutral, and nearly neutral mutations. The Fisher geometrical model (FGM) has been used to make distributions of mutations biologically interpretable. We explored an FGM-based molecular model to represent molecular evolutionary processes typically studied by nearly neutral and selection models, but in which distributions and relative rates of mutations with different selection coefficients are a consequence of biologically interpretable parameters, such as the average size of the phenotypic effect of mutations and the number of traits (complexity) of organisms. A variant of the FGM-based model that we called the static regime (SR) represents evolution as a nearly neutral process in which substitution rates are determined by a dynamic substitution process in which the population’s phenotype remains around a suboptimum equilibrium fitness produced by a balance between slightly deleterious and slightly advantageous compensatory substitutions. As in previous nearly neutral models, the SR predicts a negative relationship between molecular evolutionary rate and population size; however, SR does not have the unrealistic properties of previous nearly neutral models such as the narrow window of selection strengths in which they work. In addition, the SR suggests that compensatory mutations cannot explain the high rate of fixations driven by positive selection currently found in DNA sequences, contrary to what has been previously suggested. We also developed a generalization of SR in which the optimum phenotype can change stochastically due to environmental or physiological shifts, which we called the variable regime (VR). VR models evolution as an interplay between adaptive processes and nearly neutral steady-state processes. When strong environmental fluctuations are incorporated, the process becomes a selection model in which evolutionary rate does not depend on population size, but is critically dependent on the complexity of organisms and mutation size. For SR as well as VR we found that key parameters of molecular evolution are linked by biological factors, and we showed that they cannot be fixed independently by arbitrary criteria, as has usually been assumed in previous molecular evolutionary models. PMID:22426879

An Evolutionary Complex Systems Decision-Support Tool for the Management of Operations

NASA Astrophysics Data System (ADS)

Baldwin, J. S.; Allen, P. M.; Ridgway, K.

2011-12-01

This research aimed to add both to the development of complex systems thinking in the subject area of Operations and Production Management and to the limited number of applications of computational models and simulations from the science of complex systems. The latter potentially offer helpful decision-support tools for operations and production managers. A mechanical engineering firm was used as a case study where a combined qualitative and quantitative methodological approach was employed to extract the required data from four senior managers. Company performance measures as well as firm technologies, practices and policies, and their relation and interaction with one another, were elicited. The data were subjected to an evolutionary complex systems model resulting in a series of simulations. The findings included both reassuring and some unexpected results. The simulation based on the CEO's opinions led the most cohesive and synergistic collection of practices describing the firm, closely followed by the Marketing and R&D Managers. The Manufacturing Manager's responses led to the most extreme evolutionary trajectory where the integrity of the entire firm came into question particularly when considering how employees were utilised. By drawing directly from the opinions and views of managers rather than from logical 'if-then' rules and averaged mathematical representations of agents that characterise agent-based and other self-organisational models, this work builds on previous applications by capturing a micro-level description of diversity and a learning effect that has been problematical not only in terms of theory but also in application. This approach can be used as a decision-support tool for operations and other managers providing a forum with which to explore a) the strengths, weaknesses and consequences of different decision-making capacities within the firm; b) the introduction of new manufacturing technologies, practices and policies; and, c) the different evolutionary trajectories that a firm can take.

An evolutionary morphological approach for software development cost estimation.

PubMed

Araújo, Ricardo de A; Oliveira, Adriano L I; Soares, Sergio; Meira, Silvio

2012-08-01

In this work we present an evolutionary morphological approach to solve the software development cost estimation (SDCE) problem. The proposed approach consists of a hybrid artificial neuron based on framework of mathematical morphology (MM) with algebraic foundations in the complete lattice theory (CLT), referred to as dilation-erosion perceptron (DEP). Also, we present an evolutionary learning process, called DEP(MGA), using a modified genetic algorithm (MGA) to design the DEP model, because a drawback arises from the gradient estimation of morphological operators in the classical learning process of the DEP, since they are not differentiable in the usual way. Furthermore, an experimental analysis is conducted with the proposed model using five complex SDCE problems and three well-known performance metrics, demonstrating good performance of the DEP model to solve SDCE problems. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Speech Community in Evolutionary Language Dynamics

ERIC Educational Resources Information Center

Blythe, Richard A.; Croft, William A.

2009-01-01

Language is a complex adaptive system: Speakers are agents who interact with each other, and their past and current interactions feed into speakers' future behavior in complex ways. In this article, we describe the social cognitive linguistic basis for this analysis of language and a mathematical model developed in collaboration between…

CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

USGS Publications Warehouse

Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

2016-01-01

1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

SLiM 2: Flexible, Interactive Forward Genetic Simulations.

PubMed

Haller, Benjamin C; Messer, Philipp W

2017-01-01

Modern population genomic datasets hold immense promise for revealing the evolutionary processes operating in natural populations, but a crucial prerequisite for this goal is the ability to model realistic evolutionary scenarios and predict their expected patterns in genomic data. To that end, we present SLiM 2: an evolutionary simulation framework that combines a powerful, fast engine for forward population genetic simulations with the capability of modeling a wide variety of complex evolutionary scenarios. SLiM achieves this flexibility through scriptability, which provides control over most aspects of the simulated evolutionary scenarios with a simple R-like scripting language called Eidos. An example SLiM simulation is presented to illustrate the power of this approach. SLiM 2 also includes a graphical user interface for simulation construction, interactive runtime control, and dynamic visualization of simulation output, facilitating easy and fast model development with quick prototyping and visual debugging. We conclude with a performance comparison between SLiM and two other popular forward genetic simulation packages. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Using Evolutionary Theory to Guide Mental Health Research.

PubMed

Durisko, Zachary; Mulsant, Benoit H; McKenzie, Kwame; Andrews, Paul W

2016-03-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating "normally" (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. © The Author(s) 2016.

Using Evolutionary Theory to Guide Mental Health Research

PubMed Central

Mulsant, Benoit H.; McKenzie, Kwame; Andrews, Paul W.

2016-01-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating “normally” (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. PMID:27254091

Genetics on the Fly: A Primer on the Drosophila Model System

PubMed Central

Hales, Karen G.; Korey, Christopher A.; Larracuente, Amanda M.; Roberts, David M.

2015-01-01

Fruit flies of the genus Drosophila have been an attractive and effective genetic model organism since Thomas Hunt Morgan and colleagues made seminal discoveries with them a century ago. Work with Drosophila has enabled dramatic advances in cell and developmental biology, neurobiology and behavior, molecular biology, evolutionary and population genetics, and other fields. With more tissue types and observable behaviors than in other short-generation model organisms, and with vast genome data available for many species within the genus, the fly’s tractable complexity will continue to enable exciting opportunities to explore mechanisms of complex developmental programs, behaviors, and broader evolutionary questions. This primer describes the organism’s natural history, the features of sequenced genomes within the genus, the wide range of available genetic tools and online resources, the types of biological questions Drosophila can help address, and historical milestones. PMID:26564900

Origin and Evolutionary Alteration of the Mitochondrial Import System in Eukaryotic Lineages.

PubMed

Fukasawa, Yoshinori; Oda, Toshiyuki; Tomii, Kentaro; Imai, Kenichiro

2017-07-01

Protein transport systems are fundamentally important for maintaining mitochondrial function. Nevertheless, mitochondrial protein translocases such as the kinetoplastid ATOM complex have recently been shown to vary in eukaryotic lineages. Various evolutionary hypotheses have been formulated to explain this diversity. To resolve any contradiction, estimating the primitive state and clarifying changes from that state are necessary. Here, we present more likely primitive models of mitochondrial translocases, specifically the translocase of the outer membrane (TOM) and translocase of the inner membrane (TIM) complexes, using scrutinized phylogenetic profiles. We then analyzed the translocases' evolution in eukaryotic lineages. Based on those results, we propose a novel evolutionary scenario for diversification of the mitochondrial transport system. Our results indicate that presequence transport machinery was mostly established in the last eukaryotic common ancestor, and that primitive translocases already had a pathway for transporting presequence-containing proteins. Moreover, secondary changes including convergent and migrational gains of a presequence receptor in TOM and TIM complexes, respectively, likely resulted from constrained evolution. The nature of a targeting signal can constrain alteration to the protein transport complex. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Darwin without borders? Looking at 'generalised Darwinism' through the prism of the 'hourglass model'.

PubMed

Levit, Georgy S; Hossfeld, Uwe

2011-12-01

This article critically analyzes the arguments of the 'generalized Darwinism' recently proposed for the analysis of social-economical systems. We argue that 'generalized Darwinism' is both restrictive and empty. It is restrictive because it excludes alternative (non-selectionist) evolutionary mechanisms such as orthogenesis, saltationism and mutationism without any examination of their suitability for modeling socio-economic processes and ignoring their important roles in the development of contemporary evolutionary theory. It is empty, because it reduces Darwinism to an abstract triple-principle scheme (variation, selection and inheritance) thus ignoring the actual structure of Darwinism as a complex and dynamic theoretical structure inseparable from a very detailed system of theoretical constraints. Arguing against 'generalised Darwinism' we present our vision of the history of evolutionary biology with the help of the 'hourglass model' reflecting the internal dynamic of competing theories of evolution.

Evolutionary fuzzy modeling human diagnostic decisions.

PubMed

Peña-Reyes, Carlos Andrés

2004-05-01

Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic representation (interpretability). However, fuzzy modeling--meaning the construction of fuzzy systems--is an arduous task, demanding the identification of many parameters. To solve it, we use evolutionary computation techniques (specifically cooperative coevolution), which are widely used to search for adequate solutions in complex spaces. We have successfully applied the algorithm to model the decision processes involved in two breast cancer diagnostic problems, the WBCD problem and the Catalonia mammography interpretation problem, obtaining systems both of high performance and high interpretability. For the Catalonia problem, an evolved system was embedded within a Web-based tool-called COBRA-for aiding radiologists in mammography interpretation.

Next gen perception and cognition: augmenting perception and enhancing cognition through mobile technologies

NASA Astrophysics Data System (ADS)

Goma, Sergio R.

2015-03-01

In current times, mobile technologies are ubiquitous and the complexity of problems is continuously increasing. In the context of advancement of engineering, we explore in this paper possible reasons that could cause a saturation in technology evolution - namely the ability of problem solving based on previous results and the ability of expressing solutions in a more efficient way, concluding that `thinking outside of brain' - as in solving engineering problems that are expressed in a virtual media due to their complexity - would benefit from mobile technology augmentation. This could be the necessary evolutionary step that would provide the efficiency required to solve new complex problems (addressing the `running out of time' issue) and remove the communication of results barrier (addressing the human `perception/expression imbalance' issue). Some consequences are discussed, as in this context the artificial intelligence becomes an automation tool aid instead of a necessary next evolutionary step. The paper concludes that research in modeling as problem solving aid and data visualization as perception aid augmented with mobile technologies could be the path to an evolutionary step in advancing engineering.

Strategies and Rubrics for Teaching Complex Systems Theory to Novices (Invited)

NASA Astrophysics Data System (ADS)

Fichter, L. S.

2010-12-01

Bifurcation. Self-similarity. Fractal. Sensitive dependent. Agents. Self-organized criticality. Avalanche behavior. Power laws. Strange attractors. Emergence. The language of complexity is fundamentally different from the language of equilibrium. If students do not know these phenomena, and what they tell us about the pulse of dynamic systems, complex systems will be opaque. A complex system is a group of agents. (individual interacting units, like birds in a flock, sand grains in a ripple, or individual friction units along a fault zone), existing far from equilibrium, interacting through positive and negative feedbacks, following simple rules, forming interdependent, dynamic, evolutionary networks. Complex systems produce behaviors that cannot be predicted deductively from knowledge of the behaviors of the individual components themselves; they must be experienced. What complexity theory demonstrates is that, by following simple rules, all the agents end up coordinating their behavior—self organizing—so that what emerges is not chaos, but meaningful patterns. How can we introduce Freshman, non-science, general education students to complex systems theories, in 3 to 5 classes; in a way they really get it, and can use the principles to understand real systems? Complex systems theories are not a series of unconnected or disconnected equations or models; they are developed as narratives that makes sense of how all the pieces and properties are interrelated. The principles of complex systems must be taught as deliberately and systematically as the equilibrium principles normally taught; as, say, the systematic training from pre-algebra and geometry to algebra. We have developed a sequence of logically connected narratives (strategies and rubrics) that introduce complex systems principles using models that can be simulated in a computer, in class, in real time. The learning progression has a series of 12 models (e.g. logistic system, bifurcation diagrams, genetic algorithms, etc.) leading to 19 learning outcomes that encompass most of the universality properties that characterize complex systems. They are developed in a specific order to achieve specific ends of understanding. We use these models in various depths and formats in courses ranging from gened courses, to evolutionary systems and environmental systems, to upper level geology courses. Depending on the goals of a course, the learning outcomes can be applied to understanding many other complex systems; e.g. oscillating chemical reactions (reaction-diffusion and activator-inhibitor systems), autocatalytic networks, hysteresis (bistable) systems, networks, and the rise/collapse of complex societies. We use these and other complex systems concepts in various classes to talk about the origin of life, ecosystem organization, game theory, extinction events, and environmental system behaviors. The applications are almost endless. The complete learning progression with models, computer programs, experiments, and learning outcomes is available at: www.jmu.edu/geology/ComplexEvolutionarySystems/

Plant polyadenylation factors: conservation and variety in the polyadenylation complex in plants.

PubMed

Hunt, Arthur G; Xing, Denghui; Li, Qingshun Q

2012-11-20

Polyadenylation, an essential step in eukaryotic gene expression, requires both cis-elements and a plethora of trans-acting polyadenylation factors. The polyadenylation factors are largely conserved across mammals and fungi. The conservation seems also extended to plants based on the analyses of Arabidopsis polyadenylation factors. To extend this observation, we systemically identified the orthologs of yeast and human polyadenylation factors from 10 plant species chosen based on both the availability of their genome sequences and their positions in the evolutionary tree, which render them representatives of different plant lineages. The evolutionary trajectories revealed several interesting features of plant polyadenylation factors. First, the number of genes encoding plant polyadenylation factors was clearly increased from "lower" to "higher" plants. Second, the gene expansion in higher plants was biased to some polyadenylation factors, particularly those involved in RNA binding. Finally, while there are clear commonalities, the differences in the polyadenylation apparatus were obvious across different species, suggesting an ongoing process of evolutionary change. These features lead to a model in which the plant polyadenylation complex consists of a conserved core, which is rather rigid in terms of evolutionary conservation, and a panoply of peripheral subunits, which are less conserved and associated with the core in various combinations, forming a collection of somewhat distinct complex assemblies. The multiple forms of plant polyadenylation complex, together with the diversified polyA signals may explain the intensive alternative polyadenylation (APA) and its regulatory role in biological functions of higher plants.

An integrative model of evolutionary covariance: a symposium on body shape in fishes.

PubMed

Walker, Jeffrey A

2010-12-01

A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

Performance comparison of some evolutionary algorithms on job shop scheduling problems

NASA Astrophysics Data System (ADS)

Mishra, S. K.; Rao, C. S. P.

2016-09-01

Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.

EvoluCode: Evolutionary Barcodes as a Unifying Framework for Multilevel Evolutionary Data.

PubMed

Linard, Benjamin; Nguyen, Ngoc Hoan; Prosdocimi, Francisco; Poch, Olivier; Thompson, Julie D

2012-01-01

Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.

Test of Von Baer's law of the conservation of early development.

PubMed

Poe, Steven

2006-11-01

One of the oldest and most pervasive ideas in comparative embryology is the perceived evolutionary conservation of early ontogeny relative to late ontogeny. Karl Von Baer first noted the similarity of early ontogeny across taxa, and Ernst Haeckel and Charles Darwin gave evolutionary interpretation to this phenomenon. In spite of a resurgence of interest in comparative embryology and the development of mechanistic explanations for Von Baer's law, the pattern itself has been largely untested. Here, I use statistical phylogenetic approaches to show that Von Baer's law is an unnecessarily complex explanation of the patterns of ontogenetic timing in several clades of vertebrates. Von Baer's law suggests a positive correlation between ontogenetic time and amount of evolutionary change. I compare ranked position in ontogeny to frequency of evolutionary change in rank for developmental events and find that these measures are not correlated, thus failing to support Von Baer's model. An alternative model that postulates that small changes in ontogenetic rank are evolutionarily easier than large changes is tentatively supported.

Expanding Evolutionary Theory beyond Darwinism with Elaborating, Self-Organizing, and Fractionating Complex Evolutionary Systems

ERIC Educational Resources Information Center

Fichter, Lynn S.; Pyle, E. J.; Whitmeyer, S. J.

2010-01-01

Earth systems increase in complexity, diversity, and interconnectedness with time, driven by tectonic/solar energy that keeps the systems far from equilibrium. The evolution of Earth systems is facilitated by three evolutionary mechanisms: "elaboration," "fractionation," and "self-organization," that share…

Hill-Climbing search and diversification within an evolutionary approach to protein structure prediction.

PubMed

Chira, Camelia; Horvath, Dragos; Dumitrescu, D

2011-07-30

Proteins are complex structures made of amino acids having a fundamental role in the correct functioning of living cells. The structure of a protein is the result of the protein folding process. However, the general principles that govern the folding of natural proteins into a native structure are unknown. The problem of predicting a protein structure with minimum-energy starting from the unfolded amino acid sequence is a highly complex and important task in molecular and computational biology. Protein structure prediction has important applications in fields such as drug design and disease prediction. The protein structure prediction problem is NP-hard even in simplified lattice protein models. An evolutionary model based on hill-climbing genetic operators is proposed for protein structure prediction in the hydrophobic - polar (HP) model. Problem-specific search operators are implemented and applied using a steepest-ascent hill-climbing approach. Furthermore, the proposed model enforces an explicit diversification stage during the evolution in order to avoid local optimum. The main features of the resulting evolutionary algorithm - hill-climbing mechanism and diversification strategy - are evaluated in a set of numerical experiments for the protein structure prediction problem to assess their impact to the efficiency of the search process. Furthermore, the emerging consolidated model is compared to relevant algorithms from the literature for a set of difficult bidimensional instances from lattice protein models. The results obtained by the proposed algorithm are promising and competitive with those of related methods.

The evolution of ecosystem ascendency in a complex systems based model.

PubMed

Brinck, Katharina; Jensen, Henrik Jeldtoft

2017-09-07

General patterns in ecosystem development can shed light on driving forces behind ecosystem formation and recovery and have been of long interest. In recent years, the need for integrative and process oriented approaches to capture ecosystem growth, development and organisation, as well as the scope of information theory as a descriptive tool has been addressed from various sides. However data collection of ecological network flows is difficult and tedious and comprehensive models are lacking. We use a hierarchical version of the Tangled Nature Model of evolutionary ecology to study the relationship between structure, flow and organisation in model ecosystems, their development over evolutionary time scales and their relation to ecosystem stability. Our findings support the validity of ecosystem ascendency as a meaningful measure of ecosystem organisation, which increases over evolutionary time scales and significantly drops during periods of disturbance. The results suggest a general trend towards both higher integrity and increased stability driven by functional and structural ecosystem coadaptation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Applications of genetic programming in cancer research.

PubMed

Worzel, William P; Yu, Jianjun; Almal, Arpit A; Chinnaiyan, Arul M

2009-02-01

The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

Analytical model for orbital debris environmental management

NASA Technical Reports Server (NTRS)

Talent, David L.

1990-01-01

A differential equation, also referred to as the PIB (particle-in-a-box) model, expressing the time rate of change of the number of objects in orbit, is developed, and its applicability is illustrated. The model can be used as a tool for the assessment of LEO environment stability, and as a starting point for the development of numerical evolutionary models. Within the context of the model, evolutionary scenarios are examined, and found to be sensitive to the growth rate. It is determined that the present environment is slightly unstable to catastrophic growth, and that the number of particles on orbit will continue to increase until approximately 2250-2350 AD, with a maximum of 2,000,000. The model is expandable to the more realistic (complex) case of multiple species in a multiple-tier system.

Laboratory and modeling studies of chemistry in dense molecular clouds

NASA Technical Reports Server (NTRS)

Huntress, W. T., Jr.; Prasad, S. S.; Mitchell, G. F.

1980-01-01

A chemical evolutionary model with a large number of species and a large chemical library is used to examine the principal chemical processes in interstellar clouds. Simple chemical equilibrium arguments show the potential for synthesis of very complex organic species by ion-molecule radiative association reactions.

A review of estimation of distribution algorithms in bioinformatics

PubMed Central

Armañanzas, Rubén; Inza, Iñaki; Santana, Roberto; Saeys, Yvan; Flores, Jose Luis; Lozano, Jose Antonio; Peer, Yves Van de; Blanco, Rosa; Robles, Víctor; Bielza, Concha; Larrañaga, Pedro

2008-01-01

Evolutionary search algorithms have become an essential asset in the algorithmic toolbox for solving high-dimensional optimization problems in across a broad range of bioinformatics problems. Genetic algorithms, the most well-known and representative evolutionary search technique, have been the subject of the major part of such applications. Estimation of distribution algorithms (EDAs) offer a novel evolutionary paradigm that constitutes a natural and attractive alternative to genetic algorithms. They make use of a probabilistic model, learnt from the promising solutions, to guide the search process. In this paper, we set out a basic taxonomy of EDA techniques, underlining the nature and complexity of the probabilistic model of each EDA variant. We review a set of innovative works that make use of EDA techniques to solve challenging bioinformatics problems, emphasizing the EDA paradigm's potential for further research in this domain. PMID:18822112

An evolutionary link between capsular biogenesis and surface motility in bacteria.

PubMed

Agrebi, Rym; Wartel, Morgane; Brochier-Armanet, Céline; Mignot, Tâm

2015-05-01

Studying the evolution of macromolecular assemblies is important to improve our understanding of how complex cellular structures evolved, and to identify the functional building blocks that are involved. Recent studies suggest that the macromolecular complexes that are involved in two distinct processes in Myxococcus xanthus - surface motility and sporulation - are derived from an ancestral polysaccharide capsule assembly system. In this Opinion article, we argue that the available data suggest that the motility machinery evolved from this capsule assembly system following a gene duplication event, a change in carbohydrate polymer specificity and the acquisition of additional proteins by the motility complex, all of which are key features that distinguish the motility and sporulation systems. Furthermore, the presence of intermediates of these systems in bacterial genomes suggests a testable evolutionary model for their emergence and spread.

Modeling of biological intelligence for SCM system optimization.

PubMed

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

PubMed Central

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

Comparative genomic de-convolution of the cotton genome revealed a decaploid ancestor and widespread chromosomal fractionation.

PubMed

Wang, Xiyin; Guo, Hui; Wang, Jinpeng; Lei, Tianyu; Liu, Tao; Wang, Zhenyi; Li, Yuxian; Lee, Tae-Ho; Li, Jingping; Tang, Haibao; Jin, Dianchuan; Paterson, Andrew H

2016-02-01

The 'apparently' simple genomes of many angiosperms mask complex evolutionary histories. The reference genome sequence for cotton (Gossypium spp.) revealed a ploidy change of a complexity unprecedented to date, indeed that could not be distinguished as to its exact dosage. Herein, by developing several comparative, computational and statistical approaches, we revealed a 5× multiplication in the cotton lineage of an ancestral genome common to cotton and cacao, and proposed evolutionary models to show how such a decaploid ancestor formed. The c. 70% gene loss necessary to bring the ancestral decaploid to its current gene count appears to fit an approximate geometrical model; that is, although many genes may be lost by single-gene deletion events, some may be lost in groups of consecutive genes. Gene loss following cotton decaploidy has largely just reduced gene copy numbers of some homologous groups. We designed a novel approach to deconvolute layers of chromosome homology, providing definitive information on gene orthology and paralogy across broad evolutionary distances, both of fundamental value and serving as an important platform to support further studies in and beyond cotton and genomics communities. No claim to original US government works. New Phytologist © 2015 New Phytologist Trust.

Navigating the Perfect Storm: Research Strategies for Socialecological Systems in a Rapidly Evolving World

NASA Astrophysics Data System (ADS)

Dearing, John A.; Bullock, Seth; Costanza, Robert; Dawson, Terry P.; Edwards, Mary E.; Poppy, Guy M.; Smith, Graham M.

2012-04-01

The `Perfect Storm' metaphor describes a combination of events that causes a surprising or dramatic impact. It lends an evolutionary perspective to how social-ecological interactions change. Thus, we argue that an improved understanding of how social-ecological systems have evolved up to the present is necessary for the modelling, understanding and anticipation of current and future social-ecological systems. Here we consider the implications of an evolutionary perspective for designing research approaches. One desirable approach is the creation of multi-decadal records produced by integrating palaeoenvironmental, instrument and documentary sources at multiple spatial scales. We also consider the potential for improved analytical and modelling approaches by developing system dynamical, cellular and agent-based models, observing complex behaviour in social-ecological systems against which to test systems dynamical theory, and drawing better lessons from history. Alongside these is the need to find more appropriate ways to communicate complex systems, risk and uncertainty to the public and to policy-makers.

Reticulate evolutionary history and extensive introgression in mosquito species revealed by phylogenetic network analysis

PubMed Central

Wen, Dingqiao; Yu, Yun; Hahn, Matthew W.; Nakhleh, Luay

2016-01-01

The role of hybridization and subsequent introgression has been demonstrated in an increasing number of species. Recently, Fontaine et al. (Science, 347, 2015, 1258524) conducted a phylogenomic analysis of six members of the Anopheles gambiae species complex. Their analysis revealed a reticulate evolutionary history and pointed to extensive introgression on all four autosomal arms. The study further highlighted the complex evolutionary signals that the co-occurrence of incomplete lineage sorting (ILS) and introgression can give rise to in phylogenomic analyses. While tree-based methodologies were used in the study, phylogenetic networks provide a more natural model to capture reticulate evolutionary histories. In this work, we reanalyse the Anopheles data using a recently devised framework that combines the multispecies coalescent with phylogenetic networks. This framework allows us to capture ILS and introgression simultaneously, and forms the basis for statistical methods for inferring reticulate evolutionary histories. The new analysis reveals a phylogenetic network with multiple hybridization events, some of which differ from those reported in the original study. To elucidate the extent and patterns of introgression across the genome, we devise a new method that quantifies the use of reticulation branches in the phylogenetic network by each genomic region. Applying the method to the mosquito data set reveals the evolutionary history of all the chromosomes. This study highlights the utility of ‘network thinking’ and the new insights it can uncover, in particular in phylogenomic analyses of large data sets with extensive gene tree incongruence. PMID:26808290

An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N. V.

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test. PMID:23469172

Evolutionary Models for Simple Biosystems

NASA Astrophysics Data System (ADS)

Bagnoli, Franco

The concept of evolutionary development of structures constituted a real revolution in biology: it was possible to understand how the very complex structures of life can arise in an out-of-equilibrium system. The investigation of such systems has shown that indeed, systems under a flux of energy or matter can self-organize into complex patterns, think for instance to Rayleigh-Bernard convection, Liesegang rings, patterns formed by granular systems under shear. Following this line, one could characterize life as a state of matter, characterized by the slow, continuous process that we call evolution. In this paper we try to identify the organizational level of life, that spans several orders of magnitude from the elementary constituents to whole ecosystems. Although similar structures can be found in other contexts like ideas (memes) in neural systems and self-replicating elements (computer viruses, worms, etc.) in computer systems, we shall concentrate on biological evolutionary structure, and try to put into evidence the role and the emergence of network structure in such systems.

Structural requirements for the assembly of LINC complexes and their function in cellular mechanical stiffness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stewart-Hutchinson, P.J.; Hale, Christopher M.; Wirtz, Denis

The evolutionary-conserved interactions between KASH and SUN domain-containing proteins within the perinuclear space establish physical connections, called LINC complexes, between the nucleus and the cytoskeleton. Here, we show that the KASH domains of Nesprins 1, 2 and 3 interact promiscuously with luminal domains of Sun1 and Sun2. These constructs disrupt endogenous LINC complexes as indicated by the displacement of endogenous Nesprins from the nuclear envelope. We also provide evidence that KASH domains most probably fit a pocket provided by SUN domains and that post-translational modifications are dispensable for that interaction. We demonstrate that the disruption of endogenous LINC complexes affectmore » cellular mechanical stiffness to an extent that compares to the loss of mechanical stiffness previously reported in embryonic fibroblasts derived from mouse lacking A-type lamins, a mouse model of muscular dystrophies and cardiomyopathies. These findings support a model whereby physical connections between the nucleus and the cytoskeleton are mediated by interactions between diverse combinations of Sun proteins and Nesprins through their respective evolutionary-conserved domains. Furthermore, they emphasize, for the first time, the relevance of LINC complexes in cellular mechanical stiffness suggesting a possible involvement of their disruption in various laminopathies, a group of human diseases linked to mutations of A-type lamins.« less

Complexity in models of cultural niche construction with selection and homophily.

PubMed

Creanza, Nicole; Feldman, Marcus W

2014-07-22

Niche construction is the process by which organisms can alter the ecological environment for themselves, their descendants, and other species. As a result of niche construction, differences in selection pressures may be inherited across generations. Homophily, the tendency of like phenotypes to mate or preferentially associate, influences the evolutionary dynamics of these systems. Here we develop a model that includes selection and homophily as independent culturally transmitted traits that influence the fitness and mate choice determined by another focal cultural trait. We study the joint dynamics of a focal set of beliefs, a behavior that can differentially influence the fitness of those with certain beliefs, and a preference for partnering based on similar beliefs. Cultural transmission, selection, and homophily interact to produce complex evolutionary dynamics, including oscillations, stable polymorphisms of all cultural phenotypes, and simultaneous stability of oscillation and fixation, which have not previously been observed in models of cultural evolution or gene-culture interactions. We discuss applications of this model to the interaction of beliefs and behaviors regarding education, contraception, and animal domestication.

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

Evolutionary inference via the Poisson Indel Process.

PubMed

Bouchard-Côté, Alexandre; Jordan, Michael I

2013-01-22

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

Evolutionary inference via the Poisson Indel Process

PubMed Central

Bouchard-Côté, Alexandre; Jordan, Michael I.

2013-01-01

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114–124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments. PMID:23275296

A test of genetic models for the evolutionary maintenance of same-sex sexual behaviour.

PubMed

Hoskins, Jessica L; Ritchie, Michael G; Bailey, Nathan W

2015-06-22

The evolutionary maintenance of same-sex sexual behaviour (SSB) has received increasing attention because it is perceived to be an evolutionary paradox. The genetic basis of SSB is almost wholly unknown in non-human animals, though this is key to understanding its persistence. Recent theoretical work has yielded broadly applicable predictions centred on two genetic models for SSB: overdominance and sexual antagonism. Using Drosophila melanogaster, we assayed natural genetic variation for male SSB and empirically tested predictions about the mode of inheritance and fitness consequences of alleles influencing its expression. We screened 50 inbred lines derived from a wild population for male-male courtship and copulation behaviour, and examined crosses between the lines for evidence of overdominance and antagonistic fecundity selection. Consistent variation among lines revealed heritable genetic variation for SSB, but the nature of the genetic variation was complex. Phenotypic and fitness variation was consistent with expectations under overdominance, although predictions of the sexual antagonism model were also supported. We found an unexpected and strong paternal effect on the expression of SSB, suggesting possible Y-linkage of the trait. Our results inform evolutionary genetic mechanisms that might maintain low but persistently observed levels of male SSB in D. melanogaster, but highlight a need for broader taxonomic representation in studies of its evolutionary causes. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Innovation Rather than Improvement: A Solvable High-Dimensional Model Highlights the Limitations of Scalar Fitness

NASA Astrophysics Data System (ADS)

Tikhonov, Mikhail; Monasson, Remi

2018-01-01

Much of our understanding of ecological and evolutionary mechanisms derives from analysis of low-dimensional models: with few interacting species, or few axes defining "fitness". It is not always clear to what extent the intuition derived from low-dimensional models applies to the complex, high-dimensional reality. For instance, most naturally occurring microbial communities are strikingly diverse, harboring a large number of coexisting species, each of which contributes to shaping the environment of others. Understanding the eco-evolutionary interplay in these systems is an important challenge, and an exciting new domain for statistical physics. Recent work identified a promising new platform for investigating highly diverse ecosystems, based on the classic resource competition model of MacArthur. Here, we describe how the same analytical framework can be used to study evolutionary questions. Our analysis illustrates how, at high dimension, the intuition promoted by a one-dimensional (scalar) notion of fitness can become misleading. Specifically, while the low-dimensional picture emphasizes organism cost or efficiency, we exhibit a regime where cost becomes irrelevant for survival, and link this observation to generic properties of high-dimensional geometry.

InterEvDock: a docking server to predict the structure of protein–protein interactions using evolutionary information

PubMed Central

Yu, Jinchao; Vavrusa, Marek; Andreani, Jessica; Rey, Julien; Tufféry, Pierre; Guerois, Raphaël

2016-01-01

The structural modeling of protein–protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigid-body docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock/. PMID:27131368

Holistic Darwinism: the new evolutionary paradigm and some implications for political science.

PubMed

Corning, Peter A

2008-03-01

Holistic Darwinism is a candidate name for a major paradigm shift that is currently underway in evolutionary biology and related disciplines. Important developments include (1) a growing appreciation for the fact that evolution is a multilevel process, from genes to ecosystems, and that interdependent coevolution is a ubiquitous phenomenon in nature; (2) a revitalization of group selection theory, which was banned (prematurely) from evolutionary biology over 30 years ago (groups may in fact be important evolutionary units); (3) a growing respect for the fact that the genome is not a "bean bag" (in biologist Ernst Mayr's caricature), much less a gladiatorial arena for competing selfish genes, but a complex, interdependent, cooperating system; (4) an increased recognition that symbiosis is an important phenomenon in nature and that symbiogenesis is a major source of innovation in evolution; (5) an array of new, more advanced game theory models, which support the growing evidence that cooperation is commonplace in nature and not a rare exception; (6) new research and theoretical work that stresses the role of nurture in evolution, including developmental processes, phenotypic plasticity, social information transfer (culture), and especially the role of behavioral innovations as pacemakers of evolutionary change (e.g., niche construction theory, which is concerned with the active role of organisms in shaping the evolutionary process, and gene-culture coevolution theory, which relates especially to the dynamics of human evolution); (7) and, not least, a broad effort to account for the evolution of biological complexity--from major transition theory to the "Synergism Hypothesis." Here I will briefly review these developments and will present a case for the proposition that this paradigm shift has profound implications for the social sciences, including specifically political theory, economic theory, and political science as a discipline. Interdependent superorganisms, it turns out, have played a major role in evolution--from eukaryotes to complex human societies.

Odonata (dragonflies and damselflies) as a bridge between ecology and evolutionary genomics.

PubMed

Bybee, Seth; Córdoba-Aguilar, Alex; Duryea, M Catherine; Futahashi, Ryo; Hansson, Bengt; Lorenzo-Carballa, M Olalla; Schilder, Ruud; Stoks, Robby; Suvorov, Anton; Svensson, Erik I; Swaegers, Janne; Takahashi, Yuma; Watts, Phillip C; Wellenreuther, Maren

2016-01-01

Odonata (dragonflies and damselflies) present an unparalleled insect model to integrate evolutionary genomics with ecology for the study of insect evolution. Key features of Odonata include their ancient phylogenetic position, extensive phenotypic and ecological diversity, several unique evolutionary innovations, ease of study in the wild and usefulness as bioindicators for freshwater ecosystems worldwide. In this review, we synthesize studies on the evolution, ecology and physiology of odonates, highlighting those areas where the integration of ecology with genomics would yield significant insights into the evolutionary processes that would not be gained easily by working on other animal groups. We argue that the unique features of this group combined with their complex life cycle, flight behaviour, diversity in ecological niches and their sensitivity to anthropogenic change make odonates a promising and fruitful taxon for genomics focused research. Future areas of research that deserve increased attention are also briefly outlined.

Social defense: an evolutionary-developmental model of children's strategies for coping with threat in the peer group.

PubMed

Martin, Meredith J; Davies, Patrick T; MacNeill, Leigha A

2014-04-29

Navigating the ubiquitous conflict, competition, and complex group dynamics of the peer group is a pivotal developmental task of childhood. Difficulty negotiating these challenges represents a substantial source of risk for psychopathology. Evolutionary developmental psychology offers a unique perspective with the potential to reorganize the way we think about the role of peer relationships in shaping how children cope with the everyday challenges of establishing a social niche. To address this gap, we utilize the ethological reformulation of the emotional security theory as a guide to developing an evolutionary framework for advancing an understanding of the defense strategies children use to manage antagonistic peer relationships and protect themselves from interpersonal threat (Davies and Sturge-Apple, 2007). In this way, we hope to illustrate the value of an evolutionary developmental lens in generating unique theoretical insight and novel research directions into the role of peer relationships in the development of psychopathology.

More efficient evolutionary strategies for model calibration with watershed model for demonstration

NASA Astrophysics Data System (ADS)

Baggett, J. S.; Skahill, B. E.

2008-12-01

Evolutionary strategies allow automatic calibration of more complex models than traditional gradient based approaches, but they are more computationally intensive. We present several efficiency enhancements for evolution strategies, many of which are not new, but when combined have been shown to dramatically decrease the number of model runs required for calibration of synthetic problems. To reduce the number of expensive model runs we employ a surrogate objective function for an adaptively determined fraction of the population at each generation (Kern et al., 2006). We demonstrate improvements to the adaptive ranking strategy that increase its efficiency while sacrificing little reliability and further reduce the number of model runs required in densely sampled parts of parameter space. Furthermore, we include a gradient individual in each generation that is usually not selected when the search is in a global phase or when the derivatives are poorly approximated, but when selected near a smooth local minimum can dramatically increase convergence speed (Tahk et al., 2007). Finally, the selection of the gradient individual is used to adapt the size of the population near local minima. We show, by incorporating these enhancements into the Covariance Matrix Adaption Evolution Strategy (CMAES; Hansen, 2006), that their synergetic effect is greater than their individual parts. This hybrid evolutionary strategy exploits smooth structure when it is present but degrades to an ordinary evolutionary strategy, at worst, if smoothness is not present. Calibration of 2D-3D synthetic models with the modified CMAES requires approximately 10%-25% of the model runs of ordinary CMAES. Preliminary demonstration of this hybrid strategy will be shown for watershed model calibration problems. Hansen, N. (2006). The CMA Evolution Strategy: A Comparing Review. In J.A. Lozano, P. Larrañga, I. Inza and E. Bengoetxea (Eds.). Towards a new evolutionary computation. Advances in estimation of distribution algorithms. pp. 75-102, Springer Kern, S., N. Hansen and P. Koumoutsakos (2006). Local Meta-Models for Optimization Using Evolution Strategies. In Ninth International Conference on Parallel Problem Solving from Nature PPSN IX, Proceedings, pp.939-948, Berlin: Springer. Tahk, M., Woo, H., and Park. M, (2007). A hybrid optimization of evolutionary and gradient search. Engineering Optimization, (39), 87-104.

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model

PubMed Central

Nené, Nuno R.; Dunham, Alistair S.; Illingworth, Christopher J. R.

2018-01-01

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. PMID:29500183

A road map for integrating eco-evolutionary processes into biodiversity models.

PubMed

Thuiller, Wilfried; Münkemüller, Tamara; Lavergne, Sébastien; Mouillot, David; Mouquet, Nicolas; Schiffers, Katja; Gravel, Dominique

2013-05-01

The demand for projections of the future distribution of biodiversity has triggered an upsurge in modelling at the crossroads between ecology and evolution. Despite the enthusiasm around these so-called biodiversity models, most approaches are still criticised for not integrating key processes known to shape species ranges and community structure. Developing an integrative modelling framework for biodiversity distribution promises to improve the reliability of predictions and to give a better understanding of the eco-evolutionary dynamics of species and communities under changing environments. In this article, we briefly review some eco-evolutionary processes and interplays among them, which are essential to provide reliable projections of species distributions and community structure. We identify gaps in theory, quantitative knowledge and data availability hampering the development of an integrated modelling framework. We argue that model development relying on a strong theoretical foundation is essential to inspire new models, manage complexity and maintain tractability. We support our argument with an example of a novel integrated model for species distribution modelling, derived from metapopulation theory, which accounts for abiotic constraints, dispersal, biotic interactions and evolution under changing environmental conditions. We hope such a perspective will motivate exciting and novel research, and challenge others to improve on our proposed approach. © 2013 John Wiley & Sons Ltd/CNRS.

Hybridization could be a common phenomenon within the highly diverse lizard genus Liolaemus.

PubMed

Olave, Melisa; Avila, Luciano J; Sites, Jack W; Morando, Mariana

2018-03-26

Hybridization is likely to occur more often between closely related taxa that have had insufficient time to diverge to the point of reproductive incompatibility; hybridization between deeply divergent lineages is rare. In squamate reptiles, hybridization has been proposed as a possible explanation for the extensive paraphyly observed in mitochondrial gene trees in several species complexes of the South American lizard genus Liolaemus. One of the best-documented cases is within the L. boulengeri and L. rothi complexes, which diverged ~5.5 million years ago. Here, we describe a comprehensive study for approaching the hybridization hypothesis between these lizard species complexes. We explored the level of gene tree discordance using the novel 'extra lineage contribution' statistics (XLC, presented in this study) that quantifies the level of gene tree discordance contribution per individual within a species. We included molecular data (12 nuclear and two mitochondrial genes) from 127 individuals, and results of a coalescent model-based analysis show that the most likely explanation for the gene tree-species tree discordance is interspecific hybridization. Our best-supported hypothesis suggests current and past hybridization between L. rothi (rothi complex) and L. tehuelche (boulengeri complex), and independently between L. rothi and L. boulengeri and L. telsen (boulengeri complex). The hybrid descendants are characterized by intermediate phenotypes between the parental species, but are more similar to L. rothi in body size. We discuss the possible role of hybridization in Liolaemus evolution. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

The Origin of Species by Means of Mathematical Modelling.

PubMed

Bessonov, Nikolai; Reinberg, Natalia; Banerjee, Malay; Volpert, Vitaly

2018-04-30

Darwin described biological species as groups of morphologically similar individuals. These groups of individuals can split into several subgroups due to natural selection, resulting in the emergence of new species. Some species can stay stable without the appearance of a new species, some others can disappear or evolve. Some of these evolutionary patterns were described in our previous works independently of each other. In this work we have developed a single model which allows us to reproduce the principal patterns in Darwin's diagram. Some more complex evolutionary patterns are also observed. The relation between Darwin's definition of species, stated above, and Mayr's definition of species (group of individuals that can reproduce) is also discussed.

Archaeogenomic insights into the adaptation of plants to the human environment: pushing plant-hominin co-evolution back to the Pliocene.

PubMed

Allaby, Robin G; Kistler, Logan; Gutaker, Rafal M; Ware, Roselyn; Kitchen, James L; Smith, Oliver; Clarke, Andrew C

2015-02-01

The colonization of the human environment by plants, and the consequent evolution of domesticated forms is increasingly being viewed as a co-evolutionary plant-human process that occurred over a long time period, with evidence for the co-evolutionary relationship between plants and humans reaching ever deeper into the hominin past. This developing view is characterized by a change in emphasis on the drivers of evolution in the case of plants. Rather than individual species being passive recipients of artificial selection pressures and ultimately becoming domesticates, entire plant communities adapted to the human environment. This evolutionary scenario leads to systems level genetic expectations from models that can be explored through ancient DNA and Next Generation Sequencing approaches. Emerging evidence suggests that domesticated genomes fit well with these expectations, with periods of stable complex evolution characterized by large amounts of change associated with relatively small selective value, punctuated by periods in which changes in one-half of the plant-hominin relationship cause rapid, low-complexity adaptation in the other. A corollary of a single plant-hominin co-evolutionary process is that clues about the initiation of the domestication process may well lie deep within the hominin lineage. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

An integrative approach to understanding bird origins.

PubMed

Xu, Xing; Zhou, Zhonghe; Dudley, Robert; Mackem, Susan; Chuong, Cheng-Ming; Erickson, Gregory M; Varricchio, David J

2014-12-12

Recent discoveries of spectacular dinosaur fossils overwhelmingly support the hypothesis that birds are descended from maniraptoran theropod dinosaurs, and furthermore, demonstrate that distinctive bird characteristics such as feathers, flight, endothermic physiology, unique strategies for reproduction and growth, and a novel pulmonary system originated among Mesozoic terrestrial dinosaurs. The transition from ground-living to flight-capable theropod dinosaurs now probably represents one of the best-documented major evolutionary transitions in life history. Recent studies in developmental biology and other disciplines provide additional insights into how bird characteristics originated and evolved. The iconic features of extant birds for the most part evolved in a gradual and stepwise fashion throughout archosaur evolution. However, new data also highlight occasional bursts of morphological novelty at certain stages particularly close to the origin of birds and an unavoidable complex, mosaic evolutionary distribution of major bird characteristics on the theropod tree. Research into bird origins provides a premier example of how paleontological and neontological data can interact to reveal the complexity of major innovations, to answer key evolutionary questions, and to lead to new research directions. A better understanding of bird origins requires multifaceted and integrative approaches, yet fossils necessarily provide the final test of any evolutionary model. Copyright © 2014, American Association for the Advancement of Science.

Evolution of heliobacteria: implications for photosynthetic reaction center complexes

NASA Technical Reports Server (NTRS)

Vermaas, W. F.; Blankenship, R. E. (Principal Investigator)

1994-01-01

The evolutionary position of the heliobacteria, a group of green photosynthetic bacteria with a photosynthetic apparatus functionally resembling Photosystem I of plants and cyanobacteria, has been investigated with respect to the evolutionary relationship to Gram-positive bacteria and cyanobacteria. On the basis of 16S rRNA sequence analysis, the heliobacteria appear to be most closely related to Gram-positive bacteria, but also an evolutionary link to cyanobacteria is evident. Interestingly, a 46-residue domain including the putative sixth membrane-spanning region of the heliobacterial reaction center protein show rather strong similarity (33% identity and 72% similarity) to a region including the sixth membrane-spanning region of the CP47 protein, a chlorophyll-binding core antenna polypeptide of Photosystem II. The N-terminal half of the heliobacterial reaction center polypeptide shows a moderate sequence similarity (22% identity over 232 residues) with the CP47 protein, which is significantly more than the similarity with the Photosystem I core polypeptides in this region. An evolutionary model for photosynthetic reaction center complexes is discussed, in which an ancestral homodimeric reaction center protein (possibly resembling the heliobacterial reaction center protein) with 11 membrane-spanning regions per polypeptide has diverged to give rise to the core of Photosystem I, Photosystem II, and of the photosynthetic apparatus in green, purple, and heliobacteria.

Genome sequencing reveals loci under artificial selection that underlie disease phenotypes in the laboratory rat.

PubMed

Atanur, Santosh S; Diaz, Ana Garcia; Maratou, Klio; Sarkis, Allison; Rotival, Maxime; Game, Laurence; Tschannen, Michael R; Kaisaki, Pamela J; Otto, Georg W; Ma, Man Chun John; Keane, Thomas M; Hummel, Oliver; Saar, Kathrin; Chen, Wei; Guryev, Victor; Gopalakrishnan, Kathirvel; Garrett, Michael R; Joe, Bina; Citterio, Lorena; Bianchi, Giuseppe; McBride, Martin; Dominiczak, Anna; Adams, David J; Serikawa, Tadao; Flicek, Paul; Cuppen, Edwin; Hubner, Norbert; Petretto, Enrico; Gauguier, Dominique; Kwitek, Anne; Jacob, Howard; Aitman, Timothy J

2013-08-01

Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analysis of strain-specific selective sweeps and gene clusters implicated genes and pathways involved in cation transport, angiotensin production, and regulators of oxidative stress in the development of cardiovascular disease phenotypes in rats. Many of the rat loci that we identified overlap with previously mapped loci for related traits in humans, indicating the presence of shared pathways underlying these phenotypes in rats and humans. These data represent a step change in resources available for evolutionary analysis of complex traits in disease models. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Genome Sequencing Reveals Loci under Artificial Selection that Underlie Disease Phenotypes in the Laboratory Rat

PubMed Central

Atanur, Santosh S.; Diaz, Ana Garcia; Maratou, Klio; Sarkis, Allison; Rotival, Maxime; Game, Laurence; Tschannen, Michael R.; Kaisaki, Pamela J.; Otto, Georg W.; Ma, Man Chun John; Keane, Thomas M.; Hummel, Oliver; Saar, Kathrin; Chen, Wei; Guryev, Victor; Gopalakrishnan, Kathirvel; Garrett, Michael R.; Joe, Bina; Citterio, Lorena; Bianchi, Giuseppe; McBride, Martin; Dominiczak, Anna; Adams, David J.; Serikawa, Tadao; Flicek, Paul; Cuppen, Edwin; Hubner, Norbert; Petretto, Enrico; Gauguier, Dominique; Kwitek, Anne; Jacob, Howard; Aitman, Timothy J.

2013-01-01

Summary Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analysis of strain-specific selective sweeps and gene clusters implicated genes and pathways involved in cation transport, angiotensin production, and regulators of oxidative stress in the development of cardiovascular disease phenotypes in rats. Many of the rat loci that we identified overlap with previously mapped loci for related traits in humans, indicating the presence of shared pathways underlying these phenotypes in rats and humans. These data represent a step change in resources available for evolutionary analysis of complex traits in disease models. PaperClip PMID:23890820

Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity.

PubMed

Frickel, Jens; Theodosiou, Loukas; Becks, Lutz

2017-10-17

Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus-host and prey-predator) with a more complex three-species system (virus-host-predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host-virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host-virus coevolution in the complex system and that the virus' effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species.

Phenotypic landscape inference reveals multiple evolutionary paths to C4 photosynthesis

PubMed Central

Williams, Ben P; Johnston, Iain G; Covshoff, Sarah; Hibberd, Julian M

2013-01-01

C4 photosynthesis has independently evolved from the ancestral C3 pathway in at least 60 plant lineages, but, as with other complex traits, how it evolved is unclear. Here we show that the polyphyletic appearance of C4 photosynthesis is associated with diverse and flexible evolutionary paths that group into four major trajectories. We conducted a meta-analysis of 18 lineages containing species that use C3, C4, or intermediate C3–C4 forms of photosynthesis to parameterise a 16-dimensional phenotypic landscape. We then developed and experimentally verified a novel Bayesian approach based on a hidden Markov model that predicts how the C4 phenotype evolved. The alternative evolutionary histories underlying the appearance of C4 photosynthesis were determined by ancestral lineage and initial phenotypic alterations unrelated to photosynthesis. We conclude that the order of C4 trait acquisition is flexible and driven by non-photosynthetic drivers. This flexibility will have facilitated the convergent evolution of this complex trait. DOI: http://dx.doi.org/10.7554/eLife.00961.001 PMID:24082995

Strain-weakening rheology of marine sponges and its evolutionary implication

NASA Astrophysics Data System (ADS)

Kraus, Emily; Janmey, Paul; Sweeney, Alison; van Oosten, Anne

Animal cells respond to mechanical stimuli as sensitively as they do to chemical stimuli. Further, cell proliferation is dependent on the viscoelasticity of the polymeric extracellular matrix (ECM) in which they are embedded. Biophysicists are therefore motivated to understand the biomechanics of the ECM itself. To date, this work has focused on the more familiar Bilateria, animals, including humans, with bilateral symmetry. The ECM of this group of animals is now understood to exhibit non-linear rheology that is typically strain- and compression-stiffening, and shear moduli that are frequency-dependent. These complex properties have been attributed to the semi-flexible nature of the underlying polymers. In contrast, we show that marine sponges are markedly strain-weakening under physiologically relevant conditions. Since sponges are a much earlier evolutionary branch than Bilateria, we interrogate the evolutionary potential and biochemical underpinnings of this novel complex rheology in filamentous networks, and cells ability to respond. Further, their life history strategy is uniquely dependent on flow and correlated shear stress, making them a model organism to study self-assembly algorithms organized around flow.

The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules

PubMed Central

Orsini, Luisa; Schwenk, Klaus; De Meester, Luc; Colbourne, John K.; Pfrender, Michael E.; Weider, Lawrence J.

2013-01-01

Evolutionary changes are determined by a complex assortment of ecological, demographic and adaptive histories. Predicting how evolution will shape the genetic structures of populations coping with current (and future) environmental challenges has principally relied on investigations through space, in lieu of time, because long-term phenotypic and molecular data are scarce. Yet, dormant propagules in sediments, soils and permafrost are convenient natural archives of population-histories from which to trace adaptive trajectories along extended time periods. DNA sequence data obtained from these natural archives, combined with pioneering methods for analyzing both ecological and population genomic time-series data, are likely to provide predictive models to forecast evolutionary responses of natural populations to environmental changes resulting from natural and anthropogenic stressors, including climate change. PMID:23395434

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

PubMed

Zhu, Xuli; Jiang, Libo; Ye, Meixia; Sun, Lidan; Gragnoli, Claudia; Wu, Rongling

2016-05-01

Natural selection has shaped the evolution of organisms toward optimizing their structural and functional design. However, how this universal principle can enhance genotype-phenotype mapping of quantitative traits has remained unexplored. Here we show that the integration of this principle and functional mapping through evolutionary game theory gains new insight into the genetic architecture of complex traits. By viewing phenotype formation as an evolutionary system, we formulate mathematical equations to model the ecological mechanisms that drive the interaction and coordination of its constituent components toward population dynamics and stability. Functional mapping provides a procedure for estimating the genetic parameters that specify the dynamic relationship of competition and cooperation and predicting how genes mediate the evolution of this relationship during trait formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

The environmental zero-point problem in evolutionary reaction norm modeling.

PubMed

Ergon, Rolf

2018-04-01

There is a potential problem in present quantitative genetics evolutionary modeling based on reaction norms. Such models are state-space models, where the multivariate breeder's equation in some form is used as the state equation that propagates the population state forward in time. These models use the implicit assumption of a constant reference environment, in many cases set to zero. This zero-point is often the environment a population is adapted to, that is, where the expected geometric mean fitness is maximized. Such environmental reference values follow from the state of the population system, and they are thus population properties. The environment the population is adapted to, is, in other words, an internal population property, independent of the external environment. It is only when the external environment coincides with the internal reference environment, or vice versa, that the population is adapted to the current environment. This is formally a result of state-space modeling theory, which is an important theoretical basis for evolutionary modeling. The potential zero-point problem is present in all types of reaction norm models, parametrized as well as function-valued, and the problem does not disappear when the reference environment is set to zero. As the environmental reference values are population characteristics, they ought to be modeled as such. Whether such characteristics are evolvable is an open question, but considering the complexity of evolutionary processes, such evolvability cannot be excluded without good arguments. As a straightforward solution, I propose to model the reference values as evolvable mean traits in their own right, in addition to other reaction norm traits. However, solutions based on an evolvable G matrix are also possible.

Evolutionary games on multilayer networks: a colloquium

NASA Astrophysics Data System (ADS)

Wang, Zhen; Wang, Lin; Szolnoki, Attila; Perc, Matjaž

2015-05-01

Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.

Cultural evolutionary theory: How culture evolves and why it matters

PubMed Central

Creanza, Nicole; Kolodny, Oren; Feldman, Marcus W.

2017-01-01

Human cultural traits—behaviors, ideas, and technologies that can be learned from other individuals—can exhibit complex patterns of transmission and evolution, and researchers have developed theoretical models, both verbal and mathematical, to facilitate our understanding of these patterns. Many of the first quantitative models of cultural evolution were modified from existing concepts in theoretical population genetics because cultural evolution has many parallels with, as well as clear differences from, genetic evolution. Furthermore, cultural and genetic evolution can interact with one another and influence both transmission and selection. This interaction requires theoretical treatments of gene–culture coevolution and dual inheritance, in addition to purely cultural evolution. In addition, cultural evolutionary theory is a natural component of studies in demography, human ecology, and many other disciplines. Here, we review the core concepts in cultural evolutionary theory as they pertain to the extension of biology through culture, focusing on cultural evolutionary applications in population genetics, ecology, and demography. For each of these disciplines, we review the theoretical literature and highlight relevant empirical studies. We also discuss the societal implications of the study of cultural evolution and of the interactions of humans with one another and with their environment. PMID:28739941

Cultural evolutionary theory: How culture evolves and why it matters.

