scholarly journals Inferring parameters of the distribution of fitness effects of new mutations when beneficial mutations are strongly advantageous and rare

2019 ◽  
Author(s):  
Tom R. Booker
Keyword(s):  
Evolutionary Genetics ◽  
Molecular Data ◽  
Substantial Contribution ◽  
Beneficial Mutations ◽  
Adaptive Mutations ◽  
Fitness Effects ◽  
Relative Contribution ◽  
Standing Variation ◽  
Accuracy And Precision ◽  
New Mutations

AbstractCharacterising the distribution of fitness effects (DFE) for new mutations is central in evolutionary genetics. Analysis of molecular data under the McDonald-Kreitman test has suggested that adaptive substitutions make a substantial contribution to between-species divergence. Methods have been proposed to estimate the parameters of the distribution of fitness effects for positively selected mutations from the unfolded site frequency spectrum (uSFS). However, when beneficial mutations are strongly selected and rare, they may make little contribution to standing variation and will thus be difficult to detect from the uSFS. In this study, I analyse uSFS data from simulated populations subject to advantageous mutations with effects on fitness ranging from mildly to strongly beneficial. When advantageous mutations are strongly selected and rare, there are very few segregating in populations at any one time. Fitting the uSFS in such cases leads to underestimates of the strength of positive selection and may lead researchers to false conclusions regarding the relative contribution adaptive mutations make to molecular evolution. Fortunately, the parameters for the distribution of fitness effects for harmful mutations are estimated with high accuracy and precision. The results from this study suggest that the parameters of positively selected mutations obtained by analysis of the uSFS should be treated with caution and that variability at linked sites should be used in conjunction with standing variability to estimate parameters of the distribution of fitness effects in the future.

scholarly journals Inferring Parameters of the Distribution of Fitness Effects of New Mutations When Beneficial Mutations Are Strongly Advantageous and Rare

2020 ◽  
Vol 10 (7) ◽  
pp. 2317-2326 ◽  
Author(s):  
Tom R. Booker
Keyword(s):  
Evolutionary Genetics ◽  
Molecular Data ◽  
Substantial Contribution ◽  
Beneficial Mutations ◽  
Adaptive Mutations ◽  
Fitness Effects ◽  
Relative Contribution ◽  
Standing Variation ◽  
Accuracy And Precision ◽  
New Mutations

Characterizing the distribution of fitness effects (DFE) for new mutations is central in evolutionary genetics. Analysis of molecular data under the McDonald-Kreitman test has suggested that adaptive substitutions make a substantial contribution to between-species divergence. Methods have been proposed to estimate the parameters of the distribution of fitness effects for positively selected mutations from the unfolded site frequency spectrum (uSFS). Such methods perform well when beneficial mutations are mildly selected and frequent. However, when beneficial mutations are strongly selected and rare, they may make little contribution to standing variation and will thus be difficult to detect from the uSFS. In this study, I analyze uSFS data from simulated populations subject to advantageous mutations with effects on fitness ranging from mildly to strongly beneficial. As expected, frequent, mildly beneficial mutations contribute substantially to standing genetic variation and parameters are accurately recovered from the uSFS. However, when advantageous mutations are strongly selected and rare, there are very few segregating in populations at any one time. Fitting the uSFS in such cases leads to underestimates of the strength of positive selection and may lead researchers to false conclusions regarding the relative contribution adaptive mutations make to molecular evolution. Fortunately, the parameters for the distribution of fitness effects for harmful mutations are estimated with high accuracy and precision. The results from this study suggest that the parameters of positively selected mutations obtained by analysis of the uSFS should be treated with caution and that variability at linked sites should be used in conjunction with standing variability to estimate parameters of the distribution of fitness effects in the future.

scholarly journals How does adaptation sweep through the genome? Insights from long-term selection experiments

2012 ◽  
Vol 279 (1749) ◽  
pp. 5029-5038 ◽  
Author(s):  
Molly K. Burke
Keyword(s):  
Genetic Variation ◽  
Natural Selection ◽  
Population Biology ◽  
De Novo ◽  
Whole Genome ◽  
Beneficial Mutations ◽  
Adaptive Mutations ◽  
Laboratory Selection ◽  
Standing Variation ◽  
New Mutations

