On the unfounded enthusiasm for soft selective sweeps

Abstract

Underlying any understanding of the mode, tempo and relative importance of the adaptive process in the evolution of natural populations is the notion of whether adaptation is mutation limited. Two very different population genetic models have recently been proposed in which the rate of adaptation is not strongly limited by the rate at which newly arising beneficial mutations enter the population. However, empirical and experimental evidence to date challenges the recent enthusiasm for invoking these models to explain observed patterns of variation in humans and Drosophila.I dentifying the action of positive selection from genomic patterns of variation has remained as a central focus in population genetics. This owes both to the importance of specific applications in fields ranging from ecology to medicine, but also to the desire to address more general evolutionary questions concerning the mode and tempo of adaptation. In this vein, the notion of a soft selective sweep has grown in popularity in the recent literature, and with this increasing usage the definition of the term itself has grown increasingly vague. A soft sweep does not reference a particular population genetic model per se, but rather a set of very different models that may result in similar genomic patterns of variation. Further, it is a term commonly used in juxtaposition with the notion of a hard selective sweep, the classic model in which a single novel beneficial mutation arises in a population and rises in frequency quickly to fixation. Patterns expected under the hard sweep model have been well described in the literature (see reviews of refs 1,2; Box 1), and consist of a reduction in variation surrounding the beneficial mutation owing to the fixation of the single haplotype carrying the beneficial, with resulting well-described skews in the frequency spectrum 3-5 and in patterns of linkage disequilibrium [6][7][8] . Indeed, a part of the recent popularity of soft sweeps comes from the seeming rarity of these expected hard sweep patterns in many natural populations (for example, see refs 9-11).In terms of patterns of variation, the primary difference between soft and hard selective sweeps lies in the expected number of different haplotypes carrying the beneficial mutation or mutations, and thus in the expected number of haplotypes that hitchhike to appreciable frequency during the selective sweep, and which remain in the population at the time of fixation. This key difference results in different expectations in both the site frequency spectrum and in linkage disequilibrium, and thus in the many test statistics based on these patterns (see Box 1). Owing to this ambiguous definition, a number of models have been associated with producing a soft sweep pattern-including selection acting on previously segregating mutations, and multiple beneficials arising via mutation in quick succession (see review ref. 11 and Box 1).

Soft Shoulders Ahead: Spurious Signatures of Soft and Partial Selective Sweeps Result from Linked Hard Sweeps

“…This more pessimistic view is supported by multiple considerations. First, the distinction between hard and soft sweeps may not be so distinct (Jensen 2014). While new mutations always begin at frequency 1/2N, soft sweeps from standing variation may be selecting on variants from frequency 2/2N to (2N 2 1)/2N.…”

Factors influencing the effect size distribution of adaptive substitutions

“…Given sufficient mutational input, the likelihood of adaptation from SGV is predicted to depend on the selection coefficients of the alleles before and after the change in the environment [20,22,65,69]. For previously neutral alleles, even those with currently small beneficial effects are predicted to have higher probabilities of fixation relative to new mutations of equal effect sizes because they have escaped loss by drift [20].…”

Genetic hitchhiking and resistance evolution to transgenic Bt toxins: insights from the African stalk borer Busseola fusca (Noctuidae)

“…Various population genetics approaches have aimed at taking advantage of such phenomena to capture signatures from positive selection (Jensen, 2014), notably in non-model organisms (e.g., de Villemereuil and Gaggiotti, 2015). The size of a hitchhiking effect depends on several factors, including: age and frequency of the mutation under selection; the intensity of selection; and recombination distance to the locus under selection.…”

“…The size of a hitchhiking effect depends on several factors, including: age and frequency of the mutation under selection; the intensity of selection; and recombination distance to the locus under selection. In particular, the initial frequency of the selected allele in the population before a selective shift, as well as the age of a mutation, has a crucial role (MaynardSmith and Haigh, 1974;Jensen, 2014). As a consequence, the effectiveness of genome scans is lowered when e.g.…”

“…As a consequence, the effectiveness of genome scans is lowered when e.g. : populations have undergone a particular demographic history (e.g., bottleneck); a recessive allele is involved; or selection acts on an ancient and previously neutral allele (Teshima et al, 2006;Jensen, 2014).…”