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 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.

Population fragmentation causes inadequate gene flow and increases extinction risk

2017 ◽  
Author(s):  
Richard Frankham ◽  
Jonathan D. Ballou ◽  
Katherine Ralls ◽  
Mark D. B. Eldridge ◽  
Michele R. Dudash ◽  
...  
Keyword(s):  
Gene Flow ◽  
Extinction Risk ◽  
Random Mating ◽  
Large Population ◽  
Isolated Population ◽  
Population Fragmentation ◽  
Single Population ◽  
Total Size ◽  
Limited Gene Flow

Most species now have fragmented distributions, often with adverse genetic consequences. The genetic impacts of population fragmentation depend critically upon gene flow among fragments and their effective sizes. Fragmentation with cessation of gene flow is highly harmful in the long term, leading to greater inbreeding, increased loss of genetic diversity, decreased likelihood of evolutionary adaptation and elevated extinction risk, when compared to a single population of the same total size. The consequences of fragmentation with limited gene flow typically lie between those for a large population with random mating and isolated population fragments with no gene flow.

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 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.

scholarly journals The potential of forest-derived bioenergy to contribute to China's future energy and transportation fuel requirements

2012 ◽  
Vol 88 (05) ◽  
pp. 547-552
Author(s):  
Ling Li ◽  
Sergios Karatzos ◽  
Jack Saddler
Keyword(s):  
Cellulosic Ethanol ◽  
First Generation ◽  
Fossil Fuel ◽  
Large Population ◽  
Forest Biomass ◽  
Marginal Land ◽  
Transportation Fuel ◽  
Transportation Fuels ◽  
Energy Dependent

Increasing concerns of oil security, greenhouse gas emissions, and sustainability have encouraged nations to consider the contribution that agriculture/forestry for bioenergy (and biofuels in particular) could make as alternatives to current fossil-based energy and transportation fuels. Despite China's large population and geographical size, it has only relatively recently developed into a highly industrialized and energy-dependent economy. Coal is, and will remain, China's dominant energy source. However, over the last few years with China's growing middle class, increasing growth in production and sale of cars/trucks and a growing chemical based sector, oil and its derivatives are predicted to experience the fastest fossil fuel growth. China's ability to produce so-called “first-generation” or conventional biofuels from sugar, starch or vegetable oil based plants is very restricted because of “food vs. fuel” issues. Thus, biomass-based and forest-based biofuels, in particular, can form a medium-to-long-term solution that could contribute to China's national biofuels targets. Oilseed trees have been suggested as an initial forest-based biodiesel strategy with about 13 million ha of marginal land identified for possible plantation. It is also estimated that 17 million tonnes of cellulosic ethanol per annum could be derived from forest biomass that is currently available in China.

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