PubMed

Creanza, Nicole; Kolodny, Oren; Feldman, Marcus W

2017-07-24

Human cultural traits-behaviors, ideas, and technologies that can be learned from other individuals-can exhibit complex patterns of transmission and evolution, and researchers have developed theoretical models, both verbal and mathematical, to facilitate our understanding of these patterns. Many of the first quantitative models of cultural evolution were modified from existing concepts in theoretical population genetics because cultural evolution has many parallels with, as well as clear differences from, genetic evolution. Furthermore, cultural and genetic evolution can interact with one another and influence both transmission and selection. This interaction requires theoretical treatments of gene-culture coevolution and dual inheritance, in addition to purely cultural evolution. In addition, cultural evolutionary theory is a natural component of studies in demography, human ecology, and many other disciplines. Here, we review the core concepts in cultural evolutionary theory as they pertain to the extension of biology through culture, focusing on cultural evolutionary applications in population genetics, ecology, and demography. For each of these disciplines, we review the theoretical literature and highlight relevant empirical studies. We also discuss the societal implications of the study of cultural evolution and of the interactions of humans with one another and with their environment.

Emergence of structured communities through evolutionary dynamics.

PubMed

Shtilerman, Elad; Kessler, David A; Shnerb, Nadav M

2015-10-21

Species-rich communities, in which many competing species coexist in a single trophic level, are quite frequent in nature, but pose a formidable theoretical challenge. In particular, it is known that complex competitive systems become unstable and unfeasible when the number of species is large. Recently, many studies have attributed the stability of natural communities to the structure of the interspecific interaction network, yet the nature of such structures and the underlying mechanisms responsible for them remain open questions. Here we introduce an evolutionary model, based on the generic Lotka-Volterra competitive framework, from which a stable, structured, diverse community emerges spontaneously. The modular structure of the competition matrix reflects the phylogeny of the community, in agreement with the hierarchial taxonomic classification. Closely related species tend to have stronger niche overlap and weaker fitness differences, as opposed to pairs of species from different modules. The competitive-relatedness hypothesis and the idea of emergent neutrality are discussed in the context of this evolutionary model. Copyright © 2015 Elsevier Ltd. All rights reserved.

On the Origin of Complex Adaptive Traits: Progress Since the Darwin Versus Mivart Debate.

PubMed

Suzuki, Takao K

2017-06-01

The evolutionary origin of complex adaptive traits has been a controversial topic in the history of evolutionary biology. Although Darwin argued for the gradual origins of complex adaptive traits within the theory of natural selection, Mivart insisted that natural selection could not account for the incipient stages of complex traits. The debate starting from Darwin and Mivart eventually engendered two opposite views: gradualism and saltationism. Although this has been a long-standing debate, the issue remains unresolved. However, recent studies have interrogated classic examples of complex traits, such as the asymmetrical eyes of flatfishes and leaf mimicry of butterfly wings, whose origins were debated by Darwin and Mivart. Here, I review recent findings as a starting point to provide a modern picture of the evolution of complex adaptive traits. First, I summarize the empirical evidence that unveils the evolutionary steps toward complex traits. I then argue that the evolution of complex traits could be understood within the concept of "reducible complexity." Through these discussions, I propose a conceptual framework for the formation of complex traits, named as reducible-composable multicomponent systems, that satisfy two major characteristics: reducibility into a sum of subcomponents and composability to construct traits from various additional and combinatorial arrangements of the subcomponents. This conceptual framework provides an analytical foundation for exploring evolutionary pathways to build up complex traits. This review provides certain essential avenues for deciphering the origin of complex adaptive traits. © 2017 Wiley Periodicals, Inc.

Rise and fall of political complexity in island South-East Asia and the Pacific.

PubMed

Currie, Thomas E; Greenhill, Simon J; Gray, Russell D; Hasegawa, Toshikazu; Mace, Ruth

2010-10-14

There is disagreement about whether human political evolution has proceeded through a sequence of incremental increases in complexity, or whether larger, non-sequential increases have occurred. The extent to which societies have decreased in complexity is also unclear. These debates have continued largely in the absence of rigorous, quantitative tests. We evaluated six competing models of political evolution in Austronesian-speaking societies using phylogenetic methods. Here we show that in the best-fitting model political complexity rises and falls in a sequence of small steps. This is closely followed by another model in which increases are sequential but decreases can be either sequential or in bigger drops. The results indicate that large, non-sequential jumps in political complexity have not occurred during the evolutionary history of these societies. This suggests that, despite the numerous contingent pathways of human history, there are regularities in cultural evolution that can be detected using computational phylogenetic methods.

[Morphogenetic foundations for increased evolutionary complexity in the organization of thecate hydroids shoots (Cnidaria, Hydroidomedusa, Leptomedusae)].

PubMed

Kosevich, I A

2012-01-01

The morphogenetic approach is applied to analyze the diversity of spatial organization of shoots in thecate hydroids (Cnidaria, Hydroidomedusa, Leptomedusae). The main tendencies and constraints of increased evolutionary complexity in thecate hydroids colonies are uncovered.

Ecological and evolutionary consequences of explicit spatial structure in exploiter-victim systems

NASA Astrophysics Data System (ADS)

Klopfer, Eric David

One class of spatial model which has been widely used in ecology has been termed "pseudo-spatial models" and classically employs various types of aggregation in studying the coexistence of competing parasitoids. Yet, little is known about the relative effects of each of these aggregation behaviors. Thus, in Chapter 1 I chose to examine three types of aggregation and explore their relative strengths in promoting coexistence of two competing parasitoids. A striking shortcoming of spatial models in ecology to date is that there is a relative lack of use of spatial models to investigate problems on the evolutionary as opposed to ecological time scale. Consequently, in Chapter 2 I chose to start with a classic problem of evolutionary time scale--the evolution of virulence and predation rates. Debate about this problem has continued through several decades, yet many instances are not adequately explained by current models. In this study I explored the effect of explicit spatial structure on exploitation rates by comparing a cellular automata (CA) exploiter-victim model which incorporates local dynamics to a metapopulation model which does not include such dynamics. One advantage of CA models is that they are defined by simple rules rather than the often complex equations of other types of spatial models. This is an extremely useful attribute when one wants to convey results of models to an audience with an applied bent that is often uncomfortable with hard-to-understand equations. Thus, in Chapter 3, through the use of CA models I show that there are spatial phenomena which alter the impact of introduced predators and that these phenomena are potentially important in the implementation of biocontrol programs. The relatively recent incorporation of spatial models into the ecological literature has left most ecologists and evolutionary biologists without the ability to understand, let alone employ, spatial models in evolutionary problems. In order to give the next generation of potential ecologists a better understanding of these models, in Chapter 4 I present an interactive tutorial in which students are able to explore the most well studied of these models (the evolution of cooperation in a spatial environment).

Investigation of a protein complex network

NASA Astrophysics Data System (ADS)

Mashaghi, A. R.; Ramezanpour, A.; Karimipour, V.

2004-09-01

The budding yeast Saccharomyces cerevisiae is the first eukaryote whose genome has been completely sequenced. It is also the first eukaryotic cell whose proteome (the set of all proteins) and interactome (the network of all mutual interactions between proteins) has been analyzed. In this paper we study the structure of the yeast protein complex network in which weighted edges between complexes represent the number of shared proteins. It is found that the network of protein complexes is a small world network with scale free behavior for many of its distributions. However we find that there are no strong correlations between the weights and degrees of neighboring complexes. To reveal non-random features of the network we also compare it with a null model in which the complexes randomly select their proteins. Finally we propose a simple evolutionary model based on duplication and divergence of proteins.

Estimating the dilemma strength for game systems. Comment on "Universal scaling for the dilemma strength in evolutionary games", by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Chen, Xiaojie

2015-09-01

The puzzle of cooperation exists widely in the realistic world, including biological, social, and engineering systems. How to solve the cooperation puzzle has received considerable attention in recent years [1]. Evolutionary game theory provides a common mathematical framework to study the problem of cooperation. In principle, these practical biological, social, or engineering systems can be described by complex game models composed of multiple autonomous individuals with mutual interactions. And generally there exists a dilemma for the evolution of cooperation in the game systems.

Wetting of nonconserved residue-backbones: A feature indicative of aggregation associated regions of proteins.

PubMed

Pradhan, Mohan R; Pal, Arumay; Hu, Zhongqiao; Kannan, Srinivasaraghavan; Chee Keong, Kwoh; Lane, David P; Verma, Chandra S

2016-02-01

Aggregation is an irreversible form of protein complexation and often toxic to cells. The process entails partial or major unfolding that is largely driven by hydration. We model the role of hydration in aggregation using "Dehydrons." "Dehydrons" are unsatisfied backbone hydrogen bonds in proteins that seek shielding from water molecules by associating with ligands or proteins. We find that the residues at aggregation interfaces have hydrated backbones, and in contrast to other forms of protein-protein interactions, are under less evolutionary pressure to be conserved. Combining evolutionary conservation of residues and extent of backbone hydration allows us to distinguish regions on proteins associated with aggregation (non-conserved dehydron-residues) from other interaction interfaces (conserved dehydron-residues). This novel feature can complement the existing strategies used to investigate protein aggregation/complexation. © 2015 Wiley Periodicals, Inc.

Rethinking the dispersal of Homo sapiens out of Africa.

PubMed

Groucutt, Huw S; Petraglia, Michael D; Bailey, Geoff; Scerri, Eleanor M L; Parton, Ash; Clark-Balzan, Laine; Jennings, Richard P; Lewis, Laura; Blinkhorn, James; Drake, Nick A; Breeze, Paul S; Inglis, Robyn H; Devès, Maud H; Meredith-Williams, Matthew; Boivin, Nicole; Thomas, Mark G; Scally, Aylwyn

2015-01-01

Current fossil, genetic, and archeological data indicate that Homo sapiens originated in Africa in the late Middle Pleistocene. By the end of the Late Pleistocene, our species was distributed across every continent except Antarctica, setting the foundations for the subsequent demographic and cultural changes of the Holocene. The intervening processes remain intensely debated and a key theme in hominin evolutionary studies. We review archeological, fossil, environmental, and genetic data to evaluate the current state of knowledge on the dispersal of Homo sapiens out of Africa. The emerging picture of the dispersal process suggests dynamic behavioral variability, complex interactions between populations, and an intricate genetic and cultural legacy. This evolutionary and historical complexity challenges simple narratives and suggests that hybrid models and the testing of explicit hypotheses are required to understand the expansion of Homo sapiens into Eurasia. © 2015 Wiley Periodicals, Inc.

Brain shape convergence in the adaptive radiation of New World monkeys

PubMed Central

Aristide, Leandro; dos Reis, Sergio Furtado; Machado, Alessandra C.; Lima, Inaya; Lopes, Ricardo T.; Perez, S. Ivan

2016-01-01

Primates constitute one of the most diverse mammalian clades, and a notable feature of their diversification is the evolution of brain morphology. However, the evolutionary processes and ecological factors behind these changes are largely unknown. In this work, we investigate brain shape diversification of New World monkeys during their adaptive radiation in relation to different ecological dimensions. Our results reveal that brain diversification in this clade can be explained by invoking a model of adaptive peak shifts to unique and shared optima, defined by a multidimensional ecological niche hypothesis. Particularly, we show that the evolution of convergent brain phenotypes may be related to ecological factors associated with group size (e.g., social complexity). Together, our results highlight the complexity of brain evolution and the ecological significance of brain shape changes during the evolutionary diversification of a primate clade. PMID:26858427

Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

NASA Astrophysics Data System (ADS)

Wagh, Aditi

Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both modalities, with students who built models not incorporating slippage explanations in responses. Study 3 compares these modalities with a control using traditional activities. Pre and posttests reveal that the two modalities manifested greater facility with accessing and assembling rules than the control. The dissertation offers implications for the design of learning environments for evolutionary change, design of the two modalities based on their strengths and weaknesses, and teacher training for the same.

Multi-target drugs to address multiple checkpoints in complex inflammatory pathologies: evolutionary cues for novel "first-in-class" anti-inflammatory drug candidates: a reviewer's perspective.

PubMed

Mathew, Geetha; Unnikrishnan, M K

2015-10-01

Inflammation is a complex, metabolically expensive process involving multiple signaling pathways and regulatory mechanisms which have evolved over evolutionary timescale. Addressing multiple targets of inflammation holistically, in moderation, is probably a more evolutionarily viable strategy, as compared to current therapy which addresses drug targets in isolation. Polypharmacology, addressing multiple targets, is commonly used in complex ailments, suggesting the superior safety and efficacy profile of multi-target (MT) drugs. Phenotypic drug discovery, which generated successful MT and first-in-class drugs in the past, is now re-emerging. A multi-pronged approach, which modulates the evolutionarily conserved, robust and pervasive cellular mechanisms of tissue repair, with AMPK at the helm, regulating the complex metabolic/immune/redox pathways underlying inflammation, is perhaps a more viable strategy than addressing single targets in isolation. Molecules that modulate multiple molecular mechanisms of inflammation in moderation (modulating TH cells toward the anti-inflammatory phenotype, activating AMPK, stimulating Nrf2 and inhibiting NFκB) might serve as a model for a novel Darwinian "first-in-class" therapeutic category that holistically addresses immune, redox and metabolic processes associated with inflammatory repair. Such a multimodal biological activity is supported by the fact that several non-calorific pleiotropic natural products with anti-inflammatory action have been incorporated into diet (chiefly guided by the adaptive development of olfacto-gustatory preferences over evolutionary timescales) rendering such molecules, endowed with evolutionarily privileged molecular scaffolds, naturally oriented toward multiple targets.

Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity

PubMed Central

Frickel, Jens; Theodosiou, Loukas

2017-01-01

Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus–host and prey–predator) with a more complex three-species system (virus–host–predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host–virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host–virus coevolution in the complex system and that the virus’ effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species. PMID:28973943

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model.

PubMed

Nené, Nuno R; Dunham, Alistair S; Illingworth, Christopher J R

2018-05-01

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. Copyright © 2018 Nené et al.

Exploring the evolutionary mechanism of complex supply chain systems using evolving hypergraphs

NASA Astrophysics Data System (ADS)

Suo, Qi; Guo, Jin-Li; Sun, Shiwei; Liu, Han

2018-01-01

A new evolutionary model is proposed to describe the characteristics and evolution pattern of supply chain systems using evolving hypergraphs, in which nodes represent enterprise entities while hyperedges represent the relationships among diverse trades. The nodes arrive at the system in accordance with a Poisson process, with the evolving process incorporating the addition of new nodes, linking of old nodes, and rewiring of links. Grounded in the Poisson process theory and continuum theory, the stationary average hyperdegree distribution is shown to follow a shifted power law (SPL), and the theoretical predictions are consistent with the results of numerical simulations. Testing the impact of parameters on the model yields a positive correlation between hyperdegree and degree. The model also uncovers macro characteristics of the relationships among enterprises due to the microscopic interactions among individuals.

The Langley Research Center CSI phase-0 evolutionary model testbed-design and experimental results

NASA Technical Reports Server (NTRS)

Belvin, W. K.; Horta, Lucas G.; Elliott, K. B.

1991-01-01

A testbed for the development of Controls Structures Interaction (CSI) technology is described. The design philosophy, capabilities, and early experimental results are presented to introduce some of the ongoing CSI research at NASA-Langley. The testbed, referred to as the Phase 0 version of the CSI Evolutionary model (CEM), is the first stage of model complexity designed to show the benefits of CSI technology and to identify weaknesses in current capabilities. Early closed loop test results have shown non-model based controllers can provide an order of magnitude increase in damping in the first few flexible vibration modes. Model based controllers for higher performance will need to be robust to model uncertainty as verified by System ID tests. Data are presented that show finite element model predictions of frequency differ from those obtained from tests. Plans are also presented for evolution of the CEM to study integrated controller and structure design as well as multiple payload dynamics.

The evolutionary dynamics of language.

PubMed

Steels, Luc; Szathmáry, Eörs

2018-02-01

The well-established framework of evolutionary dynamics can be applied to the fascinating open problems how human brains are able to acquire and adapt language and how languages change in a population. Schemas for handling grammatical constructions are the replicating unit. They emerge and multiply with variation in the brains of individuals and undergo selection based on their contribution to needed expressive power, communicative success and the reduction of cognitive effort. Adopting this perspective has two major benefits. (i) It makes a bridge to neurobiological models of the brain that have also adopted an evolutionary dynamics point of view, thus opening a new horizon for studying how human brains achieve the remarkably complex competence for language. And (ii) it suggests a new foundation for studying cultural language change as an evolutionary dynamics process. The paper sketches this novel perspective, provides references to empirical data and computational experiments, and points to open problems. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

A single evolutionary innovation drives the deep evolution of symbiotic N2-fixation in angiosperms

PubMed Central

Werner, Gijsbert D. A.; Cornwell, William K.; Sprent, Janet I.; Kattge, Jens; Kiers, E. Toby

2014-01-01

Symbiotic associations occur in every habitat on earth, but we know very little about their evolutionary histories. Current models of trait evolution cannot adequately reconstruct the deep history of symbiotic innovation, because they assume homogenous evolutionary processes across millions of years. Here we use a recently developed, heterogeneous and quantitative phylogenetic framework to study the origin of the symbiosis between angiosperms and nitrogen-fixing (N2) bacterial symbionts housed in nodules. We compile the largest database of global nodulating plant species and reconstruct the symbiosis’ evolution. We identify a single, cryptic evolutionary innovation driving symbiotic N2-fixation evolution, followed by multiple gains and losses of the symbiosis, and the subsequent emergence of ‘stable fixers’ (clades extremely unlikely to lose the symbiosis). Originating over 100 MYA, this innovation suggests deep homology in symbiotic N2-fixation. Identifying cryptic innovations on the tree of life is key to understanding the evolution of complex traits, including symbiotic partnerships. PMID:24912610

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Thompson, Joel; Fisher, Daniel

2013-03-01

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

Evolutionary analyses of non-genealogical bonds produced by introgressive descent.

PubMed

Bapteste, Eric; Lopez, Philippe; Bouchard, Frédéric; Baquero, Fernando; McInerney, James O; Burian, Richard M

2012-11-06

All evolutionary biologists are familiar with evolutionary units that evolve by vertical descent in a tree-like fashion in single lineages. However, many other kinds of processes contribute to evolutionary diversity. In vertical descent, the genetic material of a particular evolutionary unit is propagated by replication inside its own lineage. In what we call introgressive descent, the genetic material of a particular evolutionary unit propagates into different host structures and is replicated within these host structures. Thus, introgressive descent generates a variety of evolutionary units and leaves recognizable patterns in resemblance networks. We characterize six kinds of evolutionary units, of which five involve mosaic lineages generated by introgressive descent. To facilitate detection of these units in resemblance networks, we introduce terminology based on two notions, P3s (subgraphs of three nodes: A, B, and C) and mosaic P3s, and suggest an apparatus for systematic detection of introgressive descent. Mosaic P3s correspond to a distinct type of evolutionary bond that is orthogonal to the bonds of kinship and genealogy usually examined by evolutionary biologists. We argue that recognition of these evolutionary bonds stimulates radical rethinking of key questions in evolutionary biology (e.g., the relations among evolutionary players in very early phases of evolutionary history, the origin and emergence of novelties, and the production of new lineages). This line of research will expand the study of biological complexity beyond the usual genealogical bonds, revealing additional sources of biodiversity. It provides an important step to a more realistic pluralist treatment of evolutionary complexity.

Evolution of complex organic molecules in hot molecular cores. Synthetic spectra at (sub-)mm wavebands

NASA Astrophysics Data System (ADS)

Choudhury, R.; Schilke, P.; Stéphan, G.; Bergin, E.; Möller, T.; Schmiedeke, A.; Zernickel, A.

2015-03-01

Context. Hot molecular cores (HMCs) are intermediate stages of high-mass star formation and are also known for their rich chemical reservoirs and emission line spectra at (sub-)mm wavebands. Complex organic molecules (COMs) such as methanol (CH3OH), ethanol (C2H5OH), dimethyl ether (CH3OCH3), and methyl formate (HCOOCH3) produce most of these observed lines. The observed spectral feature of HMCs such as total number of emission lines and associated line intensities are also found to vary with evolutionary stages. Aims: We aim to investigate the spectral evolution of these COMs to explore the initial evolutionary stages of high-mass star formation including HMCs. Methods: We developed various 3D models for HMCs guided by the evolutionary scenarios proposed by recent empirical and modeling studies. We then investigated the spatio-temporal variation of temperature and molecular abundances in HMCs by consistently coupling gas-grain chemical evolution with radiative transfer calculations. We explored the effects of varying physical conditions on molecular abundances including density distribution and luminosity evolution of the central protostar(s) among other parameters. Finally, we simulated the synthetic spectra for these models at different evolutionary timescales to compare with observations. Results: Temperature has a profound effect on the formation of COMs through the depletion and diffusion on grain surface to desorption and further gas-phase processing. The time-dependent temperature structure of the hot core models provides a realistic framework for investigating the spatial variation of ice mantle evaporation as a function of evolutionary timescales. We find that a slightly higher value (15 K) than the canonical dark cloud temperature (10 K) provides a more productive environment for COM formation on grain surface. With increasing protostellar luminosity, the water ice evaporation font (~100 K) expands and the spatial distribution of gas phase abundances of these COMs also spreads out. We calculated the temporal variation of the radial profiles of these COMs for different hot core models. These profiles resemble the so-called jump profiles with relative abundances higher than 10-9 within the evaporation font will furthermore be useful to model the observed spectra of hot cores. We present the simulated spectra of these COMs for different hot core models at various evolutionary timescales. A qualitative comparison of the simulated and observed spectra suggests that these self-consistent hot core models can reproduce the notable trends in hot core spectral variation within the typical hot core timescales of 105 year. These models predict that the spatial distribution of various emission line maps will also expand with evolutionary time; this feature can be used to constrain the relative desorption energies of the molecules that mainly form on the grain surface and return to the gas phase via thermal desorption. The detailed modeling of the thermal structure of hot cores with similar masses along with the characterization of the desorption energies of different molecules can be used to constrain the luminosity evolution of the central protostars. The model predictions can be compared with high resolution observation that can probe scales of a few thousand AU in high-mass star forming regions such as from Atacama Large Millimeter/submillimeter Array (ALMA). We used a spectral fitting method to analyze the simulated spectra and find that it significantly underestimates some of the physical parameters such as temperature. The coupling of chemical evolution with radiative transfer models will be particularly useful to decipher the physical structure of hot cores and also to constrain the initial evolutionary stages of high-mass star formation. Appendices are available in electronic form at http://www.aanda.org

On the evolution of misunderstandings about evolutionary psychology.

PubMed

Young, J; Persell, R

2000-04-01

Some of the controversy surrounding evolutionary explanations of human behavior may be due to cognitive information-processing patterns that are themselves the result of evolutionary processes. Two such patterns are (1) the tendency to oversimplify information so as to reduce demand on cognitive resources and (2) our strong desire to generate predictability and stability from perceptions of the external world. For example, research on social stereotyping has found that people tend to focus automatically on simplified social-categorical information, to use such information when deciding how to behave, and to rely on such information even in the face of contradictory evidence. Similarly, an undying debate over nature vs. nurture is shaped by various data-reduction strategies that frequently oversimplify, and thus distort, the intent of the supporting arguments. This debate is also often marked by an assumption that either the nature or the nurture domain may be justifiably excluded at an explanatory level because one domain appears to operate in a sufficiently stable and predictable way for a particular argument. As a result, critiques in-veighed against evolutionary explanations of behavior often incorporate simplified--and erroneous--assumptions about either the mechanics of how evolution operates or the inevitable implications of evolution for understanding human behavior. The influences of these tendencies are applied to a discussion of the heritability of behavioral characteristics. It is suggested that the common view that Mendelian genetics can explain the heritability of complex behaviors, with a one-gene-one-trait process, is misguided. Complex behaviors are undoubtedly a product of a more complex interaction between genes and environment, ensuring that both nature and nurture must be accommodated in a yet-to-be-developed post-Mendelian model of genetic influence. As a result, current public perceptions of evolutionary explanations of behavior are handicapped by the lack of clear articulation of the relationship between inherited genes and manifest behavior.

An IUR evolutionary game model on the patent cooperate of Shandong China

NASA Astrophysics Data System (ADS)

Liu, Mengmeng; Ma, Yinghong; Liu, Zhiyuan; You, Xuemei

2017-06-01

Organizations of industries and university & research institutes cooperate to meet their respective needs based on social contacts, trust and share complementary resources. From the perspective of complex network together with the patent data of Shandong province in China, a novel evolutionary game model on patent cooperation network is presented. Two sides in the game model are industries and universities & research institutes respectively. The cooperation is represented by a connection when a new patent is developed together by the two sides. The optimal strategy of the evolutionary game model is quantified by the average positive cooperation probability p ¯ and the average payoff U ¯ . The feasibility of this game model is simulated on the parameters such as the knowledge spillover, the punishment, the development cost and the distribution coefficient of the benefit. The numerical simulations show that the cooperative behaviors are affected by the variation of parameters. The knowledge spillover displays different behaviors when the punishment is larger than the development cost or less than it. Those results indicate that reasonable punishment would improve the positive cooperation. The appropriate punishment will be useful to enhance the big degree nodes positively cooperate with industries and universities & research institutes. And an equitable plan for the distribution of cooperative profits is half-and-half distribution strategy for the two sides in game.

Evolution of morphology and locomotor performance in anurans: relationships with microhabitat diversification.

PubMed

Citadini, J M; Brandt, R; Williams, C R; Gomes, F R

2018-03-01

The relationships between morphology, performance, behavior and ecology provide evidence for multiple and complex phenotypic adaptations. The anuran body plan, for example, is evolutionarily conserved and shows clear specializations to jumping performance back at least to the early Jurassic. However, there are instances of more recent adaptation to habit diversity in the post-cranial skeleton, including relative limb length. The present study tested adaptive models of morphological evolution in anurans associated with the diversity of microhabitat use (semi-aquatic arboreal, fossorial, torrent, and terrestrial) in species of anuran amphibians from Brazil and Australia. We use phylogenetic comparative methods to determine which evolutionary models, including Brownian motion (BM) and Ornstein-Uhlenbeck (OU) are consistent with morphological variation observed across anuran species. Furthermore, this study investigated the relationship of maximum distance jumped as a function of components of morphological variables and microhabitat use. We found there are multiple optima of limb lengths associated to different microhabitats with a trend of increasing hindlimbs in torrent, arboreal, semi-aquatic whereas fossorial and terrestrial species evolve toward optima with shorter hindlimbs. Moreover, arboreal, semi-aquatic and torrent anurans have higher jumping performance and longer hindlimbs, when compared to terrestrial and fossorial species. We corroborate the hypothesis that evolutionary modifications of overall limb morphology have been important in the diversification of locomotor performance along the anuran phylogeny. Such evolutionary changes converged in different phylogenetic groups adapted to similar microhabitat use in two different zoogeographical regions. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

The complex interplay between macronutrient intake, cuticular hydrocarbon expression and mating success in male decorated crickets.

PubMed

Rapkin, J; Jensen, K; House, C M; Sakaluk, S K; Sakaluk, J K; Hunt, J

2017-04-01

The condition dependence of male sexual traits plays a central role in sexual selection theory. Relatively little, however, is known about the condition dependence of chemical signals used in mate choice and their subsequent effects on male mating success. Furthermore, few studies have isolated the specific nutrients responsible for condition-dependent variation in male sexual traits. Here, we used nutritional geometry to determine the effect of protein (P) and carbohydrate (C) intake on male cuticular hydrocarbon (CHC) expression and mating success in male decorated crickets (Gryllodes sigillatus). We show that both traits are maximized at a moderate-to-high intake of nutrients in a P:C ratio of 1 : 1.5. We also show that female precopulatory mate choice exerts a complex pattern of linear and quadratic sexual selection on this condition-dependent variation in male CHC expression. Structural equation modelling revealed that although the effect of nutrient intake on mating success is mediated through condition-dependent CHC expression, it is not exclusively so, suggesting that other traits must also play an important role. Collectively, our results suggest that the complex interplay between nutrient intake, CHC expression and mating success plays an important role in the operation of sexual selection in G. sigillatus. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Opsins have evolved under the permanent heterozygote model: insights from phylotranscriptomics of Odonata.

PubMed

Suvorov, Anton; Jensen, Nicholas O; Sharkey, Camilla R; Fujimoto, M Stanley; Bodily, Paul; Wightman, Haley M Cahill; Ogden, T Heath; Clement, Mark J; Bybee, Seth M

2017-03-01

Gene duplication plays a central role in adaptation to novel environments by providing new genetic material for functional divergence and evolution of biological complexity. Several evolutionary models have been proposed for gene duplication to explain how new gene copies are preserved by natural selection, but these models have rarely been tested using empirical data. Opsin proteins, when combined with a chromophore, form a photopigment that is responsible for the absorption of light, the first step in the phototransduction cascade. Adaptive gene duplications have occurred many times within the animal opsins' gene family, leading to novel wavelength sensitivities. Consequently, opsins are an attractive choice for the study of gene duplication evolutionary models. Odonata (dragonflies and damselflies) have the largest opsin repertoire of any insect currently known. Additionally, there is tremendous variation in opsin copy number between species, particularly in the long-wavelength-sensitive (LWS) class. Using comprehensive phylotranscriptomic and statistical approaches, we tested various evolutionary models of gene duplication. Our results suggest that both the blue-sensitive (BS) and LWS opsin classes were subjected to strong positive selection that greatly weakens after multiple duplication events, a pattern that is consistent with the permanent heterozygote model. Due to the immense interspecific variation and duplicability potential of opsin genes among odonates, they represent a unique model system to test hypotheses regarding opsin gene duplication and diversification at the molecular level. © 2016 John Wiley & Sons Ltd.

Probabilistic modeling of the evolution of gene synteny within reconciled phylogenies

PubMed Central

2015-01-01

Background Most models of genome evolution concern either genetic sequences, gene content or gene order. They sometimes integrate two of the three levels, but rarely the three of them. Probabilistic models of gene order evolution usually have to assume constant gene content or adopt a presence/absence coding of gene neighborhoods which is blind to complex events modifying gene content. Results We propose a probabilistic evolutionary model for gene neighborhoods, allowing genes to be inserted, duplicated or lost. It uses reconciled phylogenies, which integrate sequence and gene content evolution. We are then able to optimize parameters such as phylogeny branch lengths, or probabilistic laws depicting the diversity of susceptibility of syntenic regions to rearrangements. We reconstruct a structure for ancestral genomes by optimizing a likelihood, keeping track of all evolutionary events at the level of gene content and gene synteny. Ancestral syntenies are associated with a probability of presence. We implemented the model with the restriction that at most one gene duplication separates two gene speciations in reconciled gene trees. We reconstruct ancestral syntenies on a set of 12 drosophila genomes, and compare the evolutionary rates along the branches and along the sites. We compare with a parsimony method and find a significant number of results not supported by the posterior probability. The model is implemented in the Bio++ library. It thus benefits from and enriches the classical models and methods for molecular evolution. PMID:26452018

Evolutionary public health: introducing the concept.

PubMed

Wells, Jonathan C K; Nesse, Randolph M; Sear, Rebecca; Johnstone, Rufus A; Stearns, Stephen C

2017-07-29

The emerging discipline of evolutionary medicine is breaking new ground in understanding why people become ill. However, the value of evolutionary analyses of human physiology and behaviour is only beginning to be recognised in the field of public health. Core principles come from life history theory, which analyses the allocation of finite amounts of energy between four competing functions-maintenance, growth, reproduction, and defence. A central tenet of evolutionary theory is that organisms are selected to allocate energy and time to maximise reproductive success, rather than health or longevity. Ecological interactions that influence mortality risk, nutrient availability, and pathogen burden shape energy allocation strategies throughout the life course, thereby affecting diverse health outcomes. Public health interventions could improve their own effectiveness by incorporating an evolutionary perspective. In particular, evolutionary approaches offer new opportunities to address the complex challenges of global health, in which populations are differentially exposed to the metabolic consequences of poverty, high fertility, infectious diseases, and rapid changes in nutrition and lifestyle. The effect of specific interventions is predicted to depend on broader factors shaping life expectancy. Among the important tools in this approach are mathematical models, which can explore probable benefits and limitations of interventions in silico, before their implementation in human populations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fitness and Individuality in Complex Life Cycles.

PubMed

Herron, Matthew D

2016-12-01

Complex life cycles are common in the eukaryotic world, and they complicate the question of how to define individuality. Using a bottom-up, gene-centric approach, I consider the concept of fitness in the context of complex life cycles. I analyze the fitness effects of an allele (or a trait) on different biological units within a complex life history and how these effects drive evolutionary change within populations. Based on these effects, I attempt to construct a concept of fitness that accurately predicts evolutionary change in the context of complex life cycles.

Stimulating Scientific Reasoning with Drawing-Based Modeling

NASA Astrophysics Data System (ADS)

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-02-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each iteration, the user interface and instructions were adjusted based on students' remarks and the teacher's observations. Students' conversations were analyzed on reasoning complexity as a measurement of efficacy of the modeling tool and the instructions. These findings were also used to compose a set of recommendations for teachers and curriculum designers for using and constructing models in the classroom. Our findings suggest that to stimulate scientific reasoning in students working with a drawing-based modeling, tool instruction about the tool and the domain should be integrated. In creating models, a sufficient level of scaffolding is necessary. Without appropriate scaffolds, students are not able to create the model. With scaffolding that is too high, students may show reasoning that incorrectly assigns external causes to behavior in the model.

An evolutionary algorithm that constructs recurrent neural networks.

PubMed

Angeline, P J; Saunders, G M; Pollack, J B

1994-01-01

Standard methods for simultaneously inducing the structure and weights of recurrent neural networks limit every task to an assumed class of architectures. Such a simplification is necessary since the interactions between network structure and function are not well understood. Evolutionary computations, which include genetic algorithms and evolutionary programming, are population-based search methods that have shown promise in many similarly complex tasks. This paper argues that genetic algorithms are inappropriate for network acquisition and describes an evolutionary program, called GNARL, that simultaneously acquires both the structure and weights for recurrent networks. GNARL's empirical acquisition method allows for the emergence of complex behaviors and topologies that are potentially excluded by the artificial architectural constraints imposed in standard network induction methods.

Improving processes through evolutionary optimization.

PubMed

Clancy, Thomas R

2011-09-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies on complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 18th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, I discuss methods to optimize complex healthcare processes through learning, adaptation, and evolutionary planning.

Deciphering the evolution of herbicide resistance in weeds.

PubMed

Délye, Christophe; Jasieniuk, Marie; Le Corre, Valérie

2013-11-01

Resistance to herbicides in arable weeds is increasing rapidly worldwide and threatening global food security. Resistance has now been reported to all major herbicide modes of action despite the development of resistance management strategies in the 1990s. We review here recent advances in understanding the genetic bases and evolutionary drivers of herbicide resistance that highlight the complex nature of selection for this adaptive trait. Whereas early studied cases of resistance were highly herbicide-specific and largely under monogenic control, cases of greatest concern today generally involve resistance to multiple modes of action, are under polygenic control, and are derived from pre-existing stress response pathways. Although 'omics' approaches should enable unraveling the genetic bases of complex resistances, the appearance, selection, and spread of herbicide resistance in weed populations can only be fully elucidated by focusing on evolutionary dynamics and implementing integrative modeling efforts. Copyright © 2013 Elsevier Ltd. All rights reserved.

Morphogenesis and mechanostabilization of complex natural and 3D printed shapes

PubMed Central

Tiwary, Chandra Sekhar; Kishore, Sharan; Sarkar, Suman; Mahapatra, Debiprosad Roy; Ajayan, Pulickel M.; Chattopadhyay, Kamanio

2015-01-01

The natural selection and the evolutionary optimization of complex shapes in nature are closely related to their functions. Mechanostabilization of shape of biological structure via morphogenesis has several beautiful examples. With the help of simple mechanics-based modeling and experiments, we show an important causality between natural shape selection as evolutionary outcome and the mechanostabilization of seashells. The effect of biological growth on the mechanostabilization process is identified with examples of two natural shapes of seashells, one having a diametrically converging localization of stresses and the other having a helicoidally concentric localization of stresses. We demonstrate how the evolved shape enables predictable protection of soft body parts of the species. The effect of bioavailability of natural material is found to be a secondary factor compared to shape selectivity, where material microstructure only acts as a constraint to evolutionary optimization. This is confirmed by comparing the mechanostabilization behavior of three-dimensionally printed synthetic polymer structural shapes with that of natural seashells consisting of ceramic and protein. This study also highlights interesting possibilities in achieving a new design of structures made of ordinary materials which have bio-inspired optimization objectives. PMID:26601170

The complex evolutionary history of big-eared horseshoe bats (Rhinolophus macrotis complex): insights from genetic, morphological and acoustic data

PubMed Central

Sun, Keping; Kimball, Rebecca T.; Liu, Tong; Wei, Xuewen; Jin, Longru; Jiang, Tinglei; Lin, Aiqing; Feng, Jiang

2016-01-01

Palaeoclimatic oscillations and different landscapes frequently result in complex population-level structure or the evolution of cryptic species. Elucidating the potential mechanisms is vital to understanding speciation events. However, such complex evolutionary patterns have rarely been reported in bats. In China, the Rhinolophus macrotis complex contains a large form and a small form, suggesting the existence of a cryptic bat species. Our field surveys found these two sibling species have a continuous and widespread distribution with partial sympatry. However, their evolutionary history has received little attention. Here, we used extensive sampling, morphological and acoustic data, as well as different genetic markers to investigate their evolutionary history. Genetic analyses revealed discordance between the mitochondrial and nuclear data. Mitochondrial data identified three reciprocally monophyletic lineages: one representing all small forms from Southwest China, and the other two containing all large forms from Central and Southeast China, respectively. The large form showed paraphyly with respect to the small form. However, clustering analyses of microsatellite and Chd1 gene sequences support two divergent clusters separating the large form and the small form. Moreover, morphological and acoustic analyses were consistent with nuclear data. This unusual pattern in the R. macrotis complex might be accounted for by palaeoclimatic oscillations, shared ancestral polymorphism and/or interspecific hybridization. PMID:27748429

Life history determines genetic structure and evolutionary potential of host–parasite interactions

PubMed Central

Barrett, Luke G.; Thrall, Peter H.; Burdon, Jeremy J.; Linde, Celeste C.

2009-01-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns. PMID:18947899

Life history determines genetic structure and evolutionary potential of host-parasite interactions.

PubMed

Barrett, Luke G; Thrall, Peter H; Burdon, Jeremy J; Linde, Celeste C

2008-12-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.

Games of life and death: antibiotic resistance and production through the lens of evolutionary game theory.

PubMed

Conlin, Peter L; Chandler, Josephine R; Kerr, Benjamin

2014-10-01

In this review, we demonstrate how game theory can be a useful first step in modeling and understanding interactions among bacteria that produce and resist antibiotics. We introduce the basic features of evolutionary game theory and explore model microbial systems that correspond to some classical games. Each game discussed defines a different category of social interaction with different resulting population dynamics (exclusion, coexistence, bistability, cycling). We then explore how the framework can be extended to incorporate some of the complexity of natural microbial communities. Overall, the game theoretical perspective helps to guide our expectations about the evolution of some forms of antibiotic resistance and production because it makes clear the precise nature of social interaction in this context. Copyright © 2014 Elsevier Ltd. All rights reserved.

Landscape community genomics: understanding eco-evolutionary processes in complex environments

USGS Publications Warehouse

Hand, Brian K.; Lowe, Winsor H.; Kovach, Ryan P.; Muhlfeld, Clint C.; Luikart, Gordon

2015-01-01

Extrinsic factors influencing evolutionary processes are often categorically lumped into interactions that are environmentally (e.g., climate, landscape) or community-driven, with little consideration of the overlap or influence of one on the other. However, genomic variation is strongly influenced by complex and dynamic interactions between environmental and community effects. Failure to consider both effects on evolutionary dynamics simultaneously can lead to incomplete, spurious, or erroneous conclusions about the mechanisms driving genomic variation. We highlight the need for a landscape community genomics (LCG) framework to help to motivate and challenge scientists in diverse fields to consider a more holistic, interdisciplinary perspective on the genomic evolution of multi-species communities in complex environments.

Transforming Biology Assessment with Machine Learning: Automated Scoring of Written Evolutionary Explanations

NASA Astrophysics Data System (ADS)

Nehm, Ross H.; Ha, Minsu; Mayfield, Elijah

2012-02-01

This study explored the use of machine learning to automatically evaluate the accuracy of students' written explanations of evolutionary change. Performance of the Summarization Integrated Development Environment (SIDE) program was compared to human expert scoring using a corpus of 2,260 evolutionary explanations written by 565 undergraduate students in response to two different evolution instruments (the EGALT-F and EGALT-P) that contained prompts that differed in various surface features (such as species and traits). We tested human-SIDE scoring correspondence under a series of different training and testing conditions, using Kappa inter-rater agreement values of greater than 0.80 as a performance benchmark. In addition, we examined the effects of response length on scoring success; that is, whether SIDE scoring models functioned with comparable success on short and long responses. We found that SIDE performance was most effective when scoring models were built and tested at the individual item level and that performance degraded when suites of items or entire instruments were used to build and test scoring models. Overall, SIDE was found to be a powerful and cost-effective tool for assessing student knowledge and performance in a complex science domain.

Cultural selection drives the evolution of human communication systems

PubMed Central

Tamariz, Monica; Ellison, T. Mark; Barr, Dale J.; Fay, Nicolas

2014-01-01

Human communication systems evolve culturally, but the evolutionary mechanisms that drive this evolution are not well understood. Against a baseline that communication variants spread in a population following neutral evolutionary dynamics (also known as drift models), we tested the role of two cultural selection models: coordination- and content-biased. We constructed a parametrized mixed probabilistic model of the spread of communicative variants in four 8-person laboratory micro-societies engaged in a simple communication game. We found that selectionist models, working in combination, explain the majority of the empirical data. The best-fitting parameter setting includes an egocentric bias and a content bias, suggesting that participants retained their own previously used communicative variants unless they encountered a superior (content-biased) variant, in which case it was adopted. This novel pattern of results suggests that (i) a theory of the cultural evolution of human communication systems must integrate selectionist models and (ii) human communication systems are functionally adaptive complex systems. PMID:24966310

Cultural selection drives the evolution of human communication systems.

PubMed

Tamariz, Monica; Ellison, T Mark; Barr, Dale J; Fay, Nicolas

2014-08-07

Human communication systems evolve culturally, but the evolutionary mechanisms that drive this evolution are not well understood. Against a baseline that communication variants spread in a population following neutral evolutionary dynamics (also known as drift models), we tested the role of two cultural selection models: coordination- and content-biased. We constructed a parametrized mixed probabilistic model of the spread of communicative variants in four 8-person laboratory micro-societies engaged in a simple communication game. We found that selectionist models, working in combination, explain the majority of the empirical data. The best-fitting parameter setting includes an egocentric bias and a content bias, suggesting that participants retained their own previously used communicative variants unless they encountered a superior (content-biased) variant, in which case it was adopted. This novel pattern of results suggests that (i) a theory of the cultural evolution of human communication systems must integrate selectionist models and (ii) human communication systems are functionally adaptive complex systems.

Breaking symmetry: the zebrafish as a model for understanding left-right asymmetry in the developing brain.

PubMed

Roussigne, Myriam; Blader, Patrick; Wilson, Stephen W

2012-03-01

How does left-right asymmetry develop in the brain and how does the resultant asymmetric circuitry impact on brain function and lateralized behaviors? By enabling scientists to address these questions at the levels of genes, neurons, circuitry and behavior,the zebrafish model system provides a route to resolve the complexity of brain lateralization. In this review, we present the progress made towards characterizing the nature of the gene networks and the sequence of morphogenetic events involved in the asymmetric development of zebrafish epithalamus. In an attempt to integrate the recent extensive knowledge into a working model and to identify the future challenges,we discuss how insights gained at a cellular/developmental level can be linked to the data obtained at a molecular/genetic level. Finally, we present some evolutionary thoughts and discuss how significant discoveries made in zebrafish should provide entry points to better understand the evolutionary origins of brain lateralization.

Sequence co-evolution gives 3D contacts and structures of protein complexes

PubMed Central

Hopf, Thomas A; Schärfe, Charlotta P I; Rodrigues, João P G L M; Green, Anna G; Kohlbacher, Oliver; Sander, Chris; Bonvin, Alexandre M J J; Marks, Debora S

2014-01-01

Protein–protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein–protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein–protein interaction networks and used for interaction predictions at residue resolution. DOI: http://dx.doi.org/10.7554/eLife.03430.001 PMID:25255213

Neurobiology of rodent self-grooming and its value for translational neuroscience

PubMed Central

Kalueff, Allan V.; Stewart, Adam Michael; Song, Cai; Berridge, Kent C.; Graybiel, Ann M.; Fentress, John C.

2016-01-01

Self-grooming is a complex innate behaviour with an evolutionary conserved sequencing pattern and is one of the most frequently performed behavioural activities in rodents. In this Review, we discuss the neurobiology of rodent self-grooming, and we highlight studies of rodent models of neuropsychiatric disorders — including models of autism spectrum disorder and obsessive compulsive disorder — that have assessed self-grooming phenotypes. We suggest that rodent self-grooming may be a useful measure of repetitive behaviour in such models, and therefore of value to translational psychiatry. Assessment of rodent self-grooming may also be useful for understanding the neural circuits that are involved in complex sequential patterns of action. PMID:26675822

Improving hospital bed occupancy and resource utilization through queuing modeling and evolutionary computation.

PubMed

Belciug, Smaranda; Gorunescu, Florin

2015-02-01

Scarce healthcare resources require carefully made policies ensuring optimal bed allocation, quality healthcare service, and adequate financial support. This paper proposes a complex analysis of the resource allocation in a hospital department by integrating in the same framework a queuing system, a compartmental model, and an evolutionary-based optimization. The queuing system shapes the flow of patients through the hospital, the compartmental model offers a feasible structure of the hospital department in accordance to the queuing characteristics, and the evolutionary paradigm provides the means to optimize the bed-occupancy management and the resource utilization using a genetic algorithm approach. The paper also focuses on a "What-if analysis" providing a flexible tool to explore the effects on the outcomes of the queuing system and resource utilization through systematic changes in the input parameters. The methodology was illustrated using a simulation based on real data collected from a geriatric department of a hospital from London, UK. In addition, the paper explores the possibility of adapting the methodology to different medical departments (surgery, stroke, and mental illness). Moreover, the paper also focuses on the practical use of the model from the healthcare point of view, by presenting a simulated application. Copyright © 2014 Elsevier Inc. All rights reserved.

Hierarchical coordinate systems for understanding complexity and its evolution, with applications to genetic regulatory networks.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.

Selection of relevant input variables in storm water quality modeling by multiobjective evolutionary polynomial regression paradigm

NASA Astrophysics Data System (ADS)

Creaco, E.; Berardi, L.; Sun, Siao; Giustolisi, O.; Savic, D.

2016-04-01

The growing availability of field data, from information and communication technologies (ICTs) in "smart" urban infrastructures, allows data modeling to understand complex phenomena and to support management decisions. Among the analyzed phenomena, those related to storm water quality modeling have recently been gaining interest in the scientific literature. Nonetheless, the large amount of available data poses the problem of selecting relevant variables to describe a phenomenon and enable robust data modeling. This paper presents a procedure for the selection of relevant input variables using the multiobjective evolutionary polynomial regression (EPR-MOGA) paradigm. The procedure is based on scrutinizing the explanatory variables that appear inside the set of EPR-MOGA symbolic model expressions of increasing complexity and goodness of fit to target output. The strategy also enables the selection to be validated by engineering judgement. In such context, the multiple case study extension of EPR-MOGA, called MCS-EPR-MOGA, is adopted. The application of the proposed procedure to modeling storm water quality parameters in two French catchments shows that it was able to significantly reduce the number of explanatory variables for successive analyses. Finally, the EPR-MOGA models obtained after the input selection are compared with those obtained by using the same technique without benefitting from input selection and with those obtained in previous works where other data-modeling techniques were used on the same data. The comparison highlights the effectiveness of both EPR-MOGA and the input selection procedure.

Introduction to the special issue: Tree invasions: towards a better understanding of their complex evolutionary dynamics.

PubMed

Hirsch, Heidi; Richardson, David M; Le Roux, Johannes J

2017-05-01

Many invasive plants show evidence of trait-based evolutionary change, but these remain largely unexplored for invasive trees. The increasing number of invasive trees and their tremendous impacts worldwide, however, illustrates the urgent need to bridge this knowledge gap to apply efficient management. Consequently, an interdisciplinary workshop, held in 2015 at Stellenbosch University in Stellenbosch, South Africa, brought together international researchers to discuss our understanding of evolutionary dynamics in invasive trees. The main outcome of this workshop is this Special Issue of AoB PLANTS . The collection of papers in this issue has helped to identify and assess the evolutionary mechanisms that are likely to influence tree invasions. It also facilitated expansion of the unified framework for biological invasions to incorporate key evolutionary processes. The papers cover a wide range of evolutionary mechanisms in tree genomes (adaptation), epigenomes (phenotypic plasticity) and their second genomes (mutualists), and show how such mechanisms can impact tree invasion processes and management. The special issue provides a comprehensive overview of the factors that promote and mitigate the invasive success of tree species in many parts of the world. It also shows that incorporating evolutionary concepts is crucial for understanding the complex drivers of tree invasions and has much potential to improve management. The contributions of the special issue also highlight many priorities for further work in the face of ever-increasing tree invasions; the complexity of this research needs calls for expanded interdisciplinary research collaborations.

Mechanisms of bacterial morphogenesis: evolutionary cell biology approaches provide new insights.

PubMed

Jiang, Chao; Caccamo, Paul D; Brun, Yves V

2015-04-01

How Darwin's "endless forms most beautiful" have evolved remains one of the most exciting questions in biology. The significant variety of bacterial shapes is most likely due to the specific advantages they confer with respect to the diverse environments they occupy. While our understanding of the mechanisms generating relatively simple shapes has improved tremendously in the last few years, the molecular mechanisms underlying the generation of complex shapes and the evolution of shape diversity are largely unknown. The emerging field of bacterial evolutionary cell biology provides a novel strategy to answer this question in a comparative phylogenetic framework. This relatively novel approach provides hypotheses and insights into cell biological mechanisms, such as morphogenesis, and their evolution that would have been difficult to obtain by studying only model organisms. We discuss the necessary steps, challenges, and impact of integrating "evolutionary thinking" into bacterial cell biology in the genomic era. © 2015 WILEY Periodicals, Inc.

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

NASA Technical Reports Server (NTRS)

Terrile, Richard J.; Guillaume, Alexandre

2009-01-01

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Genome Diversity and Evolution in the Budding Yeasts (Saccharomycotina)

PubMed Central

Dujon, Bernard A.; Louis, Edward J.

2017-01-01

Considerable progress in our understanding of yeast genomes and their evolution has been made over the last decade with the sequencing, analysis, and comparisons of numerous species, strains, or isolates of diverse origins. The role played by yeasts in natural environments as well as in artificial manufactures, combined with the importance of some species as model experimental systems sustained this effort. At the same time, their enormous evolutionary diversity (there are yeast species in every subphylum of Dikarya) sparked curiosity but necessitated further efforts to obtain appropriate reference genomes. Today, yeast genomes have been very informative about basic mechanisms of evolution, speciation, hybridization, domestication, as well as about the molecular machineries underlying them. They are also irreplaceable to investigate in detail the complex relationship between genotypes and phenotypes with both theoretical and practical implications. This review examines these questions at two distinct levels offered by the broad evolutionary range of yeasts: inside the best-studied Saccharomyces species complex, and across the entire and diversified subphylum of Saccharomycotina. While obviously revealing evolutionary histories at different scales, data converge to a remarkably coherent picture in which one can estimate the relative importance of intrinsic genome dynamics, including gene birth and loss, vs. horizontal genetic accidents in the making of populations. The facility with which novel yeast genomes can now be studied, combined with the already numerous available reference genomes, offer privileged perspectives to further examine these fundamental biological questions using yeasts both as eukaryotic models and as fungi of practical importance. PMID:28592505

The universal ancestor

NASA Technical Reports Server (NTRS)

Woese, C.

1998-01-01

A genetic annealing model for the universal ancestor of all extant life is presented; the name of the model derives from its resemblance to physical annealing. The scenario pictured starts when "genetic temperatures" were very high, cellular entities (progenotes) were very simple, and information processing systems were inaccurate. Initially, both mutation rate and lateral gene transfer levels were elevated. The latter was pandemic and pervasive to the extent that it, not vertical inheritance, defined the evolutionary dynamic. As increasingly complex and precise biological structures and processes evolved, both the mutation rate and the scope and level of lateral gene transfer, i.e., evolutionary temperature, dropped, and the evolutionary dynamic gradually became that characteristic of modern cells. The various subsystems of the cell "crystallized," i.e., became refractory to lateral gene transfer, at different stages of "cooling," with the translation apparatus probably crystallizing first. Organismal lineages, and so organisms as we know them, did not exist at these early stages. The universal phylogenetic tree, therefore, is not an organismal tree at its base but gradually becomes one as its peripheral branchings emerge. The universal ancestor is not a discrete entity. It is, rather, a diverse community of cells that survives and evolves as a biological unit. This communal ancestor has a physical history but not a genealogical one. Over time, this ancestor refined into a smaller number of increasingly complex cell types with the ancestors of the three primary groupings of organisms arising as a result.

Systems Engineering Metrics: Organizational Complexity and Product Quality Modeling

NASA Technical Reports Server (NTRS)

Mog, Robert A.

1997-01-01

Innovative organizational complexity and product quality models applicable to performance metrics for NASA-MSFC's Systems Analysis and Integration Laboratory (SAIL) missions and objectives are presented. An intensive research effort focuses on the synergistic combination of stochastic process modeling, nodal and spatial decomposition techniques, organizational and computational complexity, systems science and metrics, chaos, and proprietary statistical tools for accelerated risk assessment. This is followed by the development of a preliminary model, which is uniquely applicable and robust for quantitative purposes. Exercise of the preliminary model using a generic system hierarchy and the AXAF-I architectural hierarchy is provided. The Kendall test for positive dependence provides an initial verification and validation of the model. Finally, the research and development of the innovation is revisited, prior to peer review. This research and development effort results in near-term, measurable SAIL organizational and product quality methodologies, enhanced organizational risk assessment and evolutionary modeling results, and 91 improved statistical quantification of SAIL productivity interests.

Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift.

PubMed

Laarits, T; Bordalo, P; Lemos, B

2016-08-01

Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long-term adaptation of complex phenotypes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

A modified Wright-Fisher model that incorporates Ne: A variant of the standard model with increased biological realism and reduced computational complexity.

PubMed

Zhao, Lei; Gossmann, Toni I; Waxman, David

2016-03-21

The Wright-Fisher model is an important model in evolutionary biology and population genetics. It has been applied in numerous analyses of finite populations with discrete generations. It is recognised that real populations can behave, in some key aspects, as though their size that is not the census size, N, but rather a smaller size, namely the effective population size, Ne. However, in the Wright-Fisher model, there is no distinction between the effective and census population sizes. Equivalently, we can say that in this model, Ne coincides with N. The Wright-Fisher model therefore lacks an important aspect of biological realism. Here, we present a method that allows Ne to be directly incorporated into the Wright-Fisher model. The modified model involves matrices whose size is determined by Ne. Thus apart from increased biological realism, the modified model also has reduced computational complexity, particularly so when Ne⪡N. For complex problems, it may be hard or impossible to numerically analyse the most commonly-used approximation of the Wright-Fisher model that incorporates Ne, namely the diffusion approximation. An alternative approach is simulation. However, the simulations need to be sufficiently detailed that they yield an effective size that is different to the census size. Simulations may also be time consuming and have attendant statistical errors. The method presented in this work may then be the only alternative to simulations, when Ne differs from N. We illustrate the straightforward application of the method to some problems involving allele fixation and the determination of the equilibrium site frequency spectrum. We then apply the method to the problem of fixation when three alleles are segregating in a population. This latter problem is significantly more complex than a two allele problem and since the diffusion equation cannot be numerically solved, the only other way Ne can be incorporated into the analysis is by simulation. We have achieved good accuracy in all cases considered. In summary, the present work extends the realism and tractability of an important model of evolutionary biology and population genetics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks

PubMed Central

2011-01-01

Background Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. Results A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Conclusions Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced. PMID:21849086

Evolutionary versatility of eukaryotic protein domains revealed by their bigram networks.

