Landscape genomics of Quercus lobata reveals genes involved in local climate adaptation at multiple spatial scales.

Understanding how the environment shapes genetic variation provides critical insight about the evolution of local adaptation in natural populations. At multiple spatial scales and multiple geographic contexts within a single species, such information could address a number of fundamental questions about the scale of local adaptation and whether or not the same loci are involved at different spatial scales or geographic contexts. We used landscape genomic approaches from three local elevational transects and rangewide sampling to (a) identify genetic variation underlying local adaptation to environmental gradients in the California endemic oak, Quercus lobata; (b) examine whether putatively adaptive SNPs show signatures of selection at multiple spatial scales; and (c) map putatively adaptive variation to assess the scale and pattern of local adaptation. Of over 10 k single-nucleotide polymorphisms (SNPs) generated with genotyping-by-sequencing, we found signatures of natural selection by climate or local environment at over 600 SNPs (536 loci), some at multiple spatial scales across multiple analyses. Candidate SNPs identified with gene-environment tests (LFMM) at the rangewide scale also showed elevated associations with climate variables compared to the background at both rangewide and elevational transect scales with gradient forest analysis. Some loci overlap with those detected in other oak species, raising the question of whether the same loci might be involved in local climate adaptation in different congeneric species that inhabit different geographic contexts. Mapping landscape patterns of adaptive versus background genetic variation identified regions of marked local adaptation and suggests nonlinear association of candidate SNPs and environmental variables. Taken together, our results offer robust evidence for novel candidate genes for local climate adaptation at multiple spatial scales.