Soft sweeps II--molecular population genetics of adaptation from recurrent mutation or migration

In the classical model of molecular adaptation, a favored allele derives from a single mutational origin. This ignores that beneficial alleles can enter a population recurrently, either by mutation or migration, during the selective phase. In this case, descendants of several of these independent origins may contribute to the fixation. As a consequence, all ancestral haplotypes that are linked to any of these copies will be retained in the population, affecting the pattern of a selective sweep on linked neutral variation. In this study, we use analytical calculations based on coalescent theory and computer simulations to analyze molecular adaptation from recurrent mutation or migration. Under the assumption of complete linkage, we derive a robust analytical approximation for the number of ancestral haplotypes and their distribution in a sample from the population. We find that so-called "soft sweeps," where multiple ancestral haplotypes appear in a sample, are likely for biologically realistic values of mutation or migration rates.     

Haldane's sieve and adaptation from the standing genetic variation

We consider populations that adapt to a sudden environmental change by fixing alleles found at mutation-selection balance. In particular, we calculate probabilities of fixation for previously deleterious alleles, ignoring the input of new mutations. We find that "Haldane's sieve"--the bias against the establishment of recessive beneficial mutations--does not hold under these conditions. Instead probabilities of fixation are generally independent of dominance. We show that this result is robust to patterns of sex expression for both X-linked and autosomal loci. We further show that adaptive evolution is invariably slower at X-linked than autosomal loci when evolution begins from mutation-selection balance. This result differs from that obtained when adaptation uses new mutations, a finding that may have some bearing on recent attempts to distinguish between hitchhiking and background selection by contrasting the molecular population genetics of X-linked vs. autosomal loci. Last, we suggest a test to determine whether adaptation used new mutations or previously deleterious alleles from the standing genetic variation.     

Adaptation from standing genetic variation

Populations adapt to novel environments in two distinct ways: selection on pre-existing genetic variation and selection on new mutations. These alternative sources of beneficial alleles can result in different evolutionary dynamics and distinct genetic outcomes. Compared with new mutations, adaptation from standing genetic variation is likely to lead to faster evolution, the fixation of more alleles of small effect and the spread of more recessive alleles. There is potential to distinguish between adaptation from standing variation and that from new mutations by differences in the genomic signature of selection. Here we review these approaches and possible examples of adaptation from standing variation in natural populations. Understanding how the source of genetic variation affects adaptation will be integral for predicting how populations will respond to changing environments.     

Allele surfing promotes microbial adaptation from standing variation

The coupling of ecology and evolution during range expansions enables mutations to establish at expanding range margins and reach high frequencies. This phenomenon, called allele surfing, is thought to have caused revolutions in the gene pool of many species, most evidently in microbial communities. It has remained unclear, however, under which conditions allele surfing promotes or hinders adaptation. Here, using microbial experiments and simulations, we show that, starting with standing adaptive variation, range expansions generate a larger increase in mean fitness than spatially uniform population expansions. The adaptation gain results from ‘soft’ selective sweeps emerging from surfing beneficial mutations. The rate of these surfing events is shown to sensitively depend on the strength of genetic drift, which varies among strains and environmental conditions. More generally, allele surfing promotes the rate of adaptation per biomass produced, which could help developing biofilms and other resource‐limited populations to cope with environmental challenges.     

Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation

Evolve and resequence (E&R) is a new approach to investigate the genomic responses to selection during experimental evolution. By using whole genome sequencing of pools of individuals (Pool-Seq), this method can identify selected variants in controlled and replicable experimental settings. Reviewing the current state of the field, we show that E&R can be powerful enough to identify causative genes and possibly even single-nucleotide polymorphisms. We also discuss how the experimental design and the complexity of the trait could result in a large number of false positive candidates. We suggest experimental and analytical strategies to maximize the power of E&R to uncover the genotype–phenotype link and serve as an important research tool for a broad range of evolutionary questions.Experimental evolution has a long tradition in biology (Garland and Rose, 2009). By exposing an evolving population to conditions chosen by the researcher, it is possible to study the response to this selection regime. A recent review highlighted the broad range of applications that have been investigated with this methodology and concluded that the breadth of research questions is only limited by the creativity of the experimenter (Kawecki et al., 2012). In addition to the great diversity of experimental designs, experimental evolution provides a unique advantage compared with other evolutionary analyses: the ability to replicate an experiment under identical conditions. Through this replication, experimenters are able to distinguish between stochastic and deterministic effects. Until recently, experimental evolution has mainly focused on phenotypes, sometimes combined with the analysis of a small number of markers (see, for example, Nuzhdin et al., 1993; Teotonio et al., 2009). In the wake of the latest sequencing technologies and the ongoing drop in DNA sequencing costs, however, the ultimate goal to connect the phenotypic response to the underlying genetic changes during an experimental evolution study has now come within reach.Depending on the starting population, two conceptually different approaches of experimental evolution can be distinguished. Either the experiment starts from a genetically homogeneous (invariable) population or from a polymorphic population. In the first approach, adaptation occurs through the accumulation of new beneficial mutations during the experiment (Elena and Lenski, 2003). These experiments therefore require very large population sizes and many generations to ensure a sufficient mutation supply and are thus largely restricted to microorganisms. Alternatively, experiments starting with a polymorphic population do not require novel mutations as selection can act on beneficial alleles that are already present at the beginning of the experiment. Given the massive genetic variation that is present in the starting population, the key challenge for this approach is distinguishing between selected and neutral variants. Neither randomly selected markers nor whole genome sequencing of a few representative individuals can provide sufficient information about the true target(s) of selection. Rather, genome-wide polymorphism data are needed.As whole genome sequencing is still not feasible for large numbers of individuals, experimental evolution studies starting from polymorphic base populations rely on a modified next-generation sequencing approach. Rather than sequencing individuals separately, DNA of multiple individuals from a population are sequenced together (Pool-Seq). This method is more cost effective than sequencing of individuals (Futschik and Schlötterer, 2010) and yields highly accurate genome-wide allele frequency estimates (reviewed in Rellstab et al., 2013; Schlötterer et al., 2014). The combination of experimental evolution with Pool-Seq is also known as Evolve and Resequence (E&R; Turner et al., 2011; Figure 1). Here, we review the state of the art of whole genome polymorphism analysis in experimental evolution studies relying primarily on segregating variation in the starting population.Open in a separate windowFigure 1Overview of E&R studies. (a) A population of flies is exposed for 60 generations to ultraviolet (UV) radiation (purple arrows). We assume here, for the sake of illustration, that darker pigmentation is beneficial in high UV environments, whereby darker flies will increase in frequency. (b) At the genotypic level, the allele frequency of the causative allele (dark brown) will increase, more so than hitchhiking variants (dark gray background) that will be recombined onto other backgrounds (breaks between dark and light gray background). (c) The allele frequencies of the starting population and the selected population are measured with Pool-Seq. (d) Causative variants can be identified by contrasting the allele frequencies between base and selected population and visualized with Manhattan plots. A full color version of this figure is available at the Heredity journal online.In many experimental evolution studies, researchers select for a well-defined trait in a controlled environment. This assures that both the phenotypic and the underlying genomic response are triggered either directly or indirectly by the selection regime applied during the experiment. Thus, E&R studies provide a complementary approach to genome-wide association studies (GWASs) and linkage mapping experiments as strategies to connect genotype and phenotype.     

The probability of parallel genetic evolution from standing genetic variation

Parallel evolution is often assumed to result from repeated adaptation to novel, yet ecologically similar, environments. Here, we develop and analyse a mathematical model that predicts the probability of parallel genetic evolution from standing genetic variation as a function of the strength of phenotypic selection and constraints imposed by genetic architecture. Our results show that the probability of parallel genetic evolution increases with the strength of natural selection and effective population size and is particularly likely to occur for genes with large phenotypic effects. Building on these results, we develop a Bayesian framework for estimating the strength of parallel phenotypic selection from genetic data. Using extensive individual‐based simulations, we show that our estimator is robust across a wide range of genetic and evolutionary scenarios and provides a useful tool for rigorously testing the hypothesis that parallel genetic evolution is the result of adaptive evolution. An important result that emerges from our analyses is that existing studies of parallel genetic evolution frequently rely on data that is insufficient for distinguishing between adaptive evolution and neutral evolution driven by random genetic drift. Overcoming this challenge will require sampling more populations and the inclusion of larger numbers of loci.     

Evidence for adaptation from standing genetic variation on an antimicrobial peptide gene in the mussel Mytilus edulis

Genome scans of population differentiation identify candidate loci for adaptation but provide little information on how selection has influenced the genetic structure of these loci. Following a genome scan, we investigated the nature of the selection responsible for the outlying differentiation observed between populations of the marine mussel Mytilus edulis at a leucine/arginine polymorphism (L31R) in the antimicrobial peptide MGD2. We analysed DNA sequence polymorphisms, allele frequencies and population differentiation of polymorphisms closely linked to L31R, and pairwise and third‐order linkage disequilibria. An outlying level of population differentiation was observed at L31R only, while no departure from panmixia was observed at linked loci surrounding L31R, as in most of the genome. Selection therefore seems to affect L31R directly. Three hypotheses can explain the lack of differentiation in the chromosomal region close to L31R: (i) hitchhiking has occurred but migration and recombination subsequently erased the signal, (ii) selection was weak enough and recombination strong enough to limit the hitchhiking effect to a very small chromosomal region or (iii) selection acted on a pre‐existing polymorphism (i.e. standing variation) at linkage equilibrium with its background. Linkage equilibrium was observed between L31R and linked polymorphisms in every population analysed, as expected under the three hypotheses. However, linkage disequilibrium was observed in some populations between pairs of loci located upstream and downstream to L31R, generating a complex pattern of third‐order linkage disequilibria which is best explained by the hypothesis of selection on a pre‐existing polymorphism. We hypothesise that selection could be either balanced, maintaining alleles at different frequencies depending on the pathogen community encountered locally by mussels, or intermittent, resulting in sporadic fluctuations in allele frequency.     