PubMed

Xie, Xueying; Jin, Jing; Mao, Yongyi

2011-08-18

Protein domains are globular structures of independently folded polypeptides that exert catalytic or binding activities. Their sequences are recognized as evolutionary units that, through genome recombination, constitute protein repertoires of linkage patterns. Via mutations, domains acquire modified functions that contribute to the fitness of cells and organisms. Recent studies have addressed the evolutionary selection that may have shaped the functions of individual domains and the emergence of particular domain combinations, which led to new cellular functions in multi-cellular animals. This study focuses on modeling domain linkage globally and investigates evolutionary implications that may be revealed by novel computational analysis. A survey of 77 completely sequenced eukaryotic genomes implies a potential hierarchical and modular organization of biological functions in most living organisms. Domains in a genome or multiple genomes are modeled as a network of hetero-duplex covalent linkages, termed bigrams. A novel computational technique is introduced to decompose such networks, whereby the notion of domain "networking versatility" is derived and measured. The most and least "versatile" domains (termed "core domains" and "peripheral domains" respectively) are examined both computationally via sequence conservation measures and experimentally using selected domains. Our study suggests that such a versatility measure extracted from the bigram networks correlates with the adaptivity of domains during evolution, where the network core domains are highly adaptive, significantly contrasting the network peripheral domains. Domain recombination has played a major part in the evolution of eukaryotes attributing to genome complexity. From a system point of view, as the results of selection and constant refinement, networks of domain linkage are structured in a hierarchical modular fashion. Domains with high degree of networking versatility appear to be evolutionary adaptive, potentially through functional innovations. Domain bigram networks are informative as a model of biological functions. The networking versatility indices extracted from such networks for individual domains reflect the strength of evolutionary selection that the domains have experienced.

A Cross-Grade Study Validating the Evolutionary Pathway of Student Mental Models in Electric Circuits

ERIC Educational Resources Information Center

Lin, Jing-Wen

2017-01-01

Cross-grade studies are valuable for the development of sequential curriculum. However such studies are time and resource intensive and fail to provide a clear representation to integrate different levels of representational complexity. Lin (Lin, 2006; Lin & Chiu, 2006; Lin, Chiu, & Hsu, 2006) proposed a cladistics approach in conceptual…

Garter snake population dynamics from a 16-year study: considerations for ecological monitoring

Treesearch

Amy J. Lind; Hartwell H. Welsh Jr; David A. Tallmon

2005-01-01

Snakes have recently been proposed as model organisms for addressing both evolutionary and ecological questions. Because of their middle position in many food webs they may be useful indicators of trophic complexity and dynamics. However, reliable data on snake populations are rare due to the challenges of sampling these patchily distributed, cryptic, and often...

Human vs. Computer Diagnosis of Students' Natural Selection Knowledge: Testing the Efficacy of Text Analytic Software

ERIC Educational Resources Information Center

Nehm, Ross H.; Haertig, Hendrik

2012-01-01

Our study examines the efficacy of Computer Assisted Scoring (CAS) of open-response text relative to expert human scoring within the complex domain of evolutionary biology. Specifically, we explored whether CAS can diagnose the explanatory elements (or Key Concepts) that comprise undergraduate students' explanatory models of natural selection with…

Prevalent Role of Gene Features in Determining Evolutionary Fates of Whole-Genome Duplication Duplicated Genes in Flowering Plants1[W][OA

PubMed Central

Jiang, Wen-kai; Liu, Yun-long; Xia, En-hua; Gao, Li-zhi

2013-01-01

The evolution of genes and genomes after polyploidization has been the subject of extensive studies in evolutionary biology and plant sciences. While a significant number of duplicated genes are rapidly removed during a process called fractionation, which operates after the whole-genome duplication (WGD), another considerable number of genes are retained preferentially, leading to the phenomenon of biased gene retention. However, the evolutionary mechanisms underlying gene retention after WGD remain largely unknown. Through genome-wide analyses of sequence and functional data, we comprehensively investigated the relationships between gene features and the retention probability of duplicated genes after WGDs in six plant genomes, Arabidopsis (Arabidopsis thaliana), poplar (Populus trichocarpa), soybean (Glycine max), rice (Oryza sativa), sorghum (Sorghum bicolor), and maize (Zea mays). The results showed that multiple gene features were correlated with the probability of gene retention. Using a logistic regression model based on principal component analysis, we resolved evolutionary rate, structural complexity, and GC3 content as the three major contributors to gene retention. Cluster analysis of these features further classified retained genes into three distinct groups in terms of gene features and evolutionary behaviors. Type I genes are more prone to be selected by dosage balance; type II genes are possibly subject to subfunctionalization; and type III genes may serve as potential targets for neofunctionalization. This study highlights that gene features are able to act jointly as primary forces when determining the retention and evolution of WGD-derived duplicated genes in flowering plants. These findings thus may help to provide a resolution to the debate on different evolutionary models of gene fates after WGDs. PMID:23396833

Evolution of precopulatory and post-copulatory strategies of inbreeding avoidance and associated polyandry.

PubMed

Duthie, A B; Bocedi, G; Germain, R R; Reid, J M

2018-01-01

Inbreeding depression is widely hypothesized to drive adaptive evolution of precopulatory and post-copulatory mechanisms of inbreeding avoidance, which in turn are hypothesized to affect evolution of polyandry (i.e. female multiple mating). However, surprisingly little theory or modelling critically examines selection for precopulatory or post-copulatory inbreeding avoidance, or both strategies, given evolutionary constraints and direct costs, or examines how evolution of inbreeding avoidance strategies might feed back to affect evolution of polyandry. Selection for post-copulatory inbreeding avoidance, but not for precopulatory inbreeding avoidance, requires polyandry, whereas interactions between precopulatory and post-copulatory inbreeding avoidance might cause functional redundancy (i.e. 'degeneracy') potentially generating complex evolutionary dynamics among inbreeding strategies and polyandry. We used individual-based modelling to quantify evolution of interacting precopulatory and post-copulatory inbreeding avoidance and associated polyandry given strong inbreeding depression and different evolutionary constraints and direct costs. We found that evolution of post-copulatory inbreeding avoidance increased selection for initially rare polyandry and that evolution of a costly inbreeding avoidance strategy became negligible over time given a lower-cost alternative strategy. Further, fixed precopulatory inbreeding avoidance often completely precluded evolution of polyandry and hence post-copulatory inbreeding avoidance, but fixed post-copulatory inbreeding avoidance did not preclude evolution of precopulatory inbreeding avoidance. Evolution of inbreeding avoidance phenotypes and associated polyandry is therefore affected by evolutionary feedbacks and degeneracy. All else being equal, evolution of precopulatory inbreeding avoidance and resulting low polyandry is more likely when post-copulatory inbreeding avoidance is precluded or costly, and evolution of post-copulatory inbreeding avoidance greatly facilitates evolution of costly polyandry. © The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.

The Evolution of Biological Complexity in Digital Organisms

NASA Astrophysics Data System (ADS)

Ofria, Charles

2013-03-01

When Darwin first proposed his theory of evolution by natural selection, he realized that it had a problem explaining the origins of traits of ``extreme perfection and complication'' such as the vertebrate eye. Critics of Darwin's theory have latched onto this perceived flaw as a proof that Darwinian evolution is impossible. In anticipation of this issue, Darwin described the perfect data needed to understand this process, but lamented that such data are ``scarcely ever possible'' to obtain. In this talk, I will discuss research where we use populations of digital organisms (self-replicating and evolving computer programs) to elucidate the genetic and evolutionary processes by which new, highly-complex traits arise, drawing inspiration directly from Darwin's wistful thinking and hypotheses. During the process of evolution in these fully-transparent computational environments we can measure the incorporation of new information into the genome, a process akin to a natural Maxwell's Demon, and identify the original source of any such information. We show that, as Darwin predicted, much of the information used to encode a complex trait was already in the genome as part of simpler evolved traits, and that many routes must be possible for a new complex trait to have a high probability of successfully evolving. In even more extreme examples of the evolution of complexity, we are now using these same principles to examine the evolutionary dynamics the drive major transitions in evolution; that is transitions to higher-levels of organization, which are some of the most complex evolutionary events to occur in nature. Finally, I will explore some of the implications of this research to other aspects of evolutionary biology and as well as ways that these evolutionary principles can be applied toward solving computational and engineering problems.

Evolutionary game theory using agent-based methods.

PubMed

Adami, Christoph; Schossau, Jory; Hintze, Arend

2016-12-01

Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Anonymous nuclear markers reveal taxonomic incongruence and long-term disjunction in a cactus species complex with continental-island distribution in South America.

PubMed

Perez, Manolo F; Carstens, Bryan C; Rodrigues, Gustavo L; Moraes, Evandro M

2016-02-01

The Pilosocereus aurisetus complex consists of eight cactus species with a fragmented distribution associated to xeric enclaves within the Cerrado biome in eastern South America. The phylogeny of these species is incompletely resolved, and this instability complicates evolutionary analyses. Previous analyses based on both plastid and microsatellite markers suggested that this complex contained species with inherent phylogeographic structure, which was attributed to recent diversification and recurring range shifts. However, limitations of the molecular markers used in these analyses prevented some questions from being properly addressed. In order to better understand the relationship among these species and make a preliminary assessment of the genetic structure within them, we developed anonymous nuclear loci from pyrosequencing data of 40 individuals from four species in the P. aurisetus complex. The data obtained from these loci were used to identify genetic clusters within species, and to investigate the phylogenetic relationship among these inferred clusters using a species tree methodology. Coupled with a palaeodistributional modelling, our results reveal a deep phylogenetic and climatic disjunction between two geographic lineages. Our results highlight the importance of sampling more regions from the genome to gain better insights on the evolution of species with an intricate evolutionary history. The methodology used here provides a feasible approach to develop numerous genealogical molecular markers throughout the genome for non-model species. These data provide a more robust hypothesis for the relationship among the lineages of the P. aurisetus complex. Copyright © 2015 Elsevier Inc. All rights reserved.

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

NASA Astrophysics Data System (ADS)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Linear and evolutionary polynomial regression models to forecast coastal dynamics: Comparison and reliability assessment

NASA Astrophysics Data System (ADS)

Bruno, Delia Evelina; Barca, Emanuele; Goncalves, Rodrigo Mikosz; de Araujo Queiroz, Heithor Alexandre; Berardi, Luigi; Passarella, Giuseppe

2018-01-01

In this paper, the Evolutionary Polynomial Regression data modelling strategy has been applied to study small scale, short-term coastal morphodynamics, given its capability for treating a wide database of known information, non-linearly. Simple linear and multilinear regression models were also applied to achieve a balance between the computational load and reliability of estimations of the three models. In fact, even though it is easy to imagine that the more complex the model, the more the prediction improves, sometimes a "slight" worsening of estimations can be accepted in exchange for the time saved in data organization and computational load. The models' outcomes were validated through a detailed statistical, error analysis, which revealed a slightly better estimation of the polynomial model with respect to the multilinear model, as expected. On the other hand, even though the data organization was identical for the two models, the multilinear one required a simpler simulation setting and a faster run time. Finally, the most reliable evolutionary polynomial regression model was used in order to make some conjecture about the uncertainty increase with the extension of extrapolation time of the estimation. The overlapping rate between the confidence band of the mean of the known coast position and the prediction band of the estimated position can be a good index of the weakness in producing reliable estimations when the extrapolation time increases too much. The proposed models and tests have been applied to a coastal sector located nearby Torre Colimena in the Apulia region, south Italy.

Cancer heterogeneity and multilayer spatial evolutionary games.

PubMed

Świerniak, Andrzej; Krześlak, Michał

2016-10-13

Evolutionary game theory (EGT) has been widely used to simulate tumour processes. In almost all studies on EGT models analysis is limited to two or three phenotypes. Our model contains four main phenotypes. Moreover, in a standard approach only heterogeneity of populations is studied, while cancer cells remain homogeneous. A multilayer approach proposed in this paper enables to study heterogeneity of single cells. In the extended model presented in this paper we consider four strategies (phenotypes) that can arise by mutations. We propose multilayer spatial evolutionary games (MSEG) played on multiple 2D lattices corresponding to the possible phenotypes. It enables simulation and investigation of heterogeneity on the player-level in addition to the population-level. Moreover, it allows to model interactions between arbitrary many phenotypes resulting from the mixture of basic traits. Different equilibrium points and scenarios (monomorphic and polymorphic populations) have been achieved depending on model parameters and the type of played game. However, there is a possibility of stable quadromorphic population in MSEG games for the same set of parameters like for the mean-field game. The model assumes an existence of four possible phenotypes (strategies) in the population of cells that make up tumour. Various parameters and relations between cells lead to complex analysis of this model and give diverse results. One of them is a possibility of stable coexistence of different tumour cells within the population, representing almost arbitrary mixture of the basic phenotypes. This article was reviewed by Tomasz Lipniacki, Urszula Ledzewicz and Jacek Banasiak.

The place of development in mathematical evolutionary theory.

PubMed

Rice, Sean H

2012-09-01

Development plays a critical role in structuring the joint offspring-parent phenotype distribution. It thus must be part of any truly general evolutionary theory. Historically, the offspring-parent distribution has often been treated in such a way as to bury the contribution of development, by distilling from it a single term, either heritability or additive genetic variance, and then working only with this term. I discuss two reasons why this approach is no longer satisfactory. First, the regression of expected offspring phenotype on parent phenotype can easily be nonlinear, and this nonlinearity can have a pronounced impact on the response to selection. Second, even when the offspring-parent regression is linear, it is nearly always a function of the environment, and the precise way that heritability covaries with the environment can have a substantial effect on adaptive evolution. Understanding these complexities of the offspring-parent distribution will require understanding of the developmental processes underlying the traits of interest. I briefly discuss how we can incorporate such complexity into formal evolutionary theory, and why it is likely to be important even for traits that are not traditionally the focus of evo-devo research. Finally, I briefly discuss a topic that is widely seen as being squarely in the domain of evo-devo: novelty. I argue that the same conceptual and mathematical framework that allows us to incorporate developmental complexity into simple models of trait evolution also yields insight into the evolution of novel traits. Copyright © 2011 Wiley Periodicals, Inc., A Wiley Company.

Decoupled evolution of floral traits and climatic preferences in a clade of Neotropical Gesneriaceae.

PubMed

Serrano-Serrano, Martha Liliana; Perret, Mathieu; Guignard, Maïté; Chautems, Alain; Silvestro, Daniele; Salamin, Nicolas

2015-11-10

Major factors influencing the phenotypic diversity of a lineage can be recognized by characterizing the extent and mode of trait evolution between related species. Here, we compared the evolutionary dynamics of traits associated with floral morphology and climatic preferences in a clade composed of the genera Codonanthopsis, Codonanthe and Nematanthus (Gesneriaceae). To test the mode and specific components that lead to phenotypic diversity in this group, we performed a Bayesian phylogenetic analysis of combined nuclear and plastid DNA sequences and modeled the evolution of quantitative traits related to flower shape and size and to climatic preferences. We propose an alternative approach to display graphically the complex dynamics of trait evolution along a phylogenetic tree using a wide range of evolutionary scenarios. Our results demonstrated heterogeneous trait evolution. Floral shapes displaced into separate regimes selected by the different pollinator types (hummingbirds versus insects), while floral size underwent a clade-specific evolution. Rates of evolution were higher for the clade that is hummingbird pollinated and experienced flower resupination, compared with species pollinated by bees, suggesting a relevant role of plant-pollinator interactions in lowland rainforest. The evolution of temperature preferences is best explained by a model with distinct selective regimes between the Brazilian Atlantic Forest and the other biomes, whereas differentiation along the precipitation axis was characterized by higher rates, compared with temperature, and no regime or clade-specific patterns. Our study shows different selective regimes and clade-specific patterns in the evolution of morphological and climatic components during the diversification of Neotropical species. Our new graphical visualization tool allows the representation of trait trajectories under parameter-rich models, thus contributing to a better understanding of complex evolutionary dynamics.

Evolution with Stochastic Fitness and Stochastic Migration

PubMed Central

Rice, Sean H.; Papadopoulos, Anthony

2009-01-01

Background Migration between local populations plays an important role in evolution - influencing local adaptation, speciation, extinction, and the maintenance of genetic variation. Like other evolutionary mechanisms, migration is a stochastic process, involving both random and deterministic elements. Many models of evolution have incorporated migration, but these have all been based on simplifying assumptions, such as low migration rate, weak selection, or large population size. We thus have no truly general and exact mathematical description of evolution that incorporates migration. Methodology/Principal Findings We derive an exact equation for directional evolution, essentially a stochastic Price equation with migration, that encompasses all processes, both deterministic and stochastic, contributing to directional change in an open population. Using this result, we show that increasing the variance in migration rates reduces the impact of migration relative to selection. This means that models that treat migration as a single parameter tend to be biassed - overestimating the relative impact of immigration. We further show that selection and migration interact in complex ways, one result being that a strategy for which fitness is negatively correlated with migration rates (high fitness when migration is low) will tend to increase in frequency, even if it has lower mean fitness than do other strategies. Finally, we derive an equation for the effective migration rate, which allows some of the complex stochastic processes that we identify to be incorporated into models with a single migration parameter. Conclusions/Significance As has previously been shown with selection, the role of migration in evolution is determined by the entire distributions of immigration and emigration rates, not just by the mean values. The interactions of stochastic migration with stochastic selection produce evolutionary processes that are invisible to deterministic evolutionary theory. PMID:19816580

Biogeography predicts macro‐evolutionary patterning of gestural display complexity in a passerine family

PubMed Central

Miles, Meredith C.; Cheng, Samantha; Fuxjager, Matthew J.

2017-01-01

Gestural displays are incorporated into the signaling repertoire of numerous animal species. These displays range from complex signals that involve impressive and challenging maneuvers, to simpler displays or no gesture at all. The factors that drive this evolution remain largely unclear, and we therefore investigate this issue in New World blackbirds by testing how factors related to a species’ geographical distribution and social mating system predict macro‐evolutionary patterns of display elaboration. We report that species inhabiting temperate regions produce more complex displays than species living in tropical regions, and we attribute this to (i) ecological factors that increase the competitiveness of the social environment in temperate regions, and (ii) different evolutionary and geological contexts under which species in temperate and tropical regions evolved. Meanwhile, we find no evidence that social mating system predicts species differences in display complexity, which is consistent with the idea that gestural displays evolve independently of social mating system. Together, these results offer some of the first insight into the role played by geographic factors and evolutionary context in the evolution of the remarkable physical displays of birds and other vertebrates. PMID:28240772

Between “design” and “bricolage”: Genetic networks, levels of selection, and adaptive evolution

PubMed Central

Wilkins, Adam S.

2007-01-01

The extent to which “developmental constraints” in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a “network perspective” may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed. PMID:17494754

Between "design" and "bricolage": genetic networks, levels of selection, and adaptive evolution.

PubMed

Wilkins, Adam S

2007-05-15

The extent to which "developmental constraints" in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a "network perspective" may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed.

Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis

PubMed Central

Dura-Bernal, S.; Neymotin, S. A.; Kerr, C. C.; Sivagnanam, S.; Majumdar, A.; Francis, J. T.; Lytton, W. W.

2017-01-01

Biomimetic simulation permits neuroscientists to better understand the complex neuronal dynamics of the brain. Embedding a biomimetic simulation in a closed-loop neuroprosthesis, which can read and write signals from the brain, will permit applications for amelioration of motor, psychiatric, and memory-related brain disorders. Biomimetic neuroprostheses require real-time adaptation to changes in the external environment, thus constituting an example of a dynamic data-driven application system. As model fidelity increases, so does the number of parameters and the complexity of finding appropriate parameter configurations. Instead of adapting synaptic weights via machine learning, we employed major biological learning methods: spike-timing dependent plasticity and reinforcement learning. We optimized the learning metaparameters using evolutionary algorithms, which were implemented in parallel and which used an island model approach to obtain sufficient speed. We employed these methods to train a cortical spiking model to utilize macaque brain activity, indicating a selected target, to drive a virtual musculoskeletal arm with realistic anatomical and biomechanical properties to reach to that target. The optimized system was able to reproduce macaque data from a comparable experimental motor task. These techniques can be used to efficiently tune the parameters of multiscale systems, linking realistic neuronal dynamics to behavior, and thus providing a useful tool for neuroscience and neuroprosthetics. PMID:29200477

Controlled fire use in early humans might have triggered the evolutionary emergence of tuberculosis.

PubMed

Chisholm, Rebecca H; Trauer, James M; Curnoe, Darren; Tanaka, Mark M

2016-08-09

Tuberculosis (TB) is caused by the Mycobacterium tuberculosis complex (MTBC), a wildly successful group of organisms and the leading cause of death resulting from a single bacterial pathogen worldwide. It is generally accepted that MTBC established itself in human populations in Africa and that animal-infecting strains diverged from human strains. However, the precise causal factors of TB emergence remain unknown. Here, we propose that the advent of controlled fire use in early humans created the ideal conditions for the emergence of TB as a transmissible disease. This hypothesis is supported by mathematical modeling together with a synthesis of evidence from epidemiology, evolutionary genetics, and paleoanthropology.

THE `IN' AND THE `OUT': An Evolutionary Approach

NASA Astrophysics Data System (ADS)

Medina-Martins, P. R.; Rocha, L.

It is claimed that a great deal of the problems which the mechanist approaches to the emulation/modelling of the human mind are presently facing are due to a host of canons so `readily' accepted and acquainted that some of their underlying processes have not yet been the objective of intensive research. The essay proposes a (possible) solution for some of these problems introducing the tenets of a new paradigm which, based on a reappraisal of the concepts of purposiveness and teleology, lays emphasis on the evolutionary aspects (biological and mental) of alive beings. A complex neuro-fuzzy system which works as the supporting realization of this paradigm is briefly described in the essay.

Microbial multicellular development: mechanical forces in action.

PubMed

Rivera-Yoshida, Natsuko; Arias Del Angel, Juan A; Benítez, Mariana

2018-06-06

Multicellular development occurs in diverse microbial lineages and involves the complex interaction among biochemical, physical and ecological factors. We focus on the mechanical forces that appear to be relevant for the scale and material qualities of individual cells and small cellular conglomerates. We review the effects of such forces on the development of some paradigmatic microorganisms, as well as their overall consequences in multicellular structures. Microbes exhibiting multicellular development have been considered models for the evolutionary transition to multicellularity. Therefore, we discuss how comparative, integrative and dynamic approaches to the mechanical effects involved in microbial development can provide valuable insights into some of the principles behind the evolutionary transition to multicellularity. Copyright © 2018 Elsevier Ltd. All rights reserved.

An Agent-based Model for Groundwater Allocation and Management at the Bakken Shale in Western North Dakota

NASA Astrophysics Data System (ADS)

Lin, T.; Lin, Z.; Lim, S.

2017-12-01

We present an integrated modeling framework to simulate groundwater level change under the dramatic increase of hydraulic fracturing water use in the Bakken Shale oil production area. The framework combines the agent-based model (ABM) with the Fox Hills-Hell Creek (FH-HC) groundwater model. In development of the ABM, institution theory is used to model the regulation policies from the North Dakota State Water Commission, while evolutionary programming and cognitive maps are used to model the social structure that emerges from the behavior of competing individual water businesses. Evolutionary programming allows individuals to select an appropriate strategy when annually applying for potential water use permits; whereas cognitive maps endow agent's ability and willingness to compete for more water sales. All agents have their own influence boundaries that inhibit their competitive behavior toward their neighbors but not to non-neighbors. The decision-making process is constructed and parameterized with both quantitative and qualitative information, i.e., empirical water use data and knowledge gained from surveys with stakeholders. By linking institution theory, evolutionary programming, and cognitive maps, our approach addresses a higher complexity of the real decision making process. Furthermore, this approach is a new exploration for modeling the dynamics of Coupled Human and Natural System. After integrating ABM with the FH-HC model, drought and limited water accessibility scenarios are simulated to predict FH-HC ground water level changes in the future. The integrated modeling framework of ABM and FH-HC model can be used to support making scientifically sound policies in water allocation and management.

Targeting Common but Complex Proteoglycans on Breast Cancer Cells and Stem Cells Using Evolutionary Refined Malaria Proteins

DTIC Science & Technology

2015-11-01

AWARD NUMBER: W81XWH-13-1-0139 TITLE: Targeting Common but Complex Proteoglycans on Breast Cancer Cells and Stem Cells Using Evolutionary Refined...DATES COVERED 15Aug2013 - 14Aug2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-13-1-0139 Targeting Common but Complex Proteoglycans on...outbreaks in epidemic regions of the world. Prior to this application we discovered that human breast cancer cells express this same carbohydrate

Birth order in small multihospital systems.

PubMed

Luke, R D; Ozcan, Y A; Begun, J W

1990-06-01

The strategic behaviors of small multihospital systems have received little attention in the literature despite the fact that small systems are the predominant scale among multihospital systems. This study examines one important aspect of small-system strategic behaviors: the birth-order or evolutionary patterns of hospital acquisition. The evolutionary patterns of acquisition are compared across three strategic model types studied elsewhere: local market, investment, and historical. Using data obtained from a variety of sources, local market model systems are found, in the sequence of acquisition, to be significantly different from the other two model types in terms of relative distances of acquisitions from the initiating or parent hospital, the sizes of acquisition hospitals, the complexity of those hospitals, and the likelihood that the acquisitions are located in rural areas. Differences between parents and acquisitions are also significant, as hypothesized, for the market model system types, although they are not generally significant for the other two model types. The findings suggest that the market model represents an important strategic form that may have important implications for the restructuring of hospital markets.

Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management

NASA Astrophysics Data System (ADS)

Bellomo, N.; Clarke, D.; Gibelli, L.; Townsend, P.; Vreugdenhil, B. J.

2016-09-01

This paper proposes an essay concerning the understanding of human behaviours and crisis management of crowds in extreme situations, such as evacuation through complex venues. The first part focuses on the understanding of the main features of the crowd viewed as a living, hence complex system. The main concepts are subsequently addressed, in the second part, to a critical analysis of mathematical models suitable to capture them, as far as it is possible. Then, the third part focuses on the use, toward safety problems, of a model derived by the methods of the mathematical kinetic theory and theoretical tools of evolutionary game theory. It is shown how this model can depict critical situations and how these can be managed with the aim of minimizing the risk of catastrophic events.

Cultural macroevolution matters

PubMed Central

Gray, Russell D.

2017-01-01

Evolutionary thinking can be applied to both cultural microevolution and macroevolution. However, much of the current literature focuses on cultural microevolution. In this article, we argue that the growing availability of large cross-cultural datasets facilitates the use of computational methods derived from evolutionary biology to answer broad-scale questions about the major transitions in human social organization. Biological methods can be extended to human cultural evolution. We illustrate this argument with examples drawn from our recent work on the roles of Big Gods and ritual human sacrifice in the evolution of large, stratified societies. These analyses show that, although the presence of Big Gods is correlated with the evolution of political complexity, in Austronesian cultures at least, they do not play a causal role in ratcheting up political complexity. In contrast, ritual human sacrifice does play a causal role in promoting and sustaining the evolution of stratified societies by maintaining and legitimizing the power of elites. We briefly discuss some common objections to the application of phylogenetic modeling to cultural evolution and argue that the use of these methods does not require a commitment to either gene-like cultural inheritance or to the view that cultures are like vertebrate species. We conclude that the careful application of these methods can substantially enhance the prospects of an evolutionary science of human history. PMID:28739960

Evolutionary innovation and diversification of carotenoid-based pigmentation in finches.

PubMed

Ligon, Russell A; Simpson, Richard K; Mason, Nicholas A; Hill, Geoffrey E; McGraw, Kevin J

2016-12-01

The ornaments used by animals to mediate social interactions are diverse, and by reconstructing their evolutionary pathways we can gain new insights into the mechanisms underlying ornamental innovation and variability. Here, we examine variation in plumage carotenoids among the true finches (Aves: Fringillidae) using biochemical and comparative phylogenetic analyses to reconstruct the evolutionary history of carotenoid states and evaluate competing models of carotenoid evolution. Our comparative analyses reveal that the most likely ancestor of finches used dietary carotenoids as yellow plumage colorants, and that the ability to metabolically modify dietary carotenoids into more complex pigments arose secondarily once finches began to use modified carotenoids to create red plumage. Following the evolutionary "innovation" that enabled modified red carotenoid pigments to be deposited as plumage colorants, many finch species subsequently modified carotenoid biochemical pathways to create yellow plumage. However, no reversions to dietary carotenoids were observed. The finding that ornaments and their underlying mechanisms may be operating under different selection regimes-where ornamental trait colors undergo frequent reversions (e.g., between red and yellow plumage) while carotenoid metabolization mechanisms are more conserved-supports a growing empirical framework suggesting different evolutionary patterns for ornaments and the mechanistic innovations that facilitate their diversification. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Laboratory evolution of the migratory polymorphism in the sand cricket: combining physiology with quantitative genetics.

PubMed

Roff, Derek A; Fairbairn, Daphne J

2007-01-01

Predicting evolutionary change is the central goal of evolutionary biology because it is the primary means by which we can test evolutionary hypotheses. In this article, we analyze the pattern of evolutionary change in a laboratory population of the wing-dimorphic sand cricket Gryllus firmus resulting from relaxation of selection favoring the migratory (long-winged) morph. Based on a well-characterized trade-off between fecundity and flight capability, we predict that evolution in the laboratory environment should result in a reduction in the proportion of long-winged morphs. We also predict increased fecundity and reduced functionality and weight of the major flight muscles in long-winged females but little change in short-winged (flightless) females. Based on quantitative genetic theory, we predict that the regression equation describing the trade-off between ovary weight and weight of the major flight muscles will show a change in its intercept but not in its slope. Comparisons across generations verify all of these predictions. Further, using values of genetic parameters estimated from previous studies, we show that a quantitative genetic simulation model can account for not only the qualitative changes but also the evolutionary trajectory. These results demonstrate the power of combining quantitative genetic and physiological approaches for understanding the evolution of complex traits.

Physalis and physaloids: A recent and complex evolutionary history.

PubMed

Zamora-Tavares, María Del Pilar; Martínez, Mahinda; Magallón, Susana; Guzmán-Dávalos, Laura; Vargas-Ponce, Ofelia

2016-07-01

The complex evolutionary history of the subtribe Physalinae is reflected in the poor resolution of the relationships of Physalis and the physaloid genera. We hypothesize that this low resolution is caused by recent evolutionary history in a complex geographic setting. The aims of this study were twofold: (1) To determine the phylogenetic relationships of the current genera recognized in Physalinae in order to identify monophyletic groups and resolve the physaloid grade; and (2) to determine the probable causes of the recent divergence in Physalinae. We conducted phylogenetic analyses with maximum likelihood (ML) and Bayesian inference with 50 Physalinae species and 19 others as outgroups, using morphological and molecular data from five plastid and two nuclear regions. A relaxed molecular clock was obtained from the ML topology and ancestral area reconstruction was conducted using the DEC model. The genera Chamaesaracha, Leucophysalis, and Physalis subgenus Rydbergis were recovered as monophyletic. Three clades, Alkekengi-Calliphysalis, Schraderanthus-Tzeltalia, and Witheringia-Brachistus, also received good support. However, even with morphological data and that of the DNA of seven regions, the tree was not completely resolved and many clades remained unsupported. Physalinae diverged at the end of the Miocene (∼9.22Mya) with one trend indicating that the greatest diversification within the subtribe occurred during the last 5My. The Neotropical region presented the highest probability (45%) of being the ancestral area of Physalinae followed by the Mexican Transition Zone (35%). During the Pliocene and Pleistocene, the geographical areas where species were found experienced significant geological and climatic changes, giving rise to rapid and relatively recent diversification events in Physalinae. Thus, recent origin, high diversification, and morphological complexity have contributed, at least with the currently available methods, to the inability to completely disentangle the phylogenetic relationships of Physalinae. Copyright © 2016 Elsevier Inc. All rights reserved.

The genetic architecture of normal variation in human pigmentation: an evolutionary perspective and model.

PubMed

McEvoy, Brian; Beleza, Sandra; Shriver, Mark D

2006-10-15

Skin pigmentation varies substantially across human populations in a manner largely coincident with ultraviolet radiation intensity. This observation suggests that natural selection in response to sunlight is a major force in accounting for pigmentation variability. We review recent progress in identifying the genes controlling this variation with a particular focus on the trait's evolutionary past and the potential role of testing for signatures of selection in aiding the discovery of functionally important genes. We have analyzed SNP data from the International HapMap project in 77 pigmentation candidate genes for such signatures. On the basis of these results and other similar work, we provide a tentative three-population model (West Africa, East Asia and North Europe) of the evolutionary-genetic architecture of human pigmentation. These results suggest a complex evolutionary history, with selection acting on different gene targets at different times and places in the human past. Some candidate genes may have been selected in the ancestral human population, others in the 'out of Africa' proto European-Asian population, whereas most appear to have selectively evolved solely in either Europeans or East Asians separately despite the pigmentation similarities between these two populations. Selection signatures can provide important clues to aid gene discovery. However, these should be viewed as complements, rather than replacements of, functional studies including linkage and association analyses, which can directly refine our understanding of the trait.

Evolution in health and medicine Sackler colloquium: Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease.

PubMed

Feinberg, Andrew P; Irizarry, Rafael A

2010-01-26

Neo-Darwinian evolutionary theory is based on exquisite selection of phenotypes caused by small genetic variations, which is the basis of quantitative trait contribution to phenotype and disease. Epigenetics is the study of nonsequence-based changes, such as DNA methylation, heritable during cell division. Previous attempts to incorporate epigenetics into evolutionary thinking have focused on Lamarckian inheritance, that is, environmentally directed epigenetic changes. Here, we propose a new non-Lamarckian theory for a role of epigenetics in evolution. We suggest that genetic variants that do not change the mean phenotype could change the variability of phenotype; and this could be mediated epigenetically. This inherited stochastic variation model would provide a mechanism to explain an epigenetic role of developmental biology in selectable phenotypic variation, as well as the largely unexplained heritable genetic variation underlying common complex disease. We provide two experimental results as proof of principle. The first result is direct evidence for stochastic epigenetic variation, identifying highly variably DNA-methylated regions in mouse and human liver and mouse brain, associated with development and morphogenesis. The second is a heritable genetic mechanism for variable methylation, namely the loss or gain of CpG dinucleotides over evolutionary time. Finally, we model genetically inherited stochastic variation in evolution, showing that it provides a powerful mechanism for evolutionary adaptation in changing environments that can be mediated epigenetically. These data suggest that genetically inherited propensity to phenotypic variability, even with no change in the mean phenotype, substantially increases fitness while increasing the disease susceptibility of a population with a changing environment.

Phylogenetic signal, feeding behaviour and brain volume in Neotropical bats.

PubMed

Rojas, D; Mancina, C A; Flores-Martínez, J J; Navarro, L

2013-09-01

Comparative correlational studies of brain size and ecological traits (e.g. feeding habits and habitat complexity) have increased our knowledge about the selective pressures on brain evolution. Studies conducted in bats as a model system assume that shared evolutionary history has a maximum effect on the traits. However, this effect has not been quantified. In addition, the effect of levels of diet specialization on brain size remains unclear. We examined the role of diet on the evolution of brain size in Mormoopidae and Phyllostomidae using two comparative methods. Body mass explained 89% of the variance in brain volume. The effect of feeding behaviour (either characterized as feeding habits, as levels of specialization on a type of item or as handling behaviour) on brain volume was also significant albeit not consistent after controlling for body mass and the strength of the phylogenetic signal (λ). Although the strength of the phylogenetic signal of brain volume and body mass was high when tested individually, λ values in phylogenetic generalized least squares models were significantly different from 1. This suggests that phylogenetic independent contrasts models are not always the best approach for the study of ecological correlates of brain size in New World bats. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Computer modeling describes gravity-related adaptation in cell cultures.

PubMed

Alexandrov, Ludmil B; Alexandrova, Stoyana; Usheva, Anny

2009-12-16

Questions about the changes of biological systems in response to hostile environmental factors are important but not easy to answer. Often, the traditional description with differential equations is difficult due to the overwhelming complexity of the living systems. Another way to describe complex systems is by simulating them with phenomenological models such as the well-known evolutionary agent-based model (EABM). Here we developed an EABM to simulate cell colonies as a multi-agent system that adapts to hyper-gravity in starvation conditions. In the model, the cell's heritable characteristics are generated and transferred randomly to offspring cells. After a qualitative validation of the model at normal gravity, we simulate cellular growth in hyper-gravity conditions. The obtained data are consistent with previously confirmed theoretical and experimental findings for bacterial behavior in environmental changes, including the experimental data from the microgravity Atlantis and the Hypergravity 3000 experiments. Our results demonstrate that it is possible to utilize an EABM with realistic qualitative description to examine the effects of hypergravity and starvation on complex cellular entities.

Evolving Communicative Complexity: Insight from Rodents and Beyond

DTIC Science & Technology

2012-01-01

Group size in animal societies: the potential role of social and ecological limitations in the group-living fish , Paragobiodon xanthosomus. Ethology... Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA 2Human Research and Engineering Directorate, Perceptual Sciences...evolve is an active question in behavioural ecology . Sciurid rodents (ground squirrels, prairie dogs and marmots) provide an excellent model system for

[Evolutionary process unveiled by the maximum genetic diversity hypothesis].

PubMed

Huang, Yi-Min; Xia, Meng-Ying; Huang, Shi

2013-05-01

As two major popular theories to explain evolutionary facts, the neutral theory and Neo-Darwinism, despite their proven virtues in certain areas, still fail to offer comprehensive explanations to such fundamental evolutionary phenomena as the genetic equidistance result, abundant overlap sites, increase in complexity over time, incomplete understanding of genetic diversity, and inconsistencies with fossil and archaeological records. Maximum genetic diversity hypothesis (MGD), however, constructs a more complete evolutionary genetics theory that incorporates all of the proven virtues of existing theories and adds to them the novel concept of a maximum or optimum limit on genetic distance or diversity. It has yet to meet a contradiction and explained for the first time the half-century old Genetic Equidistance phenomenon as well as most other major evolutionary facts. It provides practical and quantitative ways of studying complexity. Molecular interpretation using MGD-based methods reveal novel insights on the origins of humans and other primates that are consistent with fossil evidence and common sense, and reestablished the important role of China in the evolution of humans. MGD theory has also uncovered an important genetic mechanism in the construction of complex traits and the pathogenesis of complex diseases. We here made a series of sequence comparisons among yeasts, fishes and primates to illustrate the concept of limit on genetic distance. The idea of limit or optimum is in line with the yin-yang paradigm in the traditional Chinese view of the universal creative law in nature.

Two possible driving forces supporting the evolution of animal communication. Comment on "Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain" by Michael A. Arbib

NASA Astrophysics Data System (ADS)

Moulin-Frier, Clément; Verschure, Paul F. M. J.

2016-03-01

In the target paper [1], M.A. Arbib proposes a quite exhaustive review of the (often computational) models developed during the last decades that support his detailed scenario on language evolution (the Mirror System Hypothesis, MSH). The approach considers that language evolved from a mirror system for grasping already present in LCA-m (the last common ancestor of macaques and humans), to a simple imitation system for grasping present in LCA-c (the last common ancestor of chimpanzees and humans), to a complex imitation system for grasping that developed in the hominid line since that ancestor. MSH considers that this complex imitation system is a key evolutionary step for a language-ready brain, providing all the required elements for an open-ended gestural communication system. The transition from the gestural (bracchio-manual and visual) to the vocal (articulatory and auditory) domain is supposed to be a less important evolutionary step.

Unfolding of a ClC chloride transporter retains memory of its evolutionary history.

PubMed

Min, Duyoung; Jefferson, Robert E; Qi, Yifei; Wang, Jing Yang; Arbing, Mark A; Im, Wonpil; Bowie, James U

2018-05-01

ClC chloride channels and transporters are important for chloride homeostasis in species from bacteria to human. Mutations in ClC proteins cause genetically inherited diseases, some of which are likely to involve folding defects. The ClC proteins present a challenging and unusual biological folding problem because they are large membrane proteins possessing a complex architecture, with many reentrant helices that go only partway through membrane and loop back out. Here we were able to examine the unfolding of the Escherichia coli ClC transporter, ClC-ec1, using single-molecule forced unfolding methods. We found that the protein could be separated into two stable halves that unfolded independently. The independence of the two domains is consistent with an evolutionary model in which the two halves arose from independently folding subunits that later fused together. Maintaining smaller folding domains of lesser complexity within large membrane proteins may be an advantageous strategy to avoid misfolding traps.

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

PubMed

Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

Understanding variation in human fertility: what can we learn from evolutionary demography?

PubMed

Sear, Rebecca; Lawson, David W; Kaplan, Hillard; Shenk, Mary K

2016-04-19

Decades of research on human fertility has presented a clear picture of how fertility varies, including its dramatic decline over the last two centuries in most parts of the world. Why fertility varies, both between and within populations, is not nearly so well understood. Fertility is a complex phenomenon, partly physiologically and partly behaviourally determined, thus an interdisciplinary approach is required to understand it. Evolutionary demographers have focused on human fertility since the 1980s. The first wave of evolutionary demographic research made major theoretical and empirical advances, investigating variation in fertility primarily in terms of fitness maximization. Research focused particularly on variation within high-fertility populations and small-scale subsistence societies and also yielded a number of hypotheses for why fitness maximization seems to break down as fertility declines during the demographic transition. A second wave of evolutionary demography research on fertility is now underway, paying much more attention to the cultural and psychological mechanisms underpinning fertility. It is also engaging with the complex, multi-causal nature of fertility variation, and with understanding fertility in complex modern and transitioning societies. Here, we summarize the history of evolutionary demographic work on human fertility, describe the current state of the field, and suggest future directions. © 2016 The Author(s).

Understanding variation in human fertility: what can we learn from evolutionary demography?

PubMed Central

Sear, Rebecca; Lawson, David W.; Kaplan, Hillard

2016-01-01

Decades of research on human fertility has presented a clear picture of how fertility varies, including its dramatic decline over the last two centuries in most parts of the world. Why fertility varies, both between and within populations, is not nearly so well understood. Fertility is a complex phenomenon, partly physiologically and partly behaviourally determined, thus an interdisciplinary approach is required to understand it. Evolutionary demographers have focused on human fertility since the 1980s. The first wave of evolutionary demographic research made major theoretical and empirical advances, investigating variation in fertility primarily in terms of fitness maximization. Research focused particularly on variation within high-fertility populations and small-scale subsistence societies and also yielded a number of hypotheses for why fitness maximization seems to break down as fertility declines during the demographic transition. A second wave of evolutionary demography research on fertility is now underway, paying much more attention to the cultural and psychological mechanisms underpinning fertility. It is also engaging with the complex, multi-causal nature of fertility variation, and with understanding fertility in complex modern and transitioning societies. Here, we summarize the history of evolutionary demographic work on human fertility, describe the current state of the field, and suggest future directions. PMID:27022071

Transmissible cancers in an evolutionary context.

PubMed

Ujvari, Beata; Papenfuss, Anthony T; Belov, Katherine

2016-07-01

Cancer is an evolutionary and ecological process in which complex interactions between tumour cells and their environment share many similarities with organismal evolution. Tumour cells with highest adaptive potential have a selective advantage over less fit cells. Naturally occurring transmissible cancers provide an ideal model system for investigating the evolutionary arms race between cancer cells and their surrounding micro-environment and macro-environment. However, the evolutionary landscapes in which contagious cancers reside have not been subjected to comprehensive investigation. Here, we provide a multifocal analysis of transmissible tumour progression and discuss the selection forces that shape it. We demonstrate that transmissible cancers adapt to both their micro-environment and macro-environment, and evolutionary theories applied to organisms are also relevant to these unique diseases. The three naturally occurring transmissible cancers, canine transmissible venereal tumour (CTVT) and Tasmanian devil facial tumour disease (DFTD) and the recently discovered clam leukaemia, exhibit different evolutionary phases: (i) CTVT, the oldest naturally occurring cell line is remarkably stable; (ii) DFTD exhibits the signs of stepwise cancer evolution; and (iii) clam leukaemia shows genetic instability. While all three contagious cancers carry the signature of ongoing and fairly recent adaptations to selective forces, CTVT appears to have reached an evolutionary stalemate with its host, while DFTD and the clam leukaemia appear to be still at a more dynamic phase of their evolution. Parallel investigation of contagious cancer genomes and transcriptomes and of their micro-environment and macro-environment could shed light on the selective forces shaping tumour development at different time points: during the progressive phase and at the endpoint. A greater understanding of transmissible cancers from an evolutionary ecology perspective will provide novel avenues for the prevention and treatment of both contagious and non-communicable cancers. © 2016 The Authors. BioEssays published by WILEY Periodicals, Inc.

A climate for speciation: rapid spatial diversification within the Sorex cinereus complex of shrews

USGS Publications Warehouse

Hope, Andrew G.; Speer, Kelly A.; Demboski, John R.; Talbot, Sandra L.; Cook, Joseph A.

2012-01-01

The cyclic climate regime of the late Quaternary caused dramatic environmental change at high latitudes. Although these events may have been brief in periodicity from an evolutionary standpoint, multiple episodes of allopatry and divergence have been implicated in rapid radiations of a number of organisms. Shrews of the Sorex cinereus complex have long challenged taxonomists due to similar morphology and parapatric geographic ranges. Here, multi-locus phylogenetic and demographic assessments using a coalescent framework were combined to investigate spatiotemporal evolution of 13 nominal species with a widespread distribution throughout North America and across Beringia into Siberia. For these species, we first test a hypothesis of recent differentiation in response to Pleistocene climate versus more ancient divergence that would coincide with pre-Pleistocene perturbations. We then investigate the processes driving diversification over multiple continents. Our genetic analyses highlight novel diversity within these morphologically conserved mammals and clarify relationships between geographic distribution and evolutionary history. Demography within and among species indicates both regional stability and rapid expansion. Ancestral ecological differentiation coincident with early cladogenesis within the complex enabled alternating and repeated episodes of allopatry and expansion where successive glacial and interglacial phases each promoted divergence. The Sorex cinereus complex constitutes a valuable model for future comparative assessments of evolution in response to cyclic environmental change.

Examples of equilibrium and non-equilibrium behavior in evolutionary systems

NASA Astrophysics Data System (ADS)

Soulier, Arne

With this thesis, we want to shed some light into the darkness of our understanding of simply defined statistical mechanics systems and the surprisingly complex dynamical behavior they exhibit. We will do so by presenting in turn one equilibrium and then one non-equilibrium system with evolutionary dynamics. In part 1, we will present the seceder-model, a newly developed system that cannot equilibrate. We will then study several properties of the system and obtain an idea of the richness of the dynamics of the seceder model, which is particular impressive given the minimal amount of modeling necessary in its setup. In part 2, we will present extensions to the directed polymer in random media problem on a hypercube and its connection to the Eigen model of evolution. Our main interest will be the influence of time-dependent and time-independent changes in the fitness landscape viewed by an evolving population. This part contains the equilibrium dynamics. The stochastic models and the topic of evolution and non-equilibrium in general will allow us to point out similarities to the various lines of thought in game theory.

Genetics of dispersal.

PubMed

Saastamoinen, Marjo; Bocedi, Greta; Cote, Julien; Legrand, Delphine; Guillaume, Frédéric; Wheat, Christopher W; Fronhofer, Emanuel A; Garcia, Cristina; Henry, Roslyn; Husby, Arild; Baguette, Michel; Bonte, Dries; Coulon, Aurélie; Kokko, Hanna; Matthysen, Erik; Niitepõld, Kristjan; Nonaka, Etsuko; Stevens, Virginie M; Travis, Justin M J; Donohue, Kathleen; Bullock, James M; Del Mar Delgado, Maria

2018-02-01

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal-related phenotypes or evidence for the micro-evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment-dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non-additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non-equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context-dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits. © 2017 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

Genetics of dispersal

PubMed Central

Bocedi, Greta; Cote, Julien; Legrand, Delphine; Guillaume, Frédéric; Wheat, Christopher W.; Fronhofer, Emanuel A.; Garcia, Cristina; Henry, Roslyn; Husby, Arild; Baguette, Michel; Bonte, Dries; Coulon, Aurélie; Kokko, Hanna; Matthysen, Erik; Niitepõld, Kristjan; Nonaka, Etsuko; Stevens, Virginie M.; Travis, Justin M. J.; Donohue, Kathleen; Bullock, James M.; del Mar Delgado, Maria

2017-01-01

ABSTRACT Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits. PMID:28776950

Evolution of complex dynamics

NASA Astrophysics Data System (ADS)

Wilds, Roy; Kauffman, Stuart A.; Glass, Leon

2008-09-01

We study the evolution of complex dynamics in a model of a genetic regulatory network. The fitness is associated with the topological entropy in a class of piecewise linear equations, and the mutations are associated with changes in the logical structure of the network. We compare hill climbing evolution, in which only mutations that increase the fitness are allowed, with neutral evolution, in which mutations that leave the fitness unchanged are allowed. The simple structure of the fitness landscape enables us to estimate analytically the rates of hill climbing and neutral evolution. In this model, allowing neutral mutations accelerates the rate of evolutionary advancement for low mutation frequencies. These results are applicable to evolution in natural and technological systems.

Histories of molecules: Reconciling the past.

PubMed

O'Malley, Maureen A

2016-02-01

Molecular data and methods have become centrally important to evolutionary analysis, largely because they have enabled global phylogenetic reconstructions of the relationships between organisms in the tree of life. Often, however, molecular stories conflict dramatically with morphology-based histories of lineages. The evolutionary origin of animal groups provides one such case. In other instances, different molecular analyses have so far proved irreconcilable. The ancient and major divergence of eukaryotes from prokaryotic ancestors is an example of this sort of problem. Efforts to overcome these conflicts highlight the role models play in phylogenetic reconstruction. One crucial model is the molecular clock; another is that of 'simple-to-complex' modification. I will examine animal and eukaryote evolution against a backdrop of increasing methodological sophistication in molecular phylogeny, and conclude with some reflections on the nature of historical science in the molecular era of phylogeny. Copyright © 2015 Elsevier Ltd. All rights reserved.

Paleo-tribology: development of wear measurement techniques and a three-dimensional model revealing how grinding dentitions self-wear to enable functionality

NASA Astrophysics Data System (ADS)

Erickson, Gregory M.; Sidebottom, Mark A.; Curry, John F.; Kay, David Ian; Kuhn-Hendricks, Stephen; Norell, Mark A.; Sawyer, W. Gregory; Krick, Brandon A.

2016-06-01

In most mammals and a rare few reptilian lineages the evolution of precise dental occlusion led to the capacity to form functional chewing surfaces due to pressures generated while feeding. The complex dental architectures of such teeth and the biomechanics of their self-wearing nature are poorly understood. Our research team composed of paleontologists, evolutionary biologists, and engineers have developed a protocol to: (1) determine the histological make-up of grinding dentitions in extant and fossil taxa; (2) ascertain wear-relevant material properties of the tissues; (3) determine how those properties relate to inter-tissue-biomechanics leading the dental functionality using a three-dimensional Archard’s wear model developed specifically for dental applications; (4) analyze those data in phylogenetic contexts to infer evolutionary patterns as they relate to feeding. Finally we discuss industrial applications that are emerging from our paleontologically-inspired research.

An integrative method for testing form–function linkages and reconstructed evolutionary pathways of masticatory specialization

PubMed Central

Tseng, Z. Jack; Flynn, John J.

2015-01-01

Morphology serves as a ubiquitous proxy in macroevolutionary studies to identify potential adaptive processes and patterns. Inferences of functional significance of phenotypes or their evolution are overwhelmingly based on data from living taxa. Yet, correspondence between form and function has been tested in only a few model species, and those linkages are highly complex. The lack of explicit methodologies to integrate form and function analyses within a deep-time and phylogenetic context weakens inferences of adaptive morphological evolution, by invoking but not testing form–function linkages. Here, we provide a novel approach to test mechanical properties at reconstructed ancestral nodes/taxa and the strength and direction of evolutionary pathways in feeding biomechanics, in a case study of carnivorous mammals. Using biomechanical profile comparisons that provide functional signals for the separation of feeding morphologies, we demonstrate, using experimental optimization criteria on estimation of strength and direction of functional changes on a phylogeny, that convergence in mechanical properties and degree of evolutionary optimization can be decoupled. This integrative approach is broadly applicable to other clades, by using quantitative data and model-based tests to evaluate interpretations of function from morphology and functional explanations for observed macroevolutionary pathways. PMID:25994295

Island Rule, quantitative genetics and brain–body size evolution in Homo floresiensis

PubMed Central

2017-01-01

Colonization of islands often activate a complex chain of adaptive events that, over a relatively short evolutionary time, may drive strong shifts in body size, a pattern known as the Island Rule. It is arguably difficult to perform a direct analysis of the natural selection forces behind such a change in body size. Here, we used quantitative evolutionary genetic models, coupled with simulations and pattern-oriented modelling, to analyse the evolution of brain and body size in Homo floresiensis, a diminutive hominin species that appeared around 700 kya and survived up to relatively recent times (60–90 kya) on Flores Island, Indonesia. The hypothesis of neutral evolution was rejected in 97% of the simulations, and estimated selection gradients are within the range found in living natural populations. We showed that insularity may have triggered slightly different evolutionary trajectories for body and brain size, which means explaining the exceedingly small cranial volume of H. floresiensis requires additional selective forces acting on brain size alone. Our analyses also support previous conclusions that H. floresiensis may be most likely derived from an early Indonesian H. erectus, which is coherent with currently accepted biogeographical scenario for Homo expansion out of Africa. PMID:28637851

Island Rule, quantitative genetics and brain-body size evolution in Homo floresiensis.

PubMed

Diniz-Filho, José Alexandre Felizola; Raia, Pasquale

2017-06-28

Colonization of islands often activate a complex chain of adaptive events that, over a relatively short evolutionary time, may drive strong shifts in body size, a pattern known as the Island Rule. It is arguably difficult to perform a direct analysis of the natural selection forces behind such a change in body size. Here, we used quantitative evolutionary genetic models, coupled with simulations and pattern-oriented modelling, to analyse the evolution of brain and body size in Homo floresiensis , a diminutive hominin species that appeared around 700 kya and survived up to relatively recent times (60-90 kya) on Flores Island, Indonesia. The hypothesis of neutral evolution was rejected in 97% of the simulations, and estimated selection gradients are within the range found in living natural populations. We showed that insularity may have triggered slightly different evolutionary trajectories for body and brain size, which means explaining the exceedingly small cranial volume of H. floresiensis requires additional selective forces acting on brain size alone. Our analyses also support previous conclusions that H. floresiensis may be most likely derived from an early Indonesian H. erectus , which is coherent with currently accepted biogeographical scenario for Homo expansion out of Africa. © 2017 The Author(s).

The influence of tie strength on evolutionary games on networks: An empirical investigation

NASA Astrophysics Data System (ADS)

Buesser, Pierre; Peña, Jorge; Pestelacci, Enea; Tomassini, Marco

2011-11-01

Extending previous work on unweighted networks, we present here a systematic numerical investigation of standard evolutionary games on weighted networks. In the absence of any reliable model for generating weighted social networks, we attribute weights to links in a few ways supported by empirical data ranging from totally uncorrelated to weighted bipartite networks. The results of the extensive simulation work on standard complex network models show that, except in a case that does not seem to be common in social networks, taking the tie strength into account does not change in a radical manner the long-run steady-state behavior of the studied games. Besides model networks, we also included a real-life case drawn from a coauthorship network. In this case also, taking the weights into account only changes the results slightly with respect to the raw unweighted graph, although to draw more reliable conclusions on real social networks many more cases should be studied as these weighted networks become available.

Forecasting Caspian Sea level changes using satellite altimetry data (June 1992-December 2013) based on evolutionary support vector regression algorithms and gene expression programming

NASA Astrophysics Data System (ADS)

Imani, Moslem; You, Rey-Jer; Kuo, Chung-Yen

2014-10-01

Sea level forecasting at various time intervals is of great importance in water supply management. Evolutionary artificial intelligence (AI) approaches have been accepted as an appropriate tool for modeling complex nonlinear phenomena in water bodies. In the study, we investigated the ability of two AI techniques: support vector machine (SVM), which is mathematically well-founded and provides new insights into function approximation, and gene expression programming (GEP), which is used to forecast Caspian Sea level anomalies using satellite altimetry observations from June 1992 to December 2013. SVM demonstrates the best performance in predicting Caspian Sea level anomalies, given the minimum root mean square error (RMSE = 0.035) and maximum coefficient of determination (R2 = 0.96) during the prediction periods. A comparison between the proposed AI approaches and the cascade correlation neural network (CCNN) model also shows the superiority of the GEP and SVM models over the CCNN.

A combined analytical formulation and genetic algorithm to analyze the nonlinear damage responses of continuous fiber toughened composites

NASA Astrophysics Data System (ADS)

Jeon, Haemin; Yu, Jaesang; Lee, Hunsu; Kim, G. M.; Kim, Jae Woo; Jung, Yong Chae; Yang, Cheol-Min; Yang, B. J.

