Fitness effects of advantageous mutations in evolving
            <i>Escherichia coli</i>
            populations

Imhof, Marianne; Schlötterer, Christian

doi:10.1073/pnas.98.3.1113

Cited by 233 publications

(204 citation statements)

References 26 publications

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“…For instance, in [108], the distribution of the fitness conferred in the first step was measured in E. coli, which supports the above observation of the occurrence of few mutations with large benefits and many with small payoffs. Similar experiments have also been performed on the RNA virus φ 6 [109].…”

Section: Dynamics Of Microbial Evolutionsupporting

confidence: 58%

Adaptation in Simple and Complex Fitness Landscapes

Jain

Krug

2007

Structural Approaches to Sequence Evolution

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Section: Dynamics Of Microbial Evolutionsupporting

confidence: 58%

Adaptation in Simple and Complex Fitness Landscapes

Jain

Krug

2007

Structural Approaches to Sequence Evolution

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“…There has been recent empirical evidence (Imhof and Schlotterer 2001;Rozen, de Visser, and Gerrish 2002;Lenski, Rose, Simpson, and Tadler 1991;Sanjuan, Moya, and Elena 2004;Nilsson, Kugelberg, Berg, and Anderson 2004;Joseph and Hall 2004) that rates of adaptive mutations are much higher than previously proposed (Kimura 1983). For example, very recently, evolution experiments of adaptation of the bacterium Salmonella typhimurium to mice have suggested that the adaptive mutation rate for that bacterium can be higher than 10 −6 /cell/generation (Nilsson, Kugelberg, Berg, and Anderson 2004).…”

Section: Discussionmentioning

confidence: 94%

“…He showed that, for a large random mating sexual population, the probability of fixation of a newly arising beneficial mutation is only twice its selective advantage. This means that for mutations that increase fitness of only a few percent (as seems to be the case, (Imhof and Schlotterer 2001;Rozen, de Visser, and Gerrish 2002;Lenski, Rose, Simpson, and Tadler 1991;Sanjuan, Moya, and Elena 2004)) there is more than ninety percent chance that they get lost soon after their appearance. Due to the Hill-Robertson effect (Hill and Robertson 1966), asexual organisms or non-recombining regions of sexual organisms, such as mitochondria and the Y chromosome, suffer from an even smaller probability of fixing adaptive mutations.…”

Section: Introductionmentioning

confidence: 99%

Adaptive evolution in a spatially structured asexual population

Gordo

Campos

2006

Genetica

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We study the process of adaptation in a spatially structured asexual haploid population. The model assumes a local competition for replication, where each organism interacts only with its nearest neighbors. We observe that the substitution rate of beneficial mutations is smaller for a spatially structured population than that seen for populations without structure. The difference between structured and unstructured populations increases as the adaptive mutation rate increases. Furthermore, the substitution rate decreases as the number of neighbors for local competition is reduced. We have also studied the impact of structure on the distribution of adaptive mutations that fix during adaptation.Adaptive evolution in a spatially structured asexual population AbstractWe study the process of adaptation in a spatially structured asexual haploid population. The model assumes a local competition for replication, where each organism interacts only with its nearest neighbors. We observe that the substitution rate of beneficial mutations is smaller for a spatially structured population than that seen for populations without structure. The difference between structured and unstructured populations increases as the adaptive mutation rate increases. Furthermore, the substitution rate decreases as the number of neighbors for local competition is reduced. We have also studied the impact of structure on the distribution of adaptive mutations that fix during adaptation.

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“…For example, a basic prediction is that adaptation involves more substitutions in gradually changing environments than under constant selection. The number of substitutions might be estimated from DNA sequence data or by marker-based approaches as in Imhof and Schlö tterer (2001). Furthermore, a hallmark of the moving optimum scenario is a reversal of fitness effects over time (i.e., selection favors first small and then large mutations).…”

Section: Discussionmentioning

confidence: 99%

The Genetic Basis of Phenotypic Adaptation II: The Distribution of Adaptive Substitutions in the Moving Optimum Model

2009

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We consider a population that adapts to a gradually changing environment. Our aim is to describe how ecological and genetic factors combine to determine the genetic basis of adaptation. Specifically, we consider the evolution of a polygenic trait that is under stabilizing selection with a moving optimum. The ecological dynamics are defined by the strength of selection,s, and the speed of the optimum,ṽ; the key genetic parameters are the mutation rate Q and the variance of the effects of new mutations, v. We develop analytical approximations within an ''adaptive-walk'' framework and describe how selection acts as a sieve that transforms a given distribution of new mutations into the distribution of adaptive substitutions. Our analytical results are complemented by individual-based simulations. We find that (i) the ecological dynamics have a strong effect on the distribution of adaptive substitutions and their impact depends largely on a single composite measure g ¼ṽ=ðsQv 3 Þ, which combines the ecological and genetic parameters; (ii) depending on g, we can distinguish two distinct adaptive regimes: for large g the adaptive process is mutation limited and dominated by genetic constraints, whereas for small g it is environmentally limited and dominated by the external ecological dynamics; (iii) deviations from the adaptive-walk approximation occur for large mutation rates, when different mutant alleles interact via linkage or epistasis; and (iv) in contrast to predictions from previous models assuming constant selection, the distribution of adaptive substitutions is generally not exponential.A N important aim for both empirical and theoretical evolutionary biologists is to better understand the genetics of adaptation (e.g., Orr 2005a). For example, among the multitude of mutations that arise in a population, which ones are eventually fixed and contribute to evolutionary change? That is, given a distribution of new mutations, what is the distribution of adaptive substitutions (or fixed mutations)? Here, distribution means the probability distribution of the effects of mutations on either the phenotype or the fitness of their carriers. In principle, both the distribution of new mutations and the distribution of adaptive substitutions can be measured empirically, the former from mutation accumulation experiments (Eyre-Walker and Keightley 2007) and the latter from QTL (e.g., Bradshaw et al. 1998) or experimental evolution (Elena and Lenski 2003) studies. However, as only a small subset of all mutations is beneficial, such measurements are difficult. Therefore, a large role in studying the genetics of adaptation has to be played by theoretical modeling.In recent years, several different approaches have emerged for modeling the process of adaptation. Gillespie 1983Gillespie , 1984Orr 2002), various models of so-called ''adaptive walks'' on rugged fitness landscapes (e.g., Kauffman and Levin 1987;Kauffman 1993), and models of clonal interference in asexual populations (e.g., Gerrish and Lenski 1998;Park and Krug...

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Fitness effects of advantageous mutations in evolving Escherichia coli populations

Cited by 233 publications

References 26 publications

Adaptation in Simple and Complex Fitness Landscapes

Adaptation in Simple and Complex Fitness Landscapes

Adaptive evolution in a spatially structured asexual population

The Genetic Basis of Phenotypic Adaptation II: The Distribution of Adaptive Substitutions in the Moving Optimum Model

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