Abstract
Plant populations can undergo very localized adaptation, allowing widely distributed populations to adapt to divergent habitats in spite of recurrent gene flow. Neotropical trees whose large and undisturbed populations often span a variety of environmental conditions and local habitats are particularly good models to study this process. Here, we carried out a genome scan for selection through whole-genome sequencing of pools of populations, sampled according to a nested sampling design, to evaluate microgeographic adaptation in the hyperdominant Amazonian tree Eperua falcata Aubl. (Fabaceae). A high-coverage genomic resource of 250 Mb was assembled de novo and annotated, leading to 32,789 predicted genes. 97,062 bi-allelic SNPs were detected over 25,803 contigs, and a custom Bayesian model was implemented to uncover candidate genomic targets of divergent selection. A set of 290 divergence outlier SNPs was detected at the regional scale (between study sites), while 185 SNPs located in the vicinity of 106 protein-coding genes were detected as replicated outliers between microhabitats within regions. These genes potentially underlie ecologically important phenotypes and indicate that adaptation to microgeographic habitat patchiness would affect genomic regions involved in a variety of physiological processes, among which plant response to stress (for e.g., oxidative stress, hypoxia and metal toxicity) and biotic interactions. Identification of genomic targets of microgeographic adaptation in the Neotropics is consistent with the hypothesis that local adaptation is a key driver of ecological diversification, operating across multiple spatial scales, from large (i.e. regional) to microgeographic (i.e. landscape) scales.