2017-09-01

Continuous fiber-reinforced composites are important materials that have the highest commercialized potential in the upcoming future among existing advanced materials. Despite their wide use and value, their theoretical mechanisms have not been fully established due to the complexity of the compositions and their unrevealed failure mechanisms. This study proposes an effective three-dimensional damage modeling of a fibrous composite by combining analytical micromechanics and evolutionary computation. The interface characteristics, debonding damage, and micro-cracks are considered to be the most influential factors on the toughness and failure behaviors of composites, and a constitutive equation considering these factors was explicitly derived in accordance with the micromechanics-based ensemble volume averaged method. The optimal set of various model parameters in the analytical model were found using modified evolutionary computation that considers human-induced error. The effectiveness of the proposed formulation was validated by comparing a series of numerical simulations with experimental data from available studies.

Hierarchical complexity and the size limits of life.

PubMed

Heim, Noel A; Payne, Jonathan L; Finnegan, Seth; Knope, Matthew L; Kowalewski, Michał; Lyons, S Kathleen; McShea, Daniel W; Novack-Gottshall, Philip M; Smith, Felisa A; Wang, Steve C

2017-06-28

Over the past 3.8 billion years, the maximum size of life has increased by approximately 18 orders of magnitude. Much of this increase is associated with two major evolutionary innovations: the evolution of eukaryotes from prokaryotic cells approximately 1.9 billion years ago (Ga), and multicellular life diversifying from unicellular ancestors approximately 0.6 Ga. However, the quantitative relationship between organismal size and structural complexity remains poorly documented. We assessed this relationship using a comprehensive dataset that includes organismal size and level of biological complexity for 11 172 extant genera. We find that the distributions of sizes within complexity levels are unimodal, whereas the aggregate distribution is multimodal. Moreover, both the mean size and the range of size occupied increases with each additional level of complexity. Increases in size range are non-symmetric: the maximum organismal size increases more than the minimum. The majority of the observed increase in organismal size over the history of life on the Earth is accounted for by two discrete jumps in complexity rather than evolutionary trends within levels of complexity. Our results provide quantitative support for an evolutionary expansion away from a minimal size constraint and suggest a fundamental rescaling of the constraints on minimal and maximal size as biological complexity increases. © 2017 The Author(s).

Towards a mechanistic foundation of evolutionary theory.

PubMed

Doebeli, Michael; Ispolatov, Yaroslav; Simon, Burt

2017-02-15

Most evolutionary thinking is based on the notion of fitness and related ideas such as fitness landscapes and evolutionary optima. Nevertheless, it is often unclear what fitness actually is, and its meaning often depends on the context. Here we argue that fitness should not be a basal ingredient in verbal or mathematical descriptions of evolution. Instead, we propose that evolutionary birth-death processes, in which individuals give birth and die at ever-changing rates, should be the basis of evolutionary theory, because such processes capture the fundamental events that generate evolutionary dynamics. In evolutionary birth-death processes, fitness is at best a derived quantity, and owing to the potential complexity of such processes, there is no guarantee that there is a simple scalar, such as fitness, that would describe long-term evolutionary outcomes. We discuss how evolutionary birth-death processes can provide useful perspectives on a number of central issues in evolution.

The Nature of Culture: an eight-grade model for the evolution and expansion of cultural capacities in hominins and other animals.

PubMed

Haidle, Miriam Noël; Bolus, Michael; Collard, Mark; Conard, Nicholas; Garofoli, Duilio; Lombard, Marlize; Nowell, April; Tennie, Claudio; Whiten, Andrew

2015-07-20

Tracing the evolution of human culture through time is arguably one of the most controversial and complex scholarly endeavors, and a broad evolutionary analysis of how symbolic, linguistic, and cultural capacities emerged and developed in our species is lacking. Here we present a model that, in broad terms, aims to explain the evolution and portray the expansion of human cultural capacities (the EECC model), that can be used as a point of departure for further multidisciplinary discussion and more detailed investigation. The EECC model is designed to be flexible, and can be refined to accommodate future archaeological, paleoanthropological, genetic or evolutionary psychology/behavioral analyses and discoveries. Our proposed concept of cultural behavior differentiates between empirically traceable behavioral performances and behavioral capacities that are theoretical constructs. Based largely on archaeological data (the 'black box' that most directly opens up hominin cultural evolution), and on the extension of observable problem-solution distances, we identify eight grades of cultural capacity. Each of these grades is considered within evolutionary-biological and historical-social trajectories. Importantly, the model does not imply an inevitable progression, but focuses on expansion of cultural capacities based on the integration of earlier achievements. We conclude that there is not a single cultural capacity or a single set of abilities that enabled human culture; rather, several grades of cultural capacity in animals and hominins expanded during our evolution to shape who we are today.

Vocal learning, prosody, and basal ganglia: don't underestimate their complexity.

PubMed

Ravignani, Andrea; Martins, Mauricio; Fitch, W Tecumseh

2014-12-01

Ackermann et al.'s arguments in the target article need sharpening and rethinking at both mechanistic and evolutionary levels. First, the authors' evolutionary arguments are inconsistent with recent evidence concerning nonhuman animal rhythmic abilities. Second, prosodic intonation conveys much more complex linguistic information than mere emotional expression. Finally, human adults' basal ganglia have a considerably wider role in speech modulation than Ackermann et al. surmise.

Biogeography predicts macro-evolutionary patterning of gestural display complexity in a passerine family.

PubMed

Miles, Meredith C; Cheng, Samantha; Fuxjager, Matthew J

2017-05-01

Gestural displays are incorporated into the signaling repertoire of numerous animal species. These displays range from complex signals that involve impressive and challenging maneuvers, to simpler displays or no gesture at all. The factors that drive this evolution remain largely unclear, and we therefore investigate this issue in New World blackbirds by testing how factors related to a species' geographical distribution and social mating system predict macro-evolutionary patterns of display elaboration. We report that species inhabiting temperate regions produce more complex displays than species living in tropical regions, and we attribute this to (i) ecological factors that increase the competitiveness of the social environment in temperate regions, and (ii) different evolutionary and geological contexts under which species in temperate and tropical regions evolved. Meanwhile, we find no evidence that social mating system predicts species differences in display complexity, which is consistent with the idea that gestural displays evolve independently of social mating system. Together, these results offer some of the first insight into the role played by geographic factors and evolutionary context in the evolution of the remarkable physical displays of birds and other vertebrates. © 2017 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Evolutionary foundations for cancer biology.

PubMed

Aktipis, C Athena; Nesse, Randolph M

2013-01-01

New applications of evolutionary biology are transforming our understanding of cancer. The articles in this special issue provide many specific examples, such as microorganisms inducing cancers, the significance of within-tumor heterogeneity, and the possibility that lower dose chemotherapy may sometimes promote longer survival. Underlying these specific advances is a large-scale transformation, as cancer research incorporates evolutionary methods into its toolkit, and asks new evolutionary questions about why we are vulnerable to cancer. Evolution explains why cancer exists at all, how neoplasms grow, why cancer is remarkably rare, and why it occurs despite powerful cancer suppression mechanisms. Cancer exists because of somatic selection; mutations in somatic cells result in some dividing faster than others, in some cases generating neoplasms. Neoplasms grow, or do not, in complex cellular ecosystems. Cancer is relatively rare because of natural selection; our genomes were derived disproportionally from individuals with effective mechanisms for suppressing cancer. Cancer occurs nonetheless for the same six evolutionary reasons that explain why we remain vulnerable to other diseases. These four principles-cancers evolve by somatic selection, neoplasms grow in complex ecosystems, natural selection has shaped powerful cancer defenses, and the limitations of those defenses have evolutionary explanations-provide a foundation for understanding, preventing, and treating cancer.

Evolutionary foundations for cancer biology

PubMed Central

Aktipis, C Athena; Nesse, Randolph M

2013-01-01

New applications of evolutionary biology are transforming our understanding of cancer. The articles in this special issue provide many specific examples, such as microorganisms inducing cancers, the significance of within-tumor heterogeneity, and the possibility that lower dose chemotherapy may sometimes promote longer survival. Underlying these specific advances is a large-scale transformation, as cancer research incorporates evolutionary methods into its toolkit, and asks new evolutionary questions about why we are vulnerable to cancer. Evolution explains why cancer exists at all, how neoplasms grow, why cancer is remarkably rare, and why it occurs despite powerful cancer suppression mechanisms. Cancer exists because of somatic selection; mutations in somatic cells result in some dividing faster than others, in some cases generating neoplasms. Neoplasms grow, or do not, in complex cellular ecosystems. Cancer is relatively rare because of natural selection; our genomes were derived disproportionally from individuals with effective mechanisms for suppressing cancer. Cancer occurs nonetheless for the same six evolutionary reasons that explain why we remain vulnerable to other diseases. These four principles—cancers evolve by somatic selection, neoplasms grow in complex ecosystems, natural selection has shaped powerful cancer defenses, and the limitations of those defenses have evolutionary explanations—provide a foundation for understanding, preventing, and treating cancer. PMID:23396885

The Evolutionary Basis of Risky Adolescent Behavior: Implications for Science, Policy, and Practice

ERIC Educational Resources Information Center

Ellis, Bruce J.; Del Giudice, Marco; Dishion, Thomas J.; Figueredo, Aurelio Jose; Gray, Peter; Griskevicius, Vladas; Hawley, Patricia H.; Jacobs, W. Jake; James, Jenee; Volk, Anthony A.; Wilson, David Sloan

2012-01-01

This article proposes an evolutionary model of risky behavior in adolescence and contrasts it with the prevailing developmental psychopathology model. The evolutionary model contends that understanding the evolutionary functions of adolescence is critical to explaining why adolescents engage in risky behavior and that successful intervention…

Spiraling patterns in evolutionary models inspired by bacterial games with cyclic dominance

NASA Astrophysics Data System (ADS)

Mobilia, Mauro

2015-03-01

Understanding the mechanisms allowing the maintenance of biodiversity is a central issue in biology. Evolutionary game theory, where the success of one species depends on what the others are doing, provides a promising framework to investigate this complex problem. Experiments on microbial populations have shown that cyclic local interactions promote species coexistence. In this context, rock-paper-scissors games - in which rock crushes scissors, scissors cut paper, and paper wraps rock - are often used to model the dynamics of populations in cyclic competition. After a brief survey of some inspiring experiments, I will discuss the subtle interplay between individuals' mobility and their local interactions in two-dimensional rock-paper-scissors systems. This leads to the loss of biodiversity above a certain mobility threshold, and to the formation of spiraling patterns below the critical mobility rate. I will then study a generic rock-paper-scissors metapopulation model formulated on a two-dimensional grid of patches. When these have a large carrying capacity, the model's dynamics is faithfully described in terms of the system's complex Ginzburg-Landau equation properly derived from a multiscale expansion. The properties of the ensuing complex Ginzburg-Landau equation are exploited to derive the system's phase diagram and to characterize the spatio-temporal properties of the spiraling patterns in each phase. This enables us to analyze the spiral waves stability, how these are influenced by linear and nonlinear diffusion, and to discuss phenomena such as far-field breakup. Presentation mainy based on joint work with B. Szczesny and A. M. Rucklidge. Fruitful earlier collaborations with E. Frey, Q. He, T. Reichenbach, and U. C. Täuber are also acknowledged. Work supported by the UK EPSRC (Grant No. EP/P505593/1).

Quantitative proteomic analysis reveals evolutionary divergence and species-specific peptides in the Alexandrium tamarense complex (Dinophyceae).

PubMed

Li, Cheng; Zhang, Yong; Xie, Zhang-Xian; He, Zhi-Ping; Lin, Lin; Wang, Da-Zhi

2013-06-28

The Alexandrium tamarense/catenella/fundyense complex is the major causative agent responsible for harmful algal blooms and paralytic shellfish poisoning around the world. However, taxonomy of the A. tamarense complex is contentious and the evolutionary relationships within the complex are unclear. This study compared protein profiles of the A. tamarense complex collected from different geographic regions using the two dimensional fluorescence difference gel electrophoresis (2-D DIGE) approach, and identified species-specific peptides using MALDI-TOF/TOF mass spectrometry. The results showed that three Alexandrium morphotypes presented significantly different protein expression patterns with about 30-40% shared proteins. However, ecotypes from different geographic regions within a species exhibited the same expression patterns, although a few proteins were altered in abundance. Several proteins, i.e. ribulose-1,5-bisphosphate carboxylase oxygenase form II, plastid protein NAP50, methionine S-adenosyltransferase, and peridinin-chlorophyll a-binding protein, were identified and presented different shift patterns in isoelectric point and/or molecular weight in the 2-D DIGE gels, indicating that amino acid mutation and/or posttranslational modification of these proteins had occurred. The species-specific peptide mass fingerprint and amino acid sequence of ribulose-1,5-bisphosphate carboxylase oxygenase were characterized in the A. tamarense complex, and amino acid substitution occurred among them. This study indicated that evolutionary divergence had occurred at the proteomic level in the A. tamarense complex, and that the species-specific peptides could be used as potential biomarkers to distinguish the three morphotypes. Scientific question: The Alexandrium tamarense/catenella/fundyense complex is the major causative agent responsible for harmful algal blooms and paralytic shellfish poisoning around the world. However, taxonomy of the A. tamarense complex is contentious and the evolutionary relationships within the complex are unclear, which has seriously impeded our understanding of Alexandrium-causing HABs and, consequently, the monitoring, mitigation and prevention. Technical significance: This study, for the first time, compared the global protein expression patterns of eight ecotypes from the A. tamarense complex and identified species-specific peptides using a quantitative proteomic approach combining 2-D DIGE and MALDI-TOF/TOF MS. This study demonstrated that the evolutionary divergence had occurred in the A. tamarense complex at the proteomic level, and the complex should be classified into three species, i.e. A. tamarense, A. catenella, and A. fundyense. Moreover, the species-specific peptide mass fingerprints could be used as potential biomarkers to distinguish the three morphotypes. Copyright © 2013 Elsevier B.V. All rights reserved.

Nature-Inspired Cognitive Evolution to Play MS. Pac-Man

NASA Astrophysics Data System (ADS)

Tan, Tse Guan; Teo, Jason; Anthony, Patricia

Recent developments in nature-inspired computation have heightened the need for research into the three main areas of scientific, engineering and industrial applications. Some approaches have reported that it is able to solve dynamic problems and very useful for improving the performance of various complex systems. So far however, there has been little discussion about the effectiveness of the application of these models to computer and video games in particular. The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. This paper investigates the abilities of Evolution Strategies (ES) to evolve feed-forward artificial neural network's internal parameters (i.e. weight and bias values) for automatically generating Ms. Pac-man controllers. The main objective of this game is to clear a maze of dots while avoiding the ghosts and to achieve the highest possible score. The experimental results show that an ES-based system can be successfully applied to automatically generate artificial intelligence for a complex, dynamic and highly stochastic video game environment.

Cognition, Information Fields and Hologenomic Entanglement: Evolution in Light and Shadow

PubMed Central

Miller, William B.

2016-01-01

As the prime unification of Darwinism and genetics, the Modern Synthesis continues to epitomize mainstay evolutionary theory. Many decades after its formulation, its anchor assumptions remain fixed: conflict between macro organic organisms and selection at that level represent the near totality of any evolutionary narrative. However, intervening research has revealed a less easily appraised cellular and microbial focus for eukaryotic existence. It is now established that all multicellular eukaryotic organisms are holobionts representing complex collaborations between the co-aligned microbiome of each eukaryote and its innate cells into extensive mixed cellular ecologies. Each of these ecological constituents has demonstrated faculties consistent with basal cognition. Consequently, an alternative hologenomic entanglement model is proposed with cognition at its center and conceptualized as Pervasive Information Fields within a quantum framework. Evolutionary development can then be reconsidered as being continuously based upon communication between self-referential constituencies reiterated at every scope and scale. Immunological reactions support and reinforce self-recognition juxtaposed against external environmental stresses. PMID:27213462

Competition among cooperators: Altruism and reciprocity

PubMed Central

Danielson, Peter

2002-01-01

Levine argues that neither self-interest nor altruism explains experimental results in bargaining and public goods games. Subjects' preferences appear also to be sensitive to their opponents' perceived altruism. Sethi and Somanathan provide a general account of reciprocal preferences that survive under evolutionary pressure. Although a wide variety of reciprocal strategies pass this evolutionary test, Sethi and Somanthan conjecture that fewer are likely to survive when reciprocal strategies compete with each other. This paper develops evolutionary agent-based models to test their conjecture in cases where reciprocal preferences can differ in a variety of games. We confirm that reciprocity is necessary but not sufficient for optimal cooperation. We explore the theme of competition among reciprocal cooperators and display three interesting emergent organizations: racing to the “moral high ground,” unstable cycles of preference change, and, when we implement reciprocal mechanisms, hierarchies resulting from exploiting fellow cooperators. If reciprocity is a basic mechanism facilitating cooperation, we can expect interaction that evolves around it to be complex, non-optimal, and resistant to change. PMID:12011403

Multi Sensor Fusion Using Fitness Adaptive Differential Evolution

NASA Astrophysics Data System (ADS)

Giri, Ritwik; Ghosh, Arnob; Chowdhury, Aritra; Das, Swagatam

The rising popularity of multi-source, multi-sensor networks supports real-life applications calls for an efficient and intelligent approach to information fusion. Traditional optimization techniques often fail to meet the demands. The evolutionary approach provides a valuable alternative due to its inherent parallel nature and its ability to deal with difficult problems. We present a new evolutionary approach based on a modified version of Differential Evolution (DE), called Fitness Adaptive Differential Evolution (FiADE). FiADE treats sensors in the network as distributed intelligent agents with various degrees of autonomy. Existing approaches based on intelligent agents cannot completely answer the question of how their agents could coordinate their decisions in a complex environment. The proposed approach is formulated to produce good result for the problems that are high-dimensional, highly nonlinear, and random. The proposed approach gives better result in case of optimal allocation of sensors. The performance of the proposed approach is compared with an evolutionary algorithm coordination generalized particle model (C-GPM).

"Ménage à Trois": the evolutionary interplay between JSRV, enJSRVs and domestic sheep.

PubMed

Armezzani, Alessia; Varela, Mariana; Spencer, Thomas E; Palmarini, Massimo; Arnaud, Frédérick

2014-12-09

Sheep betaretroviruses represent a fascinating model to study the complex evolutionary interplay between host and pathogen in natural settings. In infected sheep, the exogenous and pathogenic Jaagsiekte sheep retrovirus (JSRV) coexists with a variety of highly related endogenous JSRVs, referred to as enJSRVs. During evolution, some of them were co-opted by the host as they fulfilled important biological functions, including placental development and protection against related exogenous retroviruses. In particular, two enJSRV loci, enJS56A1 and enJSRV-20, were positively selected during sheep domestication due to their ability to interfere with the replication of related competent retroviruses. Interestingly, viruses escaping these transdominant enJSRVs have recently emerged, probably less than 200 years ago. Overall, these findings suggest that in sheep the process of endogenization is still ongoing and, therefore, the evolutionary interplay between endogenous and exogenous sheep betaretroviruses and their host has not yet reached an equilibrium.

“Ménage à Trois”: The Evolutionary Interplay between JSRV, enJSRVs and Domestic Sheep

PubMed Central

Armezzani, Alessia; Varela, Mariana; Spencer, Thomas E.; Palmarini, Massimo; Arnaud, Frédérick

2014-01-01

Sheep betaretroviruses represent a fascinating model to study the complex evolutionary interplay between host and pathogen in natural settings. In infected sheep, the exogenous and pathogenic Jaagsiekte sheep retrovirus (JSRV) coexists with a variety of highly related endogenous JSRVs, referred to as enJSRVs. During evolution, some of them were co-opted by the host as they fulfilled important biological functions, including placental development and protection against related exogenous retroviruses. In particular, two enJSRV loci, enJS56A1 and enJSRV-20, were positively selected during sheep domestication due to their ability to interfere with the replication of related competent retroviruses. Interestingly, viruses escaping these transdominant enJSRVs have recently emerged, probably less than 200 years ago. Overall, these findings suggest that in sheep the process of endogenization is still ongoing and, therefore, the evolutionary interplay between endogenous and exogenous sheep betaretroviruses and their host has not yet reached an equilibrium. PMID:25502326

Robust Design of Biological Circuits: Evolutionary Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise. PMID:22187523

Fixation, transient landscape, and diffusion dilemma in stochastic evolutionary game dynamics

NASA Astrophysics Data System (ADS)

Zhou, Da; Qian, Hong

2011-09-01

Agent-based stochastic models for finite populations have recently received much attention in the game theory of evolutionary dynamics. Both the ultimate fixation and the pre-fixation transient behavior are important to a full understanding of the dynamics. In this paper, we study the transient dynamics of the well-mixed Moran process through constructing a landscape function. It is shown that the landscape playing a central theoretical “device” that integrates several lines of inquiries: the stable behavior of the replicator dynamics, the long-time fixation, and continuous diffusion approximation associated with asymptotically large population. Several issues relating to the transient dynamics are discussed: (i) multiple time scales phenomenon associated with intra- and inter-attractoral dynamics; (ii) discontinuous transition in stochastically stationary process akin to Maxwell construction in equilibrium statistical physics; and (iii) the dilemma diffusion approximation facing as a continuous approximation of the discrete evolutionary dynamics. It is found that rare events with exponentially small probabilities, corresponding to the uphill movements and barrier crossing in the landscape with multiple wells that are made possible by strong nonlinear dynamics, plays an important role in understanding the origin of the complexity in evolutionary, nonlinear biological systems.

Symbiosis in eukaryotic evolution.

PubMed

López-García, Purificación; Eme, Laura; Moreira, David

2017-12-07

Fifty years ago, Lynn Margulis, inspiring in early twentieth-century ideas that put forward a symbiotic origin for some eukaryotic organelles, proposed a unified theory for the origin of the eukaryotic cell based on symbiosis as evolutionary mechanism. Margulis was profoundly aware of the importance of symbiosis in the natural microbial world and anticipated the evolutionary significance that integrated cooperative interactions might have as mechanism to increase cellular complexity. Today, we have started fully appreciating the vast extent of microbial diversity and the importance of syntrophic metabolic cooperation in natural ecosystems, especially in sediments and microbial mats. Also, not only the symbiogenetic origin of mitochondria and chloroplasts has been clearly demonstrated, but improvement in phylogenomic methods combined with recent discoveries of archaeal lineages more closely related to eukaryotes further support the symbiogenetic origin of the eukaryotic cell. Margulis left us in legacy the idea of 'eukaryogenesis by symbiogenesis'. Although this has been largely verified, when, where, and specifically how eukaryotic cells evolved are yet unclear. Here, we shortly review current knowledge about symbiotic interactions in the microbial world and their evolutionary impact, the status of eukaryogenetic models and the current challenges and perspectives ahead to reconstruct the evolutionary path to eukaryotes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust design of biological circuits: evolutionary systems biology approach.

PubMed

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise.

Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

PubMed Central

2011-01-01

Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C) in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass), and each trait harboured significant additive genetic variance in the standard temperature (27°C) only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass). Of the female traits measured, only ovary mass for crickets reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance. Conclusions Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. PMID:21791118

Mycobacterium tuberculosis complex genetic diversity: mining the fourth international spoligotyping database (SpolDB4) for classification, population genetics and epidemiology

PubMed Central

Brudey, Karine; Driscoll, Jeffrey R; Rigouts, Leen; Prodinger, Wolfgang M; Gori, Andrea; Al-Hajoj, Sahal A; Allix, Caroline; Aristimuño, Liselotte; Arora, Jyoti; Baumanis, Viesturs; Binder, Lothar; Cafrune, Patricia; Cataldi, Angel; Cheong, Soonfatt; Diel, Roland; Ellermeier, Christopher; Evans, Jason T; Fauville-Dufaux, Maryse; Ferdinand, Séverine; de Viedma, Dario Garcia; Garzelli, Carlo; Gazzola, Lidia; Gomes, Harrison M; Guttierez, M Cristina; Hawkey, Peter M; van Helden, Paul D; Kadival, Gurujaj V; Kreiswirth, Barry N; Kremer, Kristin; Kubin, Milan; Kulkarni, Savita P; Liens, Benjamin; Lillebaek, Troels; Ly, Ho Minh; Martin, Carlos; Martin, Christian; Mokrousov, Igor; Narvskaïa, Olga; Ngeow, Yun Fong; Naumann, Ludmilla; Niemann, Stefan; Parwati, Ida; Rahim, Zeaur; Rasolofo-Razanamparany, Voahangy; Rasolonavalona, Tiana; Rossetti, M Lucia; Rüsch-Gerdes, Sabine; Sajduda, Anna; Samper, Sofia; Shemyakin, Igor G; Singh, Urvashi B; Somoskovi, Akos; Skuce, Robin A; van Soolingen, Dick; Streicher, Elisabeth M; Suffys, Philip N; Tortoli, Enrico; Tracevska, Tatjana; Vincent, Véronique; Victor, Tommie C; Warren, Robin M; Yap, Sook Fan; Zaman, Khadiza; Portaels, Françoise; Rastogi, Nalin; Sola, Christophe

2006-01-01

Background The Direct Repeat locus of the Mycobacterium tuberculosis complex (MTC) is a member of the CRISPR (Clustered regularly interspaced short palindromic repeats) sequences family. Spoligotyping is the widely used PCR-based reverse-hybridization blotting technique that assays the genetic diversity of this locus and is useful both for clinical laboratory, molecular epidemiology, evolutionary and population genetics. It is easy, robust, cheap, and produces highly diverse portable numerical results, as the result of the combination of (1) Unique Events Polymorphism (UEP) (2) Insertion-Sequence-mediated genetic recombination. Genetic convergence, although rare, was also previously demonstrated. Three previous international spoligotype databases had partly revealed the global and local geographical structures of MTC bacilli populations, however, there was a need for the release of a new, more representative and extended, international spoligotyping database. Results The fourth international spoligotyping database, SpolDB4, describes 1939 shared-types (STs) representative of a total of 39,295 strains from 122 countries, which are tentatively classified into 62 clades/lineages using a mixed expert-based and bioinformatical approach. The SpolDB4 update adds 26 new potentially phylogeographically-specific MTC genotype families. It provides a clearer picture of the current MTC genomes diversity as well as on the relationships between the genetic attributes investigated (spoligotypes) and the infra-species classification and evolutionary history of the species. Indeed, an independent Naïve-Bayes mixture-model analysis has validated main of the previous supervised SpolDB3 classification results, confirming the usefulness of both supervised and unsupervised models as an approach to understand MTC population structure. Updated results on the epidemiological status of spoligotypes, as well as genetic prevalence maps on six main lineages are also shown. Our results suggests the existence of fine geographical genetic clines within MTC populations, that could mirror the passed and present Homo sapiens sapiens demographical and mycobacterial co-evolutionary history whose structure could be further reconstructed and modelled, thereby providing a large-scale conceptual framework of the global TB Epidemiologic Network. Conclusion Our results broaden the knowledge of the global phylogeography of the MTC complex. SpolDB4 should be a very useful tool to better define the identity of a given MTC clinical isolate, and to better analyze the links between its current spreading and previous evolutionary history. The building and mining of extended MTC polymorphic genetic databases is in progress. PMID:16519816

To Cooperate or Not to Cooperate: Why Behavioural Mechanisms Matter

PubMed Central

2016-01-01

Mutualistic cooperation often requires multiple individuals to behave in a coordinated fashion. Hence, while the evolutionary stability of mutualistic cooperation poses no particular theoretical difficulty, its evolutionary emergence faces a chicken and egg problem: an individual cannot benefit from cooperating unless other individuals already do so. Here, we use evolutionary robotic simulations to study the consequences of this problem for the evolution of cooperation. In contrast with standard game-theoretic results, we find that the transition from solitary to cooperative strategies is very unlikely, whether interacting individuals are genetically related (cooperation evolves in 20% of all simulations) or unrelated (only 3% of all simulations). We also observe that successful cooperation between individuals requires the evolution of a specific and rather complex behaviour. This behavioural complexity creates a large fitness valley between solitary and cooperative strategies, making the evolutionary transition difficult. These results reveal the need for research on biological mechanisms which may facilitate this transition. PMID:27148874

Improving protein-protein interaction prediction using evolutionary information from low-quality MSAs.

PubMed

Várnai, Csilla; Burkoff, Nikolas S; Wild, David L

2017-01-01

Evolutionary information stored in multiple sequence alignments (MSAs) has been used to identify the interaction interface of protein complexes, by measuring either co-conservation or co-mutation of amino acid residues across the interface. Recently, maximum entropy related correlated mutation measures (CMMs) such as direct information, decoupling direct from indirect interactions, have been developed to identify residue pairs interacting across the protein complex interface. These studies have focussed on carefully selected protein complexes with large, good-quality MSAs. In this work, we study protein complexes with a more typical MSA consisting of fewer than 400 sequences, using a set of 79 intramolecular protein complexes. Using a maximum entropy based CMM at the residue level, we develop an interface level CMM score to be used in re-ranking docking decoys. We demonstrate that our interface level CMM score compares favourably to the complementarity trace score, an evolutionary information-based score measuring co-conservation, when combined with the number of interface residues, a knowledge-based potential and the variability score of individual amino acid sites. We also demonstrate, that, since co-mutation and co-complementarity in the MSA contain orthogonal information, the best prediction performance using evolutionary information can be achieved by combining the co-mutation information of the CMM with co-conservation information of a complementarity trace score, predicting a near-native structure as the top prediction for 41% of the dataset. The method presented is not restricted to small MSAs, and will likely improve interface prediction also for complexes with large and good-quality MSAs.

Evolution of disorder in Mediator complex and its functional relevance

PubMed Central

Nagulapalli, Malini; Maji, Sourobh; Dwivedi, Nidhi; Dahiya, Pradeep; Thakur, Jitendra K.

2016-01-01

Mediator, an important component of eukaryotic transcriptional machinery, is a huge multisubunit complex. Though the complex is known to be conserved across all the eukaryotic kingdoms, the evolutionary topology of its subunits has never been studied. In this study, we profiled disorder in the Mediator subunits of 146 eukaryotes belonging to three kingdoms viz., metazoans, plants and fungi, and attempted to find correlation between the evolution of Mediator complex and its disorder. Our analysis suggests that disorder in Mediator complex have played a crucial role in the evolutionary diversification of complexity of eukaryotic organisms. Conserved intrinsic disordered regions (IDRs) were identified in only six subunits in the three kingdoms whereas unique patterns of IDRs were identified in other Mediator subunits. Acquisition of novel molecular recognition features (MoRFs) through evolution of new subunits or through elongation of the existing subunits was evident in metazoans and plants. A new concept of ‘junction-MoRF’ has been introduced. Evolutionary link between CBP and Med15 has been provided which explain the evolution of extended-IDR in CBP from Med15 KIX-IDR junction-MoRF suggesting role of junction-MoRF in evolution and modulation of protein–protein interaction repertoire. This study can be informative and helpful in understanding the conserved and flexible nature of Mediator complex across eukaryotic kingdoms. PMID:26590257

Hybrid modeling and empirical analysis of automobile supply chain network

NASA Astrophysics Data System (ADS)

Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying

2017-05-01

Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.

Evolutionary Determinants of Cancer

PubMed Central

Greaves, Mel

2015-01-01

‘Nothing in biology makes sense except in the light of evolution’ Th. Dobzhansky, 1973 Our understanding of cancer is being transformed by exploring clonal diversity, drug resistance and causation within an evolutionary framework. The therapeutic resilience of advanced cancer is a consequence of its character as complex, dynamic and adaptive ecosystem engendering robustness, underpinned by genetic diversity and epigenetic plasticity. The risk of mutation-driven escape by self-renewing cells is intrinsic to multicellularity but is countered by multiple restraints facilitating increasing complexity and longevity of species. But our own has disrupted this historical narrative by rapidly escalating intrinsic risk. Evolutionary principles illuminate these challenges and provide new avenues to explore for more effective control. PMID:26193902

The statistical geometry of transcriptome divergence in cell-type evolution and cancer.

PubMed

Liang, Cong; Forrest, Alistair R R; Wagner, Günter P

2015-01-14

In evolution, body plan complexity increases due to an increase in the number of individualized cell types. Yet, there is very little understanding of the mechanisms that produce this form of organismal complexity. One model for the origin of novel cell types is the sister cell-type model. According to this model, each cell type arises together with a sister cell type through specialization from an ancestral cell type. A key prediction of the sister cell-type model is that gene expression profiles of cell types exhibit tree structure. Here we present a statistical model for detecting tree structure in transcriptomic data and apply it to transcriptomes from ENCODE and FANTOM5. We show that transcriptomes of normal cells harbour substantial amounts of hierarchical structure. In contrast, cancer cell lines have less tree structure, suggesting that the emergence of cancer cells follows different principles from that of evolutionary cell-type origination.

The protein-protein interface evolution acts in a similar way to antibody affinity maturation.

PubMed

Li, Bohua; Zhao, Lei; Wang, Chong; Guo, Huaizu; Wu, Lan; Zhang, Xunming; Qian, Weizhu; Wang, Hao; Guo, Yajun

2010-02-05

Understanding the evolutionary mechanism that acts at the interfaces of protein-protein complexes is a fundamental issue with high interest for delineating the macromolecular complexes and networks responsible for regulation and complexity in biological systems. To investigate whether the evolution of protein-protein interface acts in a similar way as antibody affinity maturation, we incorporated evolutionary information derived from antibody affinity maturation with common simulation techniques to evaluate prediction success rates of the computational method in affinity improvement in four different systems: antibody-receptor, antibody-peptide, receptor-membrane ligand, and receptor-soluble ligand. It was interesting to find that the same evolutionary information could improve the prediction success rates in all the four protein-protein complexes with an exceptional high accuracy (>57%). One of the most striking findings in our present study is that not only in the antibody-combining site but in other protein-protein interfaces almost all of the affinity-enhancing mutations are located at the germline hotspot sequences (RGYW or WA), indicating that DNA hot spot mechanisms may be widely used in the evolution of protein-protein interfaces. Our data suggest that the evolution of distinct protein-protein interfaces may use the same basic strategy under selection pressure to maintain interactions. Additionally, our data indicate that classical simulation techniques incorporating the evolutionary information derived from in vivo antibody affinity maturation can be utilized as a powerful tool to improve the binding affinity of protein-protein complex with a high accuracy.

Does constructive neutral evolution play an important role in the origin of cellular complexity? Making sense of the origins and uses of biological complexity.

PubMed

Speijer, Dave

2011-05-01

Recently, constructive neutral evolution has been touted as an important concept for the understanding of the emergence of cellular complexity. It has been invoked to help explain the development and retention of, amongst others, RNA splicing, RNA editing and ribosomal and mitochondrial respiratory chain complexity. The theory originated as a welcome explanation of isolated small scale cellular idiosyncrasies and as a reaction to 'overselectionism'. Here I contend, that in its extended form, it has major conceptual problems, can not explain observed patterns of complex processes, is too easily dismissive of alternative selectionist models, underestimates the creative force of complexity as such, and--if seen as a major evolutionary mechanism for all organisms--could stifle further thought regarding the evolution of highly complex biological processes. Copyright © 2011 WILEY Periodicals, Inc.

Evolutionary dynamics of a smoothed war of attrition game.

PubMed

Iyer, Swami; Killingback, Timothy

2016-05-07

In evolutionary game theory the War of Attrition game is intended to model animal contests which are decided by non-aggressive behavior, such as the length of time that a participant will persist in the contest. The classical War of Attrition game assumes that no errors are made in the implementation of an animal׳s strategy. However, it is inevitable in reality that such errors must sometimes occur. Here we introduce an extension of the classical War of Attrition game which includes the effect of errors in the implementation of an individual׳s strategy. This extension of the classical game has the important feature that the payoff is continuous, and as a consequence admits evolutionary behavior that is fundamentally different from that possible in the original game. We study the evolutionary dynamics of this new game in well-mixed populations both analytically using adaptive dynamics and through individual-based simulations, and show that there are a variety of possible outcomes, including simple monomorphic or dimorphic configurations which are evolutionarily stable and cannot occur in the classical War of Attrition game. In addition, we study the evolutionary dynamics of this extended game in a variety of spatially and socially structured populations, as represented by different complex network topologies, and show that similar outcomes can also occur in these situations. Copyright © 2016 Elsevier Ltd. All rights reserved.

A molecular signaling approach to linking intraspecific variation and macro-evolutionary patterns.

PubMed

Swanson, Eli M; Snell-Rood, Emilie C

2014-11-01

Macro-evolutionary comparisons are a valued tool in evolutionary biology. Nevertheless, our understanding of how systems involved in molecular signaling change in concert with phenotypic diversification has lagged. We argue that integrating our understanding of the evolution of molecular signaling systems with phylogenetic comparative methods is an important step toward understanding the processes linking variation among individuals with variation among species. Focusing mostly on the endocrine system, we discuss how the complexity and mechanistic nature of molecular signaling systems may influence the application and interpretation of macro-evolutionary comparisons. We also detail five hypotheses concerning the role that physiological mechanisms can play in shaping macro-evolutionary patterns, and discuss ways in which these hypotheses could influence phenotypic diversification. Finally, we review a series of tools able to analyze the complexity of physiological systems and the way they change in concert with the phenotypes for which they coordinate development. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Evolutionary domestication in Drosophila subobscura.

PubMed

Simões, P; Rose, M R; Duarte, A; Gonçalves, R; Matos, M

2007-03-01

The domestication of plants and animals is historically one of the most important topics in evolutionary biology. The evolutionary genetic changes arising from human cultivation are complex because of the effects of such varied processes as continuing natural selection, artificial selection, deliberate inbreeding, genetic drift and hybridization of different lineages. Despite the interest of domestication as an evolutionary process, few studies of multicellular sexual species have approached this topic using well-replicated experiments. Here we present a comprehensive study in which replicated evolutionary trajectories from several Drosophila subobscura populations provide a detailed view of the evolutionary dynamics of domestication in an outbreeding animal species. Our results show a clear evolutionary response in fecundity traits, but no clear pattern for adult starvation resistance and juvenile traits such as development time and viability. These results supply new perspectives on the confounding of adaptation with other evolutionary mechanisms in the process of domestication.

Evolutionary Games of Multiplayer Cooperation on Graphs

PubMed Central

Arranz, Jordi; Traulsen, Arne

2016-01-01

There has been much interest in studying evolutionary games in structured populations, often modeled as graphs. However, most analytical results so far have only been obtained for two-player or linear games, while the study of more complex multiplayer games has been usually tackled by computer simulations. Here we investigate evolutionary multiplayer games on graphs updated with a Moran death-Birth process. For cycles, we obtain an exact analytical condition for cooperation to be favored by natural selection, given in terms of the payoffs of the game and a set of structure coefficients. For regular graphs of degree three and larger, we estimate this condition using a combination of pair approximation and diffusion approximation. For a large class of cooperation games, our approximations suggest that graph-structured populations are stronger promoters of cooperation than populations lacking spatial structure. Computer simulations validate our analytical approximations for random regular graphs and cycles, but show systematic differences for graphs with many loops such as lattices. In particular, our simulation results show that these kinds of graphs can even lead to more stringent conditions for the evolution of cooperation than well-mixed populations. Overall, we provide evidence suggesting that the complexity arising from many-player interactions and spatial structure can be captured by pair approximation in the case of random graphs, but that it need to be handled with care for graphs with high clustering. PMID:27513946

A brief introduction to mixed effects modelling and multi-model inference in ecology

PubMed Central

Donaldson, Lynda; Correa-Cano, Maria Eugenia; Goodwin, Cecily E.D.

2018-01-01

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions. PMID:29844961

A brief introduction to mixed effects modelling and multi-model inference in ecology.

PubMed

Harrison, Xavier A; Donaldson, Lynda; Correa-Cano, Maria Eugenia; Evans, Julian; Fisher, David N; Goodwin, Cecily E D; Robinson, Beth S; Hodgson, David J; Inger, Richard

2018-01-01

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.

On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks.

PubMed

Guerra, Concettina

2015-01-01

Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.

The storytelling brain. Commentary on "On social attribution: implications of recent cognitive neuroscience research for race, law, and politics".

PubMed

Nigam, Sanjay K

2012-09-01

The well-established techniques of the professional storyteller not only have the potential to model complex "truth" but also to dig deeply into that complexity, thereby perhaps getting closer to that truth. This applies not only to fiction, but also to medicine and even science. Compelling storytelling ability may have conferred an evolutionary survival advantage and, if so, is likely represented in the neural circuitry of the human brain. Functional imaging will likely point to a neuroanatomical basis for compelling storytelling ability; this will presumably reflect underlying cellular and molecular mechanisms.

Different Evolutionary Paths to Complexity for Small and Large Populations of Digital Organisms

PubMed Central

2016-01-01

A major aim of evolutionary biology is to explain the respective roles of adaptive versus non-adaptive changes in the evolution of complexity. While selection is certainly responsible for the spread and maintenance of complex phenotypes, this does not automatically imply that strong selection enhances the chance for the emergence of novel traits, that is, the origination of complexity. Population size is one parameter that alters the relative importance of adaptive and non-adaptive processes: as population size decreases, selection weakens and genetic drift grows in importance. Because of this relationship, many theories invoke a role for population size in the evolution of complexity. Such theories are difficult to test empirically because of the time required for the evolution of complexity in biological populations. Here, we used digital experimental evolution to test whether large or small asexual populations tend to evolve greater complexity. We find that both small and large—but not intermediate-sized—populations are favored to evolve larger genomes, which provides the opportunity for subsequent increases in phenotypic complexity. However, small and large populations followed different evolutionary paths towards these novel traits. Small populations evolved larger genomes by fixing slightly deleterious insertions, while large populations fixed rare beneficial insertions that increased genome size. These results demonstrate that genetic drift can lead to the evolution of complexity in small populations and that purifying selection is not powerful enough to prevent the evolution of complexity in large populations. PMID:27923053

Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures

PubMed Central

Bryson, David M.; Ofria, Charles

2013-01-01

We investigate fundamental decisions in the design of instruction set architectures for linear genetic programs that are used as both model systems in evolutionary biology and underlying solution representations in evolutionary computation. We subjected digital organisms with each tested architecture to seven different computational environments designed to present a range of evolutionary challenges. Our goal was to engineer a general purpose architecture that would be effective under a broad range of evolutionary conditions. We evaluated six different types of architectural features for the virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more precisely modify the function of genetic instructions, (2) memory: we provided an increased number of registers in the virtual CPUs, (3) decoupled sensors and actuators: we separated input and output operations to enable greater control over data flow. We also tested a variety of methods to regulate expression: (4) explicit labels that allow programs to dynamically refer to specific genome positions, (5) position-relative search instructions, and (6) multiple new flow control instructions, including conditionals and jumps. Each of these features also adds complication to the instruction set and risks slowing evolution due to epistatic interactions. Two features (multiple argument specification and separated I/O) demonstrated substantial improvements in the majority of test environments, along with versions of each of the remaining architecture modifications that show significant improvements in multiple environments. However, some tested modifications were detrimental, though most exhibit no systematic effects on evolutionary potential, highlighting the robustness of digital evolution. Combined, these observations enhance our understanding of how instruction architecture impacts evolutionary potential, enabling the creation of architectures that support more rapid evolution of complex solutions to a broad range of challenges. PMID:24376669

An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

PubMed

Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano

2017-11-22

Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.

Bringing Together Evolution on Serpentine and Polyploidy: Spatiotemporal History of the Diploid-Tetraploid Complex of Knautia arvensis (Dipsacaceae)

PubMed Central

Kolář, Filip; Fér, Tomáš; Štech, Milan; Trávníček, Pavel; Dušková, Eva; Schönswetter, Peter; Suda, Jan

2012-01-01

Polyploidization is one of the leading forces in the evolution of land plants, providing opportunities for instant speciation and rapid gain of evolutionary novelties. Highly selective conditions of serpentine environments act as an important evolutionary trigger that can be involved in various speciation processes. Whereas the significance of both edaphic speciation on serpentine and polyploidy is widely acknowledged in plant evolution, the links between polyploid evolution and serpentine differentiation have not yet been examined. To fill this gap, we investigated the evolutionary history of the perennial herb Knautia arvensis (Dipsacaceae), a diploid-tetraploid complex that exhibits an intriguing pattern of eco-geographic differentiation. Using plastid DNA sequencing and AFLP genotyping of 336 previously cytotyped individuals from 40 populations from central Europe, we unravelled the patterns of genetic variation among the cytotypes and the edaphic types. Diploids showed the highest levels of genetic differentiation, likely as a result of long term persistence of several lineages in ecologically distinct refugia and/or independent immigration. Recurrent polyploidization, recorded in one serpentine island, seems to have opened new possibilities for the local serpentine genotype. Unlike diploids, the serpentine tetraploids were able to escape from the serpentine refugium and spread further; this was also attributable to hybridization with the neighbouring non-serpentine tetraploid lineages. The spatiotemporal history of K. arvensis allows tracing the interplay of polyploid evolution and ecological divergence on serpentine, resulting in a complex evolutionary pattern. Isolated serpentine outcrops can act as evolutionary capacitors, preserving distinct karyological and genetic diversity. The serpentine lineages, however, may not represent evolutionary ‘dead-ends’ but rather dynamic systems with a potential to further influence the surrounding populations, e.g., via independent polyplodization and hybridization. The complex eco-geographical pattern together with the incidence of both primary and secondary diploid-tetraploid contact zones makes K. arvensis a unique system for addressing general questions of polyploid research. PMID:22792207

MOCASSIN-prot: A multi-objective clustering approach for protein similarity networks

USDA-ARS?s Scientific Manuscript database

Motivation: Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary h...

The evolution of individuality revisited.

PubMed

Radzvilavicius, Arunas L; Blackstone, Neil W

2018-03-25

Evolutionary theory is formulated in terms of individuals that carry heritable information and are subject to selective pressures. However, individuality itself is a trait that had to evolve - an individual is not an indivisible entity, but a result of evolutionary processes that necessarily begin at the lower level of hierarchical organisation. Traditional approaches to biological individuality focus on cooperation and relatedness within a group, division of labour, policing mechanisms and strong selection at the higher level. Nevertheless, despite considerable theoretical progress in these areas, a full dynamical first-principles account of how new types of individuals arise is missing. To the extent that individuality is an emergent trait, the problem can be approached by recognising the importance of individuating mechanisms that are present from the very beginning of the transition, when only lower-level selection is acting. Here we review some of the most influential theoretical work on the role of individuating mechanisms in these transitions, and demonstrate how a lower-level, bottom-up evolutionary framework can be used to understand biological complexity involved in the origin of cellular life, early eukaryotic evolution, sexual life cycles and multicellular development. Some of these mechanisms inevitably stem from environmental constraints, population structure and ancestral life cycles. Others are unique to specific transitions - features of the natural history and biochemistry that are co-opted into conflict mediation. Identifying mechanisms of individuation that provide a coarse-grained description of the system's evolutionary dynamics is an important step towards understanding how biological complexity and hierarchical organisation evolves. In this way, individuality can be reconceptualised as an approximate model that with varying degrees of precision applies to a wide range of biological systems. © 2018 Cambridge Philosophical Society.

Self-organized modularization in evolutionary algorithms.

PubMed

Dauscher, Peter; Uthmann, Thomas

2005-01-01

The principle of modularization has proven to be extremely successful in the field of technical applications and particularly for Software Engineering purposes. The question to be answered within the present article is whether mechanisms can also be identified within the framework of Evolutionary Computation that cause a modularization of solutions. We will concentrate on processes, where modularization results only from the typical evolutionary operators, i.e. selection and variation by recombination and mutation (and not, e.g., from special modularization operators). This is what we call Self-Organized Modularization. Based on a combination of two formalizations by Radcliffe and Altenberg, some quantitative measures of modularity are introduced. Particularly, we distinguish Built-in Modularity as an inherent property of a genotype and Effective Modularity, which depends on the rest of the population. These measures can easily be applied to a wide range of present Evolutionary Computation models. It will be shown, both theoretically and by simulation, that under certain conditions, Effective Modularity (as defined within this paper) can be a selection factor. This causes Self-Organized Modularization to take place. The experimental observations emphasize the importance of Effective Modularity in comparison with Built-in Modularity. Although the experimental results have been obtained using a minimalist toy model, they can lead to a number of consequences for existing models as well as for future approaches. Furthermore, the results suggest a complex self-amplification of highly modular equivalence classes in the case of respected relations. Since the well-known Holland schemata are just the equivalence classes of respected relations in most Simple Genetic Algorithms, this observation emphasizes the role of schemata as Building Blocks (in comparison with arbitrary subsets of the search space).

Coevolution of patch-type dependent emigration and patch-type dependent immigration.

PubMed

Weigang, Helene C

2017-08-07

The three phases of dispersal - emigration, transfer and immigration - are affecting each other and the former and latter decisions may depend on patch types. Despite the inevitable fact of the complexity of the dispersal process, patch-type dependencies of dispersal decisions modelled as emigration and immigration are usually missing in theoretical dispersal models. Here, I investigate the coevolution of patch-type dependent emigration and patch-type dependent immigration in an extended Hamilton-May model. The dispersing population inhabits a landscape structured into many patches of two types and disperses during a continuous-time season. The trait under consideration is a four dimensional vector consisting of two values for emigration probability from the patches and two values for immigration probability into the patches of each type. Using the adaptive dynamics approach I show that four qualitatively different dispersal strategies may evolve in different parameter regions, including a counterintuitive strategy, where patches of one type are fully dispersed from (emigration probability is one) but individuals nevertheless always immigrate into them during the dispersal season (immigration probability is one). I present examples of evolutionary branching in a wide parameter range, when the patches with high local death rate during the dispersal season guarantee a high expected disperser output. I find that two dispersal strategies can coexist after evolutionary branching: a strategy with full immigration only into the patches with high expected disperser output coexists with a strategy that immigrates into any patch. Stochastic simulations agree with the numerical predictions. Since evolutionary branching is also found when immigration evolves alone, the present study is adding coevolutionary constraints on the emigration traits and hence finds that the coevolution of a higher dimensional trait sometimes hinders evolutionary diversification. Copyright © 2017 Elsevier Ltd. All rights reserved.

Resolving complex phylogeographic patterns in the Balkan Peninsula using closely related wall-lizard species as a model system.

PubMed

Psonis, Nikolaos; Antoniou, Aglaia; Karameta, Emmanouela; Leaché, Adam D; Kotsakiozi, Panayiota; Darriba, Diego; Kozlov, Alexey; Stamatakis, Alexandros; Poursanidis, Dimitris; Kukushkin, Oleg; Jablonski, Daniel; Crnobrnja-Isailović, Jelka; Gherghel, Iulian; Lymberakis, Petros; Poulakakis, Nikos

2018-08-01

The Balkan Peninsula constitutes a biodiversity hotspot with high levels of species richness and endemism. The complex geological history of the Balkans in conjunction with the climate evolution are hypothesized as the main drivers generating this biodiversity. We investigated the phylogeography, historical demography, and population structure of closely related wall-lizard species from the Balkan Peninsula and southeastern Europe to better understand diversification processes of species with limited dispersal ability, from Late Miocene to the Holocene. We used several analytical methods integrating genome-wide SNPs (ddRADseq), microsatellites, mitochondrial and nuclear DNA data, as well as species distribution modelling. Phylogenomic analysis resulted in a completely resolved species level phylogeny, population level analyses confirmed the existence of at least two cryptic evolutionary lineages and extensive within species genetic structuring. Divergence time estimations indicated that the Messinian Salinity Crisis played a key role in shaping patterns of species divergence, whereas intraspecific genetic structuring was mainly driven by Pliocene tectonic events and Quaternary climatic oscillations. The present work highlights the effectiveness of utilizing multiple methods and data types coupled with extensive geographic sampling to uncover the evolutionary processes that shaped the species over space and time. Copyright © 2018 Elsevier Inc. All rights reserved.

High Selection Pressure Promotes Increase in Cumulative Adaptive Culture

PubMed Central

Vegvari, Carolin; Foley, Robert A.

2014-01-01

The evolution of cumulative adaptive culture has received widespread interest in recent years, especially the factors promoting its occurrence. Current evolutionary models suggest that an increase in population size may lead to an increase in cultural complexity via a higher rate of cultural transmission and innovation. However, relatively little attention has been paid to the role of natural selection in the evolution of cultural complexity. Here we use an agent-based simulation model to demonstrate that high selection pressure in the form of resource pressure promotes the accumulation of adaptive culture in spite of small population sizes and high innovation costs. We argue that the interaction of demography and selection is important, and that neither can be considered in isolation. We predict that an increase in cultural complexity is most likely to occur under conditions of population pressure relative to resource availability. Our model may help to explain why culture change can occur without major environmental change. We suggest that understanding the interaction between shifting selective pressures and demography is essential for explaining the evolution of cultural complexity. PMID:24489724

Proteins feel more than they see: fine-tuning of binding affinity by properties of the non-interacting surface.

PubMed

Kastritis, Panagiotis L; Rodrigues, João P G L M; Folkers, Gert E; Boelens, Rolf; Bonvin, Alexandre M J J

2014-07-15

Protein-protein complexes orchestrate most cellular processes such as transcription, signal transduction and apoptosis. The factors governing their affinity remain elusive however, especially when it comes to describing dissociation rates (koff). Here we demonstrate that, next to direct contributions from the interface, the non-interacting surface (NIS) also plays an important role in binding affinity, especially polar and charged residues. Their percentage on the NIS is conserved over orthologous complexes indicating an evolutionary selection pressure. Their effect on binding affinity can be explained by long-range electrostatic contributions and surface-solvent interactions that are known to determine the local frustration of the protein complex surface. Including these in a simple model significantly improves the affinity prediction of protein complexes from structural models. The impact of mutations outside the interacting surface on binding affinity is supported by experimental alanine scanning mutagenesis data. These results enable the development of more sophisticated and integrated biophysical models of binding affinity and open new directions in experimental control and modulation of biomolecular interactions. Copyright © 2014. Published by Elsevier Ltd.

Mean-field approximations of fixation time distributions of evolutionary game dynamics on graphs

NASA Astrophysics Data System (ADS)

Ying, Li-Min; Zhou, Jie; Tang, Ming; Guan, Shu-Guang; Zou, Yong

2018-02-01

The mean fixation time is often not accurate for describing the timescales of fixation probabilities of evolutionary games taking place on complex networks. We simulate the game dynamics on top of complex network topologies and approximate the fixation time distributions using a mean-field approach. We assume that there are two absorbing states. Numerically, we show that the mean fixation time is sufficient in characterizing the evolutionary timescales when network structures are close to the well-mixing condition. In contrast, the mean fixation time shows large inaccuracies when networks become sparse. The approximation accuracy is determined by the network structure, and hence by the suitability of the mean-field approach. The numerical results show good agreement with the theoretical predictions.

Networks, Trees, and Treeshrews: Assessing Support and Identifying Conflict with Multiple Loci and a Problematic Root

PubMed Central

Roberts, Trina E.; Sargis, Eric J.; Olson, Link E.

2009-01-01

Multiple unlinked genetic loci often provide a more comprehensive picture of evolutionary history than any single gene can, but analyzing multigene data presents particular challenges. Differing rates and patterns of nucleotide substitution, combined with the limited information available in any data set, can make it difficult to specify a model of evolution. In addition, conflict among loci can be the result of real differences in evolutionary process or of stochastic variance and errors in reconstruction. We used 6 presumably unlinked nuclear loci to investigate relationships within the mammalian family Tupaiidae (Scandentia), containing all but one of the extant tupaiid genera. We used a phylogenetic mixture model to analyze the concatenated data and compared this with results using partitioned models. We found that more complex models were not necessarily preferred under tests using Bayes factors and that model complexity affected both tree length and parameter variance. We also compared the results of single-gene and multigene analyses and used splits networks to analyze the source and degree of conflict among genes. Networks can show specific relationships that are inconsistent with each other; these conflicting and minority relationships, which are implicitly ignored or collapsed by traditional consensus methods, can be useful in identifying the underlying causes of topological uncertainty. In our data, conflict is concentrated around particular relationships, not widespread throughout the tree. This pattern is further clarified by considering conflict surrounding the root separately from conflict within the ingroup. Uncertainty in rooting may be because of the apparent evolutionary distance separating these genera and our outgroup, the tupaiid genus Dendrogale. Unlike a previous mitochondrial study, these nuclear data strongly suggest that the genus Tupaia is not monophyletic with respect to the monotypic Urogale, even when uncertainty about rooting is taken into account. These data concur with mitochondrial DNA on other relationships, including the close affinity of Tupaia tana with the enigmatic Tupaia splendidula and of Tupaia belangeri with Tupaia glis. We also discuss the taxonomic and biogeographic implications of these results. PMID:20525582

Spatial multiobjective optimization of agricultural conservation practices using a SWAT model and an evolutionary algorithm.

