Adaptation in eukaryotes is generally assumed to be mutation-limited because of small effective population sizes. This view is difficult to reconcile, however, with the observation that adaptation to anthropogenic changes, such as the introduction of pesticides, can occur very rapidly. Here we investigate adaptation at a key insecticide resistance locus (Ace) in Drosophila melanogaster and show that multiple simple and complex resistance alleles evolved quickly and repeatedly within individual populations. Our results imply that the current effective population size of modern D. melanogaster populations is likely to be substantially larger (≥100-fold) than commonly believed. This discrepancy arises because estimates of the effective population size are generally derived from levels of standing variation and thus reveal long-term population dynamics dominated by sharp—even if infrequent—bottlenecks. The short-term effective population sizes relevant for strong adaptation, on the other hand, might be much closer to census population sizes. Adaptation in Drosophila may therefore not be limited by waiting for mutations at single sites, and complex adaptive alleles can be generated quickly without fixation of intermediate states. Adaptive events should also commonly involve the simultaneous rise in frequency of independently generated adaptive mutations. These so-called soft sweeps have very distinct effects on the linked neutral polymorphisms compared to the standard hard sweeps in mutation-limited scenarios. Methods for the mapping of adaptive mutations or association mapping of evolutionarily relevant mutations may thus need to be reconsidered.

Plants have evolved an array of defenses against pathogens. However, mounting a defense response frequently comes with the cost of a reduction in growth and reproduction, carrying critical implications for natural and agricultural populations. This review focuses on how costs are generated and whether and how they can be mitigated. Most well-characterized growth-defense trade-offs stem from antagonistic crosstalk among hormones rather than an identified metabolic expenditure. A primary way plants mitigate such costs is through restricted expression of resistance; this can be achieved through inducible expression of defense genes or by the concentration of defense to particular times or tissues. Defense pathways can be primed for more effective induction, and primed states can be transmitted to offspring. We examine the resistance () genes as a case study of how the toll of defense can be generated and ameliorated. The fine-scale regulation of genes is critical to alleviate the burden of their expression, and the genomic organization of genes into coregulatory modules reduces costs. Plants can also recruit protection from other species. Exciting new evidence indicates that a plant's genotype influences the microbiome composition, lending credence to the hypothesis that plants shape their microbiome to enhance defense.

SummaryCrop disease outbreaks are often associated with clonal expansions of single pathogenic lineages. To determine whether similar boom-and-bust scenarios hold for wild pathosystems, we carried out a multi-year, multi-site survey of Pseudomonas in its natural host Arabidopsis thaliana. The most common Pseudomonas lineage corresponded to a ubiquitous pathogenic clade. Sequencing of 1,524 genomes revealed this lineage to have diversified approximately 300,000 years ago, containing dozens of genetically identifiable pathogenic sublineages. There is differentiation at the level of both gene content and disease phenotype, although the differentiation may not provide fitness advantages to specific sublineages. The coexistence of sublineages indicates that in contrast to crop systems, no single strain has been able to overtake the studied A. thaliana populations in the recent past. Our results suggest that selective pressures acting on a plant pathogen in wild hosts are likely to be much more complex than those in agricultural systems.

Investigating spatial patterns of loci under selection can give insight into how populations evolved in response to selective pressures and can provide monitoring tools for detecting the impact of environmental changes on populations. Drosophila is a particularly good model to study adaptation to environmental heterogeneity since it is a tropical species that originated in sub-Saharan Africa and has only recently colonized the rest of the world. There is strong evidence for the adaptive role of Transposable Elements (TEs) in the evolution of Drosophila, and TEs might play an important role specifically in adaptation to temperate climates. In this work, we analyzed the frequency of a set of putatively adaptive and putatively neutral TEs in populations with contrasting climates that were collected near the endpoints of two known latitudinal clines in Australia and North America. The contrasting results obtained for putatively adaptive and putatively neutral TEs and the consistency of the patterns between continents strongly suggest that putatively adaptive TEs are involved in adaptation to temperate climates. We integrated information on population behavior, possible environmental selective agents, and both molecular and functional information of the TEs and their nearby genes to infer the plausible phenotypic consequences of these insertions. We conclude that adaptation to temperate environments is widespread in Drosophila and that TEs play a significant role in this adaptation. It is remarkable that such a diverse set of TEs located next to a diverse set of genes are consistently adaptive to temperate climate-related factors. We argue that reverse population genomic analyses, as the one described in this work, are necessary to arrive at a comprehensive picture of adaptation.

