Estimating scale-specific and localized spatial patterns in allele frequency.

Characterizing spatial patterns in allele frequencies is fundamental to evolutionary biology because these patterns contain evidence of underlying processes. However, the spatial scales at which gene flow, changing selection, and drift act are often unknown. Many of these processes can operate inconsistently across space, causing non-stationary patterns. We present a wavelet approach to characterize spatial pattern in allele frequency that helps solve these problems. We show how our approach can characterize spatial patterns in relatedness at multiple spatial scales, i.e. a multi-locus wavelet genetic dissimilarity. We also develop wavelet tests of spatial differentiation in allele frequency and quantitative trait loci (QTL). With simulation we illustrate these methods under different scenarios. We also apply our approach to natural populations of Arabidopsis thaliana to characterize population structure and identify locally-adapted loci across scales. We find, for example, that Arabidopsis flowering time QTL show significantly elevated genetic differentiation at 300 to 1300 km scales. Wavelet transforms of allele frequencies offer a flexible way to reveal geographic patterns and underlying evolutionary processes.

Climate biogeography of Arabidopsis thaliana: linking distribution models and individual variation.

AIM: Patterns of individual variation are key to testing hypotheses about the mechanisms underlying biogeographic patterns. If species distributions are determined by environmental constraints, then populations near range margins may have reduced performance and be adapted to harsher environments. Model organisms are potentially important systems for biogeographical studies, given the available range-wide natural history collections, and the importance of providing biogeographical context to their genetic and phenotypic diversity. LOCATION: Global. TAXON: Arabidopsis thaliana ("Arabidopsis"). METHODS: We fit occurrence records to climate data, and then projected the distribution of Arabidopsis under last glacial maximum, current, and future climates. We confronted model predictions with individual performance measured on 2,194 herbarium specimens, and we asked whether predicted suitability was associated with life-history and genomic variation measured on ~900 natural accessions. RESULTS: The most important climate variables constraining the Arabidopsis distribution were winter cold in northern and high elevation regions and summer heat in southern regions. Herbarium specimens from regions with lower habitat suitability in both northern and southern regions were smaller, supporting the hypothesis that the distribution of Arabidopsis is constrained by climate-associated factors. Climate anomalies partly explained interannual variation in herbarium specimen size, but these did not closely correspond to local limiting factors identified in the distribution model. Late-flowering genotypes were absent from the lowest suitability regions, suggesting slower life histories are only viable closer to the center of the realized niche. We identified glacial refugia farther north than previously recognized, as well as refugia concordant with previous population genetic findings. Lower latitude populations, known to be genetically distinct, are most threatened by future climate change. The recently colonized range of Arabidopsis was well-predicted by our native-range model applied to certain regions but not others, suggesting it has colonized novel climates. MAIN CONCLUSIONS: Integration of distribution models with performance data from vast natural history collections is a route forward for testing biogeographical hypotheses about species distributions and their relationship with evolutionary fitness across large scales.

Pollinator type strongly impacts gene flow within and among plant populations for six Neotropical species.

Animal pollinators directly affect plant gene flow by transferring pollen grains between individuals. Pollinators with restricted mobility are predicted to limit gene flow within and among populations, whereas pollinators that fly longer distances are likely to promote genetic cohesion. These predictions, however, remain poorly tested. We examined population genetic structure and fine-scale spatial genetic structure (FSGS) in six perennial understory angiosperms in Andean cloud forests of northwestern Ecuador. Species belong to three families (Gesneriaceae, Melastomataceae, and Rubiaceae), and within each family we paired one insect-pollinated with one hummingbird-pollinated species, predicting that insect-pollinated species have greater population differentiation (as quantified with the FST statistic) and stronger FSGS (as quantified with the SP statistic) than hummingbird-pollinated species. We confirmed putative pollinators through a literature review and fieldwork, and inferred population genetic parameters with a genome-wide genotyping approach. In two of the three species pairs, insect-pollinated species had much greater (>2-fold) population-level genetic differentiation and correspondingly steeper declines in fine-scale genetic relatedness. In the Gesneriaceae pair, however, FST and SP values were similar between species and to those of the other hummingbird-pollinated plants. In this pair, the insect pollinators are euglossine bees (as opposed to small bees and flies in the other pairs), which are thought to forage over large areas, and therefore may provide similar levels of gene flow as hummingbirds. Overall, our results shed light on how different animal pollination modes influence the spatial scale of plant gene flow, suggesting that small insects strongly decrease genetic cohesion.

Global patterns of population genetic differentiation in seed plants.

Evaluating the factors that drive patterns of population differentiation in plants is critical for understanding several biological processes such as local adaptation and incipient speciation. Previous studies have given conflicting results regarding the significance of pollination mode, seed dispersal mode, mating system, growth form and latitudinal region in shaping patterns of genetic structure, as estimated by FST values, and no study to date has tested their relative importance together across a broad scale. Here, we assembled a 337-species data set for seed plants from publications with data on FST from nuclear markers and species traits, including variables pertaining to the sampling scheme of each study. We used species traits, while accounting for sampling variables, to perform phylogenetic multiple regressions. Results demonstrated that FST values were higher for tropical, mixed-mating, non-woody species pollinated by small insects, indicating greater population differentiation, and lower for temperate, outcrossing trees pollinated by wind. Among the factors we tested, latitudinal region explained the largest portion of variance, followed by pollination mode, mating system and growth form, while seed dispersal mode did not significantly relate to FST . Our analyses provide the most robust and comprehensive evaluation to date of the main ecological factors predicted to drive population differentiation in seed plants, with important implications for understanding the basis of their genetic divergence. Our study supports previous findings showing greater population differentiation in tropical regions and is the first that we are aware of to robustly demonstrate greater population differentiation in species pollinated by small insects.

Achilles is a circadian clock-controlled gene that regulates immune function in Drosophila.

The circadian clock is a transcriptional/translational feedback loop that drives the rhythmic expression of downstream mRNAs. Termed "clock-controlled genes," these molecular outputs of the circadian clock orchestrate cellular, metabolic, and behavioral rhythms. As part of our on-going work to characterize key upstream regulators of circadian mRNA expression, we have identified a novel clock-controlled gene in Drosophila melanogaster, Achilles (Achl), which is rhythmic at the mRNA level in the brain and which represses expression of antimicrobial peptides in the immune system. Achilles knock-down in neurons dramatically elevates expression of crucial immune response genes, including IM1 (Immune induced molecule 1), Mtk (Metchnikowin), and Drs (Drosomysin). As a result, flies with knocked-down Achilles expression are resistant to bacterial challenges. Meanwhile, no significant change in core clock gene expression and locomotor activity is observed, suggesting that Achilles influences rhythmic mRNA outputs rather than directly regulating the core timekeeping mechanism. Notably, Achilles knock-down in the absence of immune challenge significantly diminishes the fly's overall lifespan, indicating a behavioral or metabolic cost of constitutively activating this pathway. Together, our data demonstrate that (1) Achilles is a novel clock-controlled gene that (2) regulates the immune system, and (3) participates in signaling from neurons to immunological tissues.