PubMed

Rabotyagov, Sergey; Campbell, Todd; Valcu, Adriana; Gassman, Philip; Jha, Manoj; Schilling, Keith; Wolter, Calvin; Kling, Catherine

2012-12-09

Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,(5,12,20)) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization. Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods(3,4,9,10,13-15,17-19,22,23,25). In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model(7) with a multiobjective evolutionary algorithm SPEA2(26), and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.

Parasites, ecosystems and sustainability: an ecological and complex systems perspective.

PubMed

Horwitz, Pierre; Wilcox, Bruce A

2005-06-01

Host-parasite relationships can be conceptualised either narrowly, where the parasite is metabolically dependent on the host, or more broadly, as suggested by an ecological-evolutionary and complex systems perspective. In this view Host-parasite relationships are part of a larger set of ecological and co-evolutionary interdependencies and a complex adaptive system. These interdependencies affect not just the hosts, vectors, parasites, the immediate agents, but also those indirectly or consequentially affected by the relationship. Host-parasite relationships also can be viewed as systems embedded within larger systems represented by ecological communities and ecosystems. So defined, it can be argued that Host-parasite relationships may often benefit their hosts and contribute significantly to the structuring of ecological communities. The broader, complex adaptive system view also contributes to understanding the phenomenon of disease emergence, the ecological and evolutionary mechanisms involved, and the role of parasitology in research and management of ecosystems in light of the apparently growing problem of emerging infectious diseases in wildlife and humans. An expanded set of principles for integrated parasite management is suggested by this perspective.

Cancer Evolution: Mathematical Models and Computational Inference

PubMed Central

Beerenwinkel, Niko; Schwarz, Roland F.; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. PMID:25293804

Random genetic drift, natural selection, and noise in human cranial evolution.

PubMed

Roseman, Charles C

2016-08-01

This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology. Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality. Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Analysis and application of opinion model with multiple topic interactions.

PubMed

Xiong, Fei; Liu, Yun; Wang, Liang; Wang, Ximeng

2017-08-01

To reveal heterogeneous behaviors of opinion evolution in different scenarios, we propose an opinion model with topic interactions. Individual opinions and topic features are represented by a multidimensional vector. We measure an agent's action towards a specific topic by the product of opinion and topic feature. When pairs of agents interact for a topic, their actions are introduced to opinion updates with bounded confidence. Simulation results show that a transition from a disordered state to a consensus state occurs at a critical point of the tolerance threshold, which depends on the opinion dimension. The critical point increases as the dimension of opinions increases. Multiple topics promote opinion interactions and lead to the formation of macroscopic opinion clusters. In addition, more topics accelerate the evolutionary process and weaken the effect of network topology. We use two sets of large-scale real data to evaluate the model, and the results prove its effectiveness in characterizing a real evolutionary process. Our model achieves high performance in individual action prediction and even outperforms state-of-the-art methods. Meanwhile, our model has much smaller computational complexity. This paper provides a demonstration for possible practical applications of theoretical opinion dynamics.

Scalability issues in evolutionary synthesis of electronic circuits: lessons learned and challenges ahead

NASA Technical Reports Server (NTRS)

Stoica, A.; Keymeulen, D.; Zebulum, R. S.; Ferguson, M. I.

2003-01-01

This paper describes scalability issues of evolutionary-driven automatic synthesis of electronic circuits. The article begins by reviewing the concepts of circuit evolution and discussing the limitations of this technique when trying to achieve more complex systems.

Comparative studies of gene expression and the evolution of gene regulation

PubMed Central

Romero, Irene Gallego; Ruvinsky, Ilya; Gilad, Yoav

2014-01-01

The hypothesis that differences in gene regulation play an important role in speciation and adaptation is more than 40 years old. With the advent of new sequencing technologies, we are able to characterize and study gene expression levels and associated regulatory mechanisms in a large number of individuals and species at unprecedented resolution and scale. We have thus gained new insights into the evolutionary pressures that shape gene expression levels, as well as developed an appreciation for the relative importance of evolutionary changes in different regulatory genetic and epigenetic mechanisms. The current challenge is to link gene regulatory changes to adaptive evolution of complex phenotypes. Here we mainly focus on comparative studies in primates, and how they are complemented by studies in model organisms. PMID:22705669

Big cats as a model system for the study of the evolution of intelligence.

PubMed

Borrego, Natalia

2017-08-01

Currently, carnivores, and felids in particular, are vastly underrepresented in cognitive literature, despite being an ideal model system for tests of social and ecological intelligence hypotheses. Within Felidae, big cats (Panthera) are uniquely suited to studies investigating the evolutionary links between social, ecological, and cognitive complexity. Intelligence likely did not evolve in a unitary way but instead evolved as the result of mutually reinforcing feedback loops within the physical and social environments. The domain-specific social intelligence hypothesis proposes that social complexity drives only the evolution of cognitive abilities adapted only to social domains. The domain-general hypothesis proposes that the unique demands of social life serve as a bootstrap for the evolution of superior general cognition. Big cats are one of the few systems in which we can directly address conflicting predictions of the domain-general and domain-specific hypothesis by comparing cognition among closely related species that face roughly equivalent ecological complexity but vary considerably in social complexity. Copyright © 2017 Elsevier B.V. All rights reserved.

Reconstructing Networks from Profit Sequences in Evolutionary Games via a Multiobjective Optimization Approach with Lasso Initialization

PubMed Central

Wu, Kai; Liu, Jing; Wang, Shuai

2016-01-01

Evolutionary games (EG) model a common type of interactions in various complex, networked, natural and social systems. Given such a system with only profit sequences being available, reconstructing the interacting structure of EG networks is fundamental to understand and control its collective dynamics. Existing approaches used to handle this problem, such as the lasso, a convex optimization method, need a user-defined constant to control the tradeoff between the natural sparsity of networks and measurement error (the difference between observed data and simulated data). However, a shortcoming of these approaches is that it is not easy to determine these key parameters which can maximize the performance. In contrast to these approaches, we first model the EG network reconstruction problem as a multiobjective optimization problem (MOP), and then develop a framework which involves multiobjective evolutionary algorithm (MOEA), followed by solution selection based on knee regions, termed as MOEANet, to solve this MOP. We also design an effective initialization operator based on the lasso for MOEA. We apply the proposed method to reconstruct various types of synthetic and real-world networks, and the results show that our approach is effective to avoid the above parameter selecting problem and can reconstruct EG networks with high accuracy. PMID:27886244

Reconstructing Networks from Profit Sequences in Evolutionary Games via a Multiobjective Optimization Approach with Lasso Initialization

NASA Astrophysics Data System (ADS)

Wu, Kai; Liu, Jing; Wang, Shuai

2016-11-01

Evolutionary games (EG) model a common type of interactions in various complex, networked, natural and social systems. Given such a system with only profit sequences being available, reconstructing the interacting structure of EG networks is fundamental to understand and control its collective dynamics. Existing approaches used to handle this problem, such as the lasso, a convex optimization method, need a user-defined constant to control the tradeoff between the natural sparsity of networks and measurement error (the difference between observed data and simulated data). However, a shortcoming of these approaches is that it is not easy to determine these key parameters which can maximize the performance. In contrast to these approaches, we first model the EG network reconstruction problem as a multiobjective optimization problem (MOP), and then develop a framework which involves multiobjective evolutionary algorithm (MOEA), followed by solution selection based on knee regions, termed as MOEANet, to solve this MOP. We also design an effective initialization operator based on the lasso for MOEA. We apply the proposed method to reconstruct various types of synthetic and real-world networks, and the results show that our approach is effective to avoid the above parameter selecting problem and can reconstruct EG networks with high accuracy.

Genetic algorithm learning in a New Keynesian macroeconomic setup.

PubMed

Hommes, Cars; Makarewicz, Tomasz; Massaro, Domenico; Smits, Tom

2017-01-01

In order to understand heterogeneous behavior amongst agents, empirical data from Learning-to-Forecast (LtF) experiments can be used to construct learning models. This paper follows up on Assenza et al. (2013) by using a Genetic Algorithms (GA) model to replicate the results from their LtF experiment. In this GA model, individuals optimize an adaptive, a trend following and an anchor coefficient in a population of general prediction heuristics. We replicate experimental treatments in a New-Keynesian environment with increasing complexity and use Monte Carlo simulations to investigate how well the model explains the experimental data. We find that the evolutionary learning model is able to replicate the three different types of behavior, i.e. convergence to steady state, stable oscillations and dampened oscillations in the treatments using one GA model. Heterogeneous behavior can thus be explained by an adaptive, anchor and trend extrapolating component and the GA model can be used to explain heterogeneous behavior in LtF experiments with different types of complexity.

Evolution of disorder in Mediator complex and its functional relevance.

PubMed

Nagulapalli, Malini; Maji, Sourobh; Dwivedi, Nidhi; Dahiya, Pradeep; Thakur, Jitendra K

2016-02-29

Mediator, an important component of eukaryotic transcriptional machinery, is a huge multisubunit complex. Though the complex is known to be conserved across all the eukaryotic kingdoms, the evolutionary topology of its subunits has never been studied. In this study, we profiled disorder in the Mediator subunits of 146 eukaryotes belonging to three kingdoms viz., metazoans, plants and fungi, and attempted to find correlation between the evolution of Mediator complex and its disorder. Our analysis suggests that disorder in Mediator complex have played a crucial role in the evolutionary diversification of complexity of eukaryotic organisms. Conserved intrinsic disordered regions (IDRs) were identified in only six subunits in the three kingdoms whereas unique patterns of IDRs were identified in other Mediator subunits. Acquisition of novel molecular recognition features (MoRFs) through evolution of new subunits or through elongation of the existing subunits was evident in metazoans and plants. A new concept of 'junction-MoRF' has been introduced. Evolutionary link between CBP and Med15 has been provided which explain the evolution of extended-IDR in CBP from Med15 KIX-IDR junction-MoRF suggesting role of junction-MoRF in evolution and modulation of protein-protein interaction repertoire. This study can be informative and helpful in understanding the conserved and flexible nature of Mediator complex across eukaryotic kingdoms. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Molecular hyperdiversity and evolution in very large populations.

PubMed

Cutter, Asher D; Jovelin, Richard; Dey, Alivia

2013-04-01

The genomic density of sequence polymorphisms critically affects the sensitivity of inferences about ongoing sequence evolution, function and demographic history. Most animal and plant genomes have relatively low densities of polymorphisms, but some species are hyperdiverse with neutral nucleotide heterozygosity exceeding 5%. Eukaryotes with extremely large populations, mimicking bacterial and viral populations, present novel opportunities for studying molecular evolution in sexually reproducing taxa with complex development. In particular, hyperdiverse species can help answer controversial questions about the evolution of genome complexity, the limits of natural selection, modes of adaptation and subtleties of the mutation process. However, such systems have some inherent complications and here we identify topics in need of theoretical developments. Close relatives of the model organisms Caenorhabditis elegans and Drosophila melanogaster provide known examples of hyperdiverse eukaryotes, encouraging functional dissection of resulting molecular evolutionary patterns. We recommend how best to exploit hyperdiverse populations for analysis, for example, in quantifying the impact of noncrossover recombination in genomes and for determining the identity and micro-evolutionary selective pressures on noncoding regulatory elements. © 2013 Blackwell Publishing Ltd.

On the complex interplay between learning and dynamics in life sciences. Comment on the paper "Collective learning modeling based on the kinetic theory of active particles" by Burini et al.

NASA Astrophysics Data System (ADS)

Bellomo, Nicola; Elaiw, Ahmed; Alghamdi, Mohamed Ali

2016-03-01

The paper by Burini, De Lillo, and Gibelli [8] presents an overview and critical analysis of the literature on the modeling of learning dynamics. The first reference is the celebrated paper by Cucker and Smale [9]. Then, the authors also propose their own approach, based on suitable development of methods of the kinetic theory [6] and theoretical tools of evolutionary game theory [12,13], recently developed on graphs [2].

Multilocus phylogeny and statistical biogeography clarify the evolutionary history of major lineages of turtles.

PubMed

Pereira, Anieli G; Sterli, Juliana; Moreira, Filipe R R; Schrago, Carlos G

2017-08-01

Despite their complex evolutionary history and the rich fossil record, the higher level phylogeny and historical biogeography of living turtles have not been investigated in a comprehensive and statistical framework. To tackle these issues, we assembled a large molecular dataset, maximizing both taxonomic and gene sampling. As different models provide alternative biogeographical scenarios, we have explicitly tested such hypotheses in order to reconstruct a robust biogeographical history of Testudines. We scanned publicly available databases for nucleotide sequences and composed a dataset comprising 13 loci for 294 living species of Testudines, which accounts for all living genera and 85% of their extant species diversity. Phylogenetic relationships and species divergence times were estimated using a thorough evaluation of fossil information as calibration priors. We then carried out the analysis of historical biogeography of Testudines in a fully statistical framework. Our study recovered the first large-scale phylogeny of turtles with well-supported relationships following the topology proposed by phylogenomic works. Our dating result consistently indicated that the origin of the main clades, Pleurodira and Cryptodira, occurred in the early Jurassic. The phylogenetic and historical biogeographical inferences permitted us to clarify how geological events affected the evolutionary dynamics of crown turtles. For instance, our analyses support the hypothesis that the breakup of Pangaea would have driven the divergence between the cryptodiran and pleurodiran lineages. The reticulated pattern in the ancestral distribution of the cryptodiran lineage suggests a complex biogeographic history for the clade, which was supposedly related to the complex paleogeographic history of Laurasia. On the other hand, the biogeographical history of Pleurodira indicated a tight correlation with the paleogeography of the Gondwanan landmasses. Copyright © 2017 Elsevier Inc. All rights reserved.

Complex evolutionary footprints revealed in an analysis of reused protein segments of diverse lengths

PubMed Central

Nepomnyachiy, Sergey; Ben-Tal, Nir; Kolodny, Rachel

2017-01-01

Proteins share similar segments with one another. Such “reused parts”—which have been successfully incorporated into other proteins—are likely to offer an evolutionary advantage over de novo evolved segments, as most of the latter will not even have the capacity to fold. To systematically explore the evolutionary traces of segment “reuse” across proteins, we developed an automated methodology that identifies reused segments from protein alignments. We search for “themes”—segments of at least 35 residues of similar sequence and structure—reused within representative sets of 15,016 domains [Evolutionary Classification of Protein Domains (ECOD) database] or 20,398 chains [Protein Data Bank (PDB)]. We observe that theme reuse is highly prevalent and that reuse is more extensive when the length threshold for identifying a theme is lower. Structural domains, the best characterized form of reuse in proteins, are just one of many complex and intertwined evolutionary traces. Others include long themes shared among a few proteins, which encompass and overlap with shorter themes that recur in numerous proteins. The observed complexity is consistent with evolution by duplication and divergence, and some of the themes might include descendants of ancestral segments. The observed recursive footprints, where the same amino acid can simultaneously participate in several intertwined themes, could be a useful concept for protein design. Data are available at http://trachel-srv.cs.haifa.ac.il/rachel/ppi/themes/. PMID:29078314

Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

NASA Technical Reports Server (NTRS)

Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan

2014-01-01

Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

Generative Representations for Automated Design of Robots

NASA Technical Reports Server (NTRS)

Homby, Gregory S.; Lipson, Hod; Pollack, Jordan B.

2007-01-01

A method of automated design of complex, modular robots involves an evolutionary process in which generative representations of designs are used. The term generative representations as used here signifies, loosely, representations that consist of or include algorithms, computer programs, and the like, wherein encoded designs can reuse elements of their encoding and thereby evolve toward greater complexity. Automated design of robots through synthetic evolutionary processes has already been demonstrated, but it is not clear whether genetically inspired search algorithms can yield designs that are sufficiently complex for practical engineering. The ultimate success of such algorithms as tools for automation of design depends on the scaling properties of representations of designs. A nongenerative representation (one in which each element of the encoded design is used at most once in translating to the design) scales linearly with the number of elements. Search algorithms that use nongenerative representations quickly become intractable (search times vary approximately exponentially with numbers of design elements), and thus are not amenable to scaling to complex designs. Generative representations are compact representations and were devised as means to circumvent the above-mentioned fundamental restriction on scalability. In the present method, a robot is defined by a compact programmatic form (its generative representation) and the evolutionary variation takes place on this form. The evolutionary process is an iterative one, wherein each cycle consists of the following steps: 1. Generative representations are generated in an evolutionary subprocess. 2. Each generative representation is a program that, when compiled, produces an assembly procedure. 3. In a computational simulation, a constructor executes an assembly procedure to generate a robot. 4. A physical-simulation program tests the performance of a simulated constructed robot, evaluating the performance according to a fitness criterion to yield a figure of merit that is fed back into the evolutionary subprocess of the next iteration. In comparison with prior approaches to automated evolutionary design of robots, the use of generative representations offers two advantages: First, a generative representation enables the reuse of components in regular and hierarchical ways and thereby serves a systematic means of creating more complex modules out of simpler ones. Second, the evolved generative representation may capture intrinsic properties of the design problem, so that variations in the representations move through the design space more effectively than do equivalent variations in a nongenerative representation. This method has been demonstrated by using it to design some robots that move, variously, by walking, rolling, or sliding. Some of the robots were built (see figure). Although these robots are very simple, in comparison with robots designed by humans, their structures are more regular, modular, hierarchical, and complex than are those of evolved designs of comparable functionality synthesized by use of nongenerative representations.

Strengths and weaknesses of McNamara's evolutionary psychological model of dreaming.

PubMed

Olliges, Sandra

2010-10-07

This article includes a brief overview of McNamara's (2004) evolutionary model of dreaming. The strengths and weaknesses of this model are then evaluated in terms of its consonance with measurable neurological and biological properties of dreaming, its fit within the tenets of evolutionary theories of dreams, and its alignment with evolutionary concepts of cooperation and spirituality. McNamara's model focuses primarily on dreaming that occurs during rapid eye movement (REM) sleep; therefore this article also focuses on REM dreaming.

Adaptive processes drive ecomorphological convergent evolution in antwrens (Thamnophilidae).

PubMed

Bravo, Gustavo A; Remsen, J V; Brumfield, Robb T

2014-10-01

Phylogenetic niche conservatism (PNC) and convergence are contrasting evolutionary patterns that describe phenotypic similarity across independent lineages. Assessing whether and how adaptive processes give origin to these patterns represent a fundamental step toward understanding phenotypic evolution. Phylogenetic model-based approaches offer the opportunity not only to distinguish between PNC and convergence, but also to determine the extent that adaptive processes explain phenotypic similarity. The Myrmotherula complex in the Neotropical family Thamnophilidae is a polyphyletic group of sexually dimorphic small insectivorous forest birds that are relatively homogeneous in size and shape. Here, we integrate a comprehensive species-level molecular phylogeny of the Myrmotherula complex with morphometric and ecological data within a comparative framework to test whether phenotypic similarity is described by a pattern of PNC or convergence, and to identify evolutionary mechanisms underlying body size and shape evolution. We show that antwrens in the Myrmotherula complex represent distantly related clades that exhibit adaptive convergent evolution in body size and divergent evolution in body shape. Phenotypic similarity in the group is primarily driven by their tendency to converge toward smaller body sizes. Differences in body size and shape across lineages are associated to ecological and behavioral factors. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Mitochondrial DNA plays an equal role in influencing female and male longevity in centenarians.

PubMed

He, Yong-Han; Lu, Xiang; Tian, Jiao-Yang; Yan, Dong-Jing; Li, Yu-Chun; Lin, Rong; Perry, Benjamin; Chen, Xiao-Qiong; Yu, Qin; Cai, Wang-Wei; Kong, Qing-Peng

2016-10-01

The mitochondrion is a double membrane-bound organelle which plays important functional roles in aging and many other complex phenotypes. Transmission of the mitochondrial genome in the matrilineal line causes the evolutionary selection sieve only in females. Theoretically, beneficial or neutral variations are more likely to accumulate and be retained in the female mitochondrial genome during evolution, which may be an initial trigger of gender dimorphism in aging. The asymmetry of evolutionary processes between gender could lead to males and females aging in different ways. If so, gender specific variation loads could be an evolutionary result of maternal heritage of mitochondrial genomes, especially in centenarians who live to an extreme age and are considered as good models for healthy aging. Here, we tested whether the mitochondrial variation loads were associated with altered aging patterns by investigating the mtDNA haplogroup distribution and genetic diversity between female and male centenarians. We found no evidence of differences in aging patterns between genders in centenarians. Our results indicate that the evolutionary consequence of gender dimorphism in mitochondrial genomes is not a factor in the altered aging patterns in human, and that mitochondrial DNA contributes equally to longevity in males and females. Copyright © 2016 Elsevier Inc. All rights reserved.

Evolutionary tree reconstruction

NASA Technical Reports Server (NTRS)

Cheeseman, Peter; Kanefsky, Bob

1990-01-01

It is described how Minimum Description Length (MDL) can be applied to the problem of DNA and protein evolutionary tree reconstruction. If there is a set of mutations that transform a common ancestor into a set of the known sequences, and this description is shorter than the information to encode the known sequences directly, then strong evidence for an evolutionary relationship has been found. A heuristic algorithm is described that searches for the simplest tree (smallest MDL) that finds close to optimal trees on the test data. Various ways of extending the MDL theory to more complex evolutionary relationships are discussed.

Darwinian demons, evolutionary complexity, and information maximization.

PubMed

Krakauer, David C

2011-09-01

Natural selection is shown to be an extended instance of a Maxwell's demon device. A demonic selection principle is introduced that states that organisms cannot exceed the complexity of their selective environment. Thermodynamic constraints on error repair impose a fundamental limit to the rate that information can be transferred from the environment (via the selective demon) to the genome. Evolved mechanisms of learning and inference can overcome this limitation, but remain subject to the same fundamental constraint, such that plastic behaviors cannot exceed the complexity of reward signals. A natural measure of evolutionary complexity is provided by mutual information, and niche construction activity--the organismal contribution to the construction of selection pressures--might in principle lead to its increase, bounded by thermodynamic free energy required for error correction.

An evolutionary switch in ND2 enables Src kinase regulation of NMDA receptors

NASA Astrophysics Data System (ADS)

Scanlon, David P.; Bah, Alaji; Krzeminski, Mickaël; Zhang, Wenbo; Leduc-Pessah, Heather L.; Dong, Yi Na; Forman-Kay, Julie D.; Salter, Michael W.

2017-05-01

The non-receptor tyrosine kinase Src is a key signalling hub for upregulating the function of N-methyl D-aspartate receptors (NMDARs). Src is anchored within the NMDAR complex via NADH dehydrogenase subunit 2 (ND2), a mitochondrially encoded adaptor protein. The interacting regions between Src and ND2 have been broadly identified, but the interaction between ND2 and the NMDAR has remained elusive. Here we generate a homology model of ND2 and dock it onto the NMDAR via the transmembrane domain of GluN1. This interaction is enabled by the evolutionary loss of three helices in bilaterian ND2 proteins compared to their ancestral homologues. We experimentally validate our model and demonstrate that blocking this interaction with an ND2 fragment identified in our experimental studies prevents Src-mediated upregulation of NMDAR currents in neurons. Our findings establish the mode of interaction between an NMDAR accessory protein with one of the core subunits of the receptor.

Energy and time determine scaling in biological and computer designs

PubMed Central

Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-01-01

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy–time minimization principle may govern the design of many complex systems that process energy, materials and information. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431524

Assessment of Masonry Buildings Subjected to Landslide-Induced Settlements: From Load Path Method to Evolutionary Optimization Method

NASA Astrophysics Data System (ADS)

Palmisano, Fabrizio; Elia, Angelo

2017-10-01

One of the main difficulties, when dealing with landslide structural vulnerability, is the diagnosis of the causes of crack patterns. This is also due to the excessive complexity of models based on classical structural mechanics that makes them inappropriate especially when there is the necessity to perform a rapid vulnerability assessment at the territorial scale. This is why, a new approach, based on a ‘simple model’ (i.e. the Load Path Method, LPM), has been proposed by Palmisano and Elia for the interpretation of the behaviour of masonry buildings subjected to landslide-induced settlements. However, the LPM is very useful for rapidly finding the 'most plausible solution' instead of the exact solution. To find the solution, optimization algorithms are necessary. In this scenario, this article aims to show how the Bidirectional Evolutionary Structural Optimization method by Huang and Xie, can be very useful to optimize the strut-and-tie models obtained by using the Load Path Method.

Energy and time determine scaling in biological and computer designs.

PubMed

Moses, Melanie; Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-08-19

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

NASA Astrophysics Data System (ADS)

Wu, Yu'E.; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

2017-01-01

Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world.

Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

PubMed Central

Wu, Yu’e; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

2017-01-01

Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world. PMID:28112276

Using genomics to characterize evolutionary potential for conservation of wild populations

PubMed Central

Harrisson, Katherine A; Pavlova, Alexandra; Telonis-Scott, Marina; Sunnucks, Paul

2014-01-01

Genomics promises exciting advances towards the important conservation goal of maximizing evolutionary potential, notwithstanding associated challenges. Here, we explore some of the complexity of adaptation genetics and discuss the strengths and limitations of genomics as a tool for characterizing evolutionary potential in the context of conservation management. Many traits are polygenic and can be strongly influenced by minor differences in regulatory networks and by epigenetic variation not visible in DNA sequence. Much of this critical complexity is difficult to detect using methods commonly used to identify adaptive variation, and this needs appropriate consideration when planning genomic screens, and when basing management decisions on genomic data. When the genomic basis of adaptation and future threats are well understood, it may be appropriate to focus management on particular adaptive traits. For more typical conservations scenarios, we argue that screening genome-wide variation should be a sensible approach that may provide a generalized measure of evolutionary potential that accounts for the contributions of small-effect loci and cryptic variation and is robust to uncertainty about future change and required adaptive response(s). The best conservation outcomes should be achieved when genomic estimates of evolutionary potential are used within an adaptive management framework. PMID:25553064

Eco-Evo PVAs: Incorporating Eco-Evolutionary Processes into Population Viability Models

EPA Science Inventory

We synthesize how advances in computational methods and population genomics can be combined within an Ecological-Evolutionary (Eco-Evo) PVA model. Eco-Evo PVA models are powerful new tools for understanding the influence of evolutionary processes on plant and animal population pe...

Genealogical Working Distributions for Bayesian Model Testing with Phylogenetic Uncertainty

PubMed Central

Baele, Guy; Lemey, Philippe; Suchard, Marc A.

2016-01-01

Marginal likelihood estimates to compare models using Bayes factors frequently accompany Bayesian phylogenetic inference. Approaches to estimate marginal likelihoods have garnered increased attention over the past decade. In particular, the introduction of path sampling (PS) and stepping-stone sampling (SS) into Bayesian phylogenetics has tremendously improved the accuracy of model selection. These sampling techniques are now used to evaluate complex evolutionary and population genetic models on empirical data sets, but considerable computational demands hamper their widespread adoption. Further, when very diffuse, but proper priors are specified for model parameters, numerical issues complicate the exploration of the priors, a necessary step in marginal likelihood estimation using PS or SS. To avoid such instabilities, generalized SS (GSS) has recently been proposed, introducing the concept of “working distributions” to facilitate—or shorten—the integration process that underlies marginal likelihood estimation. However, the need to fix the tree topology currently limits GSS in a coalescent-based framework. Here, we extend GSS by relaxing the fixed underlying tree topology assumption. To this purpose, we introduce a “working” distribution on the space of genealogies, which enables estimating marginal likelihoods while accommodating phylogenetic uncertainty. We propose two different “working” distributions that help GSS to outperform PS and SS in terms of accuracy when comparing demographic and evolutionary models applied to synthetic data and real-world examples. Further, we show that the use of very diffuse priors can lead to a considerable overestimation in marginal likelihood when using PS and SS, while still retrieving the correct marginal likelihood using both GSS approaches. The methods used in this article are available in BEAST, a powerful user-friendly software package to perform Bayesian evolutionary analyses. PMID:26526428

Blockmodeling and the Estimation of Evolutionary Architectural Growth in Major Defense Acquisition Programs

DTIC Science & Technology

2016-04-30

Dabkowski, and Dixit (2015), we demonstrate that the DoDAF models required pre–MS A map to 14 of the 18 parameters of the Constructive Systems...engineering effort in complex systems. Saarbrücken, Germany: VDM Verlag. Valerdi, R., Dabkowski, M., & Dixit , I. (2015). Reliability improvement of...R., Dabkowski, M., & Dixit , I. (2015). Reliability Improvement of Major Defense Acquisition Program Cost Estimates – Mapping DoDAF to COSYSMO

Evolutionary construction by staying together and coming together.

PubMed

Tarnita, Corina E; Taubes, Clifford H; Nowak, Martin A

2013-03-07

The evolutionary trajectory of life on earth is one of increasing size and complexity. Yet the standard equations of evolutionary dynamics describe mutation and selection among similar organisms that compete on the same level of organization. Here we begin to outline a mathematical theory that might help to explore how evolution can be constructive, how natural selection can lead from lower to higher levels of organization. We distinguish two fundamental operations, which we call 'staying together' and 'coming together'. Staying together means that individuals form larger units by not separating after reproduction, while coming together means that independent individuals form aggregates. Staying together can lead to specialization and division of labor, but the developmental program must evolve in the basic unit. Coming together can be creative by combining units with different properties. Both operations have been identified in the context of multicellularity, but they have been treated very similarly. Here we point out that staying together and coming together can be found at every level of biological construction and moreover that they face different evolutionary problems. The distinction is particularly clear in the context of cooperation and defection. For staying together the stability of cooperation takes the form of a developmental error threshold, while coming together leads to evolutionary games and requires a mechanism for the evolution of cooperation. We use our models to discuss simple aspects of the evolution of protocells, eukarya, multi-cellularity and animal societies. Copyright © 2012 Elsevier Ltd. All rights reserved.

The genomic and epidemiological dynamics of human influenza A virus.

PubMed

Rambaut, Andrew; Pybus, Oliver G; Nelson, Martha I; Viboud, Cecile; Taubenberger, Jeffery K; Holmes, Edward C

2008-05-29

The evolutionary interaction between influenza A virus and the human immune system, manifest as 'antigenic drift' of the viral haemagglutinin, is one of the best described patterns in molecular evolution. However, little is known about the genome-scale evolutionary dynamics of this pathogen. Similarly, how genomic processes relate to global influenza epidemiology, in which the A/H3N2 and A/H1N1 subtypes co-circulate, is poorly understood. Here through an analysis of 1,302 complete viral genomes sampled from temperate populations in both hemispheres, we show that the genomic evolution of influenza A virus is characterized by a complex interplay between frequent reassortment and periodic selective sweeps. The A/H3N2 and A/H1N1 subtypes exhibit different evolutionary dynamics, with diverse lineages circulating in A/H1N1, indicative of weaker antigenic drift. These results suggest a sink-source model of viral ecology in which new lineages are seeded from a persistent influenza reservoir, which we hypothesize to be located in the tropics, to sink populations in temperate regions.

A High-Resolution Comparative Chromosome Map of Cricetus cricetus and Peromyscus eremicus Reveals the Involvement of Constitutive Heterochromatin in Breakpoint Regions.

PubMed

Vieira-da-Silva, Ana; Louzada, Sandra; Adega, Filomena; Chaves, Raquel

2015-01-01

Compared to humans and other mammals, rodent genomes, specifically Muroidea species, underwent intense chromosome reshuffling in which many complex structural rearrangements occurred. This fact makes them preferential animal models for studying the process of karyotype evolution. Here, we present the first combined chromosome comparative maps between 2 Cricetidae species, Cricetus cricetus and Peromyscus eremicus, and the index species Mus musculus and Rattus norvegicus. Comparative chromosome painting was done using mouse and rat paint probes together with in silico analysis from the Ensembl genome browser database. Hereby, evolutionary events (inter- and intrachromosomal rearrangements) that occurred in C. cricetus and P. eremicus since the putative ancestral Muroidea genome could be inferred, and evolutionary breakpoint regions could be detected. A colocalization of constitutive heterochromatin and evolutionary breakpoint regions in each genome was observed. Our results suggest the involvement of constitutive heterochromatin in karyotype restructuring of these species, despite the different levels of conservation of the C. cricetus (derivative) and P. eremicus (conserved) genomes. © 2015 S. Karger AG, Basel.

Fundamentals and Recent Developments in Approximate Bayesian Computation

PubMed Central

Lintusaari, Jarno; Gutmann, Michael U.; Dutta, Ritabrata; Kaski, Samuel; Corander, Jukka

2017-01-01

Abstract Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference problems, however, only approximate quantitative answers are obtainable. Approximate Bayesian computation (ABC) refers to a family of algorithms for approximate inference that makes a minimal set of assumptions by only requiring that sampling from a model is possible. We explain here the fundamentals of ABC, review the classical algorithms, and highlight recent developments. [ABC; approximate Bayesian computation; Bayesian inference; likelihood-free inference; phylogenetics; simulator-based models; stochastic simulation models; tree-based models.] PMID:28175922

Open Issues in Evolutionary Robotics.

PubMed

Silva, Fernando; Duarte, Miguel; Correia, Luís; Oliveira, Sancho Moura; Christensen, Anders Lyhne

2016-01-01

One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versus evolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1) the bootstrap problem, (2) deception, and (3) the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.

Evolutionary Game Theory Analysis of Tumor Progression

NASA Astrophysics Data System (ADS)

Wu, Amy; Liao, David; Sturm, James; Austin, Robert

2014-03-01

Evolutionary game theory applied to two interacting cell populations can yield quantitative prediction of the future densities of the two cell populations based on the initial interaction terms. We will discuss how in a complex ecology that evolutionary game theory successfully predicts the future densities of strains of stromal and cancer cells (multiple myeloma), and discuss the possible clinical use of such analysis for predicting cancer progression. Supported by the National Science Foundation and the National Cancer Institute.

Forecasting transitions in systems with high-dimensional stochastic complex dynamics: a linear stability analysis of the tangled nature model.

PubMed

Cairoli, Andrea; Piovani, Duccio; Jensen, Henrik Jeldtoft

2014-12-31

We propose a new procedure to monitor and forecast the onset of transitions in high-dimensional complex systems. We describe our procedure by an application to the tangled nature model of evolutionary ecology. The quasistable configurations of the full stochastic dynamics are taken as input for a stability analysis by means of the deterministic mean-field equations. Numerical analysis of the high-dimensional stability matrix allows us to identify unstable directions associated with eigenvalues with a positive real part. The overlap of the instantaneous configuration vector of the full stochastic system with the eigenvectors of the unstable directions of the deterministic mean-field approximation is found to be a good early warning of the transitions occurring intermittently.

Effects of complex life cycles on genetic diversity: cyclical parthenogenesis.

PubMed

Rouger, R; Reichel, K; Malrieu, F; Masson, J P; Stoeckel, S

2016-11-01

Neutral patterns of population genetic diversity in species with complex life cycles are difficult to anticipate. Cyclical parthenogenesis (CP), in which organisms undergo several rounds of clonal reproduction followed by a sexual event, is one such life cycle. Many species, including crop pests (aphids), human parasites (trematodes) or models used in evolutionary science (Daphnia), are cyclical parthenogens. It is therefore crucial to understand the impact of such a life cycle on neutral genetic diversity. In this paper, we describe distributions of genetic diversity under conditions of CP with various clonal phase lengths. Using a Markov chain model of CP for a single locus and individual-based simulations for two loci, our analysis first demonstrates that strong departures from full sexuality are observed after only a few generations of clonality. The convergence towards predictions made under conditions of full clonality during the clonal phase depends on the balance between mutations and genetic drift. Second, the sexual event of CP usually resets the genetic diversity at a single locus towards predictions made under full sexuality. However, this single recombination event is insufficient to reshuffle gametic phases towards full-sexuality predictions. Finally, for similar levels of clonality, CP and acyclic partial clonality (wherein a fixed proportion of individuals are clonally produced within each generation) differentially affect the distribution of genetic diversity. Overall, this work provides solid predictions of neutral genetic diversity that may serve as a null model in detecting the action of common evolutionary or demographic processes in cyclical parthenogens (for example, selection or bottlenecks).

Equilibria, information and frustration in heterogeneous network games with conflicting preferences

NASA Astrophysics Data System (ADS)

Mazzoli, M.; Sánchez, A.

2017-11-01

Interactions between people are the basis on which the structure of our society arises as a complex system and, at the same time, are the starting point of any physical description of it. In the last few years, much theoretical research has addressed this issue by combining the physics of complex networks with a description of interactions in terms of evolutionary game theory. We here take this research a step further by introducing a most salient societal factor such as the individuals’ preferences, a characteristic that is key to understanding much of the social phenomenology these days. We consider a heterogeneous, agent-based model in which agents interact strategically with their neighbors, but their preferences and payoffs for the possible actions differ. We study how such a heterogeneous network behaves under evolutionary dynamics and different strategic interactions, namely coordination games and best shot games. With this model we study the emergence of the equilibria predicted analytically in random graphs under best response dynamics, and we extend this test to unexplored contexts like proportional imitation and scale free networks. We show that some theoretically predicted equilibria do not arise in simulations with incomplete information, and we demonstrate the importance of the graph topology and the payoff function parameters for some games. Finally, we discuss our results with the available experimental evidence on coordination games, showing that our model agrees better with the experiment than standard economic theories, and draw hints as to how to maximize social efficiency in situations of conflicting preferences.

Identification of metapopulation dynamics among Northern Goshawks of the Alexander Archipelago, Alaska, and Coastal British Columbia

USGS Publications Warehouse

Sonsthagen, Sarah A.; McClaren, Erica L.; Doyle, Frank I.; Titus, K.; Sage, George K.; Wilson, Robert E.; Gust, Judy R.; Talbot, Sandra L.

2012-01-01

Northern Goshawks occupying the Alexander Archipelago, Alaska, and coastal British Columbia nest primarily in old-growth and mature forest, which results in spatial heterogeneity in the distribution of individuals across the landscape. We used microsatellite and mitochondrial data to infer genetic structure, gene flow, and fluctuations in population demography through evolutionary time. Patterns in the genetic signatures were used to assess predictions associated with the three population models: panmixia, metapopulation, and isolated populations. Population genetic structure was observed along with asymmetry in gene flow estimates that changed directionality at different temporal scales, consistent with metapopulation model predictions. Therefore, Northern Goshawk assemblages located in the Alexander Archipelago and coastal British Columbia interact through a metapopulation framework, though they may not fit the classic model of a metapopulation. Long-term population sources (coastal mainland British Columbia) and sinks (Revillagigedo and Vancouver islands) were identified. However, there was no trend through evolutionary time in the directionality of dispersal among the remaining assemblages, suggestive of a rescue-effect dynamic. Admiralty, Douglas, and Chichagof island complex appears to be an evolutionarily recent source population in the Alexander Archipelago. In addition, Kupreanof island complex and Kispiox Forest District populations have high dispersal rates to populations in close geographic proximity and potentially serve as local source populations. Metapopulation dynamics occurring in the Alexander Archipelago and coastal British Columbia by Northern Goshawks highlight the importance of both occupied and unoccupied habitats to long-term population persistence of goshawks in this region.

Biodiversity and Topographic Complexity: Modern and Geohistorical Perspectives

PubMed Central

Badgley, Catherine; Smiley, Tara M.; Terry, Rebecca; Davis, Edward B.; DeSantis, Larisa R.G.; Fox, David L.; Hopkins, Samantha S.B.; Jezkova, Tereza; Matocq, Marjorie D.; Matzke, Nick; McGuire, Jenny L.; Mulch, Andreas; Riddle, Brett R.; Roth, V. Louise; Samuels, Joshua X.; Strömberg, Caroline A.E.; Yanites, Brian J.

2018-01-01

Topographically complex regions on land and in the oceans feature hotspots of biodiversity that reflect geological influences on ecological and evolutionary processes. Over geologic time, topographic diversity gradients wax and wane over millions of years, tracking tectonic or climatic history. Topographic diversity gradients from the present day and the past can result from the generation of species by vicariance or from the accumulation of species from dispersal into a region with strong environmental gradients. Biological and geological approaches must be integrated to test alternative models of diversification along topographic gradients. Reciprocal illumination among phylogenetic, phylogeographic, ecological, paleontological, tectonic, and climatic perspectives is an emerging frontier of biogeographic research. PMID:28196688

The Sudbury-Serenitatis analogy and 'so-called' pristine nonmare rocks

NASA Technical Reports Server (NTRS)

Warren, Paul H.

1992-01-01

The Serenitatis Basin is the one lunar basin from which we confidently identify a suite of samples as pieces of the impact melt sheet: the distinctive Apollo 17 noritic breccias. Recent studies of the Sudbury Complex indicate that its 'irruptive' is almost entirely of impact-melt origin, making it the closest terrestrial analog to the Serenitatis melt sheet. Any attempt to model the evolution of the Moon's crust should be compatible with the relatively well-understood Sudbury Complex. However, the Sudbury-Moon analogy might be a misleading oversimplification, if applied too rigidly. The cause of evolutionary differences between the Serenitatis impact melt and the Sudbury impact melt is discussed.

Comparing Evolutionary Programs and Evolutionary Pattern Search Algorithms: A Drug Docking Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1999-02-10

Evolutionary programs (EPs) and evolutionary pattern search algorithms (EPSAS) are two general classes of evolutionary methods for optimizing on continuous domains. The relative performance of these methods has been evaluated on standard global optimization test functions, and these results suggest that EPSAs more robustly converge to near-optimal solutions than EPs. In this paper we evaluate the relative performance of EPSAs and EPs on a real-world application: flexible ligand binding in the Autodock docking software. We compare the performance of these methods on a suite of docking test problems. Our results confirm that EPSAs and EPs have comparable performance, and theymore » suggest that EPSAs may be more robust on larger, more complex problems.« less

Cancer evolution: mathematical models and computational inference.

PubMed

Beerenwinkel, Niko; Schwarz, Roland F; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

Model-based analyses of whole-genome data reveal a complex evolutionary history involving archaic introgression in Central African Pygmies.

PubMed

Hsieh, PingHsun; Woerner, August E; Wall, Jeffrey D; Lachance, Joseph; Tishkoff, Sarah A; Gutenkunst, Ryan N; Hammer, Michael F

2016-03-01

Comparisons of whole-genome sequences from ancient and contemporary samples have pointed to several instances of archaic admixture through interbreeding between the ancestors of modern non-Africans and now extinct hominids such as Neanderthals and Denisovans. One implication of these findings is that some adaptive features in contemporary humans may have entered the population via gene flow with archaic forms in Eurasia. Within Africa, fossil evidence suggests that anatomically modern humans (AMH) and various archaic forms coexisted for much of the last 200,000 yr; however, the absence of ancient DNA in Africa has limited our ability to make a direct comparison between archaic and modern human genomes. Here, we use statistical inference based on high coverage whole-genome data (greater than 60×) from contemporary African Pygmy hunter-gatherers as an alternative means to study the evolutionary history of the genus Homo. Using whole-genome simulations that consider demographic histories that include both isolation and gene flow with neighboring farming populations, our inference method rejects the hypothesis that the ancestors of AMH were genetically isolated in Africa, thus providing the first whole genome-level evidence of African archaic admixture. Our inferences also suggest a complex human evolutionary history in Africa, which involves at least a single admixture event from an unknown archaic population into the ancestors of AMH, likely within the last 30,000 yr. © 2016 Hsieh et al.; Published by Cold Spring Harbor Laboratory Press.

New frontiers in the study of human cultural and genetic evolution.

PubMed

Ross, Cody T; Richerson, Peter J

2014-12-01

In this review, we discuss the dynamic linkages between culture and the genetic evolution of the human species. We begin by briefly describing the framework of gene-culture coevolutionary (or dual-inheritance) models for human evolutionary change. Until recently, the literature on gene-culture coevolution was composed primarily of mathematical models and formalized theory describing the complex dynamics underlying human behavior, adaptation, and technological evolution, but had little empirical support concerning genetics. The rapid progress in the fields of molecular genetics and genomics, however, is now providing the kinds of data needed to produce rich empirical support for gene-culture coevolutionary models. We briefly outline how theoretical and methodological progress in genome sciences has provided ways for the strength of selection on genes to be evaluated, and then outline how evidence of selection on several key genes can be directly linked to human cultural practices. We then describe some exciting new directions in the empirical study of gene-culture coevolution, and conclude with a discussion of the role of gene-culture evolutionary models in the future integration of medical, biological, and social sciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

Storytelling and story testing in domestication.

PubMed

Gerbault, Pascale; Allaby, Robin G; Boivin, Nicole; Rudzinski, Anna; Grimaldi, Ilaria M; Pires, J Chris; Climer Vigueira, Cynthia; Dobney, Keith; Gremillion, Kristen J; Barton, Loukas; Arroyo-Kalin, Manuel; Purugganan, Michael D; Rubio de Casas, Rafael; Bollongino, Ruth; Burger, Joachim; Fuller, Dorian Q; Bradley, Daniel G; Balding, David J; Richerson, Peter J; Gilbert, M Thomas P; Larson, Greger; Thomas, Mark G

2014-04-29

The domestication of plants and animals marks one of the most significant transitions in human, and indeed global, history. Traditionally, study of the domestication process was the exclusive domain of archaeologists and agricultural scientists; today it is an increasingly multidisciplinary enterprise that has come to involve the skills of evolutionary biologists and geneticists. Although the application of new information sources and methodologies has dramatically transformed our ability to study and understand domestication, it has also generated increasingly large and complex datasets, the interpretation of which is not straightforward. In particular, challenges of equifinality, evolutionary variance, and emergence of unexpected or counter-intuitive patterns all face researchers attempting to infer past processes directly from patterns in data. We argue that explicit modeling approaches, drawing upon emerging methodologies in statistics and population genetics, provide a powerful means of addressing these limitations. Modeling also offers an approach to analyzing datasets that avoids conclusions steered by implicit biases, and makes possible the formal integration of different data types. Here we outline some of the modeling approaches most relevant to current problems in domestication research, and demonstrate the ways in which simulation modeling is beginning to reshape our understanding of the domestication process.

Storytelling and story testing in domestication

PubMed Central

Gerbault, Pascale; Allaby, Robin G.; Boivin, Nicole; Rudzinski, Anna; Grimaldi, Ilaria M.; Pires, J. Chris; Climer Vigueira, Cynthia; Dobney, Keith; Gremillion, Kristen J.; Barton, Loukas; Arroyo-Kalin, Manuel; Purugganan, Michael D.; Rubio de Casas, Rafael; Bollongino, Ruth; Burger, Joachim; Fuller, Dorian Q.; Bradley, Daniel G.; Balding, David J.; Richerson, Peter J.; Gilbert, M. Thomas P.; Larson, Greger; Thomas, Mark G.

2014-01-01

The domestication of plants and animals marks one of the most significant transitions in human, and indeed global, history. Traditionally, study of the domestication process was the exclusive domain of archaeologists and agricultural scientists; today it is an increasingly multidisciplinary enterprise that has come to involve the skills of evolutionary biologists and geneticists. Although the application of new information sources and methodologies has dramatically transformed our ability to study and understand domestication, it has also generated increasingly large and complex datasets, the interpretation of which is not straightforward. In particular, challenges of equifinality, evolutionary variance, and emergence of unexpected or counter-intuitive patterns all face researchers attempting to infer past processes directly from patterns in data. We argue that explicit modeling approaches, drawing upon emerging methodologies in statistics and population genetics, provide a powerful means of addressing these limitations. Modeling also offers an approach to analyzing datasets that avoids conclusions steered by implicit biases, and makes possible the formal integration of different data types. Here we outline some of the modeling approaches most relevant to current problems in domestication research, and demonstrate the ways in which simulation modeling is beginning to reshape our understanding of the domestication process. PMID:24753572

Dynamic multipopulation and density dependent evolutionary games related to replicator dynamics. A metasimplex concept.

PubMed

Argasinski, Krzysztof

2006-07-01

This paper contains the basic extensions of classical evolutionary games (multipopulation and density dependent models). It is shown that classical bimatrix approach is inconsistent with other approaches because it does not depend on proportion between populations. The main conclusion is that interspecific proportion parameter is important and must be considered in multipopulation models. The paper provides a synthesis of both extensions (a metasimplex concept) which solves the problem intrinsic in the bimatrix model. It allows us to model interactions among any number of subpopulations including density dependence effects. We prove that all modern approaches to evolutionary games are closely related. All evolutionary models (except classical bimatrix approaches) can be reduced to a single population general model by a simple change of variables. Differences between classic bimatrix evolutionary games and a new model which is dependent on interspecific proportion are shown by examples.

The eIF4F and eIFiso4F Complexes of Plants: An Evolutionary Perspective

PubMed Central

Patrick, Ryan M.; Browning, Karen S.

2012-01-01

Translation initiation in eukaryotes requires a number of initiation factors to recruit the assembled ribosome to mRNA. The eIF4F complex plays a key role in initiation and is a common target point for regulation of protein synthesis. Most work on the translation machinery of plants to date has focused on flowering plants, which have both the eIF4F complex (eIF4E and eIF4G) as well as the plant-specific eIFiso4F complex (eIFiso4E and eIFiso4G). The increasing availability of plant genome sequence data has made it possible to trace the evolutionary history of these two complexes in plants, leading to several interesting discoveries. eIFiso4G is conserved throughout plants, while eIFiso4E only appears with the evolution of flowering plants. The eIF4G N-terminus, which has been difficult to annotate, appears to be well conserved throughout the plant lineage and contains two motifs of unknown function. Comparison of eIFiso4G and eIF4G sequence data suggests conserved features unique to eIFiso4G and eIF4G proteins. These findings have answered some questions about the evolutionary history of the two eIF4F complexes of plants, while raising new ones. PMID:22611336

Theoretical Approaches in Evolutionary Ecology: Environmental Feedback as a Unifying Perspective.

PubMed

Lion, Sébastien

2018-01-01

Evolutionary biology and ecology have a strong theoretical underpinning, and this has fostered a variety of modeling approaches. A major challenge of this theoretical work has been to unravel the tangled feedback loop between ecology and evolution. This has prompted the development of two main classes of models. While quantitative genetics models jointly consider the ecological and evolutionary dynamics of a focal population, a separation of timescales between ecology and evolution is assumed by evolutionary game theory, adaptive dynamics, and inclusive fitness theory. As a result, theoretical evolutionary ecology tends to be divided among different schools of thought, with different toolboxes and motivations. My aim in this synthesis is to highlight the connections between these different approaches and clarify the current state of theory in evolutionary ecology. Central to this approach is to make explicit the dependence on environmental dynamics of the population and evolutionary dynamics, thereby materializing the eco-evolutionary feedback loop. This perspective sheds light on the interplay between environmental feedback and the timescales of ecological and evolutionary processes. I conclude by discussing some potential extensions and challenges to our current theoretical understanding of eco-evolutionary dynamics.

InterEvDock2: an expanded server for protein docking using evolutionary and biological information from homology models and multimeric inputs.

PubMed

Quignot, Chloé; Rey, Julien; Yu, Jinchao; Tufféry, Pierre; Guerois, Raphaël; Andreani, Jessica

2018-05-08

Computational protein docking is a powerful strategy to predict structures of protein-protein interactions and provides crucial insights for the functional characterization of macromolecular cross-talks. We previously developed InterEvDock, a server for ab initio protein docking based on rigid-body sampling followed by consensus scoring using physics-based and statistical potentials, including the InterEvScore function specifically developed to incorporate co-evolutionary information in docking. InterEvDock2 is a major evolution of InterEvDock which allows users to submit input sequences - not only structures - and multimeric inputs and to specify constraints for the pairwise docking process based on previous knowledge about the interaction. For this purpose, we added modules in InterEvDock2 for automatic template search and comparative modeling of the input proteins. The InterEvDock2 pipeline was benchmarked on 812 complexes for which unbound homology models of the two partners and co-evolutionary information are available in the PPI4DOCK database. InterEvDock2 identified a correct model among the top 10 consensus in 29% of these cases (compared to 15-24% for individual scoring functions) and at least one correct interface residue among 10 predicted in 91% of these cases. InterEvDock2 is thus a unique protein docking server, designed to be useful for the experimental biology community. The InterEvDock2 web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock2/.

Interspecific Tests of Allelism Reveal the Evolutionary Timing and Pattern of Accumulation of Reproductive Isolation Mutations

PubMed Central

Sherman, Natasha A.; Victorine, Anna; Wang, Richard J.; Moyle, Leonie C.

2014-01-01

Despite extensive theory, little is known about the empirical accumulation and evolutionary timing of mutations that contribute to speciation. Here we combined QTL (Quantitative Trait Loci) analyses of reproductive isolation, with information on species evolutionary relationships, to reconstruct the order and timing of mutations contributing to reproductive isolation between three plant (Solanum) species. To evaluate whether reproductive isolation QTL that appear to coincide in more than one species pair are homologous, we used cross-specific tests of allelism and found evidence for both homologous and lineage-specific (non-homologous) alleles at these co-localized loci. These data, along with isolation QTL unique to single species pairs, indicate that >85% of isolation-causing mutations arose later in the history of divergence between species. Phylogenetically explicit analyses of these data support non-linear models of accumulation of hybrid incompatibility, although the specific best-fit model differs between seed (pairwise interactions) and pollen (multi-locus interactions) sterility traits. Our findings corroborate theory that predicts an acceleration (‘snowballing’) in the accumulation of isolation loci as lineages progressively diverge, and suggest different underlying genetic bases for pollen versus seed sterility. Pollen sterility in particular appears to be due to complex genetic interactions, and we show this is consistent with a snowball model where later arising mutations are more likely to be involved in pairwise or multi-locus interactions that specifically involve ancestral alleles, compared to earlier arising mutations. PMID:25211473

Evolutionary Trends and the Salience Bias (with Apologies to Oil Tankers, Karl Marx, and Others).

ERIC Educational Resources Information Center

McShea, Daniel W.

1994-01-01

Examines evolutionary trends, specifically trends in size, complexity, and fitness. Notes that documentation of these trends consists of either long lists of cases, or descriptions of a small number of salient cases. Proposes the use of random samples to avoid this "saliency bias." (SR)

Unto Others: Illustrating the Human Capacity for Cooperation

ERIC Educational Resources Information Center

Morris, J. Andrew; Urbanski, John; Hunt, Jason

2011-01-01

Research in both evolutionary economics and evolutionary psychology provides strong evidence that human behavior can be, and is, a complex mix of hedonism and altruism with a strong inclination toward cooperation under certain conditions. In this article, behavioral assumptions made in mainstream business theory are compared and contrasted with…

Grand Views of Evolution.

PubMed

de Vladar, Harold P; Santos, Mauro; Szathmáry, Eörs

2017-05-01

Despite major advances in evolutionary theories, some aspects of evolution remain neglected: whether evolution: would come to a halt without abiotic change; is unbounded and open-ended; or is progressive and something beyond fitness is maximized. Here, we discuss some models of ecology and evolution and argue that ecological change, resulting in Red Queen dynamics, facilitates (but does not ensure) innovation. We distinguish three forms of open-endedness. In weak open-endedness, novel phenotypes can occur indefinitely. Strong open-endedness requires the continual appearance of evolutionary novelties and/or innovations. Ultimate open-endedness entails an indefinite increase in complexity, which requires unlimited heredity. Open-ended innovation needs exaptations that generate novel niches. This can result in new traits and new rules as the dynamics unfolds, suggesting that evolution is not fully algorithmic. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evolutionary history of Leishmania killicki (synonymous Leishmania tropica) and taxonomic implications.

PubMed

Chaara, Dhekra; Ravel, Christophe; Bañuls, Anne- Laure; Haouas, Najoua; Lami, Patrick; Talignani, Loïc; El Baidouri, Fouad; Jaouadi, Kaouther; Harrat, Zoubir; Dedet, Jean-Pierre; Babba, Hamouda; Pratlong, Francine

2015-04-01

The taxonomic status of Leishmania (L.) killicki, a parasite that causes chronic cutaneous leishmaniasis, is not well defined yet. Indeed, some researchers suggested that this taxon could be included in the L. tropica complex, whereas others considered it as a distinct phylogenetic complex. To try to solve this taxonomic issue we carried out a detailed study on the evolutionary history of L. killicki relative to L. tropica. Thirty-five L. killicki and 25 L. tropica strains isolated from humans and originating from several countries were characterized using the MultiLocus Enzyme Electrophoresis (MLEE) and the MultiLocus Sequence Typing (MLST) approaches. The results of the genetic and phylogenetic analyses strongly support the hypothesis that L. killicki belongs to the L. tropica complex. Our data suggest that L. killicki emerged from a single founder event and that it evolved independently from L. tropica. However, they do not validate the hypothesis that L. killicki is a distinct complex. Therefore, we suggest naming this taxon L. killicki (synonymous L. tropica) until further epidemiological and phylogenetic studies justify the L. killicki denomination. This study provides taxonomic and phylogenetic information on L. killicki and improves our knowledge on the evolutionary history of this taxon.

