Data from: Local adaptation (mostly) remains local: reassessing environmental associations of climate-related candidate SNPs in Arabidopsis halleri

Numerous landscape genomic studies have identified single-nucleotide polymorphisms (SNPs) and genes potentially involved in local adaptation. Rarely, it has been explicitly evaluated whether these environmental associations also hold true beyond the populations studied. We tested whether putatively adaptive SNPs in Arabidopsis halleri (Brassicaceae), characterized in a previous study investigating local adaptation to a highly heterogeneous environment, show the same environmental associations in an independent, geographically enlarged set of 18 populations. We analysed new SNP data of 444 plants with the same methodology (partial Mantel tests, PMTs) as in the original study and additionally with a latent factor mixed model (LFMM) approach. Of the 74 candidate SNPs, 41% (PMTs) and 51% (LFMM) were associated with environmental factors in the independent data set. However, only 5% (PMTs) and 15% (LFMM) of the associations showed the same environment–allele relationships as in the original study. In total, we found 11 genes (31%) containing the same association in the original and independent data set. These can be considered prime candidate genes for environmental adaptation at a broader geographical scale. Our results suggest that selection pressures in highly heterogeneous alpine environments vary locally and signatures of selection are likely to be population-specific. Thus, genotype-by-environment interactions underlying adaptation are more heterogeneous and complex than is often assumed, which might represent a problem when testing for adaptation at specific loci.

诸多景观基因组学研究已鉴定出可能参与局部适应的单核苷酸多态性（single-nucleotide polymorphisms, SNPs）与相关基因。鲜有研究明确评估过，这些环境关联是否在已研究种群之外依然成立。本研究针对此前一项探究高度异质环境下局部适应的研究中所表征的高山拟南芥（Arabidopsis halleri，十字花科Brassicaceae）的假定适应性SNPs，检验其在独立且地理范围扩大的18个种群集合中是否呈现相同的环境关联。本研究采用与原始研究一致的方法（偏曼特尔检验，partial Mantel tests, PMTs），并额外使用潜在因子混合模型（latent factor mixed model, LFMM），对444株植物的全新SNP数据展开分析。在74个候选SNPs中，独立数据集内分别有41%（偏曼特尔检验）与51%（潜在因子混合模型）的位点与环境因子存在关联。然而，仅5%（偏曼特尔检验）与15%（潜在因子混合模型）的关联呈现出与原始研究一致的环境-等位基因关系。总计有11个基因（占比31%）在原始数据集与独立数据集内均呈现相同的关联，这些基因可被视为更大地理尺度下环境适应的核心候选基因。本研究结果表明，高度异质的高山环境中选择压力存在局部分异，选择信号大概率具有种群特异性。因此，支撑适应过程的基因型-环境互作远比通常假设的更为异质且复杂，这在针对特定位点开展适应检测时可能构成挑战。