The pitfalls and virtues of population genetic summary statistics: Detecting selective sweeps in recent divergences

Landmarks in the history of selective sweeps

Half a century ago, a seminal article on the hitchhiking effect by Smith and Haigh inaugurated the concept of the selection signature. Selective sweeps are characterised by the rapid spread of an advantageous genetic variant through a population and hence play an important role in shaping evolution and research on genetic diversity. The process by which a beneficial allele arises and becomes fixed in a population, leading to a increase in the frequency of other linked alleles, is known as genetic hitchhiking or genetic draft. Kimura's neutral theory and hitchhiking theory are complementary, with Kimura's neutral evolution as the 'null model' and positive selection as the 'signal'. Both are widely accepted in evolution, especially with genomics enabling precise measurements. Significant advances in genomic technologies, such as next-generation sequencing, high-density SNP arrays and powerful bioinformatics tools, have made it possible to systematically investigate selection signatures in a variety of species. Although the history of selection signatures is relatively recent, progress has been made in the last two decades, owing to the increasing availability of large-scale genomic data and the development of computational methods. In this review, we embark on a journey through the history of research on selective sweeps, ranging from early theoretical work to recent empirical studies that utilise genomic data.

Concurrent invasions of European starlings in Australia and North America reveal population-specific differentiation in shared genomic regions

A species' success during the invasion of new areas hinges on an interplay between the demographic processes common to invasions and the specific ecological context of the novel environment. Evolutionary genetic studies of invasive species can investigate how genetic bottlenecks and ecological conditions shape genetic variation in invasions, and our study pairs two invasive populations that are hypothesized to be from the same source population to compare how each population evolved during and after introduction. Invasive European starlings (Sturnus vulgaris) established populations in both Australia and North America in the 19th century. Here, we compare whole-genome sequences among native and independently introduced European starling populations to determine how demographic processes interact with rapid evolution to generate similar genetic patterns in these recent and replicated invasions. Demographic models indicate that both invasive populations experienced genetic bottlenecks as expected based on invasion history, and we find that specific genomic regions have differentiated even on this short evolutionary timescale. Despite genetic bottlenecks, we suggest that genetic drift alone cannot explain differentiation in at least two of these regions. The demographic boom intrinsic to many invasions as well as potential inversions may have led to high population-specific differentiation, although the patterns of genetic variation are also consistent with the hypothesis that this infamous and highly mobile invader adapted to novel selection (e.g., extrinsic factors). We use targeted sampling of replicated invasions to identify and evaluate support for multiple, interacting evolutionary mechanisms that lead to differentiation during the invasion process.

Bray-Curtis (AFD) differentiation in molecular ecology: Forecasting, an adjustment ( A A), and comparative performance in selection detection

Geographic genetic differentiation measures are used for purposes such as assessing genetic diversity and connectivity, and searching for signals of selection. Confirmation by unrelated measures can minimize false positives. A popular differentiation measure, Bray‐Curtis, has been used increasingly in molecular ecology, renamed AFD (hereafter called BCAFD). Critically, BCAFD is expected to be partially independent of the commonly used Hill “Q‐profile” measures. BCAFD needs scrutiny for potential biases, by examining limits on its value, and comparing simulations against expectations. BCAFD has two dependencies on within‐population (alpha) variation, undesirable for a between‐population (beta) measure. The first dependency is derived from similarity to GST and FST. The second dependency is that BCAFD cannot be larger than the highest allele proportion in either location (alpha variation), which can be overcome by data‐filtering or by a modified statistic ^AA or “Adjusted AFD”. The first dependency does not forestall applications such as assessing connectivity or selection, if we know the measure's null behavior under selective neutrality with specified conditions—which is shown in this article for ^AA, for equilibrium, and nonequilibrium, for the commonly used data type of single‐nucleotide‐polymorphisms (SNPs) in two locations. Thus, ^AA can be used in tandem with mathematically contrasting differentiation measures, with the aim of reducing false inferences. For detecting adaptive loci, the relative performance of ^AA and other measures was evaluated, showing that it is best to use two mathematically different measures simultaneously, and that ^AA is in one of the best such pairwise criteria. For any application, using ^AA, rather than BCAFD, avoids the counterintuitive limitation by maximum allele proportion within localities.

Capturing the rapidly evolving study of adaptation

Research on the genomics of adaptation is rapidly changing. In the last few decades, progress in this area has been driven by methodological advances, not only in the way increasingly large amounts of molecular data are generated (e.g. with high-throughput sequencing), but also in the way these data are analysed. This includes a growing appreciation and quantitative treatment of covariation among units within the same data type (e.g. genes) or across data types (e.g. genes and phenotypes). The development and adoption of more and more integrative tools have resulted in richer and more interesting empirical work. This special issue - comprising methodological, empirical, and review papers - aims to capture a 'snapshot' of this rapidly evolving field. We discuss in particular three important themes in the study of adaptation: the genetic architecture of adaptive variation, protein-coding and regulatory changes, and parallel evolution. We highlight how more traditional key themes in the study of genetic architecture (e.g. the number of loci underlying adaptive traits and the distribution of their effects) are now being complemented by other factors (e.g. how patterns of linkage and number of loci interact to affect the ability to adapt). Similarly, apart from addressing the relative importance of protein-coding and regulatory changes, we now have the tools to look in-depth at specific types of regulatory variation to gain a clearer picture of regulatory networks. Finally, parallel evolution has always been central to the study of adaptation, but now we are often able to address the question of whether - and to what extent - parallelism at the organismal or phenotypic level is matched by parallelism at the genetic level. Perhaps most importantly, we can now determine what mechanisms are driving parallelism (or lack thereof) across levels of biological organization. All these recent methodological developments open up new directions for future studies of adaptive changes across traits, levels of biological organization, demographic contexts and time scales.