Signatures of natural selection on Pinus cembra and P. mugo along elevational gradients in the Alps

Abstract

Alpine regions represent an interesting biome for studying local adaptation in forest trees. Strong genetic differentiation is expected along elevational gradients in spite of extensive gene flow. We sampled 18 and 20 natural populations of Pinus cembra and Pinus mugo, in two subregions and four elevational gradients. To investigate the effects of elevation on genetic diversity and adaptation, 768 and 1152 single nucleotide polymorphisms (SNPs) were genotyped in P. cembra and P. mugo. We found low but significant genetic differentiation among populations in both species. To discover outliers, we applied Bayesian simulation and hierarchical island model analyses. A larger number of outliers were found using the first method. Some SNPs were detected with both analyses: one SNP in P. cembra and three in P. mugo when using two subregions and four SNPs in P. cembra and one in P. mugo when using four elevational gradients. The association between environmental and genetic variation was tested with Bayesian simulation (Bayenv) and a latent factor mixed model (LFMM). The first method, using all populations, detected 6 and 20 SNPs associated to temperature in P. cembra and in P. mugo, respectively, 3 SNPs associated to precipitation in P. cembra, and 14 SNPs to elevation in P. mugo. The LFMM found a higher number of SNPs associated to temperature in P. mugo than in P. cembra (37 vs. 27), with a stronger association with maximum temperature (April–June). In P. cembra, the majority of associations (51 SNPs) were found with precipitation (January–March). Five SNPs in common between species were found on genes potentially involved in plant response to abiotic stress. Using these results, we confirmed that temperature was an important driver of adaptive potential for each species so that continued changes to global temperatures will likely involve continued adaptation as ranges shift upwards.