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Although many selection estimates have been published, the environmental factors that cause selection to vary in space and time have rarely been identified. One way to identify these factors is by experimentally manipulating the environment and measuring selection in each treatment. We compiled and analyzed selection estimates from experimental studies. First, we tested whether the effect of manipulating the environment on selection gradients depends on taxon, trait type, or fitness component. We found that the effect of manipulating the environment was larger when selection was measured on life-history traits or via survival. Second, we tested two predictions about the environmental factors that cause variation in selection. We found support for the prediction that variation in selection is more likely to be caused by environmental factors that have a large effect on mean fitness but not for the prediction that variation is more likely to be caused by biotic factors. Third, we compared selection gradients from experimental and observational studies. We found that selection varied more among treatments in experimental studies than among spatial and temporal replicates in observational studies, suggesting that experimental studies can detect relationships between environmental factors and selection that would not be apparent in observational studies.

In this issue of GENETICS, a new method for detecting natural selection on polygenic traits is developed and applied to several human examples (Racimo et al. 2018). By definition, many loci contribute to variation in polygenic traits, and a challenge for evolutionary geneticists has been that these traits can evolve by small, nearly undetectable shifts in allele frequencies across each of many, typically unknown, loci. Recently, a helpful remedy has arisen. Genome-wide association studies (GWAS) have been illuminating sets of loci that can be interrogated jointly for changes in allele frequencies. By aggregating small signals of change across many such loci, directional natural selection is now in principle detectable using genetic data, even for highly polygenic traits. This is an exciting arena of progress - with these methods, tests can be made for selection associated with traits, and we can now study selection in what may be its most prevalent mode. The continuing fast pace of GWAS publications suggest there will be many more polygenic tests of selection in the near future, as every new GWAS is an opportunity for an accompanying test of polygenic selection. However, it is important to be aware of complications that arise in interpretation, especially given that these studies may easily be misinterpreted both in and outside the evolutionary genetics community. Here, we provide context for understanding polygenic tests and urge caution regarding how these results are interpreted and reported upon more broadly.

Abstract Identifying the footprints of selection in coding sequences can inform about the importance and function of individual sites. Analyses of the ratio of nonsynonymous to synonymous substitutions (dN/dS) have been widely used to pinpoint changes in the intensity of selection, but cannot distinguish them from changes in the direction of selection, that is, changes in the fitness of specific amino acids at a given position. A few methods that rely on amino-acid profiles to detect changes in directional selection have been designed, but their performances have not been well characterized. In this paper, we investigate the performance of six of these methods. We evaluate them on simulations along empirical phylogenies in which transition events have been annotated and compare their ability to detect sites that have undergone changes in the direction or intensity of selection to that of a widely used dN/dS approach, codeml’s branch-site model A. We show that all methods have reduced performance in the presence of biased gene conversion but not CpG hypermutability. The best profile method, Pelican, a new implementation of Tamuri AU, Hay AJ, Goldstein RA. (2009. Identifying changes in selective constraints: host shifts in influenza. PLoS Comput Biol. 5(11):e1000564), performs as well as codeml in a range of conditions except for detecting relaxations of selection, and performs better when tree length increases, or in the presence of persistent positive selection. It is fast, enabling genome-scale searches for site-wise changes in the direction of selection associated with phenotypic changes.

Cope's rule, the tendency for species within a lineage to evolve towards larger body size, has been widely reported in the fossil record, but the mechanisms leading to such phyletic size increase remain unclear. Here we show that selection acting on individual organisms generally favors larger body size. We performed an analysis of the strength of directional selection on size compared with other quantitative traits by evaluating 854 selection estimates from 42 studies of contemporaneous natural populations. For size, more than 79% of selection estimates exceed zero, whereas for other morphological traits positive and negative values are similar in frequency. The selective advantage of increased size occurs for traits implicated in both natural selection (e.g., differences in survival) and sexual selection (e.g., differences in mating success). The predominance of positive directional selection on size within populations could translate into a macroevolutionary trend toward increased size and thereby explain Cope's rule.