The population genetics of adaptation: the adaptation of DNA sequences

I describe several patterns characterizing the genetics of adaptation at the DNA level. Following Gillespie (1983, 1984, 1991), I consider a population presently fixed for the ith best allele at a locus and study the sequential substitution of favorable mutations that results in fixation of the fittest DNA sequence locally available. Given a wild type sequence that is less than optimal, I derive the fitness rank of the next allele typically fixed by natural selection as well as the mean and variance of the jump in fitness that results when natural selection drives a substitution. Looking over the whole series of substitutions required to reach the best allele, I show that the mean fitness jumps occurring throughout an adaptive walk are constrained to a twofold window of values, assuming only that adaptation begins from a reasonably fit allele. I also show that the first substitution and the substitution of largest effect account for a large share of the total fitness increase during adaptation. I further show that the distribution of selection coefficients fixed throughout such an adaptive walk is exponential (ignoring mutations of small effect), a finding reminiscent of that seen in Fisher's geometric model of adaptation. Last, I show that adaptation by natural selection behaves in several respects as the average of two idealized forms of adaptation, perfect and random.     

Insights into recombination from population genetic variation

Patterns of genetic variation in natural populations are shaped by, and hence carry valuable information about, the underlying recombination process. In the past five years, the increasing availability of large-scale population genetic data on dense sets of markers, coupled with advances in statistical methods for extracting information from these data, have led to several important advances in our understanding of the recombination process in humans. These advances include the identification of large numbers of 'hotspots', where recombination appears to take place considerably more frequently than in the surrounding sequence, and the identification of DNA sequence motifs that are associated with the locations of these hotspots.     

The genomic signature of parallel adaptation from shared genetic variation

Parallel adaptation is common and may often occur from shared genetic variation, but the genomic consequences of this process remain poorly understood. We first use individual‐based simulations to demonstrate that comparisons between populations adapted in parallel to similar environments from shared variation reveal a characteristic genomic signature around a selected locus: a low‐divergence valley centred at the locus and flanked by twin peaks of high divergence. This signature is initiated by the hitchhiking of haplotype tracts differing between derived populations in the broader neighbourhood of the selected locus (driving the high‐divergence twin peaks) and shared haplotype tracts in the tight neighbourhood of the locus (driving the low‐divergence valley). This initial hitchhiking signature is reinforced over time because the selected locus acts as a barrier to gene flow from the source to the derived populations, thus promoting divergence by drift in its close neighbourhood. We next empirically confirm the peak‐valley‐peak signature by combining targeted and RAD sequence data at three candidate adaptation genes in multiple marine (source) and freshwater (derived) populations of threespine stickleback. Finally, we use a genome‐wide screen for the peak‐valley‐peak signature to discover additional genome regions involved in parallel marine‐freshwater divergence. Our findings offer a new explanation for heterogeneous genomic divergence and thus challenge the standard view that peaks in population divergence harbour divergently selected loci and that low‐divergence regions result from balancing selection or localized introgression. We anticipate that genome scans for peak‐valley‐peak divergence signatures will promote the discovery of adaptation genes in other organisms.     

Evolutionary genetics of rhizobia: molecular and population aspects

The molecular analysis of the genetic systems controlling the main stages of nodule bacteria (rhizobia) interaction with a legume host (signaling at early stages and symbiotic nitrogen fixation) has shown that the widespread recombination of genetic material in free-living ancestors of rhizobia was an important factor in the evolution of these systems. These recombinations could be conditioned by a high content of repeated DNA sequences and the IS elements in the rhizobial genome. A high recombination activity of rhizobia is manifested in the panmictic structure of their populations, which is associated with frequency-dependent selection favoring rare recombinants. This selection is realized through the competition of virulent strains for the nodule formation and can be controlled by the genes whose expression depends on population density (via the quorum sensing mechanism). A high degree of panmixia in rhizobial populations is associated with their ecotypic polymorphism, manifested as the coexistence of symbiotic and nonsymbiotic strains. This type of polymorphism is caused by individual selection during the periodic changes of ecological niches (soil-plant host) in the rhizobia life cycle. The rhizobia-plant interaction stimulates selection in bacterial populations, which results in the increased levels of their heterogeneity and panmixia. The combination of individual and frequency-dependent selection types resulted in the high rates of symbiosis evolution and polyphyletic origin of diverse rhizobial species.     