AIAA Aerospace America Magazine - Year in Review Article, 2010

NASA Technical Reports Server (NTRS)

Figueroa, Fernando

2010-01-01

NASA Stennis Space Center has implemented a pilot operational Integrated System Health Management (ISHM) capability. The implementation was done for the E-2 Rocket Engine Test Stand and a Chemical Steam Generator (CSG) test article; and validated during operational testing. The CSG test program is a risk mitigation activity to support building of the new A-3 Test Stand, which will be a highly complex facility for testing of engines in high altitude conditions. The foundation of the ISHM capability are knowledge-based integrated domain models for the test stand and CSG, with physical and model-based elements represented by objects the domain models enable modular and evolutionary ISHM functionality.

Genetic and morphological analyses indicate that the Australian endemic scorpion Urodacus yaschenkoi (Scorpiones: Urodacidae) is a species complex

PubMed Central

Luna-Ramirez, Karen; Miller, Adam D.

2017-01-01

Background Australian scorpions have received far less attention from researchers than their overseas counterparts. Here we provide the first insight into the molecular variation and evolutionary history of the endemic Australian scorpion Urodacus yaschenkoi. Also known as the inland robust scorpion, it is widely distributed throughout arid zones of the continent and is emerging as a model organism in biomedical research due to the chemical nature of its venom. Methods We employed Bayesian Inference (BI) methods for the phylogenetic reconstructions and divergence dating among lineages, using unique haplotype sequences from two mitochondrial loci (COXI, 16S) and one nuclear locus (28S). We also implemented two DNA taxonomy approaches (GMYC and PTP/dPTP) to evaluate the presence of cryptic species. Linear Discriminant Analysis was used to test whether the linear combination of 21 variables (ratios of morphological measurements) can predict individual’s membership to a putative species. Results Genetic and morphological data suggest that U. yaschenkoi is a species complex. High statistical support for the monophyly of several divergent lineages was found both at the mitochondrial loci and at a nuclear locus. The extent of mitochondrial divergence between these lineages exceeds estimates of interspecific divergence reported for other scorpion groups. The GMYC model and the PTP/bPTP approach identified major lineages and several sub-lineages as putative species. Ratios of several traits that approximate body shape had a strong predictive power (83–100%) in discriminating two major molecular lineages. A time-calibrated phylogeny dates the early divergence at the onset of continental-wide aridification in late Miocene and Pliocene, with finer-scale phylogeographic patterns emerging during the Pleistocene. This structuring dynamics is congruent with the diversification history of other fauna of the Australian arid zones. Discussion Our results indicate that the taxonomic status of U. yaschenkoi requires revision, and we provide recommendations for such future efforts. A complex evolutionary history and extensive diversity highlights the importance of conserving U. yaschenkoi populations from different Australian arid zones in order to preserve patterns of endemism and evolutionary potential. PMID:28123903

Biology Needs Evolutionary Software Tools: Let’s Build Them Right

PubMed Central

Team, Galaxy; Goecks, Jeremy; Taylor, James

2018-01-01

Abstract Research in population genetics and evolutionary biology has always provided a computational backbone for life sciences as a whole. Today evolutionary and population biology reasoning are essential for interpretation of large complex datasets that are characteristic of all domains of today’s life sciences ranging from cancer biology to microbial ecology. This situation makes algorithms and software tools developed by our community more important than ever before. This means that we, developers of software tool for molecular evolutionary analyses, now have a shared responsibility to make these tools accessible using modern technological developments as well as provide adequate documentation and training. PMID:29688462

AFRICAN GENETIC DIVERSITY: Implications for Human Demographic History, Modern Human Origins, and Complex Disease Mapping

PubMed Central

Campbell, Michael C.; Tishkoff, Sarah A.

2010-01-01

Comparative studies of ethnically diverse human populations, particularly in Africa, are important for reconstructing human evolutionary history and for understanding the genetic basis of phenotypic adaptation and complex disease. African populations are characterized by greater levels of genetic diversity, extensive population substructure, and less linkage disequilibrium (LD) among loci compared to non-African populations. Africans also possess a number of genetic adaptations that have evolved in response to diverse climates and diets, as well as exposure to infectious disease. This review summarizes patterns and the evolutionary origins of genetic diversity present in African populations, as well as their implications for the mapping of complex traits, including disease susceptibility. PMID:18593304

Impact of tree priors in species delimitation and phylogenetics of the genus Oligoryzomys (Rodentia: Cricetidae).

PubMed

da Cruz, Marcos de O R; Weksler, Marcelo

2018-02-01

The use of genetic data and tree-based algorithms to delimit evolutionary lineages is becoming an important practice in taxonomic identification, especially in morphologically cryptic groups. The effects of different phylogenetic and/or coalescent models in the analyses of species delimitation, however, are not clear. In this paper, we assess the impact of different evolutionary priors in phylogenetic estimation, species delimitation, and molecular dating of the genus Oligoryzomys (Mammalia: Rodentia), a group with complex taxonomy and morphological cryptic species. Phylogenetic and coalescent analyses included 20 of the 24 recognized species of the genus, comprising of 416 Cytochrome b sequences, 26 Cytochrome c oxidase I sequences, and 27 Beta-Fibrinogen Intron 7 sequences. For species delimitation, we employed the General Mixed Yule Coalescent (GMYC) and Bayesian Poisson tree processes (bPTP) analyses, and contrasted 4 genealogical and phylogenetic models: Pure-birth (Yule), Constant Population Size Coalescent, Multiple Species Coalescent, and a mixed Yule-Coalescent model. GMYC analyses of trees from different genealogical models resulted in similar species delimitation and phylogenetic relationships, with incongruence restricted to areas of poor nodal support. bPTP results, however, significantly differed from GMYC for 5 taxa. Oligoryzomys early diversification was estimated to have occurred in the Early Pleistocene, between 0.7 and 2.6 MYA. The mixed Yule-Coalescent model, however, recovered younger dating estimates for Oligoryzomys diversification, and for the threshold for the speciation-coalescent horizon in GMYC. Eight of the 20 included Oligoryzomys species were identified as having two or more independent evolutionary units, indicating that current taxonomy of Oligoryzomys is still unsettled. Copyright © 2017 Elsevier Inc. All rights reserved.

Evolutionary Artificial Neural Network Weight Tuning to Optimize Decision Making for an Abstract Game

DTIC Science & Technology

2010-03-01

separate LoA heuristic. If any of the examined heuristics produced competitive player , then the final measurement was a success . Barring that, a...if offline training actually results in a successful player . Whereas offline learning plays many games and then trains as many networks as desired...a competitive Lines of Action player , shedding light on the difficulty of developing a neural network to model such a large and complex solution

Evolutionary perspectives on wildlife disease: concepts and applications

PubMed Central

Vander Wal, Eric; Garant, Dany; Pelletier, Fanie

2014-01-01

Wildlife disease has the potential to cause significant ecological, socioeconomic, and health impacts. As a result, all tools available need to be employed when host–pathogen dynamics merit conservation or management interventions. Evolutionary principles, such as evolutionary history, phenotypic and genetic variation, and selection, have the potential to unravel many of the complex ecological realities of infectious disease in the wild. Despite this, their application to wildlife disease ecology and management remains in its infancy. In this article, we outline the impetus behind applying evolutionary principles to disease ecology and management issues in the wild. We then introduce articles from this special issue on Evolutionary Perspectives on Wildlife Disease: Concepts and Applications, outlining how each is exemplar of a practical wildlife disease challenge that can be enlightened by applied evolution. Ultimately, we aim to bring new insights to wildlife disease ecology and its management using tools and techniques commonly employed in evolutionary ecology. PMID:25469154

Probing binding hot spots at protein-RNA recognition sites.

PubMed

Barik, Amita; Nithin, Chandran; Karampudi, Naga Bhushana Rao; Mukherjee, Sunandan; Bahadur, Ranjit Prasad

2016-01-29

We use evolutionary conservation derived from structure alignment of polypeptide sequences along with structural and physicochemical attributes of protein-RNA interfaces to probe the binding hot spots at protein-RNA recognition sites. We find that the degree of conservation varies across the RNA binding proteins; some evolve rapidly compared to others. Additionally, irrespective of the structural class of the complexes, residues at the RNA binding sites are evolutionary better conserved than those at the solvent exposed surfaces. For recognitions involving duplex RNA, residues interacting with the major groove are better conserved than those interacting with the minor groove. We identify multi-interface residues participating simultaneously in protein-protein and protein-RNA interfaces in complexes where more than one polypeptide is involved in RNA recognition, and show that they are better conserved compared to any other RNA binding residues. We find that the residues at water preservation site are better conserved than those at hydrated or at dehydrated sites. Finally, we develop a Random Forests model using structural and physicochemical attributes for predicting binding hot spots. The model accurately predicts 80% of the instances of experimental ΔΔG values in a particular class, and provides a stepping-stone towards the engineering of protein-RNA recognition sites with desired affinity. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

How Good Are Statistical Models at Approximating Complex Fitness Landscapes?

PubMed Central

du Plessis, Louis; Leventhal, Gabriel E.; Bonhoeffer, Sebastian

2016-01-01

Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564

Unity and disunity in evolutionary sciences: process-based analogies open common research avenues for biology and linguistics.

PubMed

List, Johann-Mattis; Pathmanathan, Jananan Sylvestre; Lopez, Philippe; Bapteste, Eric

2016-08-20

For a long time biologists and linguists have been noticing surprising similarities between the evolution of life forms and languages. Most of the proposed analogies have been rejected. Some, however, have persisted, and some even turned out to be fruitful, inspiring the transfer of methods and models between biology and linguistics up to today. Most proposed analogies were based on a comparison of the research objects rather than the processes that shaped their evolution. Focusing on process-based analogies, however, has the advantage of minimizing the risk of overstating similarities, while at the same time reflecting the common strategy to use processes to explain the evolution of complexity in both fields. We compared important evolutionary processes in biology and linguistics and identified processes specific to only one of the two disciplines as well as processes which seem to be analogous, potentially reflecting core evolutionary processes. These new process-based analogies support novel methodological transfer, expanding the application range of biological methods to the field of historical linguistics. We illustrate this by showing (i) how methods dealing with incomplete lineage sorting offer an introgression-free framework to analyze highly mosaic word distributions across languages; (ii) how sequence similarity networks can be used to identify composite and borrowed words across different languages; (iii) how research on partial homology can inspire new methods and models in both fields; and (iv) how constructive neutral evolution provides an original framework for analyzing convergent evolution in languages resulting from common descent (Sapir's drift). Apart from new analogies between evolutionary processes, we also identified processes which are specific to either biology or linguistics. This shows that general evolution cannot be studied from within one discipline alone. In order to get a full picture of evolution, biologists and linguists need to complement their studies, trying to identify cross-disciplinary and discipline-specific evolutionary processes. The fact that we found many process-based analogies favoring transfer from biology to linguistics further shows that certain biological methods and models have a broader scope than previously recognized. This opens fruitful paths for collaboration between the two disciplines. This article was reviewed by W. Ford Doolittle and Eugene V. Koonin.

Genes, communities & invasive species: understanding the ecological and evolutionary dynamics of host-pathogen interactions.

PubMed

Burdon, J J; Thrall, P H; Ericson, L

2013-08-01

Reciprocal interactions between hosts and pathogens drive ecological, epidemiological and co-evolutionary trajectories, resulting in complex patterns of diversity at population, species and community levels. Recent results confirm the importance of negative frequency-dependent rather than 'arms-race' processes in the evolution of individual host-pathogen associations. At the community level, complex relationships between species abundance and diversity dampen or alter pathogen impacts. Invasive pathogens challenge these controls reflecting the earliest stages of evolutionary associations (akin to arms-race) where disease effects may be so great that they overwhelm the host's and community's ability to respond. Viewing these different stabilization/destabilization phases as a continuum provides a valuable perspective to assessment of the role of genetics and ecology in the dynamics of both natural and invasive host-pathogen associations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Social traits, social networks and evolutionary biology.

PubMed

Fisher, D N; McAdam, A G

2017-12-01

The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals' network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group-level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic effects) provides the potential to understand how entire networks of social interactions in populations influence phenotypes and predict how these traits may evolve. By theoretical integration of social network analysis and quantitative genetics, we hope to identify areas of compatibility and incompatibility and to direct research efforts towards the most promising areas. Continuing this synthesis could provide important insights into the evolution of traits expressed in a social context and the evolutionary consequences of complex and nuanced social phenotypes. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Structure-based Markov random field model for representing evolutionary constraints on functional sites.

PubMed

Jeong, Chan-Seok; Kim, Dongsup

2016-02-24

Elucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure. In this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time. The results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.

Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273

Approaches to understanding the impact of life-history features on plant-pathogen co-evolutionary dynamics

Treesearch

Jeremy J. Burdon; Peter H. Thrall; Adnane Nemri

2012-01-01

Natural plant-pathogen associations are complex interactions in which the interplay of environment, host, and pathogen factors results in spatially heterogeneous ecological and epidemiological dynamics. The evolutionary patterns that result from the interaction of these factors are still relatively poorly understood. Recently, integration of the appropriate spatial and...

Memetic Algorithms, Domain Knowledge, and Financial Investing

ERIC Educational Resources Information Center

Du, Jie

2012-01-01

While the question of how to use human knowledge to guide evolutionary search is long-recognized, much remains to be done to answer this question adequately. This dissertation aims to further answer this question by exploring the role of domain knowledge in evolutionary computation as applied to real-world, complex problems, such as financial…

Finding a common path: predicting gene function using inferred evolutionary trees.

PubMed

Reynolds, Kimberly A

2014-07-14

Reporting in Cell, Li and colleagues (2014) describe an innovative method to functionally classify genes using evolutionary information. This approach demonstrates broad utility for eukaryotic gene annotation and suggests an intriguing new decomposition of pathways and complexes into evolutionarily conserved modules. Copyright © 2014 Elsevier Inc. All rights reserved.

Genomic signature of natural and anthropogenic stress in wild populations of the waterflea Daphnia magna: validation in space, time and experimental evolution.

PubMed

Orsini, Luisa; Spanier, Katina I; DE Meester, Luc

2012-05-01

Natural populations are confronted with multiple selection pressures resulting in a mosaic of environmental stressors at the landscape level. Identifying the genetic underpinning of adaptation to these complex selection environments and assigning causes of natural selection within multidimensional selection regimes in the wild is challenging. The water flea Daphnia is a renowned ecological model system with its well-documented ecology, the possibility to analyse subfossil dormant egg banks and the short generation time allowing an experimental evolution approach. Capitalizing on the strengths of this model system, we here link candidate genome regions to three selection pressures, known to induce micro-evolutionary responses in Daphnia magna: fish predation, parasitism and land use. Using a genome scan approach in space, time and experimental evolution trials, we provide solid evidence of selection at the genome level under well-characterized environmental gradients in the wild and identify candidate genes linked to the three environmental stressors. Our study reveals differential selection at the genome level in Daphnia populations and provides evidence for repeatable patterns of local adaptation in a geographic mosaic of environmental stressors fuelled by standing genetic variation. Our results imply high evolutionary potential of local populations, which is relevant to understand the dynamics of trait changes in natural populations and their impact on community and ecosystem responses through eco-evolutionary feedbacks. © 2012 Blackwell Publishing Ltd.

Visual modelling suggests a weak relationship between the evolution of ultraviolet vision and plumage coloration in birds.

PubMed

Lind, O; Delhey, K

2015-03-01

Birds have sophisticated colour vision mediated by four cone types that cover a wide visual spectrum including ultraviolet (UV) wavelengths. Many birds have modest UV sensitivity provided by violet-sensitive (VS) cones with sensitivity maxima between 400 and 425 nm. However, some birds have evolved higher UV sensitivity and a larger visual spectrum given by UV-sensitive (UVS) cones maximally sensitive at 360-370 nm. The reasons for VS-UVS transitions and their relationship to visual ecology remain unclear. It has been hypothesized that the evolution of UVS-cone vision is linked to plumage colours so that visual sensitivity and feather coloration are 'matched'. This leads to the specific prediction that UVS-cone vision enhances the discrimination of plumage colours of UVS birds while such an advantage is absent or less pronounced for VS-bird coloration. We test this hypothesis using knowledge of the complex distribution of UVS cones among birds combined with mathematical modelling of colour discrimination during different viewing conditions. We find no support for the hypothesis, which, combined with previous studies, suggests only a weak relationship between UVS-cone vision and plumage colour evolution. Instead, we suggest that UVS-cone vision generally favours colour discrimination, which creates a nonspecific selection pressure for the evolution of UVS cones. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Neuroendocrine-Immune Circuits, Phenotypes, and Interactions

PubMed Central

Ashley, Noah T.; Demas, Gregory E.

2016-01-01

Multidirectional interactions among the immune, endocrine, and nervous systems have been demonstrated in humans and non-human animal models for many decades by the biomedical community, but ecological and evolutionary perspectives are lacking. Neuroendocrine-immune interactions can be conceptualized using a series of feedback loops, which culminate into distinct neuroendocrine-immune phenotypes. Behavior can exert profound influences on these phenotypes, which can in turn reciprocally modulate behavior. For example, the behavioral aspects of reproduction, including courtship, aggression, mate selection and parental behaviors can impinge upon neuroendocrine-immune interactions. One classic example is the immunocompetence handicap hypothesis (ICHH), which proposes that steroid hormones act as mediators of traits important for female choice while suppressing the immune system. Reciprocally, neuroendocrine-immune pathways can promote the development of altered behavioral states, such as sickness behavior. Understanding the energetic signals that mediate neuroendocrine-immune crosstalk is an active area of research. Although the field of psychoneuroimmunology (PNI) has begun to explore this crosstalk from a biomedical standpoint, the neuroendocrine-immune-behavior nexus has been relatively underappreciated in comparative species. The field of ecoimmunology, while traditionally emphasizing the study of non-model systems from an ecological evolutionary perspective, often under natural conditions, has focused less on the physiological mechanisms underlying behavioral responses. This review summarizes neuroendocrine-immune interactions using a comparative framework to understand the ecological and evolutionary forces that shape these complex physiological interactions. PMID:27765499

Neuroendocrine-immune circuits, phenotypes, and interactions.

PubMed

Ashley, Noah T; Demas, Gregory E

2017-01-01

Multidirectional interactions among the immune, endocrine, and nervous systems have been demonstrated in humans and non-human animal models for many decades by the biomedical community, but ecological and evolutionary perspectives are lacking. Neuroendocrine-immune interactions can be conceptualized using a series of feedback loops, which culminate into distinct neuroendocrine-immune phenotypes. Behavior can exert profound influences on these phenotypes, which can in turn reciprocally modulate behavior. For example, the behavioral aspects of reproduction, including courtship, aggression, mate selection and parental behaviors can impinge upon neuroendocrine-immune interactions. One classic example is the immunocompetence handicap hypothesis (ICHH), which proposes that steroid hormones act as mediators of traits important for female choice while suppressing the immune system. Reciprocally, neuroendocrine-immune pathways can promote the development of altered behavioral states, such as sickness behavior. Understanding the energetic signals that mediate neuroendocrine-immune crosstalk is an active area of research. Although the field of psychoneuroimmunology (PNI) has begun to explore this crosstalk from a biomedical standpoint, the neuroendocrine-immune-behavior nexus has been relatively underappreciated in comparative species. The field of ecoimmunology, while traditionally emphasizing the study of non-model systems from an ecological evolutionary perspective, often under natural conditions, has focused less on the physiological mechanisms underlying behavioral responses. This review summarizes neuroendocrine-immune interactions using a comparative framework to understand the ecological and evolutionary forces that shape these complex physiological interactions. Copyright © 2016 Elsevier Inc. All rights reserved.

BrassiBase: introduction to a novel knowledge database on Brassicaceae evolution.

PubMed

Kiefer, Markus; Schmickl, Roswitha; German, Dmitry A; Mandáková, Terezie; Lysak, Martin A; Al-Shehbaz, Ihsan A; Franzke, Andreas; Mummenhoff, Klaus; Stamatakis, Alexandros; Koch, Marcus A

2014-01-01

The Brassicaceae family (mustards or crucifers) includes Arabidopsis thaliana as one of the most important model species in plant biology and a number of important crop plants such as the various Brassica species (e.g. cabbage, canola and mustard). Moreover, the family comprises an increasing number of species that serve as study systems in many fields of plant science and evolutionary research. However, the systematics and taxonomy of the family are very complex and access to scientifically valuable and reliable information linked to species and genus names and its interpretation are often difficult. BrassiBase is a continuously developing and growing knowledge database (http://brassibase.cos.uni-heidelberg.de) that aims at providing direct access to many different types of information ranging from taxonomy and systematics to phylo- and cytogenetics. Providing critically revised key information, the database intends to optimize comparative evolutionary research in this family and supports the introduction of the Brassicaceae as the model family for evolutionary biology and plant sciences. Some features that should help to accomplish these goals within a comprehensive taxonomic framework have now been implemented in the new version 1.1.9. A 'Phylogenetic Placement Tool' should help to identify critical accessions and germplasm and provide a first visualization of phylogenetic relationships. The 'Cytogenetics Tool' provides in-depth information on genome sizes, chromosome numbers and polyploidy, and sets this information into a Brassicaceae-wide context.

Three-dimensional deformation response of a NiTi shape memory helical-coil actuator during thermomechanical cycling: experimentally validated numerical model

NASA Astrophysics Data System (ADS)

Dhakal, B.; Nicholson, D. E.; Saleeb, A. F.; Padula, S. A., II; Vaidyanathan, R.

2016-09-01

Shape memory alloy (SMA) actuators often operate under a complex state of stress for an extended number of thermomechanical cycles in many aerospace and engineering applications. Hence, it becomes important to account for multi-axial stress states and deformation characteristics (which evolve with thermomechanical cycling) when calibrating any SMA model for implementation in large-scale simulation of actuators. To this end, the present work is focused on the experimental validation of an SMA model calibrated for the transient and cyclic evolutionary behavior of shape memory Ni49.9Ti50.1, for the actuation of axially loaded helical-coil springs. The approach requires both experimental and computational aspects to appropriately assess the thermomechanical response of these multi-dimensional structures. As such, an instrumented and controlled experimental setup was assembled to obtain temperature, torque, degree of twist and extension, while controlling end constraints during heating and cooling of an SMA spring under a constant externally applied axial load. The computational component assesses the capabilities of a general, multi-axial, SMA material-modeling framework, calibrated for Ni49.9Ti50.1 with regard to its usefulness in the simulation of SMA helical-coil spring actuators. Axial extension, being the primary response, was examined on an axially-loaded spring with multiple active coils. Two different conditions of end boundary constraint were investigated in both the numerical simulations as well as the validation experiments: Case (1) where the loading end is restrained against twist (and the resulting torque measured as the secondary response) and Case (2) where the loading end is free to twist (and the degree of twist measured as the secondary response). The present study focuses on the transient and evolutionary response associated with the initial isothermal loading and the subsequent thermal cycles under applied constant axial load. The experimental results for the helical-coil actuator under two different boundary conditions are found to be within error to their counterparts in the numerical simulations. The numerical simulation and the experimental validation demonstrate similar transient and evolutionary behavior in the deformation response under the complex, inhomogeneous, multi-axial stress-state and large deformations of the helical-coil actuator. This response, although substantially different in magnitude, exhibited similar evolutionary characteristics to the simple, uniaxial, homogeneous, stress-state of the isobaric tensile tests results used for the model calibration. There was no significant difference in the axial displacement (primary response) magnitudes observed between Cases (1) and (2) for the number of cycles investigated here. The simulated secondary responses of the two cases evolved in a similar manner when compared to the experimental validation of the respective cases.

High Genetic Diversity and Distinctiveness of Rear-Edge Climate Relicts Maintained by Ancient Tetraploidisation for Alnus glutinosa

PubMed Central

Lepais, Olivier; Muller, Serge D.; Ben Saad-Limam, Samia; Benslama, Mohamed; Rhazi, Laila; Belouahem-Abed, Djamila; Daoud-Bouattour, Amina; Gammar, Amor Mokhtar; Ghrabi-Gammar, Zeineb; Bacles, Cécile Fanny Emilie

2013-01-01

Populations located at the rear-edge of a species’ distribution may have disproportionate ecological and evolutionary importance for biodiversity conservation in a changing global environment. Yet genetic studies of such populations remain rare. This study investigates the evolutionary history of North-African low latitude marginal populations of Alnus glutinosa Gaertn., a European tree species that plays a significant ecological role as a keystone of riparian ecosystems. We genotyped 551 adults from 19 populations located across North Africa at 12 microsatellite loci and applied a coalescent-based simulation approach to reconstruct the demographic and evolutionary history of these populations. Surprisingly, Moroccan trees were tetraploids demonstrating a strong distinctiveness of these populations within a species otherwise known as diploid. Best-fitting models of demographic reconstruction revealed the relict nature of Moroccan populations that were found to have withstood past climate change events and to be much older than Algerian and Tunisian populations. This study highlights the complex demographic history that can be encountered in rear-edge distribution margins that here consist of both old stable climate relict and more recent populations, distinctively diverse genetically both quantitatively and qualitatively. We emphasize the high evolutionary and conservation value of marginal rear-edge populations of a keystone riparian species in the context of on-going climate change in the Mediterranean region. PMID:24098677

Evolution of SH2 domains and phosphotyrosine signalling networks

PubMed Central

Liu, Bernard A.; Nash, Piers D.

2012-01-01

Src homology 2 (SH2) domains mediate selective protein–protein interactions with tyrosine phosphorylated proteins, and in doing so define specificity of phosphotyrosine (pTyr) signalling networks. SH2 domains and protein-tyrosine phosphatases expand alongside protein-tyrosine kinases (PTKs) to coordinate cellular and organismal complexity in the evolution of the unikont branch of the eukaryotes. Examination of conserved families of PTKs and SH2 domain proteins provides fiduciary marks that trace the evolutionary landscape for the development of complex cellular systems in the proto-metazoan and metazoan lineages. The evolutionary provenance of conserved SH2 and PTK families reveals the mechanisms by which diversity is achieved through adaptations in tissue-specific gene transcription, altered ligand binding, insertions of linear motifs and the gain or loss of domains following gene duplication. We discuss mechanisms by which pTyr-mediated signalling networks evolve through the development of novel and expanded families of SH2 domain proteins and the elaboration of connections between pTyr-signalling proteins. These changes underlie the variety of general and specific signalling networks that give rise to tissue-specific functions and increasingly complex developmental programmes. Examination of SH2 domains from an evolutionary perspective provides insight into the process by which evolutionary expansion and modification of molecular protein interaction domain proteins permits the development of novel protein-interaction networks and accommodates adaptation of signalling networks. PMID:22889907

Phylodynamics and evolutionary epidemiology of African swine fever p72-CVR genes in Eurasia and Africa.

PubMed

Alkhamis, Moh A; Gallardo, Carmina; Jurado, Cristina; Soler, Alejandro; Arias, Marisa; Sánchez-Vizcaíno, José M

2018-01-01

African swine fever (ASF) is a complex infectious disease of swine that constitutes devastating impacts on animal health and the world economy. Here, we investigated the evolutionary epidemiology of ASF virus (ASFV) in Eurasia and Africa using the concatenated gene sequences of the viral protein 72 and the central variable region of isolates collected between 1960 and 2015. We used Bayesian phylodynamic models to reconstruct the evolutionary history of the virus, to identify virus population demographics and to quantify dispersal patterns between host species. Results suggest that ASFV exhibited a significantly high evolutionary rate and population growth through time since its divergence in the 18th century from East Africa, with no signs of decline till recent years. This increase corresponds to the growing pig trade activities between continents during the 19th century, and may be attributed to an evolutionary drift that resulted from either continuous circulation or maintenance of the virus within Africa and Eurasia. Furthermore, results implicate wild suids as the ancestral host species (root state posterior probability = 0.87) for ASFV in the early 1700s in Africa. Moreover, results indicate the transmission cycle between wild suids and pigs is an important cycle for ASFV spread and maintenance in pig populations, while ticks are an important natural reservoir that can facilitate ASFV spread and maintenance in wild swine populations. We illustrated the prospects of phylodynamic methods in improving risk-based surveillance, support of effective animal health policies, and epidemic preparedness in countries at high risk of ASFV incursion.

Bayesian molecular dating: opening up the black box.

PubMed

Bromham, Lindell; Duchêne, Sebastián; Hua, Xia; Ritchie, Andrew M; Duchêne, David A; Ho, Simon Y W

2018-05-01

Molecular dating analyses allow evolutionary timescales to be estimated from genetic data, offering an unprecedented capacity for investigating the evolutionary past of all species. These methods require us to make assumptions about the relationship between genetic change and evolutionary time, often referred to as a 'molecular clock'. Although initially regarded with scepticism, molecular dating has now been adopted in many areas of biology. This broad uptake has been due partly to the development of Bayesian methods that allow complex aspects of molecular evolution, such as variation in rates of change across lineages, to be taken into account. But in order to do this, Bayesian dating methods rely on a range of assumptions about the evolutionary process, which vary in their degree of biological realism and empirical support. These assumptions can have substantial impacts on the estimates produced by molecular dating analyses. The aim of this review is to open the 'black box' of Bayesian molecular dating and have a look at the machinery inside. We explain the components of these dating methods, the important decisions that researchers must make in their analyses, and the factors that need to be considered when interpreting results. We illustrate the effects that the choices of different models and priors can have on the outcome of the analysis, and suggest ways to explore these impacts. We describe some major research directions that may improve the reliability of Bayesian dating. The goal of our review is to help researchers to make informed choices when using Bayesian phylogenetic methods to estimate evolutionary rates and timescales. © 2017 Cambridge Philosophical Society.

Testing for Independence between Evolutionary Processes.

PubMed

Behdenna, Abdelkader; Pothier, Joël; Abby, Sophie S; Lambert, Amaury; Achaz, Guillaume

2016-09-01

Evolutionary events co-occurring along phylogenetic trees usually point to complex adaptive phenomena, sometimes implicating epistasis. While a number of methods have been developed to account for co-occurrence of events on the same internal or external branch of an evolutionary tree, there is a need to account for the larger diversity of possible relative positions of events in a tree. Here we propose a method to quantify to what extent two or more evolutionary events are associated on a phylogenetic tree. The method is applicable to any discrete character, like substitutions within a coding sequence or gains/losses of a biological function. Our method uses a general approach to statistically test for significant associations between events along the tree, which encompasses both events inseparable on the same branch, and events genealogically ordered on different branches. It assumes that the phylogeny and themapping of branches is known without errors. We address this problem from the statistical viewpoint by a linear algebra representation of the localization of the evolutionary events on the tree.We compute the full probability distribution of the number of paired events occurring in the same branch or in different branches of the tree, under a null model of independence where each type of event occurs at a constant rate uniformly inthephylogenetic tree. The strengths andweaknesses of themethodare assessed via simulations;we then apply the method to explore the loss of cell motility in intracellular pathogens. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Phylodynamics and evolutionary epidemiology of African swine fever p72-CVR genes in Eurasia and Africa

PubMed Central

Jurado, Cristina; Soler, Alejandro; Arias, Marisa; Sánchez-Vizcaíno, José M.

2018-01-01

African swine fever (ASF) is a complex infectious disease of swine that constitutes devastating impacts on animal health and the world economy. Here, we investigated the evolutionary epidemiology of ASF virus (ASFV) in Eurasia and Africa using the concatenated gene sequences of the viral protein 72 and the central variable region of isolates collected between 1960 and 2015. We used Bayesian phylodynamic models to reconstruct the evolutionary history of the virus, to identify virus population demographics and to quantify dispersal patterns between host species. Results suggest that ASFV exhibited a significantly high evolutionary rate and population growth through time since its divergence in the 18th century from East Africa, with no signs of decline till recent years. This increase corresponds to the growing pig trade activities between continents during the 19th century, and may be attributed to an evolutionary drift that resulted from either continuous circulation or maintenance of the virus within Africa and Eurasia. Furthermore, results implicate wild suids as the ancestral host species (root state posterior probability = 0.87) for ASFV in the early 1700s in Africa. Moreover, results indicate the transmission cycle between wild suids and pigs is an important cycle for ASFV spread and maintenance in pig populations, while ticks are an important natural reservoir that can facilitate ASFV spread and maintenance in wild swine populations. We illustrated the prospects of phylodynamic methods in improving risk-based surveillance, support of effective animal health policies, and epidemic preparedness in countries at high risk of ASFV incursion. PMID:29489860

Molecular species delimitation methods recover most song-delimited cicada species in the European Cicadetta montana complex.

PubMed

Wade, E J; Hertach, T; Gogala, M; Trilar, T; Simon, C

2015-12-01

Molecular species delimitation is increasingly being used to discover and illuminate species level diversity, and a number of methods have been developed. Here, we compare the ability of two molecular species delimitation methods to recover song-delimited species in the Cicadetta montana cryptic species complex throughout Europe. Recent bioacoustics studies of male calling songs (premating reproductive barriers) have revealed cryptic species diversity in this complex. Maximum likelihood and Bayesian phylogenetic analyses were used to analyse the mitochondrial genes COI and COII and the nuclear genes EF1α and period for thirteen European Cicadetta species as well as the closely related monotypic genus Euboeana. Two molecular species delimitation methods, general mixed Yule-coalescent (GMYC) and Bayesian phylogenetics and phylogeography, identified the majority of song-delimited species and were largely congruent with each other. None of the molecular delimitation methods were able to fully recover a recent radiation of four Greek species. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Is sociality required for the evolution of communicative complexity? Evidence weighed against alternative hypotheses in diverse taxonomic groups

PubMed Central

Ord, Terry J.; Garcia-Porta, Joan

2012-01-01

Complex social communication is expected to evolve whenever animals engage in many and varied social interactions; that is, sociality should promote communicative complexity. Yet, informal comparisons among phylogenetically independent taxonomic groups seem to cast doubt on the putative role of social factors in the evolution of complex communication. Here, we provide a formal test of the sociality hypothesis alongside alternative explanations for the evolution of communicative complexity. We compiled data documenting variations in signal complexity among closely related species for several case study groups—ants, frogs, lizards and birds—and used new phylogenetic methods to investigate the factors underlying communication evolution. Social factors were only implicated in the evolution of complex visual signals in lizards. Ecology, and to some degree allometry, were most likely explanations for complexity in the vocal signals of frogs (ecology) and birds (ecology and allometry). There was some evidence for adaptive evolution in the pheromone complexity of ants, although no compelling selection pressure was identified. For most taxa, phylogenetic null models were consistently ranked above adaptive models and, for some taxa, signal complexity seems to have accumulated in species via incremental or random changes over long periods of evolutionary time. Becoming social presumably leads to the origin of social communication in animals, but its subsequent influence on the trajectory of signal evolution has been neither clear-cut nor general among taxonomic groups. PMID:22641820

Simulating natural selection in landscape genetics

Treesearch

E. L. Landguth; S. A. Cushman; N. Johnson

2012-01-01

Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially- explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal...

Evolutionary models of interstellar chemistry

NASA Technical Reports Server (NTRS)

Prasad, Sheo S.

1987-01-01

The goal of evolutionary models of interstellar chemistry is to understand how interstellar clouds came to be the way they are, how they will change with time, and to place them in an evolutionary sequence with other celestial objects such as stars. An improved Mark II version of an earlier model of chemistry in dynamically evolving clouds is presented. The Mark II model suggests that the conventional elemental C/O ratio less than one can explain the observed abundances of CI and the nondetection of O2 in dense clouds. Coupled chemical-dynamical models seem to have the potential to generate many observable discriminators of the evolutionary tracks. This is exciting, because, in general, purely dynamical models do not yield enough verifiable discriminators of the predicted tracks.

Evaluation of Generation Alternation Models in Evolutionary Robotics

NASA Astrophysics Data System (ADS)

Oiso, Masashi; Matsumura, Yoshiyuki; Yasuda, Toshiyuki; Ohkura, Kazuhiro

For efficient implementation of Evolutionary Algorithms (EA) to a desktop grid computing environment, we propose a new generation alternation model called Grid-Oriented-Deletion (GOD) based on comparison with the conventional techniques. In previous research, generation alternation models are generally evaluated by using test functions. However, their exploration performance on the real problems such as Evolutionary Robotics (ER) has not been made very clear yet. Therefore we investigate the relationship between the exploration performance of EA on an ER problem and its generation alternation model. We applied four generation alternation models to the Evolutionary Multi-Robotics (EMR), which is the package-pushing problem to investigate their exploration performance. The results show that GOD is more effective than the other conventional models.

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology.

PubMed

Cankorur-Cetinkaya, Ayca; Dias, Joao M L; Kludas, Jana; Slater, Nigel K H; Rousu, Juho; Oliver, Stephen G; Dikicioglu, Duygu

2017-06-01

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple-to-use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257).

Effects of behavioral response and vaccination policy on epidemic spreading--an approach based on evolutionary-game dynamics.

PubMed

Zhang, Hai-Feng; Wu, Zhi-Xi; Tang, Ming; Lai, Ying-Cheng

2014-07-11

How effective are governmental incentives to achieve widespread vaccination coverage so as to prevent epidemic outbreak? The answer largely depends on the complex interplay among the type of incentive, individual behavioral responses, and the intrinsic epidemic dynamics. By incorporating evolutionary games into epidemic dynamics, we investigate the effects of two types of incentives strategies: partial-subsidy policy in which certain fraction of the cost of vaccination is offset, and free-subsidy policy in which donees are randomly selected and vaccinated at no cost. Through mean-field analysis and computations, we find that, under the partial-subsidy policy, the vaccination coverage depends monotonically on the sensitivity of individuals to payoff difference, but the dependence is non-monotonous for the free-subsidy policy. Due to the role models of the donees for relatively irrational individuals and the unchanged strategies of the donees for rational individuals, the free-subsidy policy can in general lead to higher vaccination coverage. Our findings indicate that any disease-control policy should be exercised with extreme care: its success depends on the complex interplay among the intrinsic mathematical rules of epidemic spreading, governmental policies, and behavioral responses of individuals.

The complex evolutionary history of the tympanic middle ear in frogs and toads (Anura)

PubMed Central

Pereyra, Martín O.; Womack, Molly C.; Barrionuevo, J. Sebastián; Blotto, Boris L.; Baldo, Diego; Targino, Mariane; Ospina-Sarria, Jhon Jairo; Guayasamin, Juan M.; Coloma, Luis A.; Hoke, Kim L.; Grant, Taran; Faivovich, Julián

2016-01-01

Most anurans possess a tympanic middle ear (TME) that transmits sound waves to the inner ear; however, numerous species lack some or all TME components. To understand the evolution of these structures, we undertook a comprehensive assessment of their occurrence across anurans and performed ancestral character state reconstructions. Our analysis indicates that the TME was completely lost at least 38 independent times in Anura. The inferred evolutionary history of the TME is exceptionally complex in true toads (Bufonidae), where it was lost in the most recent common ancestor, preceding a radiation of >150 earless species. Following that initial loss, independent regains of some or all TME structures were inferred within two minor clades and in a radiation of >400 species. The reappearance of the TME in the latter clade was followed by at least 10 losses of the entire TME. The many losses and gains of the TME in anurans is unparalleled among tetrapods. Our results show that anurans, and especially bufonid toads, are an excellent model to study the behavioural correlates of earlessness, extratympanic sound pathways, and the genetic and developmental mechanisms that underlie the morphogenesis of TME structures. PMID:27677839

The complex evolutionary history of the tympanic middle ear in frogs and toads (Anura).

PubMed

Pereyra, Martín O; Womack, Molly C; Barrionuevo, J Sebastián; Blotto, Boris L; Baldo, Diego; Targino, Mariane; Ospina-Sarria, Jhon Jairo; Guayasamin, Juan M; Coloma, Luis A; Hoke, Kim L; Grant, Taran; Faivovich, Julián

2016-09-28

Most anurans possess a tympanic middle ear (TME) that transmits sound waves to the inner ear; however, numerous species lack some or all TME components. To understand the evolution of these structures, we undertook a comprehensive assessment of their occurrence across anurans and performed ancestral character state reconstructions. Our analysis indicates that the TME was completely lost at least 38 independent times in Anura. The inferred evolutionary history of the TME is exceptionally complex in true toads (Bufonidae), where it was lost in the most recent common ancestor, preceding a radiation of >150 earless species. Following that initial loss, independent regains of some or all TME structures were inferred within two minor clades and in a radiation of >400 species. The reappearance of the TME in the latter clade was followed by at least 10 losses of the entire TME. The many losses and gains of the TME in anurans is unparalleled among tetrapods. Our results show that anurans, and especially bufonid toads, are an excellent model to study the behavioural correlates of earlessness, extratympanic sound pathways, and the genetic and developmental mechanisms that underlie the morphogenesis of TME structures.

Effects of behavioral response and vaccination policy on epidemic spreading - an approach based on evolutionary-game dynamics

NASA Astrophysics Data System (ADS)

Zhang, Hai-Feng; Wu, Zhi-Xi; Tang, Ming; Lai, Ying-Cheng

2014-07-01

How effective are governmental incentives to achieve widespread vaccination coverage so as to prevent epidemic outbreak? The answer largely depends on the complex interplay among the type of incentive, individual behavioral responses, and the intrinsic epidemic dynamics. By incorporating evolutionary games into epidemic dynamics, we investigate the effects of two types of incentives strategies: partial-subsidy policy in which certain fraction of the cost of vaccination is offset, and free-subsidy policy in which donees are randomly selected and vaccinated at no cost. Through mean-field analysis and computations, we find that, under the partial-subsidy policy, the vaccination coverage depends monotonically on the sensitivity of individuals to payoff difference, but the dependence is non-monotonous for the free-subsidy policy. Due to the role models of the donees for relatively irrational individuals and the unchanged strategies of the donees for rational individuals, the free-subsidy policy can in general lead to higher vaccination coverage. Our findings indicate that any disease-control policy should be exercised with extreme care: its success depends on the complex interplay among the intrinsic mathematical rules of epidemic spreading, governmental policies, and behavioral responses of individuals.

The genetic basis of traits regulating sperm competition and polyandry: can selection favour the evolution of good- and sexy-sperm?

PubMed

Evans, Jonathan P; Simmons, Leigh W

2008-09-01

The good-sperm and sexy-sperm (GS-SS) hypotheses predict that female multiple mating (polyandry) can fuel sexual selection for heritable male traits that promote success in sperm competition. A major prediction generated by these models, therefore, is that polyandry will benefit females indirectly via their sons' enhanced fertilization success. Furthermore, like classic 'good genes' and 'sexy son' models for the evolution of female preferences, GS-SS processes predict a genetic correlation between genes for female mating frequency (analogous to the female preference) and those for traits influencing fertilization success (the sexually selected traits). We examine the premise for these predictions by exploring the genetic basis of traits thought to influence fertilization success and female mating frequency. We also highlight recent debates that stress the possible genetic constraints to evolution of traits influencing fertilization success via GS-SS processes, including sex-linked inheritance, nonadditive effects, interacting parental genotypes, and trade-offs between integrated ejaculate components. Despite these possible constraints, the available data suggest that male traits involved in sperm competition typically exhibit substantial additive genetic variance and rapid evolutionary responses to selection. Nevertheless, the limited data on the genetic variation in female mating frequency implicate strong genetic maternal effects, including X-linkage, which is inconsistent with GS-SS processes. Although the relative paucity of studies on the genetic basis of polyandry does not allow us to draw firm conclusions about the evolutionary origins of this trait, the emerging pattern of sex linkage in genes for polyandry is more consistent with an evolutionary history of antagonistic selection over mating frequency. We advocate further development of GS-SS theory to take account of the complex evolutionary dynamics imposed by sexual conflict over mating frequency.

The developmental basis of an evolutionary diversification of female gametophyte structure in Piper and Piperaceae

PubMed Central

Madrid, Eric N.; Friedman, William E.

2009-01-01

Background and Aims Fritillaria-type female gametophyte development is a complex, yet homoplasious developmental pattern that is interesting from both evolutionary and developmental perspectives. Piper (Piperaceae) was chosen for this study of Fritillaria-type female gametophyte development because Piperales represent a ‘hotspot’ of female gametophyte developmental evolution and have been the subject of several recent molecular phylogenetic analyses. This wealth of phylogenetic and descriptive data make Piper an excellent candidate for inferring the evolutionary developmental basis for the origin of Fritillaria-type female gametophytes. Methods Developing ovules of Piper peltatum were taken from greenhouse collections, embedded in glycol methacrylate, and serially sectioned. Light microscopy and laser scanning confocal microscopy were combined to produce three-dimensional computer reconstructions of developing female gametophytes. The ploidies of the developing embryos and endosperms were calculated using microspectrofluorometry. Key Results The data describe female gametophyte development in Piper with highly detailed three-dimensional models, and document two previously unknown arrangements of megaspore nuclei during early development. Also collected were microspectrofluorometric data that indicate that Fritillaria-type female gametophyte development in Piper results in pentaploid endosperm. Conclusions The three-dimensional models resolve previous ambiguities in developmental interpretations of Fritillaria-type female gametophytes in Piper. The newly discovered arrangements of megaspore nuclei that are described allow for the construction of explicit hypotheses of female gametophyte developmental evolution within Piperaceae, and more broadly throughout Piperales. These detailed hypotheses indicate that the common ancestor of Piperaceae minus Verhuellia had a Drusa-type female gametophyte, and that evolutionary transitions to derived tetrasporic female gametophyte ontogenies in Piperaceae, including Fritillaria-type female gametophyte development, are the consequence of key nuclear migration and patterning events at the end of megasporogenesis. PMID:19202137

Aerobic metabolism underlies complexity and capacity

PubMed Central

Koch, Lauren G; Britton, Steven L

2008-01-01

The evolution of biological complexity beyond single-celled organisms was linked temporally with the development of an oxygen atmosphere. Functionally, this linkage can be attributed to oxygen ranking high in both abundance and electronegativity amongst the stable elements of the universe. That is, reduction of oxygen provides for close to the largest possible transfer of energy for each electron transfer reaction. This suggests the general hypothesis that the steep thermodynamic gradient of an oxygen environment was permissive for the development of multicellular complexity. A corollary of this hypothesis is that aerobic metabolism underwrites complex biological function mechanistically at all levels of organization. The strong contemporary functional association of aerobic metabolism with both physical capacity and health is presumably a product of the integral role of oxygen in our evolutionary history. Here we provide arguments from thermodynamics, evolution, metabolic network analysis, clinical observations and animal models that are in accord with the centrality of oxygen in biology. PMID:17947307

The topological requirements for robust perfect adaptation in networks of any size.

PubMed

Araujo, Robyn P; Liotta, Lance A

2018-05-01

Robustness, and the ability to function and thrive amid changing and unfavorable environments, is a fundamental requirement for living systems. Until now it has been an open question how large and complex biological networks can exhibit robust behaviors, such as perfect adaptation to a variable stimulus, since complexity is generally associated with fragility. Here we report that all networks that exhibit robust perfect adaptation (RPA) to a persistent change in stimulus are decomposable into well-defined modules, of which there exist two distinct classes. These two modular classes represent a topological basis for all RPA-capable networks, and generate the full set of topological realizations of the internal model principle for RPA in complex, self-organizing, evolvable bionetworks. This unexpected result supports the notion that evolutionary processes are empowered by simple and scalable modular design principles that promote robust performance no matter how large or complex the underlying networks become.

The evolution of colour pattern complexity: selection for conspicuousness favours contrasting within-body colour combinations in lizards.

PubMed

Pérez I de Lanuza, G; Font, E

2016-05-01

Many animals display complex colour patterns that comprise several adjacent, often contrasting colour patches. Combining patches of complementary colours increases the overall conspicuousness of the complex pattern, enhancing signal detection. Therefore, selection for conspicuousness may act not only on the design of single colour patches, but also on their combination. Contrasting long- and short-wavelength colour patches are located on the ventral and lateral surfaces of many lacertid lizards. As the combination of long- and short-wavelength-based colours generates local chromatic contrast, we hypothesized that selection may favour the co-occurrence of lateral and ventral contrasting patches, resulting in complex colour patterns that maximize the overall conspicuousness of the signal. To test this hypothesis, we performed a comparative phylogenetic study using a categorical colour classification based on spectral data and descriptive information on lacertid coloration collected from the literature. Our results demonstrate that conspicuous ventral (long-wavelength-based) and lateral (short-wavelength-based) colour patches co-occur throughout the lacertid phylogeny more often than expected by chance, especially in the subfamily Lacertini. These results suggest that selection promotes the evolution of the complex pattern rather than the acquisition of a single conspicuous colour patch, possibly due to the increased conspicuousness caused by the combination of colours with contrasting spectral properties. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Lessons learned from the dog genome.

PubMed

Wayne, Robert K; Ostrander, Elaine A

2007-11-01

Extensive genetic resources and a high-quality genome sequence position the dog as an important model species for understanding genome evolution, population genetics and genes underlying complex phenotypic traits. Newly developed genomic resources have expanded our understanding of canine evolutionary history and dog origins. Domestication involved genetic contributions from multiple populations of gray wolves probably through backcrossing. More recently, the advent of controlled breeding practices has segregated genetic variability into distinct dog breeds that possess specific phenotypic traits. Consequently, genome-wide association and selective sweep scans now allow the discovery of genes underlying breed-specific characteristics. The dog is finally emerging as a novel resource for studying the genetic basis of complex traits, including behavior.

Biodiversity and Topographic Complexity: Modern and Geohistorical Perspectives.

PubMed

Badgley, Catherine; Smiley, Tara M; Terry, Rebecca; Davis, Edward B; DeSantis, Larisa R G; Fox, David L; Hopkins, Samantha S B; Jezkova, Tereza; Matocq, Marjorie D; Matzke, Nick; McGuire, Jenny L; Mulch, Andreas; Riddle, Brett R; Roth, V Louise; Samuels, Joshua X; Strömberg, Caroline A E; Yanites, Brian J

2017-03-01

Topographically complex regions on land and in the oceans feature hotspots of biodiversity that reflect geological influences on ecological and evolutionary processes. Over geologic time, topographic diversity gradients wax and wane over millions of years, tracking tectonic or climatic history. Topographic diversity gradients from the present day and the past can result from the generation of species by vicariance or from the accumulation of species from dispersal into a region with strong environmental gradients. Biological and geological approaches must be integrated to test alternative models of diversification along topographic gradients. Reciprocal illumination among phylogenetic, phylogeographic, ecological, paleontological, tectonic, and climatic perspectives is an emerging frontier of biogeographic research. Copyright © 2017 Elsevier Ltd. All rights reserved.

IRAS observations of the Rho Ophiuchi infrared cluster - Spectral energy distributions and luminosity function

NASA Technical Reports Server (NTRS)

Wilking, Bruce A.; Lada, Charles J.; Young, Eric T.

1989-01-01

High-sensitivity IRAS coadded survey data, coupled with new high-sensitivity near-IR observations, are used to investigate the nature of embedded objects over an 4.3-sq-pc area comprising the central star-forming cloud of the Ophiuchi molecular complex; the area encompasses the central cloud of the Rho Ophiuchi complex and includes the core region. Seventy-eight members of the embedded cluster were identified; spectral energy distributions were constructed for 53 objects and were compared with theoretical models to gain insight into their evolutionary status. Bolometric luminosities could be estimated for nearly all of the association members, leading to a revised luminosity function for this dust-embedded cluster.

Object-oriented Bayesian networks for paternity cases with allelic dependencies

PubMed Central

Hepler, Amanda B.; Weir, Bruce S.

2008-01-01

This study extends the current use of Bayesian networks by incorporating the effects of allelic dependencies in paternity calculations. The use of object-oriented networks greatly simplify the process of building and interpreting forensic identification models, allowing researchers to solve new, more complex problems. We explore two paternity examples: the most common scenario where DNA evidence is available from the alleged father, the mother and the child; a more complex casewhere DNA is not available from the alleged father, but is available from the alleged father’s brother. Object-oriented networks are built, using HUGIN, for each example which incorporate the effects of allelic dependence caused by evolutionary relatedness. PMID:19079769

Evolutionary Establishment of Moral and Double Moral Standards through Spatial Interactions

PubMed Central

Helbing, Dirk; Szolnoki, Attila; Perc, Matjaž; Szabó, György

2010-01-01

Situations where individuals have to contribute to joint efforts or share scarce resources are ubiquitous. Yet, without proper mechanisms to ensure cooperation, the evolutionary pressure to maximize individual success tends to create a tragedy of the commons (such as over-fishing or the destruction of our environment). This contribution addresses a number of related puzzles of human behavior with an evolutionary game theoretical approach as it has been successfully used to explain the behavior of other biological species many times, from bacteria to vertebrates. Our agent-based model distinguishes individuals applying four different behavioral strategies: non-cooperative individuals (“defectors”), cooperative individuals abstaining from punishment efforts (called “cooperators” or “second-order free-riders”), cooperators who punish non-cooperative behavior (“moralists”), and defectors, who punish other defectors despite being non-cooperative themselves (“immoralists”). By considering spatial interactions with neighboring individuals, our model reveals several interesting effects: First, moralists can fully eliminate cooperators. This spreading of punishing behavior requires a segregation of behavioral strategies and solves the “second-order free-rider problem”. Second, the system behavior changes its character significantly even after very long times (“who laughs last laughs best effect”). Third, the presence of a number of defectors can largely accelerate the victory of moralists over non-punishing cooperators. Fourth, in order to succeed, moralists may profit from immoralists in a way that appears like an “unholy collaboration”. Our findings suggest that the consideration of punishment strategies allows one to understand the establishment and spreading of “moral behavior” by means of game-theoretical concepts. This demonstrates that quantitative biological modeling approaches are powerful even in domains that have been addressed with non-mathematical concepts so far. The complex dynamics of certain social behaviors become understandable as the result of an evolutionary competition between different behavioral strategies. PMID:20454464

The prisoner's dilemma as a cancer model.

PubMed

West, Jeffrey; Hasnain, Zaki; Mason, Jeremy; Newton, Paul K

2016-09-01

Tumor development is an evolutionary process in which a heterogeneous population of cells with different growth capabilities compete for resources in order to gain a proliferative advantage. What are the minimal ingredients needed to recreate some of the emergent features of such a developing complex ecosystem? What is a tumor doing before we can detect it? We outline a mathematical model, driven by a stochastic Moran process, in which cancer cells and healthy cells compete for dominance in the population. Each are assigned payoffs according to a Prisoner's Dilemma evolutionary game where the healthy cells are the cooperators and the cancer cells are the defectors. With point mutational dynamics, heredity, and a fitness landscape controlling birth and death rates, natural selection acts on the cell population and simulated 'cancer-like' features emerge, such as Gompertzian tumor growth driven by heterogeneity, the log-kill law which (linearly) relates therapeutic dose density to the (log) probability of cancer cell survival, and the Norton-Simon hypothesis which (linearly) relates tumor regression rates to tumor growth rates. We highlight the utility, clarity, and power that such models provide, despite (and because of) their simplicity and built-in assumptions.

Genome-scale modeling of the evolutionary path to C4 photosynthesis

NASA Astrophysics Data System (ADS)

Myers, Christopher R.; Bogart, Eli

In C4 photosynthesis, plants maintain a high carbon dioxide level in specialized bundle sheath cells surrounding leaf veins and restrict CO2 assimilation to those cells, favoring CO2 over O2 in competition for Rubisco active sites. In C3 plants, which do not possess such a carbon concentrating mechanism, CO2 fixation is reduced due to this competition. Despite the complexity of the C4 system, it has evolved convergently from more than 60 independent origins in diverse families of plants around the world over the last 30 million years. We study the evolution of the C4 system in a genome-scale model of plant metabolism that describes interacting mesophyll and bundle sheath cells and enforces key nonlinear kinetic relationships. Adapting the zero-temperature string method for simulating transition paths in physics and chemistry, we find the highest-fitness paths connecting C3 and C4 positions in the model's high-dimensional parameter space, and show that they reproduce known aspects of the C3-C4 transition while making additional predictions about metabolic changes along the path. We explore the relationship between evolutionary history and C4 biochemical subtype, and the effects of atmospheric carbon dioxide levels.

A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape.

PubMed

Gilpin, William; Feldman, Marcus W

2017-07-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the "edge of chaos" while creating a wide distribution of opportunities for speciation during epochs of disruptive selection-a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies.

Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

PubMed

Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

2016-02-07

Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. Copyright © 2015 Elsevier Ltd. All rights reserved.

