scholarly journals The evolutionary origin of the universal distribution of mutation fitness effect

2019 ◽  
Author(s):  
Ayuna Barlukova ◽  
Igor M. Rouzine
Keyword(s):  
Exponential Distribution ◽  
Dna Sequences ◽  
Evolutionary Process ◽  
New Method ◽  
Striking Difference ◽  
Fitness Effect ◽  
Site Model ◽  
Fitness Effects ◽  
Linkage Effects

AbstractAn intriguing fact long defying explanation is the observation of a universal exponential distribution of beneficial mutations in fitness effect for different microorganisms. Here we use a general and straightforward analytic model to demonstrate that, regardless of the inherent distribution of mutation fitness effect across genomic sites, an observed exponential distribution of fitness effects emerges naturally in the long term, as a consequence of the evolutionary process. This result follows from the exponential statistics of the frequency of the less-fit alleles f predicted to evolve, in the long term, for both polymorphic and monomorphic sites. The exponential distribution disappears when the system arrives at the steady state, when it is replaced with the classical mutation-selection result, f = μ/s. Based on these findings, we develop a technique to measure selection coefficients for specific genomic sites from two single-time sequence sets. Our results demonstrate the striking difference between the distribution of fitness effects observed experimentally, for naturally occurring mutations, and the “inherent” distribution obtained in a directed-mutagenesis experiment, which can have any shape depending on organism. Based on these results, we develop a new method to measure fitness effects of mutations for each variable residue based on DNA sequences isolated from an adapting population at two time points. This new method is not sensitive to linkage effects and does not require one-site model assumptions.

scholarly journals The evolutionary origin of the universal distribution of mutation fitness effect

2021 ◽  
Vol 17 (3) ◽  
pp. e1008822
Author(s):  
Ayuna Barlukova ◽  
Igor M. Rouzine
Keyword(s):  
Exponential Distribution ◽  
Dna Sequences ◽  
Large Population ◽  
New Method ◽  
Striking Difference ◽  
Fitness Effect ◽  
Wave Regime ◽  
Site Model ◽  
Fitness Effects

An intriguing fact long defying explanation is the observation of a universal exponential distribution of beneficial mutations in fitness effect for different microorganisms. To explain this effect, we use a population model including mutation, directional selection, linkage, and genetic drift. The multiple-mutation regime of adaptation at large population sizes (traveling wave regime) is considered. We demonstrate analytically and by simulation that, regardless of the inherent distribution of mutation fitness effect across genomic sites, an exponential distribution of fitness effects emerges in the long term. This result follows from the exponential statistics of the frequency of the less-fit alleles, f, that we predict to evolve, in the long term, for both polymorphic and monomorphic sites. We map the logarithmic slope of the distribution onto the previously derived fixation probability and demonstrate that it increases linearly in time. Our results demonstrate a striking difference between the distribution of fitness effects observed experimentally for naturally occurring mutations, and the "inherent" distribution obtained in a directed-mutagenesis experiment, which can have any shape depending on the organism. Based on these results, we develop a new method to measure the fitness effect of mutations for each variable residue using DNA sequences sampled from adapting populations. This new method is not sensitive to linkage effects and does not require the one-site model assumptions.

scholarly journals New Method for Generating New Families of Distributions

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 726
Author(s):  
Lamya A. Baharith ◽  
Wedad H. Aljuhani
Keyword(s):  
Exponential Distribution ◽  
Real Data ◽  
Rate Function ◽  
New Method ◽  
Likelihood Method ◽  
Alpha Power ◽  
Unknown Parameters ◽  
Failure Rate Function ◽  
New Approach ◽  
Numerical Studies

This article presents a new method for generating distributions. This method combines two techniques—the transformed—transformer and alpha power transformation approaches—allowing for tremendous flexibility in the resulting distributions. The new approach is applied to introduce the alpha power Weibull—exponential distribution. The density of this distribution can take asymmetric and near-symmetric shapes. Various asymmetric shapes, such as decreasing, increasing, L-shaped, near-symmetrical, and right-skewed shapes, are observed for the related failure rate function, making it more tractable for many modeling applications. Some significant mathematical features of the suggested distribution are determined. Estimates of the unknown parameters of the proposed distribution are obtained using the maximum likelihood method. Furthermore, some numerical studies were carried out, in order to evaluate the estimation performance. Three practical datasets are considered to analyze the usefulness and flexibility of the introduced distribution. The proposed alpha power Weibull–exponential distribution can outperform other well-known distributions, showing its great adaptability in the context of real data analysis.

scholarly journals On the mod resc Model and the Evolution of Wolbachia Compatibility Types