A major goal in evolutionary biology is to understand the origins and fates of adaptive mutations. Natural selection may act to increase the frequency of de novo beneficial mutations, or those already present in the population as standing genetic variation. These beneficial mutations may ultimately reach fixation in a population, or they may stop increasing in frequency once a particular phenotypic state has been achieved. It is not yet well understood how different features of population biology, and/or different environmental circumstances affect these adaptive processes. Experimental evolution is a promising technique for studying the dynamics of beneficial alleles, as populations evolving in the laboratory experience natural selection in a replicated, controlled manner. Whole-genome sequencing, regularly obtained over the course of sustained laboratory selection, could potentially reveal insights into the mutational dynamics that most likely occur in natural populations under similar circumstances. To date, only a few evolution experiments for which whole-genome data are available exist. This review describes results from these resequenced laboratory-selected populations, in systems with and without sexual recombination. In asexual systems, adaptation from new mutations can be studied, and results to date suggest that the complete, unimpeded fixation of these mutations is not always observed. In sexual systems, adaptation from standing genetic variation can be studied, and in the admittedly few examples we have, the complete fixation of standing variants is not always observed. To date, the relative frequency of adaptation from new mutations versus standing variation has not been tested using a single experimental system, but recent studies using Caenorhabditis elegans and Saccharomyces cerevisiae suggest that this a realistic future goal.

scholarly journals Inference of distribution of fitness effects and proportion of adaptive substitutions from polymorphism data

2016 ◽  
Author(s):  
Paula Tataru ◽  
Maéva Mollion ◽  
Sylvain Glemin ◽  
Thomas Bataillon
Keyword(s):  
Molecular Evolution ◽  
Evolutionary Genetics ◽  
Deleterious Mutations ◽  
Probabilistic Framework ◽  
Evolutionary Trajectory ◽  
Beneficial Mutations ◽  
Fitness Effects ◽  
Polymorphism Data ◽  
Inference Methods ◽  
Biased Estimates

ABSTRACTThe distribution of fitness effects (DFE) encompasses deleterious, neutral and beneficial mutations. It conditions the evolutionary trajectory of populations, as well as the rate of adaptive molecular evolution (α). Inference of DFE and α from patterns of polymorphism (SFS) and divergence data has been a longstanding goal of evolutionary genetics. A widespread assumption shared by numerous methods developed so far to infer DFE and α from such data is that beneficial mutations contribute only negligibly to the polymorphism data. Hence, a DFE comprising only deleterious mutations tends to be estimated from SFS data, and α is only predicted by contrasting the SFS with divergence data from an outgroup. Here, we develop a hierarchical probabilistic framework that extends on previous methods and also can infer DFE and α from polymorphism data alone. We use extensive simulations to examine the performance of our method. We show that both a full DFE, comprising both deleterious and beneficial mutations, and α can be inferred without resorting to divergence data. We demonstrate that inference of DFE from polymorphism data alone can in fact provide more reliable estimates, as it does not rely on strong assumptions about a shared DFE between the outgroup and ingroup species used to obtain the SFS and divergence data. We also show that not accounting for the contribution of beneficial mutations to polymorphism data leads to substantially biased estimates of the DFE and α. We illustrate these points using our newly developed framework, while also comparing to one of the most widely used inference methods available.

scholarly journals Diverse phenotypic and genetic responses to short-term selection in evolving Escherichia coli populations

2015 ◽  
Author(s):  
Marcus M Dillon ◽  
Nicholas P Rouillard ◽  
Brian Van Dam ◽  
Romain Gallet ◽  
Vaughn S Cooper
Keyword(s):  
Escherichia Coli ◽  
Fitness Landscape ◽  
Single Point ◽  
Beneficial Mutations ◽  
True Nature ◽  
Term Selection ◽  
Adaptive Mutations ◽  
Fitness Effects ◽  
Genetic Responses

Beneficial mutations fuel adaptation by altering phenotypes that enhance the fit of organisms to their environment. However, the phenotypic effects of mutations often depend on ecological context, making the distribution of effects across multiple environments essential to understanding the true nature of beneficial mutations. Studies that address both the genetic basis and ecological consequences of adaptive mutations remain rare. Here, we characterize the direct and pleiotropic fitness effects of a collection of 21 first-step beneficial mutants derived from naive and adapted genotypes used in a long-term experimental evolution of Escherichia coli. Whole-genome sequencing was used to identify most beneficial mutations. In contrast to previous studies, we find diverse fitness effects of mutations selected in a simple environment and few cases of genetic parallelism. The pleiotropic effects of these mutations were predominantly positive but some mutants were highly antagonistic in alternative environments. Further, the fitness effects of mutations derived from the adapted genotypes were dramatically reduced in nearly all environments. These findings suggest that many beneficial variants are accessible from a single point on the fitness landscape, and the fixation of alternative beneficial mutations may have dramatic consequences for niche breadth reduction via metabolic erosion.

