Revealing local adaptation of Quercus suber L. populations under climate change through Genome Scans and Environmental Association Analysis

Abstract

Climate change is having an impact on locally adapted species, including the cork oak (Quercus suber L.), a key tree species in the Mediterranean region especially due to its role in carbon sequestration. Notably, the Maâmora forest in Morocco stands as the largest forest in the Mediterranean basin with the highest diversity compared to similar forests across Morocco. In this study, we genotyped 240 samples from natural populations of cork oak in the Maâmora forest using seven microsatellite markers, to investigate signatures of local adaptation. Using a genomic scan approach, we identified outliers loci experiencing divergent natural selection pressures, which were later correlated with climatic, edaphic, and geographic conditions of the Maâmora forest. Statistical analysis of the data shows a high allelic variation. The detection of outliers, carried out using BayeScan v2.1 software, revealed the presence of two significant outliers loci ZAG20-171 (qvalue = 0.0004) and MSQ4-211 (qvalue = 0.04). The result of the environmental association analysis revealed a significant correlation between locus ZAG20-171 with mean diurnal range, isothermality, annual precipitation, precipitation of the driest month, precipitation of the wettest quarter and altitude. This work aims to help understanding the genetic basis of adaptation in Q. suber L., and thus the selection of suitable provenances for further breeding efforts.