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.

Most natural populations are affected by seasonal changes in temperature, rainfall, or resource availability. Seasonally fluctuating selection could potentially make a large contribution to maintaining genetic polymorphism in populations. However, previous theory suggests that the conditions for multi-locus polymorphism are restrictive. Here we explore a more general class of models with multi-locus seasonally fluctuating selection in diploids.In these models, loci first contribute additively to a seasonal score, with a dominance parameter determining the relative contributions of heterozygous and homozygous loci. The seasonal score is then mapped to fitness via a monotonically increasing function, thereby accounting for epistasis. Using mathematical analysis and individual-based simulations, we show that stable polymorphism at many loci is possible if currently favored alleles are sufficiently dominant with respect to the additive seasonal score (but not necessarily with respect to fitness itself). This general mechanism, which we call "segregation lift", operates for various genotype-to-fitness maps and includes the previously known mechanism of multiplicative selection with marginal overdominance as a special case. We show that segregation lift may arise naturally in situations with antagonistic pleiotropy and 1 not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/115444 doi: bioRxiv preprint first posted online Mar. 9, 2017; seasonal changes in the relative importance of traits for fitness. Segregation lift is not affected by problems of genetic load and is robust to differences in parameters across loci and seasons. Under segregation lift, loci can exhibit conspicuous seasonal allele-frequency fluctuations, but often fluctuations may also be small and hard to detect. Via segregation lift, seasonally fluctuating selection might contribute substantially to maintaining genetic variation in natural populations.Keywords temporal heterogeneity | cyclical selection | maintenance of genetic diversity | marginal overdominance | balancing selection

Finding the specific nucleotides that underlie adaptive variation is a major goal in evolutionary biology, but polygenic traits pose a challenge because the complex genotype-phenotype relationship can obscure the effects of individual alleles. However, natural selection working in large wild populations can shift allele frequencies and indicate functional regions of the genome. Previously, we showed that the two most common alleles of a complex amino acid insertion-deletion polymorphism in the Drosophila insulin receptor show independent, parallel clines in frequency across the North American and Australian continents. Here, we report that the cline is stable over at least a five-year period and that the polymorphism also demonstrates temporal shifts in allele frequency concurrent with seasonal change. We tested the alleles for effects on levels of insulin signaling, fecundity, development time, body size, stress tolerance, and lifespan. We find that the alleles are associated with predictable differences in these traits, consistent with patterns of Drosophila life history variation across geography that likely reflect adaptation to the heterogeneous climatic environment. These results implicate insulin signaling as a major mediator of life history adaptation in Drosophila, and suggest that life history tradeoffs can be explained by extensive pleiotropy at a single locus.

Species across the tree of life can switch between asexual and sexual reproduction. In facultatively sexual species, the ability to switch between reproductive modes is often environmentally dependent and subject to local adaptation. However, the ecological and evolutionary factors that influence the maintenance and turnover of polymorphism associated with facultative sex remain unclear. To address this basic question, we studied the ecological and evolutionary dynamics of polymorphism in reproductive strategy in a metapopulation of the model facultative sexual, Daphnia pulex, located in the southern United Kingdom. We found that patterns of clonal diversity, but not genetic diversity varied with ephemerality. Reconstruction of a multi-year pedigree demonstrated the co-existence of clones that were found to differ in their investment into male production. Mapping of quantitative variation in male production using lab-generated and field-collected individuals identified multiple putative QTL underlying this trait, and we identified a plausible candidate gene. The evolutionary history of these QTL suggests that they are relatively young, and male limitation in this system is a rapidly evolving trait. Our work highlights the dynamic nature of the genetic structure and composition of facultative sex across space and time and suggests that quantitative genetic variation in reproductive strategy can undergo rapid evolutionary turnover.

Herbivores often move among spatially interspersed host plants, tracking high-quality resources through space and time. This dispersal is of particular interest for vectors of plant pathogens. Existing molecular tools to track such movement have yielded important insights, but often provide insufficient genetic resolution to infer spread at finer spatiotemporal scales. Here, we explore the use of Nextera-tagmented reductively-amplified DNA (NextRAD) sequencing to infer movement of a highly-mobile winged insect, the potato psyllid (Bactericera cockerelli), among host plants. The psyllid vectors the pathogen that causes zebra chip disease in potato (Solanum tuberosum), but understanding and managing the spread of this pathogen is limited by uncertainty about the insect's host plant(s) outside of the growing season. We identified 8,443 polymorphic loci among psyllids separated spatiotemporally on potato or in patches of bittersweet nightshade (S. dulcumara), a weedy plant proposed to be the source of potatocolonizing psyllids. A subset of the psyllids on potato exhibited close genetic similarity to insects on nightshade, consistent with regular movement between these two host plants. However, a second subset of potato-collected psyllids was genetically distinct from those collected on bittersweet nightshade; this suggests that a currently unrecognized host-plant species could be contributing to psyllid populations in potato. Oftentimes, dispersal of vectors of plant or animal pathogens must be tracked at a relatively fine scale in order to understand, predict, and manage disease spread. We demonstrate that emerging sequencing technologies that detect SNPs across a vector's entire genome can be used to infer such localized movement.