Evolutionary genetics: the nature of hidden genetic variation unveiled

It has long been known that wild-type phenotypes harbor considerable amounts of ‘hidden’ genetic variation. A new study has mapped this variation at the nucleotide level and revealed some unexpected properties.     

The signature of positive selection on standing genetic variation

Considerable interest is focused on the use of polymorphism data to identify regions of the genome that underlie recent adaptations. These searches are guided by a simple model of positive selection, in which a mutation is favored as soon as it arises. This assumption may not be realistic, as environmental changes and range expansions may lead previously neutral or deleterious alleles to become beneficial. We examine what effect this mode of selection has on patterns of variation at linked neutral sites by implementing a new coalescent model of positive directional selection on standing variation. In this model, a neutral allele arises and drifts in the population, then at frequency f becomes beneficial, and eventually reaches fixation. Depending on the value of f, this scenario can lead to a large variance in allele frequency spectra and in levels of linkage disequilibrium at linked, neutral sites. In particular, for intermediate f, the beneficial substitution often leads to a loss of rare alleles--a pattern that differs markedly from the signature of directional selection currently relied on by researchers. These findings highlight the importance of an accurate characterization of the effects of positive selection, if we are to reliably identify recent adaptations from polymorphism data.     

Distinct ecotypes within a natural haloarchaeal population enable adaptation to changing environmental conditions without causing population sweeps

Microbial communities thriving in hypersaline brines of solar salterns are highly resistant and resilient to environmental changes, and salinity is a major factor that deterministically influences community structure. Here, we demonstrate that this resilience occurs even after rapid osmotic shocks caused by a threefold change in salinity (a reduction from 34 to 12% salts) leading to massive amounts of archaeal cell lysis. Specifically, our temporal metagenomic datasets identified two co-occurring ecotypes within the most dominant archaeal population of the brines Haloquadratum walsbyi that exhibited different salt concentration preferences. The dominant ecotype was generally more abundant and occurred in high-salt conditions (34%); the low abundance ecotype always co-occurred but was enriched at salinities around 20% or lower and carried unique gene content related to solute transport and gene regulation. Despite their apparent distinct ecological preferences, the ecotypes did not outcompete each other presumably due to weak functional differentiation between them. Further, the osmotic shock selected for a temporal increase in taxonomic and functional diversity at both the Hqr. walsbyi population and whole-community levels supporting the specialization-disturbance hypothesis, that is, the expectation that disturbance favors generalists. Altogether, our results provide new insights into how intraspecies diversity is maintained in light of substantial gene-content differences and major environmental perturbations.Subject terms: Water microbiology, Microbial ecology     

The molecular population genetics of regulatory genes

Regulatory loci, which may encode both trans acting proteins as well as cis acting promoter regions, are crucial components of an organism's genetic architecture. Although evolution of these regulatory loci is believed to underlie the evolution of numerous adaptive traits, there is little information on natural variation of these genes. Recent molecular population genetic studies, however, have provided insights into the extent of natural variation at regulatory genes, the evolutionary forces that shape them and the phenotypic effects of molecular regulatory variants. These recent analyses suggest that it may be possible to study the molecular evolutionary ecology of regulatory diversification by examining both the extent and patterning of regulatory gene diversity, the phenotypic effects of molecular variation at these loci and their ecological consequences.     

Lack of adaptation from standing genetic variation despite the presence of putatively adaptive alleles in introduced sweet vernal grass (Anthoxanthum odoratum)

Population genetic theory predicts that the availability of appropriate standing genetic variation should facilitate rapid evolution when species are introduced to new environments. However, few tests of rapid evolution have been paired with empirical surveys for the presence of previously identified adaptive genetic variants in natural populations. In this study, we examined local adaptation to soil Al toxicity in the introduced range of sweet vernal grass (Anthoxanthum odoratum), and we genotyped populations for the presence of Al tolerance alleles previously identified at the long‐term ecological Park Grass Experiment (PGE, Harpenden, UK) in the species native range. We found that markers associated with Al tolerance at the PGE were present at appreciable frequency in introduced populations. Despite this, there was no strong evidence of local adaptation to soil Al toxicity among populations. Populations demonstrated significantly different intrinsic root growth rates in the absence of Al. This suggests that selection on correlated root growth traits may constrain the ability of populations to evolve significantly different root growth responses to Al. Our results demonstrate that genotype–phenotype associations may differ substantially between the native and introduced parts of a species range and that adaptive alleles from a native species range may not necessarily promote phenotypic differentiation in the introduced range.