scholarly journals The relationship between robustness and evolution

2018 ◽  
Author(s):  
Pengyao Jiang ◽  
Martin Kreitman ◽  
John Reinitz

AbstractDevelopmental robustness (canalization) is a common attribute of traits in multi-cellular organisms. High robustness ensures the reproducibility of phenotypes in the face of environmental and developmental noise, but it also dampens the expression of genetic mutation, the fuel for adaptive evolution. A reduction in robustness may therefore be adaptive under certain evolutionary scenarios. To better understand how robustness influences phenotypic evolution, and to decipher conditions under which canalization itself evolves, a genetic model was constructed in which phenotype is explicitly represented as a collection of traits, calculated from genotype, and the degree of robustness can be explicitly controlled. The genes were sub jected to mutation, altering phenotype and fitness. We then simulated the dynamics of a population evolving under two classes of initial conditions, one in which the population is at a fitness optimum and one in which it is far away. The model is formulated with two robustness parameters in the genotype to phenotype map, controlling robustness over a tight (γ) or a broad (α) range of values. Within the robustness range determined by γ, high robustness results in a equilibrium population fitness closer to the optimal fitness value than low robustness. High robustness should be favored, therefore, under a constant optimal environment. This situation reverses when populations are challenged to evolve to a new phenotype optimum. In this situation, low robustness populations adapt faster than high robustness populations and reach higher equilibrium mean fitness. A larger set of phenotypes are accessable by mutation when robustness is low, in part explaining why low robustness is favored under this condition. A larger range of robustness could be sampled by varying α, revealing a complex relationship between robustness and both the initial rate of phenotypic adaptation as well as the final equilibrium population mean fitness. Intermediate values of α produced a bifurcation in evolutionary trajectories, with some populations remaining at low population mean fitness, and others escaping to achieve high population mean fitness. We then allowed robustness itself to be encoded by a mutable genetic locus that could co-evolve along with the phenotype under selection. Low robustness genotypes are initially favored when adapting to a new optimal phenotype. A high robustness genotype then replaces it, well before maximum fitness is achieved, and moreover appears to prevent further invasion into the population of a low-robustness genotype. This phenomenon was dependent on having tight linkage (and sufficiently low mutation rate) between the robustness locus and the loci encoding phenotype.

2021 ◽  
Vol 8 ◽  
Author(s):  
Joshua Hawthorne-Madell ◽  
Eric Aaron ◽  
Ken Livingston ◽  
John H. Long

Given that selection removes genetic variance from evolving populations, thereby reducing exploration opportunities, it is important to find mechanisms that create genetic variation without the disruption of adapted genes and genomes caused by random mutation. Just such an alternative is offered by random epigenetic error, a developmental process that acts on materials and parts expressed by the genome. In this system of embodied computational evolution, simulated within a physics engine, epigenetic error was instantiated in an explicit genotype-to-phenotype map as transcription error at the initiation of gene expression. The hypothesis was that transcription error would create genetic variance by shielding genes from the direct impact of selection, creating, in the process, masquerading genomes. To test this hypothesis, populations of simulated embodied biorobots and their developmental systems were evolved under steady directional selection as equivalent rates of random mutation and random transcriptional error were covaried systematically in an 11 × 11 fully factorial experimental design. In each of the 121 different experimental conditions (unique combinations of mutation and transcription error), the same set of 10 randomly created replicate populations of 60 individuals were evolved. Selection for the improved locomotor behavior of individuals led to increased mean fitness of populations over 100 generations at nearly all levels and combinations of mutation and transcription error. When the effects of both types of error were partitioned statistically, increasing transcription error was shown to increase the final genetic variance of populations, incurring a fitness cost but acting on variance independently and differently from genetic mutation. Thus, random epigenetic errors in development feed back through selection of individuals with masquerading genomes to the population’s genetic variance over generational time. Random developmental processes offer an additional mechanism for exploration by increasing genetic variation in the face of steady, directional selection.


