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  Topic: Evolutionary Computation, Stuff that drives AEs nuts< Next Oldest | Next Newest >  

Posts: 13
Joined: June 2009

(Permalink) Posted: June 12 2009,04:18   

This new paper may be of interest:

Mustonen, V. and Lassig, M.  (2009) From fitness landscapes to seascapes: non-equilibrium dynamics of selection and adaptation.  Trends in Genetics, 25, 111-119.

Evolution is a quest for innovation. Organisms adapt to changing natural selection by evolving new phenotypes. Can we read this dynamics in their genomes? Not every mutation under positive selection responds to a change in selection: beneficial changes also occur at evolutionary equilibrium, repairing previous deleterious changes and restoring existing functions. Adaptation, by contrast, is viewed here as a non-equilibrium phenomenon: the genomic response to time-dependent selection. Our approach extends the static concept of fitness landscapes to dynamic fitness seascapes. It shows that adaptation requires a surplus of beneficial substitutions over deleterious ones. Here, we focus on the evolution of yeast and Drosophila genomes, providing examples where adaptive evolution can and cannot be inferred, despite the presence of positive selection.

there's a section on Muller's Ratchet:

Here, we argue for a sharpened concept of adaptive evolution at the molecular level. Adaptation requires positive selection, but not every mutation under positive selection is adaptive. Selection and adaptation always refer to a molecular phenotype depending on a single genomic locus or on multiple loci, such as the energy of a transcription-factor-binding site in our first example. This correlates the direction of selection at all loci contributing to the phenotype and calls for the distinction between adaptation and compensation. The infinite-sites approximation, which is contained in many population-genetic models, neglects such correlations and is therefore not optimally suited to infer adaptation [16] and [23]. Here, we address this problem by a joint dynamical approach to selection and genomic response in a genome with finite number of sites. In this approach, adaptive evolution is characterized by a positive fitness flux ?, which measures the surplus of beneficial over deleterious substitutions.

It is instructive to contrast this view of adaptive evolution with Muller's ratchet, a classical model of evolution by deleterious substitutions [53] and [54]. This model postulates a well-adapted initial state of the genome so that all, or the vast majority of, mutations have negative fitness effects. Continuous fixations of slightly deleterious changes then lead to a stationary decline in fitness (i.e. to negative values of ?). Similarly to the infinite-sites approximation, this model neglects compensatory mutations. In a picture of a finite number of sites, it becomes clear that every deleterious substitution leads to the opportunity for at least one compensatory beneficial mutation (or more, if the locus contributes to a quantitative trait), so that the rate of beneficial substitutions increases with decreasing fitness. Therefore, assuming selection is time-independent, decline of fitness (? < 0) is only a transient state and the genome will eventually reach detailed balance between deleterious and beneficial substitutions, that is, evolutionary equilibrium (? = 0). As long as selection is time-independent, an equilibrium state exists for freely recombining loci and in a strongly linked (i.e. weakly recombining) genome, although its form is altered in the latter case by interference selection [55] and [56]. Conversely, an initially poorly adapted system will have a transient state of adaptive evolution (? > 0) before reaching equilibrium. Time-dependent selection, however, continuously opens new windows of positive selection, the genome is always less adapted than at equilibrium and the adaptive state becomes stationary. Thus, we reach a conclusion contrary to Muller's ratchet. Because selection in biological systems is generically time-dependent, decline of fitness is less likely even as a transient state than suggested by Muller's ratchet: the model offers no explanation of how a well-adapted initial state without opportunities of beneficial mutations is reached in the first place.

As a minimal model for adaptive evolution, we have introduced the Fisher-Wright process in a macro-evolutionary fitness seascape, which is defined by stochastic changes of selection coefficients at individual genomic positions on time scales larger than the fixation time of polymorphisms (and is thus different from micro-evolutionary selection fluctuations and genetic draft). Time-dependence of selection is required to maintain fitness flux: the seascape model is the simplest model that has a non-equilibrium stationary state with positive ?. The two parameters of the minimal model (strength and rate of selection changes) are clearly just summary variables for a much more complex reality. The vastly larger genomic datasets within and across species will enable us to infer the dynamics of selection beyond this minimal model.

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