scholarly journals The Impact of Dominance on Adaptation in Changing Environments

Genetics ◽  
2020 ◽  
Vol 216 (1) ◽  
pp. 227-240
Author(s):  
Archana Devi ◽  
Kavita Jain
Keyword(s):  
Evolutionary Dynamics ◽  
Natural Environments ◽  
Fixation Probability ◽  
Changing Environment ◽  
Changing Environments ◽  
Recurrent Mutations ◽  
Dominant Mutant ◽  
Recessive Mutant ◽  
The Impact ◽  
Varying Environment

Natural environments are seldom static and therefore it is important to ask how a population adapts in a changing environment. We consider a finite, diploid population evolving in a periodically changing environment and study how the fixation probability of a rare mutant depends on its dominance coefficient and the rate of environmental change. We find that, in slowly changing environments, the effect of dominance is the same as in the static environment, that is, if a mutant is beneficial (deleterious) when it appears, it is more (less) likely to fix if it is dominant. But, in fast changing environments, the effect of dominance can be different from that in the static environment and is determined by the mutant’s fitness at the time of appearance as well as that in the time-averaged environment. We find that, in a rapidly varying environment that is neutral on average, an initially beneficial (deleterious) mutant that arises while selection is decreasing (increasing) has a fixation probability lower (higher) than that for a neutral mutant as a result of which the recessive (dominant) mutant is favored. If the environment is beneficial (deleterious) on average but the mutant is deleterious (beneficial) when it appears in the population, the dominant (recessive) mutant is favored in a fast changing environment. We also find that, when recurrent mutations occur, dominance does not have a strong influence on evolutionary dynamics.

scholarly journals The impact of dominance on adaptation in changing environments

2020 ◽  
Author(s):  
Archana Devi ◽  
Kavita Jain
Keyword(s):  
Evolutionary Dynamics ◽  
Natural Environments ◽  
Fixation Probability ◽  
Changing Environment ◽  
Changing Environments ◽  
Recurrent Mutations ◽  
Dominant Mutant ◽  
Recessive Mutant ◽  
The Impact ◽  
Varying Environment

AbstractNatural environments are seldom static and therefore it is important to ask how a population adapts in a changing environment. We consider a finite, diploid population evolving in a periodically changing environment and study how the fixation probability of a rare mutant depends on its dominance coefficient and the rate of environmental change. We find that in slowly changing environments, the effect of dominance is the same as in the static environment, that is, if a mutant is beneficial (deleterious) when it appears, it is more (less) likely to fix if it is dominant. But in fast changing environments, the effect of dominance can be different from that in the static environment and is determined by the mutant’s fitness at the time of appearance as well as that in the time-averaged environment. We find that in a rapidly varying environment which is neutral on average, an initially beneficial (deleterious) mutant that arises while selection is decreasing (increasing) has a fixation probability lower (higher) than that for a neutral mutant as a result of which the recessive (dominant) mutant is favored. If the environment is beneficial (deleterious) on average but the mutant is deleterious (beneficial) when it appears in the population, the dominant (recessive) mutant is favored in a fast changing environment. We also find that when recurrent mutations occur, dominance does not have a strong influence on evolutionary dynamics.

scholarly journals Dominance patterns in dynamic environments

2020 ◽  
Author(s):  
Archana Devi ◽  
Kavita Jain
Keyword(s):  
Environmental Change ◽  
Dynamic Environments ◽  
Natural Environments ◽  
Phase Lag ◽  
Fixation Probability ◽  
Diploid Population ◽  
Changing Environment ◽  
Changing Environments ◽  
Recurrent Mutations ◽  
Varying Environment