2021 ◽  
Author(s):  
Joel W. McGlothlin ◽  
David N. Fisher

AbstractEvolution by natural selection is often viewed as a process that inevitably leads to adaptation, or an increase in population fitness over time. However, maladaptation, an evolved decrease in fitness, may also occur in response to natural selection under some conditions. Social effects on fitness (or social selection) have been identified as a potential cause of maladaptation, but we lack a general rule identifying when social selection should lead to a decrease in population mean fitness. Here we use a quantitative genetic model to develop such a rule. We show that maladaptation is most likely to occur when social selection is strong relative to the nonsocial component of selection and acts in an opposing direction. In this scenario, evolutionary increases in traits that impose fitness costs on others may outweigh evolved gains in fitness for the individual, leading to a net decrease in population mean fitness. Further, we find maladaptation may also sometimes occur when phenotypes of interacting individuals negatively covary. We outline the biological situations where maladaptation in response to social selection can be expected, provide both quantitative genetic and phenotypic versions of our derived result, and suggest what empirical work would be needed to test it. We also consider the effect of social selection on inclusive fitness and support previous work showing that inclusive fitness cannot suffer an evolutionary decrease. Taken together, our results show that social selection may decrease population mean fitness when it opposes individual-level selection, even as inclusive fitness increases.


2017 ◽  
Author(s):  
Artur Rego-Costa ◽  
Florence Débarre ◽  
Luis-Miguel Chevin

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution, by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability.


2018 ◽  
Vol 14 (1) ◽  
pp. 20170694 ◽  
Author(s):  
Bernard Crespi ◽  
Silven Read ◽  
Iiro Salminen ◽  
Peter Hurd

The psychological effects of brain-expressed imprinted genes in humans are virtually unknown. Prader–Willi syndrome (PWS) is a neurogenetic condition mediated by genomic imprinting, which involves high rates of psychosis characterized by hallucinations and paranoia, as well as autism. Altered expression of two brain-expressed imprinted genes, MAGEL2 and NDN , mediates a suite of PWS-related phenotypes, including behaviour, in mice. We phenotyped a large population of typical individuals for schizophrenia-spectrum and autism-spectrum traits, and genotyped them for the single-nucleotide polymorphism rs850807, which is putatively functional and linked with MAGEL2 and NDN . Genetic variation in rs850807 was strongly and exclusively associated with the ideas of reference subscale of the schizophrenia spectrum, which is best typified as paranoia. These findings provide a single-locus genetic model for analysing the neurological and psychological bases of paranoid thinking, and implicate imprinted genes, and genomic conflicts, in human mentalistic thought.


Author(s):  
Petr Fiala ◽  
Martina Kuncová

The paper is dedicated to network development in the network economy. The current economy needs to look not only at networks with only dynamic flows and with a fixed structure, but as a dynamic system its structure evolves and changes. Structure and behaviour dynamics of network systems can be modelled as complex adaptive systems and use agent-oriented simulation to demonstrate origin, perturbation effects, and sensitivity with regard to initial conditions. Survival of firms is associated with the value of so-called fitness function. Firms whose fitness value falls below a certain threshold will be extinguished. In this way, it is possible to partially model network growth. A simulation model in SIMUL8 is proposed.


2019 ◽  
Vol 317 (3) ◽  
pp. R461-R469 ◽  
Author(s):  
Steven J. Swoap ◽  
Mark J. Bingaman ◽  
Elissa M. Hult ◽  
Noah J. Sandstrom

