von Takach Brenton, Ahrens Collin W, Lindenmayer David B, Banks Sam C
Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT, Australia.
Fenner School of Environment and Society, The Australian National University, Canberra, ACT, Australia.
Mol Ecol. 2021 May;30(10):2248-2261. doi: 10.1111/mec.15894. Epub 2021 Apr 5.
Understanding local adaptation is critical for conservation management under rapidly changing environmental conditions. Local adaptation inferred from genotype-environment associations may show different genomic patterns depending on the spatial scale of sampling, due to differences in the slope of environmental gradients and the level of gene flow. We compared signatures of local adaptation across the genome of mountain ash (Eucalyptus regnans) at two spatial scales: A species-wide data set and a topographically-complex subregional data set. We genotyped 367 individual trees at over 3700 single-nucleotide polymorphisms (SNPs), quantified patterns of spatial genetic structure among populations, and used two analytical methods to identify loci associated with at least one of three environmental variables at each spatial scale. Together, the analyses identified 549 potentially adaptive SNPs at the subregion scale, and 435 SNPs at the range-wide scale. A total of 39 genic or near-genic SNPs, associated with 28 genes, were identified at both spatial scales, although no SNP was identified by both methods at both scales. We observed that nongenic regions had significantly higher homozygote excess than genic regions, possibly due to selective elimination of inbred genotypes during stand development. Our results suggest that strong environmental selection occurs in mountain ash, and that the identification of putatively adaptive loci can differ substantially depending on the spatial scale of analyses. We also highlight the importance of multiple adaptive genetic architectures for understanding patterns of local adaptation across large heterogenous landscapes, with comparison of putatively adaptive loci among spatial scales providing crucial insights into the process of adaptation.
在快速变化的环境条件下，了解局部适应性对于保护管理至关重要。从基因型 - 环境关联推断出的局部适应性可能会因环境梯度斜率和基因流水平的差异，根据采样的空间尺度显示出不同的基因组模式。我们在两个空间尺度上比较了山毛榉（Eucalyptus regnans）全基因组的局部适应性特征：一个全物种数据集和一个地形复杂的次区域数据集。我们对367棵个体树进行了超过3700个单核苷酸多态性（SNP）的基因分型，量化了种群间的空间遗传结构模式，并使用两种分析方法在每个空间尺度上识别与三个环境变量中至少一个相关的基因座。综合分析在次区域尺度上鉴定出549个潜在适应性SNP，在全范围尺度上鉴定出435个SNP。在两个空间尺度上共鉴定出39个与28个基因相关的基因或近基因SNP，尽管没有一个SNP在两个尺度上都被两种方法鉴定出来。我们观察到非基因区域的纯合子过剩显著高于基因区域，这可能是由于林分发育过程中对近交基因型的选择性消除。我们的结果表明，山毛榉中存在强烈的环境选择，并且推定适应性基因座的鉴定可能会因分析的空间尺度而有很大差异。我们还强调了多种适应性遗传结构对于理解大型异质景观中局部适应性模式的重要性，通过比较不同空间尺度上的推定适应性基因座可以为适应过程提供关键见解。