AbstractNatural environments are seldom static and therefore it is important to ask how a population adapts in a changing environment. We consider a finite, diploid population with intermediate dominance evolving in a periodically changing environment and study how the fixation probability of a rare mutant depends on its dominance coefficient and the rate of environmental change. We find that in slowly changing environments, the dominance patterns are the same as in the static environment, that is, if a mutant is beneficial (deleterious) when it arrives, it is more (less) likely to fix if it is dominant. But in fast changing environments, these patterns depend on the mutant’s fitness on arrival as well as that in the time-averaged environment. We find that in a rapidly varying environment that is neutral or deleterious on-average, an initially beneficial (deleterious) mutant that arises while selection is decreasing (increasing) has a fixation probability lower (higher) than that for a neutral mutant leading to a reversal in the standard dominance patterns. We also find that recurrent mutations decrease the phase lag between the environment and the allele frequency, irrespective of the level of dominance.

scholarly journals Time to fixation in changing environments

Genetics ◽  
2021 ◽  
Author(s):  
Sachin Kaushik ◽  
Kavita Jain
Keyword(s):  
Fixation Time ◽  
Natural Environments ◽  
Theoretical Studies ◽  
Selection Coefficient ◽  
Diploid Population ◽  
Changing Environment ◽  
Conditional Mean ◽  
Changing Environments ◽  
Constant Environment ◽  
Experimental And Theoretical Studies

Abstract Although many experimental and theoretical studies on natural selection have been carried out in a constant environment, as natural environments typically vary in time, it is important to ask if and how the results of these investigations are affected by a changing environment. Here, we study the properties of the conditional fixation time defined as the time to fixation of a new mutant that is destined to fix in a finite, randomly mating diploid population with intermediate dominance that is evolving in a periodically changing environment. It is known that in a static environment, the conditional mean fixation time of a co-dominant beneficial mutant is equal to that of a deleterious mutant with the same magnitude of selection coefficient. We find that this symmetry is not preserved, even when the environment is changing slowly. More generally, we find that the conditional mean fixation time of an initially beneficial mutant in a slowly changing environment depends weakly on the dominance coefficient and remains close to the corresponding result in the static environment. However, for an initially deleterious mutant under moderate and slowly varying selection, the fixation time differs substantially from that in a constant environment when the mutant is recessive. As fixation times are intimately related to the levels and patterns of genetic diversity, our results suggest that for beneficial sweeps, these quantities are only mildly affected by temporal variation in environment. In contrast, environmental change is likely to impact the patterns due to recessive deleterious sweeps strongly.

scholarly journals The importance of species interactions in eco-evolutionary community dynamics under climate change

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Anna Åkesson ◽  
Alva Curtsdotter ◽  
Anna Eklöf ◽  
Bo Ebenman ◽  
Jon Norberg ◽  
...  
Keyword(s):  
Climate Change ◽  
Species Interactions ◽  
Community Dynamics ◽  
Evolutionary Dynamics ◽  
Negative Impact ◽  
Trophic Levels ◽  
Temperature Dependent ◽  
Modeling Framework ◽  
Impact Of Climate Change ◽  
The Impact

AbstractEco-evolutionary dynamics are essential in shaping the biological response of communities to ongoing climate change. Here we develop a spatially explicit eco-evolutionary framework which features more detailed species interactions, integrating evolution and dispersal. We include species interactions within and between trophic levels, and additionally, we incorporate the feature that species’ interspecific competition might change due to increasing temperatures and affect the impact of climate change on ecological communities. Our modeling framework captures previously reported ecological responses to climate change, and also reveals two key results. First, interactions between trophic levels as well as temperature-dependent competition within a trophic level mitigate the negative impact of climate change on biodiversity, emphasizing the importance of understanding biotic interactions in shaping climate change impact. Second, our trait-based perspective reveals a strong positive relationship between the within-community variation in preferred temperatures and the capacity to respond to climate change. Temperature-dependent competition consistently results both in higher trait variation and more responsive communities to altered climatic conditions. Our study demonstrates the importance of species interactions in an eco-evolutionary setting, further expanding our knowledge of the interplay between ecological and evolutionary processes.