Alternate-day fasting (ADF) is effective for weight loss and increases insulin sensitivity in diet-induced obese rodents. However, the efficacy of ADF in genetic models of obesity has not been comprehensively studied. Mice that are deficient in leptin ( ob/ob mice) are obese, diabetic, and prone to deep bouts of torpor when fasted. We tested the hypotheses that an ADF protocol in ob/ob mice would result in 1) induction of torpor on fasted days, 2) minimal body weight loss if the mice experienced torpor, and 3) no improvement in glucose control in the absence of weight loss. Female ob/ob mice and littermate controls were assigned to 1) an ad libitum regimen or 2) an ADF regimen, consisting of fasting every other day with ad libitum feeding between fasts. Over a 19-day period, littermate control mice on the ADF regimen consumed the same amount of food as littermate control mice on the ad libitum regimen, whereas the ADF ob/ob mice consumed 37% less food than ad libitum ob/ob mice. Fasting days, but not fed days, led to torpor in both genotypes. Fasting days, but not fed days, led to weight loss in both genotypes relative to ad libitum controls. Fasting days, but not fed days, produced enhanced insulin sensitivity in both genotypes and normalized circulating glucose in ob/ob mice. These data demonstrate improved glucose control on fasting days with the use of ADF in a genetic model of obesity in the face of minimal weight loss.


1975 ◽  
Vol 62 (2) ◽  
pp. 61-67
Author(s):  
V. Arunachalam
Keyword(s):  

2014 ◽  
Author(s):  
Jordan Fish ◽  
Daniel R O'Donnell ◽  
Abhijna Parigi ◽  
Ian Dworkin ◽  
Aaron P Wagner

Standing genetic variation and the historical environment in which that variation arises (evolutionary history) are both potentially significant determinants of a population’s capacity for evolutionary response to a changing environment. We evaluated the relative importance of these two factors in influencing the evolutionary trajectories in the face of sudden environmental change. We used the open-ended digital evolution software Avida to examine how historic exposure to predation pressures, different levels of genetic variation, and combinations of the two, impact anti-predator strategies and competitive abilities evolved in the face of threats from new, invasive, predator populations. We show that while standing genetic variation plays some role in determining evolutionary responses, evolutionary history has the greater influence on a population’s capacity to evolve effective anti-predator traits. This adaptability likely reflects the relative ease of repurposing existing, relevant genes and traits, and the broader potential value of the generation and maintenance of adaptively flexible traits in evolving populations.


2021 ◽  
Author(s):  
Anjali Mahilkar ◽  
Sharvari Kemkar ◽  
Supreet Saini

AbstractMutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments performed with organisms such asDrosophilahave an effective population size of one. However, in MA experiments with bacteria and yeast, a single founder is allowed to grow to a size of a colony (~108). The effective population size in these experiments is of the order of 10. In this scenario, while it is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth and therefore, the MA experiment; this effect has not been tested explicitly. In this work, we simulate colony growth and perform an MA experiment, and demonstrate that selection ensures that, in an MA experiment, fraction of all mutations that are beneficial is over represented by a factor greater than two. The DFE of beneficial and deleterious mutations are accurately captured in an MA experiment. We show that the effect of selection in a growing colony varies non-monotonically and that, in the face of natural selection dictating an MA experiment, estimates of mutation rate of an organism is not trivial. We perform experiments with 160 MA lines ofE. coli, and demonstrate that rate of change of mean fitness is a non-monotonic function of the colony size, and that selection acts differently in different sectors of a growing colony. Overall, we demonstrate that the results of MA experiments need to be revisited taking into account the action of selection in a growing colony.


2020 ◽  
Author(s):  
Dor Cohen ◽  
Ohad Lewin-Epstein ◽  
Marcus W. Feldman ◽  
Yoav Ram

AbstractCultural evolution of cooperation under vertical and non-vertical cultural transmission is studied, and conditions are found for fixation and coexistence of cooperation and defection. The evolution of cooperation is facilitated by its horizontal transmission and by an association between social interactions and horizontal transmission. The effect of oblique transmission depends on the horizontal transmission bias. Stable polymorphism of cooperation and defection can occur, and when it does, reduced association between social interactions and horizontal transmission evolves, which leads to a decreased frequency of cooperation and lower population mean fitness. The deterministic conditions are compared to outcomes of stochastic simulations of structured populations. Parallels are drawn with Hamilton’s rule incorporating assortment and effective relatedness.


Sign in / Sign up

Export Citation Format

Share Document