Inferring duplications, losses, transfers and incomplete lineage sorting with nonbinary species trees.

PubMed

Stolzer, Maureen; Lai, Han; Xu, Minli; Sathaye, Deepa; Vernot, Benjamin; Durand, Dannie

2012-09-15

Gene duplication (D), transfer (T), loss (L) and incomplete lineage sorting (I) are crucial to the evolution of gene families and the emergence of novel functions. The history of these events can be inferred via comparison of gene and species trees, a process called reconciliation, yet current reconciliation algorithms model only a subset of these evolutionary processes. We present an algorithm to reconcile a binary gene tree with a nonbinary species tree under a DTLI parsimony criterion. This is the first reconciliation algorithm to capture all four evolutionary processes driving tree incongruence and the first to reconcile non-binary species trees with a transfer model. Our algorithm infers all optimal solutions and reports complete, temporally feasible event histories, giving the gene and species lineages in which each event occurred. It is fixed-parameter tractable, with polytime complexity when the maximum species outdegree is fixed. Application of our algorithms to prokaryotic and eukaryotic data show that use of an incomplete event model has substantial impact on the events inferred and resulting biological conclusions. Our algorithms have been implemented in Notung, a freely available phylogenetic reconciliation software package, available at http://www.cs.cmu.edu/~durand/Notung. mstolzer@andrew.cmu.edu.

The Evolutionary Psychology of Envy and Jealousy

PubMed Central

Ramachandran, Vilayanur S.; Jalal, Baland

2017-01-01

The old dogma has always been that the most complex aspects of human emotions are driven by culture; Germans and English are thought to be straight-laced whereas Italians and Indians are effusive. Yet in the last two decades there has been a growing realization that even though culture plays a major role in the final expression of human nature, there must be a basic scaffolding specified by genes. While this is recognized to be true for simple emotions like anger, fear, and joy, the relevance of evolutionary arguments for more complex nuances of emotion have been inadequately explored. In this paper, we consider envy or jealousy as an example; the feeling evoked when someone is better off than you. Our approach is broadly consistent with traditional evolutionary psychology (EP) approaches, but takes it further by exploring the complexity and functional logic of the emotion – and the precise social triggers that elicit them – by using deliberately farfetched, and contrived “thought experiments” that the subject is asked to participate in. When common sense (e.g., we should be jealous of Bill Gates – not of our slightly richer neighbor) appears to contradict observed behavior (i.e., we are more envious of our neighbor) the paradox can often be resolved by evolutionary considerations which h predict the latter. Many – but not all – EP approaches fail because evolution and common sense do not make contradictory predictions. Finally, we briefly raise the possibility that gaining deeper insight into the evolutionary origins of certain undesirable emotions or behaviors can help shake them off, and may therefore have therapeutic utility. Such an approach would complement current therapies (such as cognitive behavior therapies, psychoanalysis, psychopharmacologies, and hypnotherapy), rather than negate them. PMID:28970815

Predator attack rate evolution in space: the role of ecology mediated by complex emergent spatial structure and self-shading.

PubMed

Messinger, Susanna M; Ostling, Annette

2013-11-01

Predation interactions are an important element of ecological communities. Population spatial structure has been shown to influence predator evolution, resulting in the evolution of a reduced predator attack rate; however, the evolutionary role of traits governing predator and prey ecology is unknown. The evolutionary effect of spatial structure on a predator's attack rate has primarily been explored assuming a fixed metapopulation spatial structure, and understood in terms of group selection. But endogenously generated, emergent spatial structure is common in nature. Furthermore, the evolutionary influence of ecological traits may be mediated through the spatial self-structuring process. Drawing from theory on pathogens, the evolutionary effect of emergent spatial structure can be understood in terms of self-shading, where a voracious predator limits its long-term invasion potential by reducing local prey availability. Here we formalize the effects of self-shading for predators using spatial moment equations. Then, through simulations, we show that in a spatial context self-shading leads to relationships between predator-prey ecology and the predator's attack rate that are not expected in a non-spatial context. Some relationships are analogous to relationships already shown for host-pathogen interactions, but others represent new trait dimensions. Finally, since understanding the effects of ecology using existing self-shading theory requires simplifications of the emergent spatial structure that do not apply well here, we also develop metrics describing the complex spatial structure of the predator and prey populations to help us explain the evolutionary effect of predator and prey ecology in the context of self-shading. The identification of these metrics may provide a step towards expansion of the predictive domain of self-shading theory to more complex spatial dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.

A short history of nearly every sense - The evolutionary history of vertebrate sensory cell types.

PubMed

Schlosser, Gerhard

2018-05-08

Evolving from filter feeding chordate ancestors, vertebrates adopted a more active life style. These ecological and behavioral changes went along with an elaboration of the vertebrate head including novel complex paired sense organs such as the eyes, inner ears and olfactory epithelia. However, the photoreceptors, mechanoreceptors and chemoreceptors used in these sense organs have a long evolutionary history and homologous cell types can be recognized in many other bilaterians or even cnidarians. After briefly introducing some of the major sensory cell types found in vertebrates, this review summarizes the phylogenetic distribution of sensory cell types in metazoans and presents a scenario for the evolutionary history of various sensory cell types involving several cell type diversification and fusion events. It is proposed that the evolution of novel cranial sense organs in vertebrates involved the redeployment of evolutionarily ancient sensory cell types for building larger and more complex sense organs.

[The history of development of evolutionary methods in St. Petersburg school of computer simulation in biology].

PubMed

Menshutkin, V V; Kazanskiĭ, A B; Levchenko, V F

2010-01-01

The history of rise and development of evolutionary methods in Saint Petersburg school of biological modelling is traced and analyzed. Some pioneering works in simulation of ecological and evolutionary processes, performed in St.-Petersburg school became an exemplary ones for many followers in Russia and abroad. The individual-based approach became the crucial point in the history of the school as an adequate instrument for construction of models of biological evolution. This approach is natural for simulation of the evolution of life-history parameters and adaptive processes in populations and communities. In some cases simulated evolutionary process was used for solving a reverse problem, i. e., for estimation of uncertain life-history parameters of population. Evolutionary computations is one more aspect of this approach application in great many fields. The problems and vistas of ecological and evolutionary modelling in general are discussed.

Improving the sampling efficiency of Monte Carlo molecular simulations: an evolutionary approach

NASA Astrophysics Data System (ADS)

Leblanc, Benoit; Braunschweig, Bertrand; Toulhoat, Hervé; Lutton, Evelyne

We present a new approach in order to improve the convergence of Monte Carlo (MC) simulations of molecular systems belonging to complex energetic landscapes: the problem is redefined in terms of the dynamic allocation of MC move frequencies depending on their past efficiency, measured with respect to a relevant sampling criterion. We introduce various empirical criteria with the aim of accounting for the proper convergence in phase space sampling. The dynamic allocation is performed over parallel simulations by means of a new evolutionary algorithm involving 'immortal' individuals. The method is bench marked with respect to conventional procedures on a model for melt linear polyethylene. We record significant improvement in sampling efficiencies, thus in computational load, while the optimal sets of move frequencies are liable to allow interesting physical insights into the particular systems simulated. This last aspect should provide a new tool for designing more efficient new MC moves.

Integrated pipeline for inferring the evolutionary history of a gene family embedded in the species tree: a case study on the STIMATE gene family.

PubMed

Song, Jia; Zheng, Sisi; Nguyen, Nhung; Wang, Youjun; Zhou, Yubin; Lin, Kui

2017-10-03

Because phylogenetic inference is an important basis for answering many evolutionary problems, a large number of algorithms have been developed. Some of these algorithms have been improved by integrating gene evolution models with the expectation of accommodating the hierarchy of evolutionary processes. To the best of our knowledge, however, there still is no single unifying model or algorithm that can take all evolutionary processes into account through a stepwise or simultaneous method. On the basis of three existing phylogenetic inference algorithms, we built an integrated pipeline for inferring the evolutionary history of a given gene family; this pipeline can model gene sequence evolution, gene duplication-loss, gene transfer and multispecies coalescent processes. As a case study, we applied this pipeline to the STIMATE (TMEM110) gene family, which has recently been reported to play an important role in store-operated Ca 2+ entry (SOCE) mediated by ORAI and STIM proteins. We inferred their phylogenetic trees in 69 sequenced chordate genomes. By integrating three tree reconstruction algorithms with diverse evolutionary models, a pipeline for inferring the evolutionary history of a gene family was developed, and its application was demonstrated.

Scheduling Earth Observing Satellites with Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Globus, Al; Crawford, James; Lohn, Jason; Pryor, Anna

2003-01-01

We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitness. To test the hypothesis we have developed a representative set of problems, produced optimization software (in Java) to solve them, and run experiments comparing techniques. This paper presents initial results of a comparison of several evolutionary and other optimization techniques; namely the genetic algorithm, simulated annealing, squeaky wheel optimization, and stochastic hill climbing. We also compare separate satellite vs. integrated scheduling of a two satellite constellation. While the results are not definitive, tests to date suggest that simulated annealing is the best search technique and integrated scheduling is superior.

The evolution of reciprocity in sizable human groups.

PubMed

Rothschild, Casey G

2009-04-21

The scale and complexity of human cooperation is an important and unresolved evolutionary puzzle. This article uses the finitely repeated n person Prisoners' Dilemma game to illustrate how sapience can greatly enhance group-selection effects and lead to the evolutionary stability of cooperation in large groups. This affords a simple and direct explanation of the human "exception".

Extending Galactic Habitable Zone Modeling to Include the Emergence of Intelligent Life.

PubMed

Morrison, Ian S; Gowanlock, Michael G

2015-08-01

Previous studies of the galactic habitable zone have been concerned with identifying those regions of the Galaxy that may favor the emergence of complex life. A planet is deemed habitable if it meets a set of assumed criteria for supporting the emergence of such complex life. In this work, we extend the assessment of habitability to consider the potential for life to further evolve to the point of intelligence--termed the propensity for the emergence of intelligent life, φI. We assume φI is strongly influenced by the time durations available for evolutionary processes to proceed undisturbed by the sterilizing effects of nearby supernovae. The times between supernova events provide windows of opportunity for the evolution of intelligence. We developed a model that allows us to analyze these window times to generate a metric for φI, and we examine here the spatial and temporal variation of this metric. Even under the assumption that long time durations are required between sterilizations to allow for the emergence of intelligence, our model suggests that the inner Galaxy provides the greatest number of opportunities for intelligence to arise. This is due to the substantially higher number density of habitable planets in this region, which outweighs the effects of a higher supernova rate in the region. Our model also shows that φI is increasing with time. Intelligent life emerged at approximately the present time at Earth's galactocentric radius, but a similar level of evolutionary opportunity was available in the inner Galaxy more than 2 Gyr ago. Our findings suggest that the inner Galaxy should logically be a prime target region for searches for extraterrestrial intelligence and that any civilizations that may have emerged there are potentially much older than our own.

Effects of complex life cycles on genetic diversity: cyclical parthenogenesis

PubMed Central

Rouger, R; Reichel, K; Malrieu, F; Masson, J P; Stoeckel, S

2016-01-01

Neutral patterns of population genetic diversity in species with complex life cycles are difficult to anticipate. Cyclical parthenogenesis (CP), in which organisms undergo several rounds of clonal reproduction followed by a sexual event, is one such life cycle. Many species, including crop pests (aphids), human parasites (trematodes) or models used in evolutionary science (Daphnia), are cyclical parthenogens. It is therefore crucial to understand the impact of such a life cycle on neutral genetic diversity. In this paper, we describe distributions of genetic diversity under conditions of CP with various clonal phase lengths. Using a Markov chain model of CP for a single locus and individual-based simulations for two loci, our analysis first demonstrates that strong departures from full sexuality are observed after only a few generations of clonality. The convergence towards predictions made under conditions of full clonality during the clonal phase depends on the balance between mutations and genetic drift. Second, the sexual event of CP usually resets the genetic diversity at a single locus towards predictions made under full sexuality. However, this single recombination event is insufficient to reshuffle gametic phases towards full-sexuality predictions. Finally, for similar levels of clonality, CP and acyclic partial clonality (wherein a fixed proportion of individuals are clonally produced within each generation) differentially affect the distribution of genetic diversity. Overall, this work provides solid predictions of neutral genetic diversity that may serve as a null model in detecting the action of common evolutionary or demographic processes in cyclical parthenogens (for example, selection or bottlenecks). PMID:27436524

Tol2 transposon-mediated transgenesis in the Midas cichlid (Amphilophus citrinellus) - towards understanding gene function and regulatory evolution in an ecological model system for rapid phenotypic diversification.

PubMed

Kratochwil, Claudius F; Sefton, Maggie M; Liang, Yipeng; Meyer, Axel

2017-11-23

The Midas cichlid species complex (Amphilophus spp.) is widely known among evolutionary biologists as a model system for sympatric speciation and adaptive phenotypic divergence within extremely short periods of time (a few hundred generations). The repeated parallel evolution of adaptive phenotypes in this radiation, combined with their near genetic identity, makes them an excellent model for studying phenotypic diversification. While many ecological and evolutionary studies have been performed on Midas cichlids, the molecular basis of specific phenotypes, particularly adaptations, and their underlying coding and cis-regulatory changes have not yet been studied thoroughly. For the first time in any New World cichlid, we use Tol2 transposon-mediated transgenesis in the Midas cichlid (Amphilophus citrinellus). By adapting existing microinjection protocols, we established an effective protocol for transgenesis in Midas cichlids. Embryos were injected with a Tol2 plasmid construct that drives enhanced green fluorescent protein (eGFP) expression under the control of the ubiquitin promoter. The transgene was successfully integrated into the germline, driving strong ubiquitous expression of eGFP in the first transgenic Midas cichlid line. Additionally, we show transient expression of two further transgenic constructs, ubiquitin::tdTomato and mitfa::eGFP. Transgenesis in Midas cichlids will facilitate further investigation of the genetic basis of species-specific traits, many of which are adaptations. Transgenesis is a versatile tool not only for studying regulatory elements such as promoters and enhancers, but also for testing gene function through overexpression of allelic gene variants. As such, it is an important first step in establishing the Midas cichlid as a powerful model for studying adaptive coding and non-coding changes in an ecological and evolutionary context.

Bears in a Forest of Gene Trees: Phylogenetic Inference Is Complicated by Incomplete Lineage Sorting and Gene Flow

PubMed Central

Kutschera, Verena E.; Bidon, Tobias; Hailer, Frank; Rodi, Julia L.; Fain, Steven R.; Janke, Axel

2014-01-01

Ursine bears are a mammalian subfamily that comprises six morphologically and ecologically distinct extant species. Previous phylogenetic analyses of concatenated nuclear genes could not resolve all relationships among bears, and appeared to conflict with the mitochondrial phylogeny. Evolutionary processes such as incomplete lineage sorting and introgression can cause gene tree discordance and complicate phylogenetic inferences, but are not accounted for in phylogenetic analyses of concatenated data. We generated a high-resolution data set of autosomal introns from several individuals per species and of Y-chromosomal markers. Incorporating intraspecific variability in coalescence-based phylogenetic and gene flow estimation approaches, we traced the genealogical history of individual alleles. Considerable heterogeneity among nuclear loci and discordance between nuclear and mitochondrial phylogenies were found. A species tree with divergence time estimates indicated that ursine bears diversified within less than 2 My. Consistent with a complex branching order within a clade of Asian bear species, we identified unidirectional gene flow from Asian black into sloth bears. Moreover, gene flow detected from brown into American black bears can explain the conflicting placement of the American black bear in mitochondrial and nuclear phylogenies. These results highlight that both incomplete lineage sorting and introgression are prominent evolutionary forces even on time scales up to several million years. Complex evolutionary patterns are not adequately captured by strictly bifurcating models, and can only be fully understood when analyzing multiple independently inherited loci in a coalescence framework. Phylogenetic incongruence among gene trees hence needs to be recognized as a biologically meaningful signal. PMID:24903145

Versatility and Invariance in the Evolution of Homologous Heteromeric Interfaces

PubMed Central

Andreani, Jessica; Faure, Guilhem; Guerois, Raphaël

2012-01-01

Evolutionary pressures act on protein complex interfaces so that they preserve their complementarity. Nonetheless, the elementary interactions which compose the interface are highly versatile throughout evolution. Understanding and characterizing interface plasticity across evolution is a fundamental issue which could provide new insights into protein-protein interaction prediction. Using a database of 1,024 couples of close and remote heteromeric structural interologs, we studied protein-protein interactions from a structural and evolutionary point of view. We systematically and quantitatively analyzed the conservation of different types of interface contacts. Our study highlights astonishing plasticity regarding polar contacts at complex interfaces. It also reveals that up to a quarter of the residues switch out of the interface when comparing two homologous complexes. Despite such versatility, we identify two important interface descriptors which correlate with an increased conservation in the evolution of interfaces: apolar patches and contacts surrounding anchor residues. These observations hold true even when restricting the dataset to transiently formed complexes. We show that a combination of six features related either to sequence or to geometric properties of interfaces can be used to rank positions likely to share similar contacts between two interologs. Altogether, our analysis provides important tracks for extracting meaningful information from multiple sequence alignments of conserved binding partners and for discriminating near-native interfaces using evolutionary information. PMID:22952442

Reticulate evolution and the human past: an anthropological perspective.

PubMed

Winder, Isabelle C; Winder, Nick P

2014-01-01

The evidence is mounting that reticulate (web-like) evolution has shaped the biological histories of many macroscopic plants and animals, including non-human primates closely related to Homo sapiens, but the implications of this non-hierarchical evolution for anthropological enquiry are not yet fully understood. When they are understood, the result may be a paradigm shift in evolutionary anthropology. This paper reviews the evidence for reticulated evolution in the non-human primates and human lineage. Then it makes the case for extrapolating this sort of patterning to Homo sapiens and other hominins and explores the implications this would have for research design, method and understandings of evolution in anthropology. Reticulation was significant in human evolutionary history and continues to influence societies today. Anthropologists and human scientists-whether working on ancient or modern populations-thus need to consider the implications of non-hierarchic evolution, particularly where molecular clocks, mathematical models and simplifying assumptions about evolutionary processes are used. This is not just a problem for palaeoanthropology. The simple fact of different mating systems among modern human groups, for example, may demand that more attention is paid to the potential for complexity in human genetic and cultural histories.

Cyclic dominance in evolutionary games: a review

PubMed Central

Szolnoki, Attila; Mobilia, Mauro; Jiang, Luo-Luo; Szczesny, Bartosz; Rucklidge, Alastair M.; Perc, Matjaž

2014-01-01

Rock is wrapped by paper, paper is cut by scissors and scissors are crushed by rock. This simple game is popular among children and adults to decide on trivial disputes that have no obvious winner, but cyclic dominance is also at the heart of predator–prey interactions, the mating strategy of side-blotched lizards, the overgrowth of marine sessile organisms and competition in microbial populations. Cyclical interactions also emerge spontaneously in evolutionary games entailing volunteering, reward, punishment, and in fact are common when the competing strategies are three or more, regardless of the particularities of the game. Here, we review recent advances on the rock–paper–scissors (RPS) and related evolutionary games, focusing, in particular, on pattern formation, the impact of mobility and the spontaneous emergence of cyclic dominance. We also review mean-field and zero-dimensional RPS models and the application of the complex Ginzburg–Landau equation, and we highlight the importance and usefulness of statistical physics for the successful study of large-scale ecological systems. Directions for future research, related, for example, to dynamical effects of coevolutionary rules and invasion reversals owing to multi-point interactions, are also outlined. PMID:25232048

Cyclic dominance in evolutionary games: a review.

PubMed

Szolnoki, Attila; Mobilia, Mauro; Jiang, Luo-Luo; Szczesny, Bartosz; Rucklidge, Alastair M; Perc, Matjaž

2014-11-06

Rock is wrapped by paper, paper is cut by scissors and scissors are crushed by rock. This simple game is popular among children and adults to decide on trivial disputes that have no obvious winner, but cyclic dominance is also at the heart of predator-prey interactions, the mating strategy of side-blotched lizards, the overgrowth of marine sessile organisms and competition in microbial populations. Cyclical interactions also emerge spontaneously in evolutionary games entailing volunteering, reward, punishment, and in fact are common when the competing strategies are three or more, regardless of the particularities of the game. Here, we review recent advances on the rock-paper-scissors (RPS) and related evolutionary games, focusing, in particular, on pattern formation, the impact of mobility and the spontaneous emergence of cyclic dominance. We also review mean-field and zero-dimensional RPS models and the application of the complex Ginzburg-Landau equation, and we highlight the importance and usefulness of statistical physics for the successful study of large-scale ecological systems. Directions for future research, related, for example, to dynamical effects of coevolutionary rules and invasion reversals owing to multi-point interactions, are also outlined. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Polyploidy can drive rapid adaptation in yeast

NASA Astrophysics Data System (ADS)

Selmecki, Anna M.; Maruvka, Yosef E.; Richmond, Phillip A.; Guillet, Marie; Shoresh, Noam; Sorenson, Amber L.; de, Subhajyoti; Kishony, Roy; Michor, Franziska; Dowell, Robin; Pellman, David

2015-03-01

Polyploidy is observed across the tree of life, yet its influence on evolution remains incompletely understood. Polyploidy, usually whole-genome duplication, is proposed to alter the rate of evolutionary adaptation. This could occur through complex effects on the frequency or fitness of beneficial mutations. For example, in diverse cell types and organisms, immediately after a whole-genome duplication, newly formed polyploids missegregate chromosomes and undergo genetic instability. The instability following whole-genome duplications is thought to provide adaptive mutations in microorganisms and can promote tumorigenesis in mammalian cells. Polyploidy may also affect adaptation independently of beneficial mutations through ploidy-specific changes in cell physiology. Here we perform in vitro evolution experiments to test directly whether polyploidy can accelerate evolutionary adaptation. Compared with haploids and diploids, tetraploids undergo significantly faster adaptation. Mathematical modelling suggests that rapid adaptation of tetraploids is driven by higher rates of beneficial mutations with stronger fitness effects, which is supported by whole-genome sequencing and phenotypic analyses of evolved clones. Chromosome aneuploidy, concerted chromosome loss, and point mutations all provide large fitness gains. We identify several mutations whose beneficial effects are manifest specifically in the tetraploid strains. Together, these results provide direct quantitative evidence that in some environments polyploidy can accelerate evolutionary adaptation.

Multi-locus phylogeny and divergence time estimates of Enallagma damselflies (Odonata: Coenagrionidae).

PubMed

Callahan, Melissa S; McPeek, Mark A

2016-01-01

Reconstructing evolutionary patterns of species and populations provides a framework for asking questions about the impacts of climate change. Here we use a multilocus dataset to estimate gene trees under maximum likelihood and Bayesian models to obtain a robust estimate of relationships for a genus of North American damselflies, Enallagma. Using a relaxed molecular clock, we estimate the divergence times for this group. Furthermore, to account for the fact that gene tree analyses can overestimate ages of population divergences, we use a multi-population coalescent model to gain a more accurate estimate of divergence times. We also infer diversification rates using a method that allows for variation in diversification rate through time and among lineages. Our results reveal a complex evolutionary history of Enallagma, in which divergence events both predate and occur during Pleistocene climate fluctuations. There is also evidence of diversification rate heterogeneity across the tree. These divergence time estimates provide a foundation for addressing the relative significance of historical climatic events in the diversification of this genus. Copyright © 2015 Elsevier Inc. All rights reserved.

Estimating directional epistasis

PubMed Central

Le Rouzic, Arnaud

2014-01-01

Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions—a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences. PMID:25071828

On joint subtree distributions under two evolutionary models.

PubMed

Wu, Taoyang; Choi, Kwok Pui

2016-04-01

In population and evolutionary biology, hypotheses about micro-evolutionary and macro-evolutionary processes are commonly tested by comparing the shape indices of empirical evolutionary trees with those predicted by neutral models. A key ingredient in this approach is the ability to compute and quantify distributions of various tree shape indices under random models of interest. As a step to meet this challenge, in this paper we investigate the joint distribution of cherries and pitchforks (that is, subtrees with two and three leaves) under two widely used null models: the Yule-Harding-Kingman (YHK) model and the proportional to distinguishable arrangements (PDA) model. Based on two novel recursive formulae, we propose a dynamic approach to numerically compute the exact joint distribution (and hence the marginal distributions) for trees of any size. We also obtained insights into the statistical properties of trees generated under these two models, including a constant correlation between the cherry and the pitchfork distributions under the YHK model, and the log-concavity and unimodality of the cherry distributions under both models. In addition, we show that there exists a unique change point for the cherry distributions between these two models. Copyright © 2015 Elsevier Inc. All rights reserved.

Solving Large-scale Spatial Optimization Problems in Water Resources Management through Spatial Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators to represent spatial variables in a more efficient way. The hyper-population consists of a set of populations, which correspond to the spatial distributions of the individual agents (organisms). Furthermore spatial crossover and mutation operators are designed in accordance with the tree representation and then applied to both organisms and populations. This study applies the SEA to a specific problem of water resources management- maximizing the riparian vegetation coverage in accordance with the distributed groundwater system in an arid region. The vegetation coverage is impacted greatly by the nonlinear feedbacks and interactions between vegetation and groundwater and the spatial variability of groundwater. The SEA is applied to search for an optimal vegetation configuration compatible to the groundwater flow. The results from this example demonstrate the effectiveness of the SEA. Extension of the algorithm for other water resources management problems is discussed.

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Prediction of stock markets by the evolutionary mix-game model

NASA Astrophysics Data System (ADS)

Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

2008-06-01

This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

Complex adaptive systems and their relevance for nursing: An evolutionary concept analysis.

PubMed

Notarnicola, Ippolito; Petrucci, Cristina; De Jesus Barbosa, Maria Rosimar; Giorgi, Fabio; Stievano, Alessandro; Rocco, Gennaro; Lancia, Loreto

2017-06-01

This study aimed to analyse the concept of "complex adaptive systems." The construct is still nebulous in the literature, and a further explanation of the idea is needed to have a shared knowledge of it. A concept analysis was conducted utilizing Rodgers evolutionary method. The inclusive years of bibliographic search started from 2005 to 2015. The search was conducted at PubMed©, CINAHL© (EBSCO host©), Scopus©, Web of Science©, and Academic Search Premier©. Retrieved papers were critically analysed to explore the attributes, antecedents, and consequences of the concept. Moreover, surrogates, related terms, and a pattern recognition scheme were identified. The concept analysis showed that complex systems are adaptive and have the ability to process information. They can adapt to the environment and consequently evolve. Nursing is a complex adaptive system, and the nursing profession in practice exhibits complex adaptive system characteristics. Complexity science through complex adaptive systems provides new ways of seeing and understanding the mechanisms that underpin the nursing profession. © 2017 John Wiley & Sons Australia, Ltd.

Evolutionary disarmament in interspecific competition.

PubMed

Kisdi, E; Geritz, S A

2001-12-22

Competitive asymmetry, which is the advantage of having a larger body or stronger weaponry than a contestant, drives spectacular evolutionary arms races in intraspecific competition. Similar asymmetries are well documented in interspecific competition, yet they seldom lead to exaggerated traits. Here we demonstrate that two species with substantially different size may undergo parallel coevolution towards a smaller size under the same ecological conditions where a single species would exhibit an evolutionary arms race. We show that disarmament occurs for a wide range of parameters in an ecologically explicit model of competition for a single shared resource; disarmament also occurs in a simple Lotka-Volterra competition model. A key property of both models is the interplay between evolutionary dynamics and population density. The mechanism does not rely on very specific features of the model. Thus, evolutionary disarmament may be widespread and may help to explain the lack of interspecific arms races.

Evolutionary disarmament in interspecific competition.

PubMed Central

Kisdi, E.; Geritz, S. A.

2001-01-01

Competitive asymmetry, which is the advantage of having a larger body or stronger weaponry than a contestant, drives spectacular evolutionary arms races in intraspecific competition. Similar asymmetries are well documented in interspecific competition, yet they seldom lead to exaggerated traits. Here we demonstrate that two species with substantially different size may undergo parallel coevolution towards a smaller size under the same ecological conditions where a single species would exhibit an evolutionary arms race. We show that disarmament occurs for a wide range of parameters in an ecologically explicit model of competition for a single shared resource; disarmament also occurs in a simple Lotka-Volterra competition model. A key property of both models is the interplay between evolutionary dynamics and population density. The mechanism does not rely on very specific features of the model. Thus, evolutionary disarmament may be widespread and may help to explain the lack of interspecific arms races. PMID:11749715

Network growth models: A behavioural basis for attachment proportional to fitness

NASA Astrophysics Data System (ADS)

Bell, Michael; Perera, Supun; Piraveenan, Mahendrarajah; Bliemer, Michiel; Latty, Tanya; Reid, Chris

2017-02-01

Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relative merits of such models. This paper analyses an evolutionary mechanism that would give rise to a fitness-based attachment process. In particular, it is proven by analytical and numerical methods that in homogeneous networks, the minimisation of maximum exposure to node unfitness leads to attachment probabilities that are proportional to node fitness. This result is then extended to heterogeneous networks, with supply chain networks being used as an example.

Time-dependent extinction rate and species abundance in a tangled-nature model of biological evolution.

PubMed

Hall, Matt; Christensen, Kim; di Collobiano, Simone A; Jensen, Henrik Jeldtoft

2002-07-01

We present a model of evolutionary ecology consisting of a web of interacting individuals, a tangle-nature model. The reproduction rate of individuals characterized by their genome depends on the composition of the population in genotype space. Ecological features such as the taxonomy and the macroevolutionary mode of the dynamics are emergent properties. The macrodynamics exhibit intermittent two-mode switching with a gradually decreasing extinction rate. The generated ecologies become gradually better adapted as well as more complex in a collective sense. The form of the species abundance curve compares well with observed functional forms. The model's error threshold can be understood in terms of the characteristics of the two dynamical modes of the system.

Structure and function of the C-terminal domain of MrpA in the Bacillus subtilis Mrp-antiporter complex--the evolutionary progenitor of the long horizontal helix in complex I.

PubMed

Virzintiene, Egle; Moparthi, Vamsi K; Al-Eryani, Yusra; Shumbe, Leonard; Górecki, Kamil; Hägerhäll, Cecilia

2013-10-11

MrpA and MrpD are homologous to NuoL, NuoM and NuoN in complex I over the first 14 transmembrane helices. In this work, the C-terminal domain of MrpA, outside this conserved area, was investigated. The transmembrane orientation was found to correspond to that of NuoJ in complex I. We have previously demonstrated that the subunit NuoK is homologous to MrpC. The function of the MrpA C-terminus was tested by expression in a previously used Bacillus subtilis model system. At neutral pH, the truncated MrpA still worked, but at pH 8.4, where Mrp-complex formation is needed for function, the C-terminal domain of MrpA was absolutely required. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

On the origins of Balkan endemics: the complex evolutionary history of the Cyanus napulifer group (Asteraceae).

PubMed

Olšavská, Katarína; Slovák, Marek; Marhold, Karol; Štubňová, Eliška; Kučera, Jaromír

2016-11-01

The Balkan Peninsula is one of the most important centres of plant diversity in Europe. Here we aim to fill the gap in the current knowledge of the evolutionary processes and factors modelling this astonishing biological richness by applying multiple approaches to the Cyanus napulifer group. To reconstruct the mode of diversification within the C. napulifer group and to uncover its relationships with potential relatives with x = 10 from Europe and Northern Africa, we examined variation in genetic markers (amplified fragment length polymorphisms [AFLPs]; 460 individuals), relative DNA content (4',6-diamidino-2-phenylindole [DAPI] flow cytometry, 330 individuals) and morphology (multivariate morphometrics, 40 morphological characters, 710 individuals). To elucidate its evolutionary history, we analysed chloroplast DNA (cpDNA) sequences of the genus Cyanus deposited in the GenBank database. The AFLPs revealed a suite of closely related entities with variable levels of differentiation. The C. napulifer group formed a genetically well-defined unit. Samples outside the group formed strongly diversified and mostly species-specific genetic lineages with no further geographical patterns, often characterized also by a different DNA content. AFLP analysis of the C. napulifer group revealed extensive radiation and split it into nine allopatric (sub)lineages with varying degrees of congruence among genetic, DNA-content and morphological patterns. Genetic admixture was usually detected in contact zones between genetic lineages. Plastid data indicated extensive maintenance of ancestral variation across Cyanus perennials. The C. napulifer group is an example of a rapidly and recently diversified plant group whose genetic lineages have evolved in spatio-temporal isolation on the topographically complex Balkan Peninsula. Adaptive radiation, accompanied in some cases by long-term isolation and hybridization, has contributed to the formation of this species complex and its mosaic pattern. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Assessment, Change, and Complexity.

ERIC Educational Resources Information Center

Salem, Philip

2002-01-01

Describes three types of communication assessment: structural assessment; functional assessment; and process assessment. Contends that these traditional approaches are inappropriate for assessing organizational change. Proposes that complexity theory explicitly focuses on evolutionary processes and thus is a more appropriate foundation for…

The search for Pleiades in trait constellations: functional integration and phenotypic selection in the complex flowers of Morrenia brachystephana (Apocynaceae).

PubMed

Baranzelli, M C; Sérsic, A N; Cocucci, A A

2014-04-01

Pollinator-mediated natural selection on single traits, such as corolla tube or spur length, has been well documented. However, flower phenotypes are usually complex, and selection is expected to act on several traits that functionally interact rather than on a single isolated trait. Despite the fact that selection on complex phenotypes is expectedly widespread, multivariate selection modelling on such phenotypes still remains under-explored in plants. Species of the subfamily Asclepiadoideae (Apocynaceae) provide an opportunity to study such complex flower contrivances integrated by fine-scaled organs from disparate developmental origin. We studied the correlation structure among linear floral traits (i) by testing a priori morphological, functional or developmental hypotheses among traits and (ii) by exploring the organization of flower covariation, considering alternative expectations of modular organization or whole flower integration through conditional dependence analysis (CDA) and integration matrices. The phenotypic selection approach was applied to determine whether floral traits involved in the functioning of the pollination mechanism were affected by natural selection. Floral integration was low, suggesting that flowers are organized in more than just one correlation pleiad; our hypothetical functional correlation matrix was significantly correlated with the empirical matrix, and the CDA revealed three putative modules. Analyses of phenotypic selection showed significant linear and correlational gradients, lending support to expectations of functional interactions between floral traits. Significant correlational selection gradients found involved traits of different floral whorls, providing evidence for the existence of functional integration across developmental domains. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.

PubMed

Jiménez, Fernando; Sánchez, Gracia; Juárez, José M

2014-03-01

This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case-based reasoning) obtaining with ENORA a classification rate of 0.9298, specificity of 0.9385, and sensitivity of 0.9364, with 14.2 interpretable fuzzy rules on average. Our proposal improves the accuracy and interpretability of the classifiers, compared with other non-evolutionary techniques. We also conclude that ENORA outperforms niched pre-selection and NSGA-II algorithms. Moreover, given that our multi-objective evolutionary methodology is non-combinational based on real parameter optimization, the time cost is significantly reduced compared with other evolutionary approaches existing in literature based on combinational optimization. Copyright © 2014 Elsevier B.V. All rights reserved.

Computational Study of the Genomic and Epigenomic Phenomena

NASA Astrophysics Data System (ADS)

Yang, Wenjing

Biological systems are perhaps the ultimate complex systems, uniquely capable of processing and communicating information, reproducing in their lifetimes, and adapting in evolutionary time scales. My dissertation research focuses on using computational approaches to understand the biocomplexity manifested in the multitude of length scales and time scales. At the molecular and cellular level, central to the complex behavior of a biological system is the regulatory network. My research study focused on epigenetics, which is essential for multicellular organisms to establish cellular identity during development or in response to intracellular and environmental stimuli. My computational study of epigenomics is greatly facilitated by recent advances in high-throughput sequencing technology, which enables high-resolution snapshots of epigenomes and transcriptomes. Using human CD4+ T cell as a model system, the dynamical changes in epigenome and transcriptome pertinent to T cell activation were investigated at the genome scale. Going beyond traditional focus on transcriptional regulation, I provided evidences that post-transcriptional regulation may serve as a major component of the regulatory network. In addition, I explored alternative polyadenylation, another novel aspect of gene regulation, and how it cross-talks with the local chromatin structure. As the renowned theoretical biologist Theodosius Dobzhansky said eloquently, "Nothing in biology makes sense except in the light of evolution''. To better understand this ubiquitous driving force in the biological world, I went beyond molecular events in a single organism, and investigated the dynamical changes of population structure along the evolutionary time scale. To this end, we used HIV virus population dynamics in the host immune system as a model system. The evolution of HIV viral population plays a key role in AIDS immunopathogenesis with its exceptionally high mutation rate. However, the theoretical studies of the effect of recombination have been rather limited. Given the phylogenetic and experimental evidences for the high recombination rate and its important role in HIV evolution and epidemics, I established a mathematical model to study the effect of recombination, and explored the complex behavior of this dynamics system.

Using concepts from biology to improve problem-solving methods

NASA Astrophysics Data System (ADS)

Goodman, Erik D.; Rothwell, Edward J.; Averill, Ronald C.

2011-06-01

Observing nature has been a cornerstone of engineering design. Today, engineers look not only at finished products, but imitate the evolutionary process by which highly optimized artifacts have appeared in nature. Evolutionary computation began by capturing only the simplest ideas of evolution, but today, researchers study natural evolution and incorporate an increasing number of concepts in order to evolve solutions to complex engineering problems. At the new BEACON Center for the Study of Evolution in Action, studies in the lab and field and in silico are laying the groundwork for new tools for evolutionary engineering design. This paper, which accompanies a keynote address, describes various steps in development and application of evolutionary computation, particularly as regards sensor design, and sets the stage for future advances.

Evolution of the nucleus☆

PubMed Central

Devos, Damien P; Gräf, Ralph; Field, Mark C

2014-01-01

The nucleus represents a major evolutionary transition. As a consequence of separating translation from transcription many new functions arose, which likely contributed to the remarkable success of eukaryotic cells. Here we will consider what has recently emerged on the evolutionary histories of several key aspects of nuclear biology; the nuclear pore complex, the lamina, centrosomes and evidence for prokaryotic origins of relevant players. PMID:24508984

Cyclical parthenogenesis and viviparity in aphids as evolutionary novelties.

PubMed

Davis, Gregory K

2012-09-01

Evolutionary novelties represent challenges to biologists, particularly those who would like to understand the developmental and genetic changes responsible for their appearance. Most modern aphids possess two apparent evolutionary novelties: cyclical parthenogenesis (a life cycle with both sexual and asexual phases) and viviparity (internal development and live birth of progeny) in their asexual phase. Here I discuss the evolution of these apparent novelties from a developmental standpoint. Although a full understanding of the evolution of cyclical parthenogenesis and viviparity in aphids can seem a daunting task, these complex transitions can at least be broken down into a handful of steps. I argue that these should include the following: a differentiation of two developmentally distinct oocytes; de novo synthesis of centrosomes and modification of meiosis during asexual oogenesis; a loss or bypass of any cell cycle arrest and changes in key developmental events during viviparous oogenesis; and a change in how mothers specify the sexual vs. asexual fates of their progeny. Grappling with the nature of such steps and the order in which they occurred ought to increase our understanding and reduce the apparent novelty of complex evolutionary transitions. © 2012 Wiley Periodicals, Inc.

Mode and tempo in the evolution of socio-political organization: reconciling 'Darwinian' and 'Spencerian' evolutionary approaches in anthropology.

PubMed

Currie, Thomas E; Mace, Ruth

2011-04-12

Traditional investigations of the evolution of human social and political institutions trace their ancestry back to nineteenth century social scientists such as Herbert Spencer, and have concentrated on the increase in socio-political complexity over time. More recent studies of cultural evolution have been explicitly informed by Darwinian evolutionary theory and focus on the transmission of cultural traits between individuals. These two approaches to investigating cultural change are often seen as incompatible. However, we argue that many of the defining features and assumptions of 'Spencerian' cultural evolutionary theory represent testable hypotheses that can and should be tackled within a broader 'Darwinian' framework. In this paper we apply phylogenetic comparative techniques to data from Austronesian-speaking societies of Island South-East Asia and the Pacific to test hypotheses about the mode and tempo of human socio-political evolution. We find support for three ideas often associated with Spencerian cultural evolutionary theory: (i) political organization has evolved through a regular sequence of forms, (ii) increases in hierarchical political complexity have been more common than decreases, and (iii) political organization has co-evolved with the wider presence of hereditary social stratification.

Mode and tempo in the evolution of socio-political organization: reconciling ‘Darwinian’ and ‘Spencerian’ evolutionary approaches in anthropology

PubMed Central

Currie, Thomas E.; Mace, Ruth

2011-01-01

Traditional investigations of the evolution of human social and political institutions trace their ancestry back to nineteenth century social scientists such as Herbert Spencer, and have concentrated on the increase in socio-political complexity over time. More recent studies of cultural evolution have been explicitly informed by Darwinian evolutionary theory and focus on the transmission of cultural traits between individuals. These two approaches to investigating cultural change are often seen as incompatible. However, we argue that many of the defining features and assumptions of ‘Spencerian’ cultural evolutionary theory represent testable hypotheses that can and should be tackled within a broader ‘Darwinian’ framework. In this paper we apply phylogenetic comparative techniques to data from Austronesian-speaking societies of Island South-East Asia and the Pacific to test hypotheses about the mode and tempo of human socio-political evolution. We find support for three ideas often associated with Spencerian cultural evolutionary theory: (i) political organization has evolved through a regular sequence of forms, (ii) increases in hierarchical political complexity have been more common than decreases, and (iii) political organization has co-evolved with the wider presence of hereditary social stratification. PMID:21357233

Reduction of a metapopulation genetic model to an effective one-island model

NASA Astrophysics Data System (ADS)

Parra-Rojas, César; McKane, Alan J.

2018-04-01

We explore a model of metapopulation genetics which is based on a more ecologically motivated approach than is frequently used in population genetics. The size of the population is regulated by competition between individuals, rather than by artificially imposing a fixed population size. The increased complexity of the model is managed by employing techniques often used in the physical sciences, namely exploiting time-scale separation to eliminate fast variables and then constructing an effective model from the slow modes. We analyse this effective model and show that the predictions for the probability of fixation of the alleles and the mean time to fixation agree well with those found from numerical simulations of the original model. Contribution to the Focus Issue Evolutionary Modeling and Experimental Evolution edited by José Cuesta, Joachim Krug and Susanna Manrubia.

Marr's levels and the minimalist program.

PubMed

Johnson, Mark

2017-02-01

A simple change to a cognitive system at Marr's computational level may entail complex changes at the other levels of description of the system. The implementational level complexity of a change, rather than its computational level complexity, may be more closely related to the plausibility of a discrete evolutionary event causing that change. Thus the formal complexity of a change at the computational level may not be a good guide to the plausibility of an evolutionary event introducing that change. For example, while the Minimalist Program's Merge is a simple formal operation (Berwick & Chomsky, 2016), the computational mechanisms required to implement the language it generates (e.g., to parse the language) may be considerably more complex. This has implications for the theory of grammar: theories of grammar which involve several kinds of syntactic operations may be no less evolutionarily plausible than a theory of grammar that involves only one. A deeper understanding of human language at the algorithmic and implementational levels could strengthen Minimalist Program's account of the evolution of language.

Behavioral Genetic Toolkits: Toward the Evolutionary Origins of Complex Phenotypes.

PubMed

Rittschof, C C; Robinson, G E

2016-01-01

The discovery of toolkit genes, which are highly conserved genes that consistently regulate the development of similar morphological phenotypes across diverse species, is one of the most well-known observations in the field of evolutionary developmental biology. Surprisingly, this phenomenon is also relevant for a wide array of behavioral phenotypes, despite the fact that these phenotypes are highly complex and regulated by many genes operating in diverse tissues. In this chapter, we review the use of the toolkit concept in the context of behavior, noting the challenges of comparing behaviors and genes across diverse species, but emphasizing the successes in identifying genetic toolkits for behavior; these successes are largely attributable to the creative research approaches fueled by advances in behavioral genomics. We have two general goals: (1) to acknowledge the groundbreaking progress in this field, which offers new approaches to the difficult but exciting challenge of understanding the evolutionary genetic basis of behaviors, some of the most complex phenotypes known, and (2) to provide a theoretical framework that encompasses the scope of behavioral genetic toolkit studies in order to clearly articulate the research questions relevant to the toolkit concept. We emphasize areas for growth and highlight the emerging approaches that are being used to drive the field forward. Behavioral genetic toolkit research has elevated the use of integrative and comparative approaches in the study of behavior, with potentially broad implications for evolutionary biologists and behavioral ecologists alike. © 2016 Elsevier Inc. All rights reserved.

Sociality influences cultural complexity.

PubMed

Muthukrishna, Michael; Shulman, Ben W; Vasilescu, Vlad; Henrich, Joseph

2014-01-07

Archaeological and ethnohistorical evidence suggests a link between a population's size and structure, and the diversity or sophistication of its toolkits or technologies. Addressing these patterns, several evolutionary models predict that both the size and social interconnectedness of populations can contribute to the complexity of its cultural repertoire. Some models also predict that a sudden loss of sociality or of population will result in subsequent losses of useful skills/technologies. Here, we test these predictions with two experiments that permit learners to access either one or five models (teachers). Experiment 1 demonstrates that naive participants who could observe five models, integrate this information and generate increasingly effective skills (using an image editing tool) over 10 laboratory generations, whereas those with access to only one model show no improvement. Experiment 2, which began with a generation of trained experts, shows how learners with access to only one model lose skills (in knot-tying) more rapidly than those with access to five models. In the final generation of both experiments, all participants with access to five models demonstrate superior skills to those with access to only one model. These results support theoretical predictions linking sociality to cumulative cultural evolution.

Sociality influences cultural complexity

PubMed Central

Muthukrishna, Michael; Shulman, Ben W.; Vasilescu, Vlad; Henrich, Joseph

2014-01-01

Archaeological and ethnohistorical evidence suggests a link between a population's size and structure, and the diversity or sophistication of its toolkits or technologies. Addressing these patterns, several evolutionary models predict that both the size and social interconnectedness of populations can contribute to the complexity of its cultural repertoire. Some models also predict that a sudden loss of sociality or of population will result in subsequent losses of useful skills/technologies. Here, we test these predictions with two experiments that permit learners to access either one or five models (teachers). Experiment 1 demonstrates that naive participants who could observe five models, integrate this information and generate increasingly effective skills (using an image editing tool) over 10 laboratory generations, whereas those with access to only one model show no improvement. Experiment 2, which began with a generation of trained experts, shows how learners with access to only one model lose skills (in knot-tying) more rapidly than those with access to five models. In the final generation of both experiments, all participants with access to five models demonstrate superior skills to those with access to only one model. These results support theoretical predictions linking sociality to cumulative cultural evolution. PMID:24225461

Lessons from making the Structural Classification of Proteins (SCOP) and their implications for protein structure modelling.

PubMed

Andreeva, Antonina

2016-06-15

The Structural Classification of Proteins (SCOP) database has facilitated the development of many tools and algorithms and it has been successfully used in protein structure prediction and large-scale genome annotations. During the development of SCOP, numerous exceptions were found to topological rules, along with complex evolutionary scenarios and peculiarities in proteins including the ability to fold into alternative structures. This article reviews cases of structural variations observed for individual proteins and among groups of homologues, knowledge of which is essential for protein structure modelling. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

Foundations of “new” social science: Institutional legitimacy from philosophy, complexity science, postmodernism, and agent-based modeling

PubMed Central

Henrickson, Leslie; McKelvey, Bill

2002-01-01

Since the death of positivism in the 1970s, philosophers have turned their attention to scientific realism, evolutionary epistemology, and the Semantic Conception of Theories. Building on these trends, Campbellian Realism allows social scientists to accept real-world phenomena as criterion variables against which theories may be tested without denying the reality of individual interpretation and social construction. The Semantic Conception reduces the importance of axioms, but reaffirms the role of models and experiments. Philosophers now see models as “autonomous agents” that exert independent influence on the development of a science, in addition to theory and data. The inappropriate molding effects of math models on social behavior modeling are noted. Complexity science offers a “new” normal science epistemology focusing on order creation by self-organizing heterogeneous agents and agent-based models. The more responsible core of postmodernism builds on the idea that agents operate in a constantly changing web of interconnections among other agents. The connectionist agent-based models of complexity science draw on the same conception of social ontology as do postmodernists. These recent developments combine to provide foundations for a “new” social science centered on formal modeling not requiring the mathematical assumptions of agent homogeneity and equilibrium conditions. They give this “new” social science legitimacy in scientific circles that current social science approaches lack. PMID:12011408

Toward a unifying framework for evolutionary processes.

PubMed

Paixão, Tiago; Badkobeh, Golnaz; Barton, Nick; Çörüş, Doğan; Dang, Duc-Cuong; Friedrich, Tobias; Lehre, Per Kristian; Sudholt, Dirk; Sutton, Andrew M; Trubenová, Barbora

2015-10-21

The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Models of Cultural Niche Construction with Selection and Assortative Mating

PubMed Central

Feldman, Marcus W.

2012-01-01

Niche construction is a process through which organisms modify their environment and, as a result, alter the selection pressures on themselves and other species. In cultural niche construction, one or more cultural traits can influence the evolution of other cultural or biological traits by affecting the social environment in which the latter traits may evolve. Cultural niche construction may include either gene-culture or culture-culture interactions. Here we develop a model of this process and suggest some applications of this model. We examine the interactions between cultural transmission, selection, and assorting, paying particular attention to the complexities that arise when selection and assorting are both present, in which case stable polymorphisms of all cultural phenotypes are possible. We compare our model to a recent model for the joint evolution of religion and fertility and discuss other potential applications of cultural niche construction theory, including the evolution and maintenance of large-scale human conflict and the relationship between sex ratio bias and marriage customs. The evolutionary framework we introduce begins to address complexities that arise in the quantitative analysis of multiple interacting cultural traits. PMID:22905167

Undecidability and Irreducibility Conditions for Open-Ended Evolution and Emergence.

PubMed

Hernández-Orozco, Santiago; Hernández-Quiroz, Francisco; Zenil, Hector

2018-01-01

Is undecidability a requirement for open-ended evolution (OEE)? Using methods derived from algorithmic complexity theory, we propose robust computational definitions of open-ended evolution and the adaptability of computable dynamical systems. Within this framework, we show that decidability imposes absolute limits on the stable growth of complexity in computable dynamical systems. Conversely, systems that exhibit (strong) open-ended evolution must be undecidable, establishing undecidability as a requirement for such systems. Complexity is assessed in terms of three measures: sophistication, coarse sophistication, and busy beaver logical depth. These three complexity measures assign low complexity values to random (incompressible) objects. As time grows, the stated complexity measures allow for the existence of complex states during the evolution of a computable dynamical system. We show, however, that finding these states involves undecidable computations. We conjecture that for similar complexity measures that assign low complexity values, decidability imposes comparable limits on the stable growth of complexity, and that such behavior is necessary for nontrivial evolutionary systems. We show that the undecidability of adapted states imposes novel and unpredictable behavior on the individuals or populations being modeled. Such behavior is irreducible. Finally, we offer an example of a system, first proposed by Chaitin, that exhibits strong OEE.

Evolutionary dynamics with fluctuating population sizes and strong mutualism.

PubMed

Chotibut, Thiparat; Nelson, David R

2015-08-01

Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.

Evolutionary dynamics with fluctuating population sizes and strong mutualism

NASA Astrophysics Data System (ADS)

Chotibut, Thiparat; Nelson, David R.

2015-08-01

Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.

Engineering the object-relation database model in O-Raid

NASA Technical Reports Server (NTRS)

Dewan, Prasun; Vikram, Ashish; Bhargava, Bharat

1989-01-01

Raid is a distributed database system based on the relational model. O-raid is an extension of the Raid system and will support complex data objects. The design of O-Raid is evolutionary and retains all features of relational data base systems and those of a general purpose object-oriented programming language. O-Raid has several novel properties. Objects, classes, and inheritance are supported together with a predicate-base relational query language. O-Raid objects are compatible with C++ objects and may be read and manipulated by a C++ program without any 'impedance mismatch'. Relations and columns within relations may themselves be treated as objects with associated variables and methods. Relations may contain heterogeneous objects, that is, objects of more than one class in a certain column, which can individually evolve by being reclassified. Special facilities are provided to reduce the data search in a relation containing complex objects.

Modeling infectious disease dynamics in the complex landscape of global health

PubMed Central

Heesterbeek, Hans; Anderson, Roy; Andreasen, Viggo; Bansal, Shweta; De Angelis, Daniela; Dye, Chris; Eames, Ken; Edmunds, John; Frost, Simon; Funk, Sebastian; Hollingsworth, Deirdre; House, Thomas; Isham, Valerie; Klepac, Petra; Lessler, Justin; Lloyd-Smith, James; Metcalf, Jessica; Mollison, Denis; Pellis, Lorenzo; Pulliam, Juliet; Roberts, Mick; Viboud, Cecile

2015-01-01

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational and spatial scales, which even within a single pathogen often span hours to months, cellular to ecosystem levels, and local to pandemic spread. Some pathogens are directly transmitted between individuals of a single species, while others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity, and dynamic human behavior, raise prevention and control from formerly national to international issues. In the face of this complexity, mathematical models offer essential tools for synthesizing information to understand epidemiological patterns, and for developing the quantitative evidence base for decision-making in global health. PMID:25766240

Modeling infectious disease dynamics in the complex landscape of global health.

PubMed

Heesterbeek, Hans; Anderson, Roy M; Andreasen, Viggo; Bansal, Shweta; De Angelis, Daniela; Dye, Chris; Eames, Ken T D; Edmunds, W John; Frost, Simon D W; Funk, Sebastian; Hollingsworth, T Deirdre; House, Thomas; Isham, Valerie; Klepac, Petra; Lessler, Justin; Lloyd-Smith, James O; Metcalf, C Jessica E; Mollison, Denis; Pellis, Lorenzo; Pulliam, Juliet R C; Roberts, Mick G; Viboud, Cecile

2015-03-13

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health. Copyright © 2015, American Association for the Advancement of Science.

The evolution of contralateral control of the body by the brain: is it a protective mechanism?

PubMed

Whitehead, Lorne; Banihani, Saleh

2014-01-01

Contralateral control, the arrangement whereby most of the human motor and sensory fibres cross the midline in order to provide control for contralateral portions of the body, presents a puzzle from an evolutionary perspective. What caused such a counterintuitive and complex arrangement to become dominant? In this paper we offer a new perspective on this question by showing that in a complex interactive control system there could be a significant net survival advantage with contralateral control, associated with the effect of injuries of intermediate severity. In such cases an advantage could arise from a combination of non-linear system response combined with correlations between injuries on the same side of the head and body. We show that a simple mathematical model of these ideas emulates such an advantage. Based on this model, we conclude that effects of this kind are a plausible driving force for the evolution of contralateral control.

Modelling effects of diquat under realistic exposure patterns in genetically differentiated populations of the gastropod Lymnaea stagnalis

PubMed Central

Ducrot, Virginie; Péry, Alexandre R. R.; Lagadic, Laurent

2010-01-01

Pesticide use leads to complex exposure and response patterns in non-target aquatic species, so that the analysis of data from standard toxicity tests may result in unrealistic risk forecasts. Developing models that are able to capture such complexity from toxicity test data is thus a crucial issue for pesticide risk assessment. In this study, freshwater snails from two genetically differentiated populations of Lymnaea stagnalis were exposed to repeated acute applications of environmentally realistic concentrations of the herbicide diquat, from the embryo to the adult stage. Hatching rate, embryonic development duration, juvenile mortality, feeding rate and age at first spawning were investigated during both exposure and recovery periods. Effects of diquat on mortality were analysed using a threshold hazard model accounting for time-varying herbicide concentrations. All endpoints were significantly impaired at diquat environmental concentrations in both populations. Snail evolutionary history had no significant impact on their sensitivity and responsiveness to diquat, whereas food acted as a modulating factor of toxicant-induced mortality. The time course of effects was adequately described by the model, which thus appears suitable to analyse long-term effects of complex exposure patterns based upon full life cycle experiment data. Obtained model outputs (e.g. no-effect concentrations) could be directly used for chemical risk assessment. PMID:20921047

Modelling effects of diquat under realistic exposure patterns in genetically differentiated populations of the gastropod Lymnaea stagnalis.