Studies of phenotypic selection document directional selection in many natural populations. What factors reduce total directional selection and the cumulative evolutionary responses to selection? We combine two data sets for phenotypic selection, representing more than 4,600 distinct estimates of selection from 143 studies, to evaluate the potential roles of fitness trade-offs, indirect (correlated) selection, temporally varying selection, and stabilizing selection for reducing net directional selection and cumulative responses to selection. We detected little evidence that trade-offs among different fitness components reduced total directional selection in most study systems. Comparisons of selection gradients and selection differentials suggest that correlated selection frequently reduced total selection on size but not on other types of traits. The direction of selection on a trait often changes over time in many temporally replicated studies, but these fluctuations have limited impact in reducing cumulative directional selection in most study systems. Analyses of quadratic selection gradients indicated stabilizing selection on body size in at least some studies but provided little evidence that stabilizing selection is more common than disruptive selection for most traits or study systems. Our analyses provide little evidence that fitness trade-offs, correlated selection, or stabilizing selection strongly constrains the directional selection reported for most quantitative traits.

It is widely accepted that migrating cells and tissues navigate along pre-patterned chemoattractant gradients; here it is shown that migrating tissues can also determine their own direction by generating local gradients of chemokine activity, via polarized receptor-mediated internalization, that are sufficient to ensure robust collective migration. Cells that know their place The currently accepted view of how cells migrate directionally over long distances — an important driving force in embryogenesis — is that they navigate using pre-patterned chemoattractant guidance gradients. In this study Darren Gilmour and colleagues present the first in vivo evidence for a rather different mechanism: self-generated guidance gradient formation. Using zebrafish lateral line primordium as a model for collective cell migration, the authors show that migrating tissues can determine their own direction by generating local gradients in initially uniform extracellular guidance cues, producing a travelling wave. The atypical chemokine receptor Cxcr7 is the key regulator of the process, being both necessary and sufficient for self-directed migration. The finding that cells can autonomously determine their migration routes could have wider implications in processes such as cancer metastasis. The directed migration of cell collectives is a driving force of embryogenesis 1 , 2 , 3 . The predominant view in the field is that cells in embryos navigate along pre-patterned chemoattractant gradients 2 . One hypothetical way to free migrating collectives from the requirement of long-range gradients would be through the self-generation of local gradients that travel with them 4 , 5 , a strategy that potentially allows self-determined directionality. However, a lack of tools for the visualization of endogenous guidance cues has prevented the demonstration of such self-generated gradients in vivo . Here we define the in vivo dynamics of one key guidance molecule, the chemokine Cxcl12a, by applying a fluorescent timer approach to measure ligand-triggered receptor turnover in living animals. Using the zebrafish lateral line primordium as a model, we show that migrating cell collectives can self-generate gradients of chemokine activity across their length via polarized receptor-mediated internalization. Finally, by engineering an external source of the atypical receptor Cxcr7 that moves with the primordium, we show that a self-generated gradient mechanism is sufficient to direct robust collective migration. This study thus provides, to our knowledge, the first in vivo proof for self-directed tissue migration through local shaping of an extracellular cue and provides a framework for investigating self-directed migration in many other contexts including cancer invasion 6 .

Abstract Hybridization between lineages that have not reached complete reproductive isolation appears more and more like a common phenomenon. Indeed, speciation genomic studies have now extensively shown that many species’ genomes have hybrid ancestry. However, genomic patterns of introgression are often heterogeneous across the genome. In many organisms, a positive correlation between introgression levels and recombination rate has been observed. It is usually explained by the purging of deleterious introgressed material due to incompatibilities. However, the opposite relationship was observed in a North American population of Drosophila melanogaster with admixed European and African ancestry. In order to explore how directional and epistatic selection can impact the relationship between introgression and recombination, we performed forward simulations of whole D. melanogaster genomes reflecting the North American population’s history. Our results revealed that the simplest models of positive selection often yield negative correlations between introgression and recombination such as the one observed in D. melanogaster. We also confirmed that incompatibilities tend to produce positive introgression–recombination correlations. And yet, we identify parameter space under each model where the predicted correlation is reversed. These findings deepen our understanding of the evolutionary forces that may shape patterns of ancestry across genomes, and they strengthen the foundation for future studies aimed at estimating genome-wide parameters of selection in admixed populations.