scholarly journals The Distribution of Fitness Effects Among Beneficial Mutations

Genetics ◽  
2003 ◽  
Vol 163 (4) ◽  
pp. 1519-1526 ◽  
Author(s):  
H Allen Orr
Keyword(s):  
Value Theory ◽  
Type I ◽  
Wild Type ◽  
Genetic Theory ◽  
Beneficial Mutations ◽  
Beneficial Effects ◽  
Fitness Effects ◽  
Mean Size ◽  
The Mean ◽  
New Mutations

AbstractWe know little about the distribution of fitness effects among new beneficial mutations, a problem that partly reflects the rarity of these changes. Surprisingly, though, population genetic theory allows us to predict what this distribution should look like under fairly general assumptions. Using extreme value theory, I derive this distribution and show that it has two unexpected properties. First, the distribution of beneficial fitness effects at a gene is exponential. Second, the distribution of beneficial effects at a gene has the same mean regardless of the fitness of the present wild-type allele. Adaptation from new mutations is thus characterized by a kind of invariance: natural selection chooses from the same spectrum of beneficial effects at a locus independent of the fitness rank of the present wild type. I show that these findings are reasonably robust to deviations from several assumptions. I further show that one can back calculate the mean size of new beneficial mutations from the observed mean size of fixed beneficial mutations.

scholarly journals Variance additivity of genetic populational parameter estimates obtained through bootstrapping

2003 ◽  
Vol 60 (1) ◽  
pp. 97-103 ◽  
Author(s):  
Luciana Aparecida Carlini-Garcia ◽  
Roland Vencovsky ◽  
Alexandre Siqueira Guedes Coelho
Keyword(s):  
Bootstrap Method ◽  
Natural Populations ◽  
Molecular Data ◽  
Fixation Index ◽  
Parameter Estimates ◽  
Genetic Population ◽  
Relative Contribution ◽  
Population Structure Analysis ◽  
Resampling Procedure ◽  
Variance Estimates

Studying the genetic structure of natural populations is very important for conservation and use of the genetic variability available in nature. This research is related to genetic population structure analysis using real and simulated molecular data. To obtain variance estimates of pertinent parameters, the bootstrap resampling procedure was applied over different sampling units, namely: individuals within populations (I), populations (P), and individuals and populations simultaneously (I, P). The considered parameters were: the total fixation index (F or F IT), the fixation index within populations (f or F IS) and the divergence among populations or intrapopulation coancestry (theta or F ST). The aim of this research was to verify if the variance estimates of <IMG SRC="/img/fbpe/sa/v60n1/14549x09.gif">, <IMG SRC="/img/fbpe/sa/v60n1/14549x10.gif">and <IMG SRC="/img/fbpe/sa/v60n1/14549x11.gif">, found through the resampling over individuals and populations simultaneously (I, P), correspond to the sum of the respective variance estimates obtained from separated resampling over individuals and populations (I+P). This equivalence was verified in all cases, showing that the total variance estimate of <IMG SRC="/img/fbpe/sa/v60n1/14549x09.gif">, <IMG SRC="/img/fbpe/sa/v60n1/14549x10.gif">and <IMG SRC="/img/fbpe/sa/v60n1/14549x11.gif">can be obtained summing up the variances estimated for each source of variation separately. Results also showed that this facilitates the use of the bootstrap method on data with hierarchical structure and opens the possibility of obtaining the relative contribution of each source of variation to the total variation of estimated parameters.

scholarly journals The distribution of mutational effects on fitness in Caenorhabditis elegans inferred from standing genetic variation

2020 ◽  
Author(s):  
Kimberly J. Gilbert ◽  
Stefan Zdraljevic ◽  
Daniel E. Cook ◽  
Asher D. Cutter ◽  
Erik C. Andersen ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Caenorhabditis Elegans ◽  
Population Size ◽  
Genomic Structure ◽  
Random Mating ◽  
Population Substructure ◽  
C Elegans ◽  
Fitness Effects ◽  
Self Fertilization ◽  
New Mutations