scholarly journals ANALYSIS OF THE CURRENT LOGISTICS AND TRANSPORT CHALLENGES IN THE CONTEXT OF THE CHANGING ENVIRONMENT

Transport ◽  
2015 ◽  
Vol 30 (2) ◽  
pp. 233-241 ◽  
Author(s):  
Jurgita Barysienė ◽  
Nijolė Batarlienė ◽  
Darius Bazaras ◽  
Kristina Čižiūnienė ◽  
Daiva Griškevičienė ◽  
...  
Keyword(s):  
Business Processes ◽  
Legal Framework ◽  
Transport Sector ◽  
Changing Environment ◽  
Foreign Countries ◽  
Baltic Sea Region ◽  
Key Issues ◽  
The Baltic ◽  
The Impact ◽  
Transport Management

The rapidly changing world determines changes in the business processes. Logistics and transport are the areas facing constant changes. Therefore, an important point is to analyse the current problems of logistics and transport within the context of the changing environment. For many years, the experts of the Dept of Logistics and Transport Management of the Faculty of Transport Engineering from Vilnius Gediminas Technical University have been pursuing research both, in the Baltic Sea Region (BSR) in Lithuania and foreign countries. This research has been directed toward improvements to logistics and the entire supply chain in pursuit of economic, social and ecological competitiveness, an increase in the competitiveness and attractiveness of the transport system in the context of sustainable development, the impact of this system on the economic and social welfare of society, an increase in the competitiveness and attractiveness of the transport sector of improving the legal framework and the application of innovative technologies (including IT) in the transport sector aimed at implementing economic and social cohesion goals. The article deals with some of the key issues of the above introduced research.

scholarly journals Hotspots of boundary accumulation: dynamics and statistics of micro-swimmers in flowing films

2016 ◽  
Vol 13 (115) ◽  
pp. 20150936 ◽  
Author(s):  
Arnold J. T. M. Mathijssen ◽  
Amin Doostmohammadi ◽  
Julia M. Yeomans ◽  
Tyler N. Shendruk
Keyword(s):  
Solid Wall ◽  
Critical Value ◽  
Hydrodynamic Interactions ◽  
Critical Flow ◽  
Natural Environments ◽  
Flow Strength ◽  
Surfaces And Interfaces ◽  
Biological Flows ◽  
The Impact ◽  
Systematic Framework

Biological flows over surfaces and interfaces can result in accumulation hotspots or depleted voids of microorganisms in natural environments. Apprehending the mechanisms that lead to such distributions is essential for understanding biofilm initiation. Using a systematic framework, we resolve the dynamics and statistics of swimming microbes within flowing films, considering the impact of confinement through steric and hydrodynamic interactions, flow and motility, along with Brownian and run–tumble fluctuations. Micro-swimmers can be peeled off the solid wall above a critical flow strength. However, the interplay of flow and fluctuations causes organisms to migrate back towards the wall above a secondary critical value. Hence, faster flows may not always be the most efficacious strategy to discourage biofilm initiation. Moreover, we find run–tumble dynamics commonly used by flagellated microbes to be an intrinsically more successful strategy to escape from boundaries than equivalent levels of enhanced Brownian noise in ciliated organisms.

scholarly journals Chaos and the (un)predictability of evolution in a changing environment

2017 ◽  
Author(s):  
Artur Rego-Costa ◽  
Florence Débarre ◽  
Luis-Miguel Chevin
Keyword(s):  
Evolutionary Dynamics ◽  
Initial Conditions ◽  
Strong Dependence ◽  
Environmental Stochasticity ◽  
Phenotypic Evolution ◽  
Evolutionary System ◽  
Chaotic Oscillations ◽  
Changing Environment ◽  
Environmental Forcing ◽  
Evolutionary Trajectories

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.

scholarly journals Worldwide tracing of mutations and the evolutionary dynamics of SARS-CoV-2

