Landscape Genomics of California Valley Oak (Quercus lobata)

Understanding the role of the environment in shaping genetic variation is a major goal of population genetics, and also provides important background for species management under global change. New genomic tools available for oaks (Quercus spp.) enable unprecedented insight into the genes that may be involved in local adaptation to changing environments along the landscape. To identify specific loci under the influence of natural selection for local adaptation and the particular climate factors shaping genome-wide variation, we analyzed thousands of SNPs from genotyping-by-sequencing of over 400 trees across the distribution of Q. lobata, a California endemic oak. We employed multivariate non-linear models and latent factor mixed models that account for underlying spatial genetic structure to identify SNPs with significant environmental associations and map their distributions on the landscape. We then utilized our recently generated annotated valley oak reference genome sequence to characterize the genomic context of SNPs with significant associations and attribute potential functions to them. We found that climate variables were associated with genomic variation but they varied along transects of different gradients and spatial scales. Across these transects, we repeatedly identified specific SNPs and genes as candidates for local adaptation. These results provide insight into selective forces along the natural landscape and generate a list of candidate genes associate with response to climate that warrant additional study with experimental approaches.