PubMed

Ducrot, Virginie; Péry, Alexandre R R; Lagadic, Laurent

2010-11-12

Pesticide use leads to complex exposure and response patterns in non-target aquatic species, so that the analysis of data from standard toxicity tests may result in unrealistic risk forecasts. Developing models that are able to capture such complexity from toxicity test data is thus a crucial issue for pesticide risk assessment. In this study, freshwater snails from two genetically differentiated populations of Lymnaea stagnalis were exposed to repeated acute applications of environmentally realistic concentrations of the herbicide diquat, from the embryo to the adult stage. Hatching rate, embryonic development duration, juvenile mortality, feeding rate and age at first spawning were investigated during both exposure and recovery periods. Effects of diquat on mortality were analysed using a threshold hazard model accounting for time-varying herbicide concentrations. All endpoints were significantly impaired at diquat environmental concentrations in both populations. Snail evolutionary history had no significant impact on their sensitivity and responsiveness to diquat, whereas food acted as a modulating factor of toxicant-induced mortality. The time course of effects was adequately described by the model, which thus appears suitable to analyse long-term effects of complex exposure patterns based upon full life cycle experiment data. Obtained model outputs (e.g. no-effect concentrations) could be directly used for chemical risk assessment.

Embryonic and larval development in the Midas cichlid fish species flock (Amphilophus spp.): a new evo-devo model for the investigation of adaptive novelties and species differences.

PubMed

Kratochwil, Claudius F; Sefton, Maggie M; Meyer, Axel

2015-02-26

Central American crater lake cichlid fish of the Midas species complex (Amphilophus spp.) are a model system for sympatric speciation and fast ecological diversification and specialization. Midas cichlids have been intensively analyzed from an ecological and morphological perspective. Genomic resources such as transcriptomic and genomic data sets, and a high-quality draft genome are available now. Many ecologically relevant species-specific traits and differences such as pigmentation and cranial morphology arise during development. Detailed descriptions of the early development of the Midas cichlid in particular, will help to investigate the ontogeny of species differences and adaptations. We describe the embryonic and larval development of the crater lake cichlid, Amphilophus xiloaensis, until seven days after fertilization. Similar to previous studies on teleost development, we describe six periods of embryogenesis - the zygote, cleavage, blastula, gastrula, segmentation, and post-hatching period. Furthermore, we define homologous stages to well-described teleost models such as medaka and zebrafish, as well as other cichlid species such as the Nile tilapia and the South American cichlid Cichlasoma dimerus. Key morphological differences between the embryos of Midas cichlids and other teleosts are highlighted and discussed, including the presence of adhesive glands and different early chromatophore patterns, as well as variation in developmental timing. The developmental staging of the Midas cichlid will aid researchers in the comparative investigation of teleost ontogenies. It will facilitate comparative developmental biological studies of Neotropical and African cichlid fish in particular. In the past, the species flocks of the African Great Lakes have received the most attention from researchers, but some lineages of the 300-400 species of Central American lakes are fascinating model systems for adaptive radiation and rapid phenotypic evolution. The availability of genetic resources, their status as a model system for evolutionary research, and the possibility to perform functional experiments including transgenesis makes the Midas cichlid complex a very attractive model for evolutionary-developmental research.

Effects of Mitochondrial DNA Rate Variation on Reconstruction of Pleistocene Demographic History in a Social Avian Species, Pomatostomus superciliosus

PubMed Central

Norman, Janette A.; Blackmore, Caroline J.; Rourke, Meaghan; Christidis, Les

2014-01-01

Mitochondrial sequence data is often used to reconstruct the demographic history of Pleistocene populations in an effort to understand how species have responded to past climate change events. However, departures from neutral equilibrium conditions can confound evolutionary inference in species with structured populations or those that have experienced periods of population expansion or decline. Selection can affect patterns of mitochondrial DNA variation and variable mutation rates among mitochondrial genes can compromise inferences drawn from single markers. We investigated the contribution of these factors to patterns of mitochondrial variation and estimates of time to most recent common ancestor (TMRCA) for two clades in a co-operatively breeding avian species, the white-browed babbler Pomatostomus superciliosus. Both the protein-coding ND3 gene and hypervariable domain I control region sequences showed departures from neutral expectations within the superciliosus clade, and a two-fold difference in TMRCA estimates. Bayesian phylogenetic analysis provided evidence of departure from a strict clock model of molecular evolution in domain I, leading to an over-estimation of TMRCA for the superciliosus clade at this marker. Our results suggest mitochondrial studies that attempt to reconstruct Pleistocene demographic histories should rigorously evaluate data for departures from neutral equilibrium expectations, including variation in evolutionary rates across multiple markers. Failure to do so can lead to serious errors in the estimation of evolutionary parameters and subsequent demographic inferences concerning the role of climate as a driver of evolutionary change. These effects may be especially pronounced in species with complex social structures occupying heterogeneous environments. We propose that environmentally driven differences in social structure may explain observed differences in evolutionary rate of domain I sequences, resulting from longer than expected retention times for matriarchal lineages in the superciliosus clade. PMID:25181547

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

The fundamental nature of an evolving one-dimensional (1D) Ising model is investigated with an elementary cellular automaton (CA) simulation. The emergent CA simulation employs an ensemble of cells in one spatial dimension, each cell capable of two microstates interacting with simple nearest-neighbor rules and incorporating an external field. The behavior of the CA model provides insight into the dynamics of coupled two-state systems not expressible by exact analytical solutions. For instance, state progression graphs show the causal dynamics of a system through time in relation to the system's entropy. Unique graphical analysis techniques are introduced through difference patterns, diffusion patterns, and state progression graphs of the 1D ensemble visualizing the evolution. All analyses are consistent with the known behavior of the 1D Ising system. The CA simulation and new pattern recognition techniques are scalable (in both dimension, complexity, and size) and have many potential applications such as complex design of materials, control of agent systems, and evolutionary mechanism design.

Heterogeneous update mechanisms in evolutionary games: Mixing innovative and imitative dynamics

NASA Astrophysics Data System (ADS)

Amaral, Marco Antonio; Javarone, Marco Alberto

2018-04-01

Innovation and evolution are two processes of paramount relevance for social and biological systems. In general, the former allows the introduction of elements of novelty, while the latter is responsible for the motion of a system in its phase space. Often, these processes are strongly related, since an innovation can trigger the evolution, and the latter can provide the optimal conditions for the emergence of innovations. Both processes can be studied by using the framework of evolutionary game theory, where evolution constitutes an intrinsic mechanism. At the same time, the concept of innovation requires an opportune mathematical representation. Notably, innovation can be modeled as a strategy, or it can constitute the underlying mechanism that allows agents to change strategy. Here, we analyze the second case, investigating the behavior of a heterogeneous population, composed of imitative and innovative agents. Imitative agents change strategy only by imitating that of their neighbors, whereas innovative ones change strategy without the need for a copying source. The proposed model is analyzed by means of analytical calculations and numerical simulations in different topologies. Remarkably, results indicate that the mixing of mechanisms can be detrimental to cooperation near phase transitions. In those regions, the spatial reciprocity from imitative mechanisms is destroyed by innovative agents, leading to the downfall of cooperation. Our investigation sheds some light on the complex dynamics emerging from the heterogeneity of strategy revision methods, highlighting the role of innovation in evolutionary games.

Heterogeneous update mechanisms in evolutionary games: Mixing innovative and imitative dynamics.

PubMed

Amaral, Marco Antonio; Javarone, Marco Alberto

2018-04-01

Innovation and evolution are two processes of paramount relevance for social and biological systems. In general, the former allows the introduction of elements of novelty, while the latter is responsible for the motion of a system in its phase space. Often, these processes are strongly related, since an innovation can trigger the evolution, and the latter can provide the optimal conditions for the emergence of innovations. Both processes can be studied by using the framework of evolutionary game theory, where evolution constitutes an intrinsic mechanism. At the same time, the concept of innovation requires an opportune mathematical representation. Notably, innovation can be modeled as a strategy, or it can constitute the underlying mechanism that allows agents to change strategy. Here, we analyze the second case, investigating the behavior of a heterogeneous population, composed of imitative and innovative agents. Imitative agents change strategy only by imitating that of their neighbors, whereas innovative ones change strategy without the need for a copying source. The proposed model is analyzed by means of analytical calculations and numerical simulations in different topologies. Remarkably, results indicate that the mixing of mechanisms can be detrimental to cooperation near phase transitions. In those regions, the spatial reciprocity from imitative mechanisms is destroyed by innovative agents, leading to the downfall of cooperation. Our investigation sheds some light on the complex dynamics emerging from the heterogeneity of strategy revision methods, highlighting the role of innovation in evolutionary games.

An Interdisciplinary Model for Teaching Evolutionary Ecology.

ERIC Educational Resources Information Center

Coletta, John

1992-01-01

Describes a general systems evolutionary model and demonstrates how a previously established ecological model is a function of its past development based on the evolution of the rock, nutrient, and water cycles. Discusses the applications of the model in environmental education. (MDH)

Concepts and models of coupled systems

NASA Astrophysics Data System (ADS)

Ertsen, Maurits

2017-04-01

In this paper, I will especially focus on the question of the position of human agency, social networks and complex co-evolutionary interactions in socio-hydrological models. The long term perspective of complex systems' modeling typically focuses on regional or global spatial scales and century/millennium time scales. It is still a challenge to relate correlations in outcomes defined at those longer and larger scales to the causalities at the shorter and smaller scales. How do we move today to the next 1000 years in the same way that our ancestors did move from their today to our present, in the small steps that produce reality? Please note, I am not arguing long term work is not interesting or the like. I just pose the question how to deal with the problem that we employ relations with hindsight that matter to us, but not necessarily to the agents that produced the relations we think we have observed. I would like to push the socio-hydrological community a little into rethinking how to deal with complexity, with the aim to bring together the timescales of humans and complexity. I will provide one or two examples of how larger-scale and longer-term observations on water flows and environmental loads can be broken down into smaller-scale and shorter-term production processes of these same loads.

Expert-guided evolutionary algorithm for layout design of complex space stations

NASA Astrophysics Data System (ADS)

Qian, Zhiqin; Bi, Zhuming; Cao, Qun; Ju, Weiguo; Teng, Hongfei; Zheng, Yang; Zheng, Siyu

2017-08-01

The layout of a space station should be designed in such a way that different equipment and instruments are placed for the station as a whole to achieve the best overall performance. The station layout design is a typical nondeterministic polynomial problem. In particular, how to manage the design complexity to achieve an acceptable solution within a reasonable timeframe poses a great challenge. In this article, a new evolutionary algorithm has been proposed to meet such a challenge. It is called as the expert-guided evolutionary algorithm with a tree-like structure decomposition (EGEA-TSD). Two innovations in EGEA-TSD are (i) to deal with the design complexity, the entire design space is divided into subspaces with a tree-like structure; it reduces the computation and facilitates experts' involvement in the solving process. (ii) A human-intervention interface is developed to allow experts' involvement in avoiding local optimums and accelerating convergence. To validate the proposed algorithm, the layout design of one-space station is formulated as a multi-disciplinary design problem, the developed algorithm is programmed and executed, and the result is compared with those from other two algorithms; it has illustrated the superior performance of the proposed EGEA-TSD.

Quantification of complex modular architecture in plants.

PubMed

Reeb, Catherine; Kaandorp, Jaap; Jansson, Fredrik; Puillandre, Nicolas; Dubuisson, Jean-Yves; Cornette, Raphaël; Jabbour, Florian; Coudert, Yoan; Patiño, Jairo; Flot, Jean-François; Vanderpoorten, Alain

2018-04-01

Morphometrics, the assignment of quantities to biological shapes, is a powerful tool to address taxonomic, evolutionary, functional and developmental questions. We propose a novel method for shape quantification of complex modular architecture in thalloid plants, whose extremely reduced morphologies, combined with the lack of a formal framework for thallus description, have long rendered taxonomic and evolutionary studies extremely challenging. Using graph theory, thalli are described as hierarchical series of nodes and edges, allowing for accurate, homologous and repeatable measurements of widths, lengths and angles. The computer program MorphoSnake was developed to extract the skeleton and contours of a thallus and automatically acquire, at each level of organization, width, length, angle and sinuosity measurements. Through the quantification of leaf architecture in Hymenophyllum ferns (Polypodiopsida) and a fully worked example of integrative taxonomy in the taxonomically challenging thalloid liverwort genus Riccardia, we show that MorphoSnake is applicable to all ramified plants. This new possibility of acquiring large numbers of quantitative traits in plants with complex modular architectures opens new perspectives of applications, from the development of rapid species identification tools to evolutionary analyses of adaptive plasticity. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

PubMed

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

Is evolutionary biology becoming too politically correct? A reflection on the scala naturae, phylogenetically basal clades, anatomically plesiomorphic taxa, and 'lower' animals.

PubMed

Diogo, Rui; Ziermann, Janine M; Linde-Medina, Marta

2015-05-01

The notion of scala naturae dates back to thinkers such as Aristotle, who placed plants below animals and ranked the latter along a graded scale of complexity from 'lower' to 'higher' animals, such as humans. In the last decades, evolutionary biologists have tended to move from one extreme (i.e. the idea of scala naturae or the existence of a general evolutionary trend in complexity from 'lower' to "higher" taxa, with Homo sapiens as the end stage) to the other, opposite, extreme (i.e. to avoid using terms such as 'phylogenetically basal' and 'anatomically plesiomorphic' taxa, which are seen as the undesired vestige of old teleological theories). The latter view tries to avoid any possible connotations with the original anthropocentric idea of a scala naturae crowned by man and, in that sense, it can be regarded as a more politically correct view. In the past years and months there has been renewed interest in these topics, which have been discussed in various papers and monographs that tend to subscribe, in general, to the points defended in the more politically correct view. Importantly, most evolutionary and phylogenetic studies of tetrapods and other vertebrates, and therefore most discussions on the scala naturae and related issues have been based on hard tissue and, more recently, on molecular data. Here we provide the first discussion of these topics based on a comparative myological study of all the major vertebrate clades and of myological cladistic and Bayesian phylogenetic analyses of bony fish and tetrapods, including Primates. We specifically (i) contradict the notions of a scala naturae or evolutionary progressive trends leading to more complexity in 'higher' animals and culminating in Homo sapiens, and (ii) stress that the refutation of these old notions does not necessarily mean that one should not keep using the terms 'phylogenetically basal' and particularly 'anatomically plesiomorphic' to refer to groups such as the urodeles within the Tetrapoda, or the strepsirrhines and lemurs within the Primates, for instance. This review will contribute to improving our understanding of these broad evolutionary issues and of the evolution of the vertebrate Bauplans, and hopefully will stimulate future phylogenetic, evolutionary and developmental studies of these clades. © 2014 The Authors. Biological Reviews © 2014 Cambridge Philosophical Society.

Revisiting the phylogeography, demography and taxonomy of the frog genus Ptychadena in the Ethiopian highlands with the use of genome-wide SNP data.

PubMed

Reyes-Velasco, Jacobo; Manthey, Joseph D; Bourgeois, Yann; Freilich, Xenia; Boissinot, Stéphane

2018-01-01

Understanding the diversification of biological lineages is central to evolutionary studies. To properly study the process of speciation, it is necessary to link micro-evolutionary studies with macro-evolutionary mechanisms. Micro-evolutionary studies require proper sampling across a taxon's range to adequately infer genetic diversity. Here we use the grass frogs of the genus Ptychadena from the Ethiopian highlands as a model to study the process of lineage diversification in this unique biodiversity hotspot. We used thousands of genome-wide SNPs obtained from double digest restriction site associated DNA sequencing (ddRAD-seq) in populations of the Ptychadena neumanni species complex from the Ethiopian highlands in order to infer their phylogenetic relationships and genetic structure, as well as to study their demographic history. Our genome-wide phylogenetic study supports the existence of approximately 13 lineages clustered into 3 species groups. Our phylogenetic and phylogeographic reconstructions suggest that those endemic lineages diversified in allopatry, and subsequently specialized to different habitats and elevations. Demographic analyses point to a continuous decrease in the population size across the majority of lineages and populations during the Pleistocene, which is consistent with a continuous period of aridification that East Africa experienced since the Pliocene. We discuss the taxonomic implications of our analyses and, in particular, we warn against the recent practice to solely use Bayesian species delimitation methods when proposing taxonomic changes.

Ecological genetics of sediment browsing behaviour in a planktonic crustacean.

PubMed

Arbore, R; Andras, J P; Routtu, J; Ebert, D

2016-10-01

Zooplankton can display complex habitat selection behaviours that influence the way they interact with their environments. Some species, although primarily pelagic, can exploit sediment-borne particles as a food source or use sediments as a refuge from pelagic predation. However, this strategy may increase the exposure to other risks such as benthic predation and infection from sediment-borne parasite transmission stages. The evolution of habitat selection behaviour in these species is thus expected to be influenced by multiple and possibly contrasting selective forces. Here, we study the browsing behaviour of the water flea Daphnia magna on bottom sediments. First, we demonstrated genetic variation for sediment browsing among D. magna genotypes from natural populations sampled across a broad geographic range. Next, we used an F2 recombinant panel to perform a QTL analysis and identified three regions in the D. magna genome contributing to variation in browsing behaviour. We also analysed the correlation between our data and previously published data on the phototactic behaviour of genotypes from the same F2 panel. Clonal means of the two behavioral traits were not correlated, suggesting that they may evolve independently. Browsing behaviour is likely to be a relevant component of habitat selection in D. magna, and its study may help to incorporate the interactions with the sediment into eco-evolutionary models of this key freshwater species. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

The evolutionary ecology of the Lygaeidae

PubMed Central

Burdfield-Steel, Emily R; Shuker, David M

2014-01-01

The Lygaeidae (sensu lato) are a highly successful family of true bugs found worldwide, yet many aspects of their ecology and evolution remain obscure or unknown. While a few species have attracted considerable attention as model species for the study of insect physiology, it is only relatively recently that biologists have begun to explore aspects of their behavior, life history evolution, and patterns of intra- and interspecific ecological interactions across more species. As a result though, a range of new phenotypes and opportunities for addressing current questions in evolutionary ecology has been uncovered. For example, researchers have revealed hitherto unexpectedly rich patterns of bacterial symbiosis, begun to explore the evolutionary function of the family's complex genitalia, and also found evidence of parthenogenesis. Here we review our current understanding of the biology and ecology of the group as a whole, focusing on several of the best-studied characteristics of the group, including aposematism (i.e., the evolution of warning coloration), chemical communication, sexual selection (especially, postcopulatory sexual selection), sexual conflict, and patterns of host-endosymbiont coevolution. Importantly, many of these aspects of lygaeid biology are likely to interact, offering new avenues for research, for instance into how the evolution of aposematism influences sexual selection. With the growing availability of genomic tools for previously “non-model” organisms, combined with the relative ease of keeping many of the polyphagous species in the laboratory, we argue that these bugs offer many opportunities for behavioral and evolutionary ecologists. PMID:25360267

Revisiting the phylogeography, demography and taxonomy of the frog genus Ptychadena in the Ethiopian highlands with the use of genome-wide SNP data

PubMed Central

Manthey, Joseph D.; Bourgeois, Yann; Freilich, Xenia; Boissinot, Stéphane

2018-01-01

Understanding the diversification of biological lineages is central to evolutionary studies. To properly study the process of speciation, it is necessary to link micro-evolutionary studies with macro-evolutionary mechanisms. Micro-evolutionary studies require proper sampling across a taxon’s range to adequately infer genetic diversity. Here we use the grass frogs of the genus Ptychadena from the Ethiopian highlands as a model to study the process of lineage diversification in this unique biodiversity hotspot. We used thousands of genome-wide SNPs obtained from double digest restriction site associated DNA sequencing (ddRAD-seq) in populations of the Ptychadena neumanni species complex from the Ethiopian highlands in order to infer their phylogenetic relationships and genetic structure, as well as to study their demographic history. Our genome-wide phylogenetic study supports the existence of approximately 13 lineages clustered into 3 species groups. Our phylogenetic and phylogeographic reconstructions suggest that those endemic lineages diversified in allopatry, and subsequently specialized to different habitats and elevations. Demographic analyses point to a continuous decrease in the population size across the majority of lineages and populations during the Pleistocene, which is consistent with a continuous period of aridification that East Africa experienced since the Pliocene. We discuss the taxonomic implications of our analyses and, in particular, we warn against the recent practice to solely use Bayesian species delimitation methods when proposing taxonomic changes. PMID:29389966

Insights into the origin and distribution of biodiversity in the Brazilian Atlantic forest hot spot: a statistical phylogeographic study using a low-dispersal organism.

PubMed

Álvarez-Presas, M; Sánchez-Gracia, A; Carbayo, F; Rozas, J; Riutort, M

2014-06-01

The relative importance of the processes that generate and maintain biodiversity is a major and controversial topic in evolutionary biology with large implications for conservation management. The Atlantic Forest of Brazil, one of the world's richest biodiversity hot spots, is severely damaged by human activities. To formulate an efficient conservation policy, a good understanding of spatial and temporal biodiversity patterns and their underlying evolutionary mechanisms is required. With this aim, we performed a comprehensive phylogeographic study using a low-dispersal organism, the land planarian species Cephaloflexa bergi (Platyhelminthes, Tricladida). Analysing multi-locus DNA sequence variation under the Approximate Bayesian Computation framework, we evaluated two scenarios proposed to explain the diversity of Southern Atlantic Forest (SAF) region. We found that most sampled localities harbour high levels of genetic diversity, with lineages sharing common ancestors that predate the Pleistocene. Remarkably, we detected the molecular hallmark of the isolation-by-distance effect and little evidence of a recent colonization of SAF localities; nevertheless, some populations might result from very recent secondary contacts. We conclude that extant SAF biodiversity originated and has been shaped by complex interactions between ancient geological events and more recent evolutionary processes, whereas Pleistocene climate changes had a minor influence in generating present-day diversity. We also demonstrate that land planarians are an advantageous biological model for making phylogeographic and, particularly, fine-scale evolutionary inferences, and propose appropriate conservation policies.

Protein Flexibility Facilitates Quaternary Structure Assembly and Evolution

PubMed Central

Marsh, Joseph A.; Teichmann, Sarah A.

2014-01-01

The intrinsic flexibility of proteins allows them to undergo large conformational fluctuations in solution or upon interaction with other molecules. Proteins also commonly assemble into complexes with diverse quaternary structure arrangements. Here we investigate how the flexibility of individual protein chains influences the assembly and evolution of protein complexes. We find that flexibility appears to be particularly conducive to the formation of heterologous (i.e., asymmetric) intersubunit interfaces. This leads to a strong association between subunit flexibility and homomeric complexes with cyclic and asymmetric quaternary structure topologies. Similarly, we also observe that the more nonhomologous subunits that assemble together within a complex, the more flexible those subunits tend to be. Importantly, these findings suggest that subunit flexibility should be closely related to the evolutionary history of a complex. We confirm this by showing that evolutionarily more recent subunits are generally more flexible than evolutionarily older subunits. Finally, we investigate the very different explorations of quaternary structure space that have occurred in different evolutionary lineages. In particular, the increased flexibility of eukaryotic proteins appears to enable the assembly of heteromeric complexes with more unique components. PMID:24866000

Pain expressiveness and altruistic behavior: an exploration using agent-based modeling.

PubMed

de C Williams, Amanda C; Gallagher, Elizabeth; Fidalgo, Antonio R; Bentley, Peter J

2016-03-01

Predictions which invoke evolutionary mechanisms are hard to test. Agent-based modeling in artificial life offers a way to simulate behaviors and interactions in specific physical or social environments over many generations. The outcomes have implications for understanding adaptive value of behaviors in context. Pain-related behavior in animals is communicated to other animals that might protect or help, or might exploit or predate. An agent-based model simulated the effects of displaying or not displaying pain (expresser/nonexpresser strategies) when injured and of helping, ignoring, or exploiting another in pain (altruistic/nonaltruistic/selfish strategies). Agents modeled in MATLAB interacted at random while foraging (gaining energy); random injury interrupted foraging for a fixed time unless help from an altruistic agent, who paid an energy cost, speeded recovery. Environmental and social conditions also varied, and each model ran for 10,000 iterations. Findings were meaningful in that, in general, contingencies that evident from experimental work with a variety of mammals, over a few interactions, were replicated in the agent-based model after selection pressure over many generations. More energy-demanding expression of pain reduced its frequency in successive generations, and increasing injury frequency resulted in fewer expressers and altruists. Allowing exploitation of injured agents decreased expression of pain to near zero, but altruists remained. Decreasing costs or increasing benefits of helping hardly changed its frequency, whereas increasing interaction rate between injured agents and helpers diminished the benefits to both. Agent-based modeling allows simulation of complex behaviors and environmental pressures over evolutionary time.

Bistability of Evolutionary Stable Vaccination Strategies in the Reinfection SIRI Model.

PubMed

Martins, José; Pinto, Alberto

2017-04-01

We use the reinfection SIRI epidemiological model to analyze the impact of education programs and vaccine scares on individuals decisions to vaccinate or not. The presence of the reinfection provokes the novelty of the existence of three Nash equilibria for the same level of the morbidity relative risk instead of a single Nash equilibrium as occurs in the SIR model studied by Bauch and Earn (PNAS 101:13391-13394, 2004). The existence of three Nash equilibria, with two of them being evolutionary stable, introduces two scenarios with relevant and opposite features for the same level of the morbidity relative risk: the low-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a low probability; and the high-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a high probability. We introduce the evolutionary vaccination dynamics for the SIRI model and we prove that it is bistable. The bistability of the evolutionary dynamics indicates that the damage provoked by false scares on the vaccination perceived morbidity risks can be much higher and much more persistent than in the SIR model. Furthermore, the vaccination education programs to be efficient they need to implement a mechanism to suddenly increase the vaccination coverage level.

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology

PubMed Central

Cankorur-Cetinkaya, Ayca; Dias, Joao M. L.; Kludas, Jana; Slater, Nigel K. H.; Rousu, Juho; Dikicioglu, Duygu

2017-01-01

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple‐to‐use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257). PMID:28635591

Can you sequence ecology? Metagenomics of adaptive diversification.

PubMed

Marx, Christopher J

2013-01-01

Few areas of science have benefited more from the expansion in sequencing capability than the study of microbial communities. Can sequence data, besides providing hypotheses of the functions the members possess, detect the evolutionary and ecological processes that are occurring? For example, can we determine if a species is adapting to one niche, or if it is diversifying into multiple specialists that inhabit distinct niches? Fortunately, adaptation of populations in the laboratory can serve as a model to test our ability to make such inferences about evolution and ecology from sequencing. Even adaptation to a single niche can give rise to complex temporal dynamics due to the transient presence of multiple competing lineages. If there are multiple niches, this complexity is augmented by segmentation of the population into multiple specialists that can each continue to evolve within their own niche. For a known example of parallel diversification that occurred in the laboratory, sequencing data gave surprisingly few obvious, unambiguous signs of the ecological complexity present. Whereas experimental systems are open to direct experimentation to test hypotheses of selection or ecological interaction, the difficulty in "seeing ecology" from sequencing for even such a simple system suggests translation to communities like the human microbiome will be quite challenging. This will require both improved empirical methods to enhance the depth and time resolution for the relevant polymorphisms and novel statistical approaches to rigorously examine time-series data for signs of various evolutionary and ecological phenomena within and between species.

Evolutionary change in physiological phenotypes along the human lineage

PubMed Central

Vining, Alexander Q.; Nunn, Charles L.

2016-01-01

Background and Objectives: Research in evolutionary medicine provides many examples of how evolution has shaped human susceptibility to disease. Traits undergoing rapid evolutionary change may result in associated costs or reduce the energy available to other traits. We hypothesize that humans have experienced more such changes than other primates as a result of major evolutionary change along the human lineage. We investigated 41 physiological traits across 50 primate species to identify traits that have undergone marked evolutionary change along the human lineage. Methodology: We analysed the data using two Bayesian phylogenetic comparative methods. One approach models trait covariation in non-human primates and predicts human phenotypes to identify whether humans are evolutionary outliers. The other approach models adaptive shifts under an Ornstein-Uhlenbeck model of evolution to assess whether inferred shifts are more common on the human branch than on other primate lineages. Results: We identified four traits with strong evidence for an evolutionary increase on the human lineage (amylase, haematocrit, phosphorus and monocytes) and one trait with strong evidence for decrease (neutrophilic bands). Humans exhibited more cases of distinct evolutionary change than other primates. Conclusions and Implications: Human physiology has undergone increased evolutionary change compared to other primates. Long distance running may have contributed to increases in haematocrit and mean corpuscular haemoglobin concentration, while dietary changes are likely related to increases in amylase. In accordance with the pathogen load hypothesis, human monocyte levels were increased, but many other immune-related measures were not. Determining the mechanisms underlying conspicuous evolutionary change in these traits may provide new insights into human disease. PMID:27615376

Modeling the Land Use/Cover Change in an Arid Region Oasis City Constrained by Water Resource and Environmental Policy Change using Cellular Automata Model

NASA Astrophysics Data System (ADS)

Hu, X.; Li, X.; Lu, L.

2017-12-01

Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.

Evolutionary suicide through a non-catastrophic bifurcation: adaptive dynamics of pathogens with frequency-dependent transmission.

PubMed

Boldin, Barbara; Kisdi, Éva

2016-03-01

Evolutionary suicide is a riveting phenomenon in which adaptive evolution drives a viable population to extinction. Gyllenberg and Parvinen (Bull Math Biol 63(5):981-993, 2001) showed that, in a wide class of deterministic population models, a discontinuous transition to extinction is a necessary condition for evolutionary suicide. An implicit assumption of their proof is that the invasion fitness of a rare strategy is well-defined also in the extinction state of the population. Epidemic models with frequency-dependent incidence, which are often used to model the spread of sexually transmitted infections or the dynamics of infectious diseases within herds, violate this assumption. In these models, evolutionary suicide can occur through a non-catastrophic bifurcation whereby pathogen adaptation leads to a continuous decline of host (and consequently pathogen) population size to zero. Evolutionary suicide of pathogens with frequency-dependent transmission can occur in two ways, with pathogen strains evolving either higher or lower virulence.

A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming.

PubMed

Cotto, Olivier; Wessely, Johannes; Georges, Damien; Klonner, Günther; Schmid, Max; Dullinger, Stefan; Thuiller, Wilfried; Guillaume, Frédéric

2017-05-05

Withstanding extinction while facing rapid climate change depends on a species' ability to track its ecological niche or to evolve a new one. Current methods that predict climate-driven species' range shifts use ecological modelling without eco-evolutionary dynamics. Here we present an eco-evolutionary forecasting framework that combines niche modelling with individual-based demographic and genetic simulations. Applying our approach to four endemic perennial plant species of the Austrian Alps, we show that accounting for eco-evolutionary dynamics when predicting species' responses to climate change is crucial. Perennial species persist in unsuitable habitats longer than predicted by niche modelling, causing delayed range losses; however, their evolutionary responses are constrained because long-lived adults produce increasingly maladapted offspring. Decreasing population size due to maladaptation occurs faster than the contraction of the species range, especially for the most abundant species. Monitoring of species' local abundance rather than their range may likely better inform on species' extinction risks under climate change.

Inferring the evolutionary stages of the internal structures of NGC 7538 S and IRS1 from chemistry

NASA Astrophysics Data System (ADS)

Feng, S.; Beuther, H.; Semenov, D.; Henning, Th.; Linz, H.; Mills, E. A. C.; Teague, R.

2016-09-01

Context. Radiative feedback of young (proto)stars and gas dynamics including gravitational collapse and outflows are important in high-mass star-forming regions (HMSFRs), for the reason that they may leave footprints on the gas density and temperature distributions, the velocity profile, and the chemical abundances. Aims: We unambiguously diagnose the detailed physical mechanisms and the evolutionary status of HMSFRs. Methods: We performed 0.4'' (~1000 AU) resolution observations at 1.37 mm towards two HMSFRs, NGC 7538 S and IRS1, using the Plateau de Bure Interferometre (PdBI). The observations covered abundant molecular lines, including tracers of gas column density, hot molecular cores, shocks, and complex organic molecules. We present a joint analysis of the 1.37 mm continuum emission and the line intensity of 15 molecular species (including 22 isotopologues). Assuming local thermal equilibrium (LTE), we derived molecular column densities and molecular abundances for each internal gas substructure that is spatially resolved. These derived quantities are compared with a suite of 1D gas-grain models. Results: NGC 7538 S is resolved into at least three dense gas condensations. Despite the comparable continuum intensity of these condensations, their differing molecular line emission is suggestive of an overall chemical evolutionary trend from the northeast to the southwest. Line emission from MM1 is consistent with a chemically evolved hot molecular core (HMC), whereas MM3 remains a prestellar candidate that only exhibits emission of lower-excitation lines. The condensation MM2, located between MM1 and MM3, shows an intermediate chemical evolutionary status. Since these three condensations are embedded within the same parent gas core, their differing chemical properties are most likely due to the different warm-up histories, rather than the different dynamic timescales. Despite remaining spatially unresolved, in IRS1 we detect abundant complex organic molecules (e.g. NH2CHO, CH3OH, HCOOCH3, CH3OCH3), indicating that IRS1 is the most chemically evolved HMC presented here. We observe a continuum that is dominated by absorption features with at least three strong emission lines, potentially from CH3OH. The CH3OH lines which are purely in emission have higher excitation than the ones being purely in absorption. Potential reasons for this difference are discussed. Conclusions: This is the first comprehensive comparison of observations of the two high-mass cores NGC 7538 S and IRS1 and a chemical model. We have found that different chemical evolutionary stages can coexist in the same natal gas core. Our achievement illustrates the strength of chemical analysis for understanding HMSFRs.

Stimulating Scientific Reasoning with Drawing-Based Modeling

ERIC Educational Resources Information Center

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-01-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

Comparison of multiobjective evolutionary algorithms: empirical results.

PubMed

Zitzler, E; Deb, K; Thiele, L

2000-01-01

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these different problem features separately, it is possible to predict the kind of problems to which a certain technique is or is not well suited. However, in contrast to what was suspected beforehand, the experimental results indicate a hierarchy of the algorithms under consideration. Furthermore, the emerging effects are evidence that the suggested test functions provide sufficient complexity to compare multiobjective optimizers. Finally, elitism is shown to be an important factor for improving evolutionary multiobjective search.

Understanding the mind from an evolutionary perspective: an overview of evolutionary psychology.

PubMed

Shackelford, Todd K; Liddle, James R

2014-05-01

The theory of evolution by natural selection provides the only scientific explanation for the existence of complex adaptations. The design features of the brain, like any organ, are the result of selection pressures operating over deep time. Evolutionary psychology posits that the human brain comprises a multitude of evolved psychological mechanisms, adaptations to specific and recurrent problems of survival and reproduction faced over human evolutionary history. Although some mistakenly view evolutionary psychology as promoting genetic determinism, evolutionary psychologists appreciate and emphasize the interactions between genes and environments. This approach to psychology has led to a richer understanding of a variety of psychological phenomena, and has provided a powerful foundation for generating novel hypotheses. Critics argue that evolutionary psychologists resort to storytelling, but as with any branch of science, empirical testing is a vital component of the field, with hypotheses standing or falling with the weight of the evidence. Evolutionary psychology is uniquely suited to provide a unifying theoretical framework for the disparate subdisciplines of psychology. An evolutionary perspective has provided insights into several subdisciplines of psychology, while simultaneously demonstrating the arbitrary nature of dividing psychological science into such subdisciplines. Evolutionary psychologists have amassed a substantial empirical and theoretical literature, but as a relatively new approach to psychology, many questions remain, with several promising directions for future research. For further resources related to this article, please visit the WIREs website. The authors have declared no conflicts of interest for this article. © 2014 John Wiley & Sons, Ltd.

Evolutionary perspectives on the links between mitochondrial genotype and disease phenotype.

PubMed

Dowling, Damian K

2014-04-01

Disorders of the mitochondrial respiratory chain are heterogeneous in their symptoms and underlying genetics. Simple links between candidate mutations and expression of disease phenotype typically do not exist. It thus remains unclear how the genetic variation in the mitochondrial genome contributes to the phenotypic expression of complex traits and disease phenotypes. I summarize the basic genetic processes known to underpin mitochondrial disease. I highlight other plausible processes, drawn from the evolutionary biological literature, whose contribution to mitochondrial disease expression remains largely empirically unexplored. I highlight recent advances to the field, and discuss common-ground and -goals shared by researchers across medical and evolutionary domains. Mitochondrial genetic variance is linked to phenotypic variance across a variety of traits (e.g. reproductive function, life expectancy) fundamental to the upkeep of good health. Evolutionary theory predicts that mitochondrial genomes are destined to accumulate male-harming (but female-friendly) mutations, and this prediction has received proof-of-principle support. Furthermore, mitochondrial effects on the phenotype are typically manifested via interactions between mitochondrial and nuclear genes. Thus, whether a mitochondrial mutation is pathogenic in effect can depend on the nuclear genotype in which is it expressed. Many disease phenotypes associated with OXPHOS malfunction might be determined by the outcomes of mitochondrial-nuclear interactions, and by the evolutionary forces that historically shaped mitochondrial DNA (mtDNA) sequences. Concepts and results drawn from the evolutionary sciences can have broad, but currently under-utilized, applicability to the medical sciences and provide new insights into understanding the complex genetics of mitochondrial disease. This article is part of a Special Issue entitled Frontiers of Mitochondrial Research. Copyright © 2013. Published by Elsevier B.V.

Adaptive evolution of body size subject to indirect effect in trophic cascade system.

PubMed

Wang, Xin; Fan, Meng; Hao, Lina

2017-09-01

Trophic cascades represent a classic example of indirect effect and are wide-spread in nature. Their ecological impact are well established, but the evolutionary consequences have received even less theoretical attention. We theoretically and numerically investigate the trait (i.e., body size of consumer) evolution in response to indirect effect in a trophic cascade system. By applying the quantitative trait evolutionary theory and the adaptive dynamic theory, we formulate and explore two different types of eco-evolutionary resource-consumer-predator trophic cascade model. First, an eco-evolutionary model incorporating the rapid evolution is formulated to investigate the effect of rapid evolution of the consumer's body size, and to explore the impact of density-mediate indirect effect on the population dynamics and trait dynamics. Next, by employing the adaptive dynamic theory, a long-term evolutionary model of consumer body size is formulated to evaluate the effect of long-term evolution on the population dynamics and the effect of trait-mediate indirect effect. Those models admit rich dynamics that has not been observed yet in empirical studies. It is found that, both in the trait-mediated and density-mediated system, the body size of consumer in predator-consumer-resource interaction (indirect effect) evolves smaller than that in consumer-resource and predator-consumer interaction (direct effect). Moreover, in the density-mediated system, we found that the evolution of consumer body size contributes to avoiding consumer extinction (i.e., evolutionary rescue). The trait-mediate and density-mediate effects may produce opposite evolutionary response. This study suggests that the trophic cascade indirect effect affects consumer evolution, highlights a more comprehensive mechanistic understanding of the intricate interplay between ecological and evolutionary force. The modeling approaches provide avenue for study on indirect effects from an evolutionary perspective. Copyright © 2017 Elsevier B.V. All rights reserved.

Evolution of complex life cycles in trophically transmitted helminths. II. How do life-history stages adapt to their hosts?

PubMed

Parker, G A; Ball, M A; Chubb, J C

2015-02-01

We review how trophically transmitted helminths adapt to the special problems associated with successive hosts in complex cycles. In intermediate hosts, larvae typically show growth arrest at larval maturity (GALM). Theoretical models indicate that optimization of size at GALM requires larval mortality rate to increase with time between infection and GALM: low larval growth or paratenicity (no growth) arises from unfavourable growth and mortality rates in the intermediate host and low transmission rates to the definitive host. Reverse conditions favour high GALM size or continuous growth. Some support is found for these predictions. Intermediate host manipulation involves predation suppression (which decreases host vulnerability before the larva can establish in its next host) and predation enhancement (which increases host vulnerability after the larva can establish in its next host). Switches between suppression and enhancement suggest adaptive manipulation. Manipulation conflicts can occur between larvae of different ages/species a host individual. Larvae must usually develop to GALM before becoming infective to the next host, possibly due to trade-offs, e.g. between growth/survival in the present host and infection ability for the next host. In definitive hosts, if mortality rate is constant, optimal growth before switching to reproduction is set by the growth/morality rate ratio. Rarely, no growth occurs in definitive hosts, predicted (with empirical support) when larval size on infection exceeds growth/mortality rate. Tissue migration patterns and residence sites may be explained by variations in growth/mortality rates between host gut and soma, migration costs and benefits of releasing eggs in the gut. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Bears in a forest of gene trees: phylogenetic inference is complicated by incomplete lineage sorting and gene flow.

PubMed

Kutschera, Verena E; Bidon, Tobias; Hailer, Frank; Rodi, Julia L; Fain, Steven R; Janke, Axel

2014-08-01

Ursine bears are a mammalian subfamily that comprises six morphologically and ecologically distinct extant species. Previous phylogenetic analyses of concatenated nuclear genes could not resolve all relationships among bears, and appeared to conflict with the mitochondrial phylogeny. Evolutionary processes such as incomplete lineage sorting and introgression can cause gene tree discordance and complicate phylogenetic inferences, but are not accounted for in phylogenetic analyses of concatenated data. We generated a high-resolution data set of autosomal introns from several individuals per species and of Y-chromosomal markers. Incorporating intraspecific variability in coalescence-based phylogenetic and gene flow estimation approaches, we traced the genealogical history of individual alleles. Considerable heterogeneity among nuclear loci and discordance between nuclear and mitochondrial phylogenies were found. A species tree with divergence time estimates indicated that ursine bears diversified within less than 2 My. Consistent with a complex branching order within a clade of Asian bear species, we identified unidirectional gene flow from Asian black into sloth bears. Moreover, gene flow detected from brown into American black bears can explain the conflicting placement of the American black bear in mitochondrial and nuclear phylogenies. These results highlight that both incomplete lineage sorting and introgression are prominent evolutionary forces even on time scales up to several million years. Complex evolutionary patterns are not adequately captured by strictly bifurcating models, and can only be fully understood when analyzing multiple independently inherited loci in a coalescence framework. Phylogenetic incongruence among gene trees hence needs to be recognized as a biologically meaningful signal. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Ancient connections among the European rivers and watersheds revealed from the evolutionary history of the genus Telestes (Actinopterygii; Cypriniformes).

PubMed

Buj, Ivana; Marčić, Zoran; Ćaleta, Marko; Šanda, Radek; Geiger, Matthias F; Freyhof, Jörg; Machordom, Annie; Vukić, Jasna

2017-01-01

In order to better understand the complex geologic history of the Mediterranean area, we have analysed evolutionary history, phylogeographic structure and molecular diversity of freshwater fishes belonging to the genus Telestes. As primary freshwater fishes distributed largely in the Mediterranean basin, this genus represents a suitable model system for investigating the historical biogeography of freshwater drainage systems in southern Europe. In this investigation we have included samples representing all Telestes species and based our analyses on one mitochondrial and one nuclear gene. We have investigated phylogenetic structure inside the genus Telestes, estimated divergence times, reconstructed ancestral distribution ranges and described intraspecific molecular diversity. Diversification of Telestes started in the Early Miocene, when the ancestors of T. souffia, lineage comprising T. croaticus and T. fontinalis, and the one comprising T. pleurobipunctatus and T. beoticus got isolated. The remaining species are genetically more closely related and form a common cluster in the recovered phylogenetic trees. Complex geological history of southern Europe, including formation of continental bridges, fragmentation of landmass, closing of the sea corridor, local tectonic activities, led to complicated biogeographical pattern of this genus, caused by multiple colonization events and passovers between ancient rivers and water basins. Especially pronounced diversity of Telestes found in the Adriatic watershed in Croatia and Bosnia and Herzegovina is a consequence of a triple colonization of this area by different lineages, which led to an existence of genetically distinct species in neighboring areas. Significant intraspecific structuring is present in T. souffia, T. muticellus, T. croaticus and T. pleurobipunctatus. Besides in well-structured species, elevated levels of genetic polymorphism were found inside T. turskyi and T. ukliva, as a consequence of their old origin and unconstrained evolutionary history.

Modeling individual effects in the Cormack-Jolly-Seber Model: A state-space formulation

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

In population and evolutionary biology, there exists considerable interest in individual heterogeneity in parameters of demographic models for open populations. However, flexible and practical solutions to the development of such models have proven to be elusive. In this article, I provide a state-space formulation of open population capture-recapture models with individual effects. The state-space formulation provides a generic and flexible framework for modeling and inference in models with individual effects, and it yields a practical means of estimation in these complex problems via contemporary methods of Markov chain Monte Carlo. A straightforward implementation can be achieved in the software package WinBUGS. I provide an analysis of a simple model with constant parameter detection and survival probability parameters. A second example is based on data from a 7-year study of European dippers, in which a model with year and individual effects is fitted.

1991 Annual report on scientific programs: A broad research program on the sciences of complexity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1991-01-01

1991 was continued rapid growth for the Santa Fe Institute (SFI) as it broadened its interdisciplinary research into the organization, evolution and operation of complex systems and sought deeply the principles underlying their dynamic behavior. Research on complex systems--the focus of work at SFI--involves an extraordinary range of topics normally studied in seemingly disparate fields. Natural systems displaying complex behavior range upwards from proteins and DNA through cells and evolutionary systems to human societies. Research models exhibiting complexity include nonlinear equations, spin glasses, cellular automata, genetic algorithms, classifier systems, and an array of other computational models. Some of the majormore » questions facing complex systems researchers are: (1) explaining how complexity arises from the nonlinear interaction of simples components, (2) describing the mechanisms underlying high-level aggregate behavior of complex systems (such as the overt behavior of an organism, the flow of energy in an ecology, the GNP of an economy), and (3) creating a theoretical framework to enable predictions about the likely behavior of such systems in various conditions. The importance of understanding such systems in enormous: many of the most serious challenges facing humanity--e.g., environmental sustainability, economic stability, the control of disease--as well as many of the hardest scientific questions--e.g., protein folding, the distinction between self and non-self in the immune system, the nature of intelligence, the origin of life--require deep understanding of complex systems.« less

1991 Annual report on scientific programs: A broad research program on the sciences of complexity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1991-12-31

1991 was continued rapid growth for the Santa Fe Institute (SFI) as it broadened its interdisciplinary research into the organization, evolution and operation of complex systems and sought deeply the principles underlying their dynamic behavior. Research on complex systems--the focus of work at SFI--involves an extraordinary range of topics normally studied in seemingly disparate fields. Natural systems displaying complex behavior range upwards from proteins and DNA through cells and evolutionary systems to human societies. Research models exhibiting complexity include nonlinear equations, spin glasses, cellular automata, genetic algorithms, classifier systems, and an array of other computational models. Some of the majormore » questions facing complex systems researchers are: (1) explaining how complexity arises from the nonlinear interaction of simples components, (2) describing the mechanisms underlying high-level aggregate behavior of complex systems (such as the overt behavior of an organism, the flow of energy in an ecology, the GNP of an economy), and (3) creating a theoretical framework to enable predictions about the likely behavior of such systems in various conditions. The importance of understanding such systems in enormous: many of the most serious challenges facing humanity--e.g., environmental sustainability, economic stability, the control of disease--as well as many of the hardest scientific questions--e.g., protein folding, the distinction between self and non-self in the immune system, the nature of intelligence, the origin of life--require deep understanding of complex systems.« less

Potential responses to climate change in organisms with complex life histories: evolution and plasticity in Pacific salmon.

PubMed

Crozier, L G; Hendry, A P; Lawson, P W; Quinn, T P; Mantua, N J; Battin, J; Shaw, R G; Huey, R B

2008-05-01

Salmon life histories are finely tuned to local environmental conditions, which are intimately linked to climate. We summarize the likely impacts of climate change on the physical environment of salmon in the Pacific Northwest and discuss the potential evolutionary consequences of these changes, with particular reference to Columbia River Basin spring/summer Chinook (Oncorhynchus tshawytscha) and sockeye (Oncorhynchus nerka) salmon. We discuss the possible evolutionary responses in migration and spawning date egg and juvenile growth and development rates, thermal tolerance, and disease resistance. We know little about ocean migration pathways, so cannot confidently suggest the potential changes in this life stage. Climate change might produce conflicting selection pressures in different life stages, which will interact with plastic (i.e. nongenetic) changes in various ways. To clarify these interactions, we present a conceptual model of how changing environmental conditions shift phenotypic optima and, through plastic responses, phenotype distributions, affecting the force of selection. Our predictions are tentative because we lack data on the strength of selection, heritability, and ecological and genetic linkages among many of the traits discussed here. Despite the challenges involved in experimental manipulation of species with complex life histories, such research is essential for full appreciation of the biological effects of climate change.

Potential responses to climate change in organisms with complex life histories: evolution and plasticity in Pacific salmon

PubMed Central

Crozier, L G; Hendry, A P; Lawson, P W; Quinn, T P; Mantua, N J; Battin, J; Shaw, R G; Huey, R B

2008-01-01

Salmon life histories are finely tuned to local environmental conditions, which are intimately linked to climate. We summarize the likely impacts of climate change on the physical environment of salmon in the Pacific Northwest and discuss the potential evolutionary consequences of these changes, with particular reference to Columbia River Basin spring/summer Chinook (Oncorhynchus tshawytscha) and sockeye (Oncorhynchus nerka) salmon. We discuss the possible evolutionary responses in migration and spawning date egg and juvenile growth and development rates, thermal tolerance, and disease resistance. We know little about ocean migration pathways, so cannot confidently suggest the potential changes in this life stage. Climate change might produce conflicting selection pressures in different life stages, which will interact with plastic (i.e. nongenetic) changes in various ways. To clarify these interactions, we present a conceptual model of how changing environmental conditions shift phenotypic optima and, through plastic responses, phenotype distributions, affecting the force of selection. Our predictions are tentative because we lack data on the strength of selection, heritability, and ecological and genetic linkages among many of the traits discussed here. Despite the challenges involved in experimental manipulation of species with complex life histories, such research is essential for full appreciation of the biological effects of climate change. PMID:25567630

Experimental studies of animal social learning in the wild: Trying to untangle the mystery of human culture.

PubMed

Hill, Kim

2010-08-01

Here I discuss how studies on animal social learning may help us understand human culture. It is an evolutionary truism that complex biological adaptations always evolve from less complex but related adaptations, but occasionally evolutionary transitions lead to major biological changes whose end products are difficult to anticipate. Language-based cumulative adaptive culture in humans may represent an evolutionary transition of this type. Most of the social learning observed in animals (and even plants) may be due to mechanisms that cannot produce cumulative cultural adaptations. Likewise, much of the critical content of socially transmitted human culture seems to show no parallel in nonhuman species. Thus, with regard to the uniquely human extent and quality of culture, we are forced to ask: Are other species only a few small steps away from this transition, or do they lack multiple critical features that make us the only truly cultural species? Only future research into animal social learning can answer these questions.

Evolution of epigenetic regulation in vertebrate genomes

PubMed Central

Lowdon, Rebecca F.; Jang, Hyo Sik; Wang, Ting

2016-01-01

Empirical models of sequence evolution have spurred progress in the field of evolutionary genetics for decades. We are now realizing the importance and complexity of the eukaryotic epigenome. While epigenome analysis has been applied to genomes from single cell eukaryotes to human, comparative analyses are still relatively few, and computational algorithms to quantify epigenome evolution remain scarce. Accordingly, a quantitative model of epigenome evolution remains to be established. Here we review the comparative epigenomics literature and synthesize its overarching themes. We also suggest one mechanism, transcription factor binding site turnover, which relates sequence evolution to epigenetic conservation or divergence. Lastly, we propose a framework for how the field can move forward to build a coherent quantitative model of epigenome evolution. PMID:27080453

An Integrated Framework for Modeling Air Carrier Behavior, Policy, and Impacts in the U.S. Air Transportation System

NASA Technical Reports Server (NTRS)

Horio, Brant M.; Kumar, Vivek; DeCicco, Anthony H.; Hasan, Shahab; Stouffer, Virginia L.; Smith, Jeremy C.; Guerreiro, Nelson M.

2015-01-01

The implementation of the Next Generation Air Transportation System (NextGen) in the United States is an ongoing challenge for policymakers due to the complexity of the air transportation system (ATS) with its broad array of stakeholders and dynamic interdependencies between them. The successful implementation of NextGen has a hard dependency on the active participation of U.S. commercial airlines. To assist policymakers in identifying potential policy designs that facilitate the implementation of NextGen, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework called the Air Transportation System Evolutionary Simulation (ATS-EVOS). This framework integrates large empirical data sets with multiple specialized models to simulate the evolution of the airline response to potential future policies and explore consequential impacts on ATS performance and market dynamics. In the ATS-EVOS configuration presented here, we leverage the Transportation Systems Analysis Model (TSAM), the Airline Evolutionary Simulation (AIRLINE-EVOS), the Airspace Concept Evaluation System (ACES), and the Aviation Environmental Design Tool (AEDT), all of which enable this research to comprehensively represent the complex facets of the ATS and its participants. We validated this baseline configuration of ATS-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments that explored potential implementations of a carbon tax, congestion pricing policy, and the dynamics for equipage of new technology by airlines. These experiments demonstrated ATS-EVOS's capabilities in responding to a wide range of potential NextGen-related policies and utility for decision makers to gain insights for effective policy design.

Evolutionary conceptual analysis: faith community nursing.

PubMed

Ziebarth, Deborah

2014-12-01

The aim of the study was to report an evolutionary concept analysis of faith community nursing (FCN). FCN is a source of healthcare delivery in the USA which has grown in comprehensiveness and complexity. With increasing healthcare cost and a focus on access and prevention, FCN has extended beyond the physical walls of the faith community building. Faith communities and healthcare organizations invest in FCN and standardized training programs exist. Using Rodgers' evolutionary analysis, the literature was examined for antecedents, attributes, and consequences of the concept. This design allows for understanding the historical and social nature of the concept and how it changes over time. A search of databases using the keywords FCN, faith community nurse, parish nursing, and parish nurse was done. The concept of FCN was explored using research and theoretical literature. A theoretical definition and model were developed with relevant implications. The search results netted a sample of 124 reports of research and theoretical articles from multiple disciplines: medicine, education, religion and philosophy, international health, and nursing. Theoretical definition: FCN is a method of healthcare delivery that is centered in a relationship between the nurse and client (client as person, family, group, or community). The relationship occurs in an iterative motion over time when the client seeks or is targeted for wholistic health care with the goal of optimal wholistic health functioning. Faith integrating is a continuous occurring attribute. Health promoting, disease managing, coordinating, empowering and accessing health care are other essential attributes. All essential attributes occur with intentionality in a faith community, home, health institution and other community settings with fluidity as part of a community, national, or global health initiative. A new theoretical definition and corresponding conceptual model of FCN provides a basis for future nursing knowledge and model-based applications for evidence-based practice and research.

Reverse engineering a gene network using an asynchronous parallel evolution strategy

PubMed Central

2010-01-01

Background The use of reverse engineering methods to infer gene regulatory networks by fitting mathematical models to gene expression data is becoming increasingly popular and successful. However, increasing model complexity means that more powerful global optimisation techniques are required for model fitting. The parallel Lam Simulated Annealing (pLSA) algorithm has been used in such approaches, but recent research has shown that island Evolutionary Strategies can produce faster, more reliable results. However, no parallel island Evolutionary Strategy (piES) has yet been demonstrated to be effective for this task. Results Here, we present synchronous and asynchronous versions of the piES algorithm, and apply them to a real reverse engineering problem: inferring parameters in the gap gene network. We find that the asynchronous piES exhibits very little communication overhead, and shows significant speed-up for up to 50 nodes: the piES running on 50 nodes is nearly 10 times faster than the best serial algorithm. We compare the asynchronous piES to pLSA on the same test problem, measuring the time required to reach particular levels of residual error, and show that it shows much faster convergence than pLSA across all optimisation conditions tested. Conclusions Our results demonstrate that the piES is consistently faster and more reliable than the pLSA algorithm on this problem, and scales better with increasing numbers of nodes. In addition, the piES is especially well suited to further improvements and adaptations: Firstly, the algorithm's fast initial descent speed and high reliability make it a good candidate for being used as part of a global/local search hybrid algorithm. Secondly, it has the potential to be used as part of a hierarchical evolutionary algorithm, which takes advantage of modern multi-core computing architectures. PMID:20196855

The Carnegie Mellon University Insert Project

DTIC Science & Technology

1997-02-01

Real - Time Systems (INSERT) project under the DARPA Evolutionary Design for Complex Software (EDCS) Program. The INSERT team has completed an initial API definition and ported the existing real-time publication subscription group communication software to LynxOS 2.4, a POSIX.1b compliant OS. The distributed real-time publisher/subscriber communication model is now supported by a processor membership protocol which allows a node in the system to fail, or to rejoin the system later. When a node fails, all the publishers and subscribers on that node have to be