2020 ◽  
Author(s):  
Zhong-Yin Zhou ◽  
Hang Liu ◽  
Yue-Dong Zhang ◽  
Yin-Qiao Wu ◽  
Min-Sheng Peng ◽  
...  
Keyword(s):  
Substitution Rate ◽  
Evolutionary Dynamics ◽  
Vaccine Development ◽  
Sequence Data ◽  
Immune Recognition ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Protein Coding ◽  
Theoretical Support ◽  
Recurrent Mutations

AbstractUnderstanding the mutational and evolutionary dynamics of SARS-CoV-2 is essential for treating COVID-19 and the development of a vaccine. Here, we analyzed publicly available 15,818 assembled SARS-CoV-2 genome sequences, along with 2,350 raw sequence datasets sampled worldwide. We investigated the distribution of inter-host single nucleotide polymorphisms (inter-host SNPs) and intra-host single nucleotide variations (iSNVs). Mutations have been observed at 35.6% (10,649/29,903) of the bases in the genome. The substitution rate in some protein coding regions is higher than the average in SARS-CoV-2 viruses, and the high substitution rate in some regions might be driven to escape immune recognition by diversifying selection. Both recurrent mutations and human-to-human transmission are mechanisms that generate fitness advantageous mutations. Furthermore, the frequency of three mutations (S protein, F400L; ORF3a protein, T164I; and ORF1a protein, Q6383H) has gradual increased over time on lineages, which provides new clues for the early detection of fitness advantageous mutations. Our study provides theoretical support for vaccine development and the optimization of treatment for COVID-19. We call researchers to submit raw sequence data to public databases.

scholarly journals Ability of near-infrared spectroscopy and chemometrics to predict the age of mosquitoes reared under different conditions

2020 ◽  
Author(s):  
Oselyne Ong ◽  
Elise Kho ◽  
Pedro Esperança ◽  
Chris Freebairn ◽  
Floyd Dowell ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Field Application ◽  
Machine Learning Techniques ◽  
Island Population ◽  
Natural Environments ◽  
Pls Regression ◽  
Field Methods ◽  
The Impact

Abstract Background: Practical, field-ready age-grading tools for mosquito vectors of disease are urgently needed because of the impact that daily survival has on vectorial capacity. Previous studies have shown that near-infrared spectroscopy (NIRS), in combination with chemometrics and predictive modeling, can forecast the age of laboratory-reared mosquitoes with moderate to high accuracy. It remains unclear whether the technique has utility for identifying shifts in the age structure of wild-caught mosquitoes. Here we investigate whether models derived from the laboratory strain of mosquitoes can be used to predict the age of mosquitoes grown from pupae collected in the field. Methods: NIR spectra from adult female Aedes albopictus mosquitoes reared in the laboratory (2, 5, 8, 12 and 15 days old) were compared to spectra from mosquitoes emerging from wild-caught pupae (1, 7 and 14 days old). Different partial least squares (PLS) regression methods trained on spectra from laboratory mosquitoes were evaluated on their ability to predict the age of mosquitoes from more natural environments. Results: Models trained on spectra from laboratory-reared material were able to predict the age of other laboratory-reared mosquitoes with moderate accuracy and successfully differentiated all day 2 and 15 mosquitoes. Models derived with laboratory mosquitoes could not differentiate between field-derived age groups, with age predictions relatively indistinguishable for day 1-14. Pre-processing of spectral data and improving the PLS regression framework to avoid overfitting can increase accuracy, but predictions of mosquitoes reared in different environments remained poor. Principle component analysis confirms substantial spectral variations between laboratory and field-derived mosquitoes despite both originating from the same island population. Conclusions: Models trained on laboratory mosquitoes were able to predict ages of laboratory mosquitoes with good sensitivity and specificity though they were unable to predict age of field-derived mosquitoes. This study suggests that laboratory-reared mosquitoes do not capture enough environmental variation to accurately predict the age of the same species reared under different conditions. Further research is needed to explore alternative pre-processing methods and machine learning techniques, and to understand factors that affect absorbance in mosquitoes before field application using NIRS.

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