Data from: Signatures of local adaptation in candidate genes of oaks (Quercus spp.) in respect to present and future climatic conditions

Testing how populations are locally adapted and predicting their response to their future environment is of key importance in view of climate change. Landscape genomics is a powerful approach to investigate genes and environmental factors involved in local adaptation. In a pooled amplicon sequencing approach of 94 genes in 71 populations, we tested if >3'500 single nucleotide polymorphisms (SNPs) in the three most common oak species in Switzerland (Quercus petraea, Q. pubescens, Q. robur) show an association with abiotic factors related to local topography, historical climate, and soil characteristics. In the analysis including all species, the most frequently associated environmental factors were those best describing the habitats of the species. In the species-specific analyses, the most important environmental factors and associated SNPs greatly differed among species. However, we identified one SNP and seven genes that were associated to the same environmental factor across all species. We finally used regressions of allele frequencies of the most strongly associated SNPs along environmental gradients to predict the risk of non-adaptedness (RONA), which represents the average change in allele frequency at climate-associated loci theoretically required to match future climatic conditions. RONA is considerable for some populations and species (up to 48% in single populations) and strongly differs among species. Given the long generation time of oaks, some of the required allele frequency changes might not be realistic to achieve based on standing genetic variation. Hence, future adaptedness requires gene flow or planting of individuals carrying beneficial alleles from habitats currently matching future climatic conditions.

鉴于气候变化背景下，探究种群本地适应性机制并预测其对未来环境的响应具有关键意义。景观基因组学（Landscape Genomics）是探究参与本地适应性过程的基因与环境因子的有力研究手段。本研究针对71个种群的94个基因开展混合扩增子测序分析，检测瑞士境内三种常见栎属物种——夏栎（Quercus petraea）、柔毛栎（Quercus pubescens）与欧洲栎（Quercus robur）——中超过3500个单核苷酸多态性（Single Nucleotide Polymorphism, SNPs）与本地地形、历史气候及土壤特征等非生物因子的关联情况。在涵盖所有物种的整合分析中，与位点关联最为频繁的环境因子恰是最能表征该类群栖息生境的因子；而在物种特异性分析中，不同物种间的关键环境因子及其关联的单核苷酸多态性均存在显著差异。不过本研究仍鉴定出1个单核苷酸多态性位点与7个基因，在所有栎属物种中均与同一环境因子存在关联。本研究最终借助沿环境梯度分布的强关联单核苷酸多态性的等位基因频率回归模型，预测了非适应性风险（Risk of Non-Adaptedness, RONA）——该指标指为匹配未来气候条件，理论上气候关联位点所需发生的平均等位基因频率变化幅度。部分种群与物种的非适应性风险较高，单个种群中最高可达48%，且不同物种间的风险差异显著。考虑到栎属植物较长的世代周期，基于现存遗传变异，部分所需的等位基因频率变化或许难以实现。因此，要实现未来的适应性演化，需借助基因流，或引种携带与未来气候匹配的当前生境中有益等位基因的个体。