Evidence of phenotypic and genomic adaptation along three elevational transects in Quercus lobata Née

Background/Question/Methods

Identifying phenotypes and genes in natural populations that are under selection by local climate is an important goal for evaluating local adaptation in response to climate. Elevational gradients offer a rare opportunity to evaluate the extent of local adaptation in response to climate over small spatial scales.  We sampled leaves for morphological and genetic analysis and acorns from 132 Quercus lobata trees (valley oak) from three elevational transect: Mount Hamilton (Santa Clara) in the Coastal Ranges, Madera (Madera) in the Sierra Foothills and Techachapi region (Kern Co.) of the Transverse Ranges.  Specific goals are to test: i) clines in morphological traits with climate gradients on trees samples; ii) heritability of those morphological traits on the seedlings, and iii) genetic clines with climate gradients using associations of single-nucleotide polymorphisms (SNPs) and climate variables. We measured leaf thickness, leaf dry mass, leaf shape, leaf area for each tree and analyzed the data using canonical discriminant function analysis and linear correlations. From the seedlings, we recorded days to germination, diameter, height and will record the same leaf traits as in the adult trees. We generated genomic data using a genotyping-by-sequencing approach and analyzed SNPs using multivariate redundancy analysis and linear mixed models (EMMAX).

Results/Conclusions

For adult samples, leaf dry mass and leaf thickness explained most of the difference among transects. Leaf thickness was negatively correlated with elevation in the Madera and Techachapi transects (R² = 0.31, 0.17, respectively; P< 0.01), negatively correlated with growing season precipitation (gsp) in Madera (R² = 0.38; P=0.0001), and positively correlated with frost-free period (ffp) in Techachapi (R² = 0.23; P=0.0003). For the third transect, Mt. Hamilton, we found no significant correlations between leaf traits and elevation/climate. Morphological analyses of seedlings are underway, and several traits have high heritability. For Mt. Hamilton, SNP-climate association analysis of 5,379 SNPs from 21 trees using redundancy analysis showed significant correlation between SNP allele frequency and climate (P = 0.04), where climate explains 65.2% of SNP variation when geography was controlled, and growing degree-days >5°C (dd5), ffp and gsp explained most of the SNP variation along altitudinal gradients. For Mt. Hamilton, SNP-climate association analysis using EMMAX, showed 7 SNPs significantly associated with dd5, ffp, and gsp (P< 0.0001; Q=0.0001- 0.13, after correction for multiple tests).  In conclusion, we find genetically-based morphological variation associating with gradients and SNPs that provide evidence for local adaption to climate.