Temporal variation in selection is a fundamental determinant of evolutionary outcomes. A recent paper presented a synthetic analysis of temporal variation in selection in natural populations. The authors concluded that there is substantial variation in the strength and direction of selection over time, but acknowledged that sampling error would result in estimates of selection that were more variable than the true values. We reanalyze their dataset using techniques that account for the necessary effect of sampling error to inflate apparent levels of variation and show that directional selection is remarkably constant over time, both in magnitude and direction. Thus we cannot claim that the available data support the existence of substantial temporal heterogeneity in selection. Nonetheless, we conject that temporal variation in selection could be important, but that there are good reasons why it may not appear in the available data. These new analyses highlight the importance of applying techniques that estimate parameters of the distribution of selection, rather than parameters of the distribution of estimated selection (which will reflect both sampling error and \"real\" variation in selection); indeed, despite availability of methods for the former, focus on the latter has been common in synthetic reviews of the aspects of selection in nature, and can lead to serious misinterpretations.

Despite the potential for rapid evolution, stasis is commonly observed over geological timescales—the so-called \"paradox of stasis.\" This paradox would be resolved if stabilizing selection were common, but stabilizing selection is infrequently detected in natural populations. We hypothesize a simple solution to this apparent disconnect: stabilizing selection is hard to detect empirically once populations have adapted to a fitness peak. To test this hypothesis, we developed an individual-based model of a population evolving under an invariant stabilizing fitness function. Stabilizing selection on the population was infrequently detected in an \"empirical\" sampling protocol, because (1) trait variation was low relative to the fitness peak breadth; (2) nonselective deaths masked selection; (3) populations wandered around the fitness peak; and (4) sample sizes were typically too small. Moreover, the addition of negative frequency-dependent selection further hindered detection by flattening or even dimpling the fitness peak, a phenomenon we term \"squashed stabilizing selection.\" Our model demonstrates that stabilizing selection provides a plausible resolution to the paradox of stasis despite its infrequent detection in nature. The key reason is that selection \"erases its traces\": once populations have adapted to a fitness peak, they are no longer expected to exhibit detectable stabilizing selection.

Abstract Genetic divergence is the fundamental process that drives evolution and ultimately speciation. Structural variants (SVs) are large-scale genomic differences within a species or population and can cause functionally important phenotypic differences. Characterizing SVs across invasive species will fill knowledge gaps regarding how patterns of genetic diversity and genetic architecture shape rapid adaptation under new selection regimes. Here, we seek to understand patterns in genetic diversity within the globally invasive European starling, Sturnus vulgaris. Using whole genome sequencing of eight native United Kingdom (UK), eight invasive North America (NA), and 33 invasive Australian (AU) starlings, we examine patterns in genome-wide SNPs and SVs between populations and within Australia. Our findings detail the landscape of standing genetic variation across recently diverged continental populations of this invasive avian. We demonstrate that patterns of genetic diversity estimated from SVs do not necessarily reflect relative patterns from SNP data, either when considering patterns of diversity along the length of the organism's chromosomes (owing to enrichment of SVs in subtelomeric repeat regions), or interpopulation diversity patterns (possibly a result of altered selection regimes or introduction history). Finally, we find that levels of balancing selection within the native range differ across SNP and SV of different classes and outlier classifications. Overall, our results demonstrate that the processes that shape allelic diversity within populations is complex and support the need for further investigation of SVs across a range of taxa to better understand correlations between often well-studied SNP diversity and that of SVs.