ABSTRACTThe distribution of fitness effects for new mutations is one of the most theoretically important but difficult to estimate properties in population genetics. A crucial challenge to inferring the distribution of fitness effects (DFE) from natural genetic variation is the sensitivity of the site frequency spectrum to factors like population size change, population substructure, and non-random mating. Although inference methods aim to control for population size changes, the influence of non-random mating remains incompletely understood, despite being a common feature of many species. We report the distribution of fitness effects estimated from 326 genomes of Caenorhabditis elegans, a nematode roundworm with a high rate of self-fertilization. We evaluate the robustness of DFE inferences using simulated data that mimics the genomic structure and reproductive life history of C. elegans. Our observations demonstrate how the combined influence of self-fertilization, genome structure, and natural selection can conspire to compromise estimates of the DFE from extant polymorphisms. These factors together tend to bias inferences towards weakly deleterious mutations, making it challenging to have full confidence in the inferred DFE of new mutations as deduced from standing genetic variation in species like C. elegans. Improved methods for inferring the distribution of fitness effects are needed to appropriately handle strong linked selection and selfing. These results highlight the importance of understanding the combined effects of processes that can bias our interpretations of evolution in natural populations.

scholarly journals Evolutionary stalling and a limit on the power of natural selection to improve a cellular module

2020 ◽  
Vol 117 (31) ◽  
pp. 18582-18590 ◽  
Author(s):  
Sandeep Venkataram ◽  
Ross Monasky ◽  
Shohreh H. Sikaroodi ◽  
Sergey Kryazhimskiy ◽  
Betul Kacar
Keyword(s):  
Escherichia Coli ◽  
Natural Selection ◽  
Adaptive Evolution ◽  
Genetic Load ◽  
Performance Theory ◽  
Biological Functions ◽  
Beneficial Mutations ◽  
Translation Machinery ◽  
Adaptive Mutations ◽  
Organismal Fitness

Cells consist of molecular modules which perform vital biological functions. Cellular modules are key units of adaptive evolution because organismal fitness depends on their performance. Theory shows that in rapidly evolving populations, such as those of many microbes, adaptation is driven primarily by common beneficial mutations with large effects, while other mutations behave as if they are effectively neutral. As a consequence, if a module can be improved only by rare and/or weak beneficial mutations, its adaptive evolution would stall. However, such evolutionary stalling has not been empirically demonstrated, and it is unclear to what extent stalling may limit the power of natural selection to improve modules. Here we empirically characterize how natural selection improves the translation machinery (TM), an essential cellular module. We experimentally evolved populations ofEscherichia coliwith genetically perturbed TMs for 1,000 generations. Populations with severe TM defects initially adapted via mutations in the TM, but TM adaptation stalled within about 300 generations. We estimate that the genetic load in our populations incurred by residual TM defects ranges from 0.5 to 19%. Finally, we found evidence that both epistasis and the depletion of the pool of beneficial mutations contributed to evolutionary stalling. Our results suggest that cellular modules may not be fully optimized by natural selection despite the availability of adaptive mutations.

scholarly journals Properties of spontaneous mutations affecting quantitative traits

1999 ◽  
Vol 74 (3) ◽  
pp. 341-350 ◽  
Author(s):  
A. GARCÍA-DORADO ◽  
C. LÓPEZ-FANJUL ◽  
A. CABALLERO
Keyword(s):  
Deleterious Mutation ◽  
Natural Populations ◽  
Detectable Effect ◽  
Environment Interaction ◽  
Fitness Component ◽  
Standing Variation ◽  
Genotype Environment Interaction ◽  
Component Traits ◽  
Mutational Variance ◽  
New Mutations

Recent mutation accumulation results from invertebrate species suggest that mild deleterious mutation is far less frequent than previously thought, implying smaller expressed mutational loads. Although the rate (λ) and effect (s) of very slight deleterious mutation remain unknown, most mutational fitness decline would come from moderately deleterious mutation (s ≈ 0·2, λ ≈ 0·03), and this situation would not qualitatively change in harsh environments. Estimates of the average coefficient of dominance (h¯) of non-severe deleterious mutations are controversial. The typical value of h¯ = 0·4 can be questioned, and a lower estimate (about 0·1) is suggested. Estimated mutational parameters are remarkably alike for morphological and fitness component traits (excluding lethals), indicating low mutation rates and moderate mutational effects, with a distribution generally showing strong negative asymmetry and little leptokurtosis. New mutations showed considerable genotype–environment interaction. However, the mutational variance of fitness-component traits due to non-severe detrimental mutations did not increase with environmental harshness. For morphological traits, a class of predominantly additive mutations with no detectable effect on fitness and relatively small effect on the trait was identified. This should be close to that responsible for standing variation in natural populations.

The distribution of fitness effects of new mutations

2007 ◽  
Vol 8 (8) ◽  
pp. 610-618 ◽  
Author(s):  
Adam Eyre-Walker ◽  
Peter D. Keightley
Keyword(s):  
Fitness Effects ◽  
New Mutations
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