Local adaptation in response to spatially varying selection pressures is widely recognized as a ubiquitous feature for many organisms. In contrast, our understanding of local adaptation to temporally varying selection pressures is limited. To advance our understanding of local adaptation to temporally varying selection pressures, we studied genomic signatures of seasonal adaptation in Drosophila melanogaster. We generated whole-genome estimates of allele frequencies from flies sampled during the spring and fall from 15 localities. We show that seasonal adaptation is a general feature fly populations and that the direction of seasonal adaptation can be predicted by weather conditions in the weeks prior to sampling. We find that seasonal changes in allele frequency are mirrored by spatial variation in allele frequency and that seasonal adaptation affects allele frequencies at ~1.0-2.5% of polymorphisms genomewide. Our work demonstrates that seasonal adaptation is a major evolutionary force affecting D. melanogaster populations living in temperate environments.

Plant resistance (R) genes are a crucial component in plant defence against pathogens1. Although R genes often fail to provide durable resistance in an agricultural context, they frequently persist as long-lived balanced polymorphisms in nature2–4. Standard theory explains the maintenance of such polymorphisms through a balance of the costs and benefits of resistance and virulence in a tightly coevolving host–pathogen pair5,6. However, many plant–pathogen interactions lack such specificity7. Whether, and how, balanced polymorphisms are maintained in diffusely interacting species8 is unknown. Here we identify anaturally interacting R gene and effector pair in Arabidopsis thaliana and its facultative plant pathogen, Pseudomonas syringae. The protein encoded by the R gene RPS5 recognizes an AvrPphB homologue (AvrPphB2) and exhibits a balanced polymorphism that has been maintained for over 2 million years (ref. 3). Consistent with the presence of an ancient balanced polymorphism, the R gene confers a benefit when plants are infected with P. syringae carrying avrPphB2 but also incurs a large cost in the absence of infection. RPS5 alleles are maintained at intermediate frequencies in populations globally, suggesting ubiquitous selection for resistance. However, the presence of P. syringae carrying avrPphB is probably insufficient to explain the RPS5 polymorphism. First, avrPphB homologues occur at very low frequencies in P. syringae populations on A. thaliana. Second, AvrPphB only rarely confers a virulence benefit to P. syringae on A. thaliana. Instead, we find evidence that selection for RPS5 involves multiple non-homologous effectors and multiple pathogen species. These results and an associated model suggest that the R gene polymorphism in A. thaliana may not be maintained through a tightly coupled interaction involving a single coevolved R gene and effector pair. More likely, the stable polymorphism is maintained through complex and diffuse community-wide interactions.

Pathogens apply one of the strongest selective pressures in plant populations. Understanding plant–pathogen coevolution has therefore been a major research focus for at least sixty years [1]. Recent comparative genomic studies have revealed that the genes involved in plant defense and pathogen virulence are among the most polymorphic in the respective genomes. Which fraction of this diversity influences the host–pathogen interaction? Do coevolutionary dynamics maintain variation? Here we review recent literature on the evolutionary and molecular processes that shape this variation, focusing primarily on gene-for-gene interactions. In summarizing theoretical and empirical studies of the processes that shape this variation in natural plant and pathogen populations, we find a disconnect between the complexity of ecological interactions involving hosts and their myriad microbes, and the models that describe them.

Microorganisms from all domains of life establish associations with plants. Although some harm the plant, others antagonize pathogens or prime the plant immune system, support the acquisition of nutrients, tune plant hormone levels, or perform additional services. Most culture-independent plant microbiome research has focused on amplicon sequencing of the 16S rRNA gene and/or the internal transcribed spacer (ITS) of rRNA genomic loci, which show the relative abundance of the microbes to each other. Here, we describe shotgun sequencing of 275 wild Arabidopsis thaliana leaf microbiomes from southwest Germany, with additional bacterial 16S and eukaryotic ITS1 rRNA amplicon data from 176 of these samples. Shotgun data, which unlike the amplicon data capture the ratio of microbe to plant DNA, enable scaling of microbial read abundances to reflect the microbial load on the host. In a more cost-effective hybrid strategy, we show they also allow a similar scaling of amplicon data to overcome compositionality problems. Our wild plants were dominated by bacterial sequences, with eukaryotes contributing only a minority of reads. Microbial membership showed weak associations with both site of origin and plant genotype, both of which were highly confounded in this dataset. There was large variation among microbiomes, with one extreme comprising samples of low complexity and a high load of microorganisms typical of infected plants, and the other extreme being samples of high complexity and a low microbial load. Critically, considering absolute microbial load led to fundamentally different conclusions about microbiome assembly and the interaction networks among major taxa.