Academic journal article Genetics

Pervasive Linked Selection and Intermediate-Frequency Alleles Are Implicated in an Evolve-and-Resequencing Experiment of Drosophila Simulans

Academic journal article Genetics

Pervasive Linked Selection and Intermediate-Frequency Alleles Are Implicated in an Evolve-and-Resequencing Experiment of Drosophila Simulans

Article excerpt

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IN evolve-and-resequencing (E&R) experiments, popula- tions evolve within one or more controlled environments and are then surveyed with genomic sequencing (Nuzhdin and Turner 2013; Long et al. 2015). A remarkable volume of data is produced; allele frequency changes at hundreds of thousands of loci within replicated populations. Researchers typically focus on the small fraction of sites exhibiting the largest or most consistent changes, but a wealth of informa- tion resides in the "background response," the evolution of polymorphisms that are not direct targets of selection (the overwhelming majority of the genome). In this paper, we present an analytical framework for E&R studies, first to pro- vide more detailed predictions regarding whole genome evolution, and second to robustly detect loci under parallel selection across replicate populations. We apply the method to a new E&R experiment on Drosophila simulans designed to answer two major questions: First, what is the genomic basis of rapid adaptation to a novel environment? And second, what do the features of the genetic response tell us about the maintenance of polymorphisms in nature?

The genetic basis of rapid adaptation

The traditional view is that adaptive evolution is slow relative to the ecological processes that influence contemporary pop- ulations (Slobodkin 1980; Gillespie 1991). In this paradigm, genetic change does not interact with ecological and demo- graphic processes over the short term (few to several gener- ations), encompassed by ecological processes (Thompson 1998; Hendry and Kinnison 1999; Palumbi 2001; Hairston et al. 2005). However, examples of rapid phenotypic evolu- tion have been known since the mid-20th century (Kettlewell 1958; Ford 1964; Johnston and Selander 1964) and its prev- alence has become increasingly appreciated in recent years. Rapid evolution has profound practical consequences for bi- ological control of pathogens, pests and invasive species, fisheries management, and biodiversity conservation (Conover and Munch 2002; Darimont et al. 2009), especially in the context of accelerating climate change (Ward and Kelly 2004). Indeed, this growing appreciation for rapid evolution has spawned new subdisciplines such as eco-evolutionary dynamics (Ellner etai. 2011). Rapid evolution of ecologically important traits has been documented in invertebrates (Ellner et al. 1999; Daborn et al. 2002), vertebrates (Reznick et al. 1997; Grant 1999), plants (Franks and Weis 2008), yeast (Lang et al. 2013; Levy et al. 2015), and pro- karyotes (Barrick etal. 2009). Biochemical (Ghalambor etal. 2015; Huang and Agrawal 2016), morphological (Losos etal. 1997; Grant 1999), life history (Rose 1984; Hairston and Walton 1986; Reznick et al. 1997), and behavioral (Turner and Miller 2012; Stuart et al. 2014) phenotypes can evolve substantially in just a handful of generations when popula- tions experience new selective regimes. However, less is known about the genomic changes that occur during rapid adaptation to novel environments, especially in multicellular eukaryotes (Messer et al. 2016; Jain and Stephan 2017).

A key question is whether the standing genetic variation within populations is sufficient for adaptation to a novel environment, or if new mutations are required. In sexual eukaryotes, abundant standing variation is indicated by the observation that artificial selection can immediately, and often dramatically, change the mean of almost any variable trait (Lewontin 1974). Still, it is possible that natural selection may fail where artificial selection succeeds if the alleles that respond in artificial selection experiments are encumbered with deleterious side effects. E&R studies seem an ideal al- ternative to artificial selection experiments in this regard. While the researcher controls fitness with artificial selection, organisms "select themselves" in an E&R experiment. …

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