Landscape Genomics of East Texas Loblolly Pine (Pinus taeda L.)

There is a growing need to better understand local adaptation using landscape genomics approaches to mitigate climate change and to breed more drought and disease resilient trees.  Loblolly pine (Pinus taeda L.) has a great economic importance and also a wide geographic distribution occupying a variety of environmental conditions, which makes it a good system to address these issues. We used genotypic data based on a genome-wide set of ~4000 SNPs representing expressed loci to study genetic association of East Texas loblolly pines from the Western Gulf Forest Tree Improvement Program with environmental variables. SNP genotypes of ~450 trees from 27 counties across East Texas were used in this study. Environmental data for monthly and annual temperature and precipitation for the last 40 years were obtained from PRISM (www.prismclimate.org), and elevation data from WORLDCLIM (www.worldclim.org). Two complex variables -- Growing Degree Days (Rehfeldt, 2006) representing annual growing season, and Aridity Index (ratio of precipitation to evapo-transpiration, (Eckert et al, 2010) were constructed from the environmental data. In addition, latitudes and longitudes were obtained for each county. Significance of correlation between environmental and geographic variables was first tested to identify environmental gradients across the study area. Correlation of county specific allele frequencies with various environmental variables was tested using Bayesian methods in BAYENV (Coop et al, 2010).  Clinal variation in allele frequencies was tested with logistic regression. An F_ST outlier approach was used to identify signatures of selection.  Implications of our results for breeding, genetic conservation and towards understanding local adaptation will be discussed.