Data from: Influence of range position on locally adaptive gene-environment associations in Populus flowering time genes
Keller, Stephen R.; Chhatre, Vikram E.; Fitzpatrick, Matthew C. (2017), Data from: Influence of range position on locally adaptive gene-environment associations in Populus flowering time genes, Dryad, Dataset, https://doi.org/10.5061/dryad.gp78p
Local adaptation is pervasive in forest trees, which are characterized by large effective population sizes spanning broad climatic gradients. In addition to having relatively contiguous populations, many species also form isolated populations along the rear edge of their range. These rear-edge populations may contain unique adaptive diversity reflecting a history of selection in marginal environments. Thus, discovering genomic regions conferring local adaptation in rear edge populations is a key priority for landscape genomics to ensure conservation of genetic resources under climate change. Here, we report on adaptive gene-environment associations in SNPs from 27 genes in the Populus flowering time gene network, analyzed on a range-wide collection of >1000 balsam poplar trees, including dense sampling of the southern range edge. We use a combined approach of local adaptation scans to identify candidate SNPs, followed by modeling the compositional turnover of adaptive SNPs along multivariate climate gradients using Gradient Forests (GF). Flowering time candidate genes contained extensive evidence of climate adaptation, namely outlier population structure and gene-environment associations, along with allele frequency divergence between the core and edge of the range. GF showed strong allele frequency turnover along gradients of elevation and diurnal temperature variability, as well as threshold responses to summer temperature and precipitation, with turnover especially strong in edge populations that occur at high elevation but southerly latitudes. We discuss these results in light of how climate may disrupt locally adaptivegene-environment relationships, and suggest that rear edge populations hold climate-adaptive variants that should be targeted for conservation.
National Science Foundation, Award: IOS-1461868