Genetics ◽  
2001 ◽  
Vol 159 (4) ◽  
pp. 1415-1422 ◽  
Author(s):  
Sylvain Charlat ◽  
Claire Calmet ◽  
Hervé Merçot
Keyword(s):  
Cytoplasmic Incompatibility ◽  
Natural Populations ◽  
Evolutionary Process ◽  
Embryonic Mortality ◽  
Step Process ◽  
Zygote Development ◽  
Specific Manner

Abstract Cytoplasmic incompatibility (CI) is induced by the endocellular bacterium Wolbachia. It results in an embryonic mortality occurring when infected males mate with uninfected females. The mechanism involved is currently unknown, but the mod resc model allows interpretation of all observations made so far. It postulates the existence of two bacterial functions: modification (mod) and rescue (resc). The mod function acts in the males' germline, before Wolbachia are shed from maturing sperm. If sperm is affected by mod, zygote development will fail unless resc is expressed in the egg. Interestingly, CI is also observed in crosses between infected males and infected females when the two partners bear different Wolbachia strains, demonstrating that mod and resc interact in a specific manner: Two Wolbachia strains are compatible with each other only if they harbor the same compatibility type. Here we focus on the evolutionary process involved in the emergence of new compatibility types from ancestral ones. We argue that new compatibility types are likely to evolve under a wider range of conditions than previously thought, through a two-step process. First, new mod variants can arise by mutation and spread by drift. This is possible because mod is expressed in males and Wolbachia is transmitted by females. Second, once such a mod variant achieves a certain frequency, it can create the conditions for the deterministic invasion of a new resc variant, allowing the invasion of a new mod resc pair. Furthermore, we show that a stable polymorphism might be maintained in natural populations, allowing the long-term existence of “suicidal” Wolbachia strains.

scholarly journals Novel robust time series analysis for long-term and short-term prediction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroshi Okamura ◽  
Yutaka Osada ◽  
Shota Nishijima ◽  
Shinto Eguchi
Keyword(s):  
Robust Regression ◽  
Simulated Data ◽  
New Method ◽  
Short Term ◽  
Least Absolute Deviations ◽  
Term Prediction ◽  
Regression Approach ◽  
Short Term Prediction ◽  
Long Term Prediction

AbstractNonlinear phenomena are universal in ecology. However, their inference and prediction are generally difficult because of autocorrelation and outliers. A traditional least squares method for parameter estimation is capable of improving short-term prediction by estimating autocorrelation, whereas it has weakness to outliers and consequently worse long-term prediction. In contrast, a traditional robust regression approach, such as the least absolute deviations method, alleviates the influence of outliers and has potentially better long-term prediction, whereas it makes accurately estimating autocorrelation difficult and possibly leads to worse short-term prediction. We propose a new robust regression approach that estimates autocorrelation accurately and reduces the influence of outliers. We then compare the new method with the conventional least squares and least absolute deviations methods by using simulated data and real ecological data. Simulations and analysis of real data demonstrate that the new method generally has better long-term and short-term prediction ability for nonlinear estimation problems using spawner–recruitment data. The new method provides nearly unbiased autocorrelation even for highly contaminated simulated data with extreme outliers, whereas other methods fail to estimate autocorrelation accurately.

Exceedance Degree‐Hours: A new method for assessing long‐term thermal conditions

Indoor Air ◽  
2021 ◽  
Author(s):  
Shide Salimi ◽  
Esteban Estrella Guillén ◽  
Holly Samuelson
Keyword(s):  
Thermal Conditions ◽  
New Method

scholarly journals Evolutionary dynamics of neutral phenotypes under DNA substitution models

2020 ◽  
Author(s):  
Shadi Zabad ◽  
Alan M Moses
Keyword(s):  
Dna Sequences ◽  
Evolutionary Dynamics ◽  
Gc Content ◽  
Stabilizing Selection ◽  
Restoring Force ◽  
Dna Substitution ◽  
Long Term Trends ◽  
The Mean ◽  
Molecular Phenotypes

AbstractWe study the evolution of quantitative molecular traits in the absence of selection. Using a simple theory based on Felsenstein’s 1981 DNA substitution model, we predict a linear restoring force on the mean of an additive phenotype. Remarkably, the mean dynamics are independent of the effect sizes and genotype and are similar to the widely-used OU model for stabilizing selection. We confirm the predictions empirically using additive molecular phenotypes calculated from ancestral reconstructions of putatively unconstrained DNA sequences in primate genomes. We show that the OU model is favoured by inference software even when applied to GC content of unconstrained sequences or simulations of DNA evolution. We predict and confirm empirically that the dynamics of the variance are more complicated than those predicted by the OU model, and show that our results for the restoring force of mutation hold even for non-additive phenotypes, such as number of transcription factor binding sites, longest encoded peptide and folding propensity of the encoded peptide. Our results have implications for efforts to infer selection based on quantitative phenotype dynamics as well as to understand long-term trends in evolution of quantitative molecular traits.

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