Karasov T, Messer PW, Petrov DA.. Evidence that adaptation in Drosophila is not limited by mutation at single sites. PLoS Genet 6: e1000924

Department of Biology, Stanford University, Stanford, California, United States of America.
PLoS Genetics (Impact Factor: 7.53). 06/2010; 6(6):e1000924. DOI: 10.1371/journal.pgen.1000924
Source: PubMed


Adaptation in eukaryotes is generally assumed to be mutation-limited because of small effective population sizes. This view is difficult to reconcile, however, with the observation that adaptation to anthropogenic changes, such as the introduction of pesticides, can occur very rapidly. Here we investigate adaptation at a key insecticide resistance locus (Ace) in Drosophila melanogaster and show that multiple simple and complex resistance alleles evolved quickly and repeatedly within individual populations. Our results imply that the current effective population size of modern D. melanogaster populations is likely to be substantially larger (> or = 100-fold) than commonly believed. This discrepancy arises because estimates of the effective population size are generally derived from levels of standing variation and thus reveal long-term population dynamics dominated by sharp--even if infrequent--bottlenecks. The short-term effective population sizes relevant for strong adaptation, on the other hand, might be much closer to census population sizes. Adaptation in Drosophila may therefore not be limited by waiting for mutations at single sites, and complex adaptive alleles can be generated quickly without fixation of intermediate states. Adaptive events should also commonly involve the simultaneous rise in frequency of independently generated adaptive mutations. These so-called soft sweeps have very distinct effects on the linked neutral polymorphisms compared to the standard hard sweeps in mutation-limited scenarios. Methods for the mapping of adaptive mutations or association mapping of evolutionarily relevant mutations may thus need to be reconsidered.

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    • "This process is usually referred to as boom and bust cycle, because of the often dramatic rise and fall in the effectiveness of plant resistance. The standard model for describing the population genetics of pathogen adaptation to new resistant varieties assumes that positive selection of new virulence alleles primarily acts on single de novo mutations (Stukenbrock et al., 2007; Stukenbrock & Bataillon , 2012; but see also Karasov et al., 2010). Under this model, adaptation occurs in a mutation-limited regime, with the speed of adaptation governed by the waiting time until the arrival of a new adaptive mutation, which itself depends on the mutation rate toward adaptive alleles, and the population size (Charlesworth, 2009). "
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    • "Additional examples of adaptation from standing variation have been documented in Drosophila (Magwire et al., 2011), Peromyscus (Domingues et al., 2012) and humans (Peter et al., 2012), among others. Adaptations involving simultaneous selection on multiple alleles of independent origin at the same locus have also been documented across a wide array of species (Menozzi et al., 2004; Nair et al., 2006; Karasov et al., 2010; Salgueiro et al., 2010; Schmidt et al., 2010; Jones et al., 2013). Nonetheless, the general importance of soft sweeps for the adaptive process remains somewhat contentious (see e.g. "
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    ABSTRACT: The use of genetic polymorphism data to understand the dynamics of adaptation and identify the loci that are involved has become a major pursuit of modern evolutionary genetics. In addition to the classical "hard sweep" hitchhiking model, recent research has drawn attention to the fact that the dynamics of adaptation can play out in a variety of different ways, and that the specific signatures left behind in population genetic data may depend somewhat strongly on these dynamics. One particular model for which a large number of empirical examples are already known is that in which a single derived mutation arises and drifts to some low frequency before an environmental change causes the allele to become beneficial and sweeps to fixation. Here, we pursue an analytical investigation of this model, bolstered and extended via simulation study. We use coalescent theory to develop an analytical approximation for the effect of a sweep from standing variation on the genealogy at the locus of the selected allele and sites tightly linked to it. We show that the distribution of haplotypes that the selected allele is present on at the time of the environmental change can be approximated by considering recombinant haplotypes as alleles in the infinite alleles model. We show that this approximation can be leveraged to make accurate predictions regarding patterns of genetic polymorphism following such a sweep. We then use simulations to highlight which sources of haplotypic information are likely to be most useful in distinguishing this model from neutrality, as well as from other sweep models, such as the classic hard sweep, and multiple mutation soft sweeps. We find that in general, adaptation from a unique standing variant will likely be difficult to detect on the basis of genetic polymorphism data from a single population time-point alone, and when it can be detected, it will be difficult to distinguish from other varieties of selective sweeps. Samples from multiple populations and/or time points have the potential to ease this difficulty. Copyright © 2015, The Genetics Society of America.
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    • "One approach involves scanning along the genome to identify regions with patterns or signatures of polymorphism indicative of recent selection (Sabeti et al. 2006; Voight et al. 2006; Nielsen et al. 2007; Rubin et al. 2010). Genomewide scans of reduced heterozygosity , for example, have identified selective sweeps in many species including humans (Tishkoff et al. 2007; Pickrell et al. 2009), domesticated chickens (Rubin et al. 2010), Drosophila melanogaster (Karasov et al. 2010; Cassidy et al. 2013; Garud et al. 2013), and Arabidopsis (Hancock et al. 2011). In only a few cases, however, has it been possible to directly associate a phenotypic trait with molecular adaptations. "
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