Nadeau Simon, Meirmans Patrick G, Aitken Sally N, Ritland Kermit, Isabel Nathalie
Natural Resources Canada Canadian Forest Service Laurentian Forestry Centre Québec QC Canada; Department of Forest and Conservation Sciences The University of British Columbia Vancouver BC Canada.
Institute for Biodiversity and Ecosystem Dynamics University of Amsterdam Amsterdam The Netherlands.
Ecol Evol. 2016 Oct 27;6(24):8649-8664. doi: 10.1002/ece3.2550. eCollection 2016 Dec.
Accurately detecting signatures of local adaptation using genetic-environment associations (GEAs) requires controlling for neutral patterns of population structure to reduce the risk of false positives. However, a high degree of collinearity between climatic gradients and neutral population structure can greatly reduce power, and the performance of GEA methods in such case is rarely evaluated in empirical studies. In this study, we attempted to disentangle the effects of local adaptation and isolation by environment (IBE) from those of isolation by distance (IBD) and isolation by colonization from glacial refugia (IBC) using range-wide samples in two white pine species. For this, SNPs from 168 genes, including 52 candidate genes for growth and phenology, were genotyped in 133 and 61 populations of and , respectively. For and using all 153 SNPs, climate (IBE) did not significantly explained among-population variation when controlling for IBD and IBC in redundancy analyses (RDAs). However, 26 SNPs were significantly associated with climate in single-locus GEA analyses (Bayenv2 and LFMM), suggesting that local adaptation took place in the presence of high gene flow. For , we found no evidence of IBE using RDAs and weaker signatures of local adaptation using GEA and outlier tests, consistent with adaptation via phenotypic plasticity. In both species, the majority of the explained among-population variation (69 to 96%) could not be partitioned between the effects of IBE, IBD, and IBC. GEA methods can account differently for this confounded variation, and this could explain the small overlap of SNPs detected between Bayenv2 and LFMM. Our study illustrates the inherent difficulty of taking into account neutral structure in natural populations and the importance of sampling designs that maximize climatic variation, while minimizing collinearity between climatic gradients and neutral structure.
使用遗传-环境关联(GEA)准确检测局部适应性特征需要控制种群结构的中性模式,以降低误报风险。然而,气候梯度与中性种群结构之间的高度共线性会大大降低检测效能,并且在实证研究中很少评估GEA方法在这种情况下的性能。在本研究中,我们试图利用两种白松物种的全分布样本,将局部适应性和环境隔离(IBE)的影响与距离隔离(IBD)和冰川避难所殖民隔离(IBC)的影响区分开来。为此,分别对133个和61个种群中的168个基因的单核苷酸多态性(SNP)进行了基因分型,其中包括52个与生长和物候相关的候选基因。对于 和 ,使用所有153个SNP,在冗余分析(RDA)中控制IBD和IBC时,气候(IBE)并未显著解释种群间的变异。然而,在单基因座GEA分析(Bayenv2和LFMM)中,有26个SNP与气候显著相关,这表明在高基因流存在的情况下发生了局部适应性。对于 ,我们使用RDA未发现IBE的证据,使用GEA和异常值检验发现局部适应性的特征较弱,这与通过表型可塑性进行的适应性一致。在这两个物种中,大部分解释的种群间变异(69%至96%)无法在IBE、IBD和IBC的影响之间进行划分。GEA方法对这种混淆变异的解释可能不同,这可以解释在Bayenv2和LFMM之间检测到的SNP的小重叠。我们的研究说明了在自然种群中考虑中性结构的内在困难,以及最大化气候变异同时最小化气候梯度与中性结构之间共线性的采样设计的重要性。