975 research outputs found

    Historical contingency and entrenchment in protein evolution under purifying selection

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    The fitness contribution of an allele at one genetic site may depend on alleles at other sites, a phenomenon known as epistasis. Epistasis can profoundly influence the process of evolution in populations under selection, and can shape the course of protein evolution across divergent species. Whereas epistasis between adaptive substitutions has been the subject of extensive study, relatively little is known about epistasis under purifying selection. Here we use mechanistic models of thermodynamic stability in a ligand-binding protein to explore the structure of epistatic interactions between substitutions that fix in protein sequences under purifying selection. We find that the selection coefficients of mutations that are nearly-neutral when they fix are highly contingent on the presence of preceding mutations. Conversely, mutations that are nearly-neutral when they fix are subsequently entrenched due to epistasis with later substitutions. Our evolutionary model includes insertions and deletions, as well as point mutations, and so it allows us to quantify epistasis within each of these classes of mutations, and also to study the evolution of protein length. We find that protein length remains largely constant over time, because indels are more deleterious than point mutations. Our results imply that, even under purifying selection, protein sequence evolution is highly contingent on history and so it cannot be predicted by the phenotypic effects of mutations assayed in the wild-type sequence.Comment: 42 pages, 13 figure

    The inevitability of unconditionally deleterious substitutions during adaptation

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    Studies on the genetics of adaptation typically neglect the possibility that a deleterious mutation might fix. Nonetheless, here we show that, in many regimes, the first substitution is most often deleterious, even when fitness is expected to increase in the long term. In particular, we prove that this phenomenon occurs under weak mutation for any house-of-cards model with an equilibrium distribution. We find that the same qualitative results hold under Fisher's geometric model. We also provide a simple intuition for the surprising prevalence of unconditionally deleterious substitutions during early adaptation. Importantly, the phenomenon we describe occurs on fitness landscapes without any local maxima and is therefore distinct from "valley-crossing". Our results imply that the common practice of ignoring deleterious substitutions leads to qualitatively incorrect predictions in many regimes. Our results also have implications for the substitution process at equilibrium and for the response to a sudden decrease in population size.Comment: Corrected typos and minor errors in Supporting Informatio

    Practical rare event sampling for extreme mesoscale weather

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    Extreme mesoscale weather, including tropical cyclones, squall lines, and floods, can be enormously damaging and yet challenging to simulate; hence, there is a pressing need for more efficient simulation strategies. Here we present a new rare event sampling algorithm called Quantile Diffusion Monte Carlo (Quantile DMC). Quantile DMC is a simple-to-use algorithm that can sample extreme tail behavior for a wide class of processes. We demonstrate the advantages of Quantile DMC compared to other sampling methods and discuss practical aspects of implementing Quantile DMC. To test the feasibility of Quantile DMC for extreme mesoscale weather, we sample extremely intense realizations of two historical tropical cyclones, 2010 Hurricane Earl and 2015 Hurricane Joaquin. Our results demonstrate Quantile DMC's potential to provide low-variance extreme weather statistics while highlighting the work that is necessary for Quantile DMC to attain greater efficiency in future applications.Comment: 18 pages, 9 figure
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