Abstract：
Genetic adaptation to future environmental conditions is crucial to help species persist as the climate changes. Genome scans are powerful tools to understand adaptive landscapes, enabling us to correlate genetic diversity with environmental gradients while disentangling neutral from adaptive variation. However, low gene flow can lead to both local adaptation and highly structured populations, and is a major confounding factor for genome scans, resulting in an inflated number of candidate loci. Here, we compared candidate locus detection in a marine mollusc (Onithochiton neglectus), taking advantage of a natural geographical contrast in the levels of genetic structure between its populations. O. neglectus is endemic to New Zealand and distributed throughout an environmental gradient from the subtropical north to the subantarctic south. Due to a brooding developmental mode, populations tend to be locally isolated. However, adult hitchhiking on rafting kelp increases connectivity among southern populations. We applied two genome scans for outliers (Bayescan and PCAdapt) and two genotype-environment association (GEA) tests (BayeScEnv and RDA). To limit issues with false positives, we combined results using the geometric mean of q-values and performed association tests with random environmental variables. This novel approach is a compromise between stringent and relaxed approaches widely used before, and allowed us to classify candidate loci as low confidence or high confidence. Genome scans for outliers detected a large number of significant outliers in strong and moderately structured populations. No high-confidence GEA loci were detected in the context of strong population structure. However, 86 high-confidence loci were associated predominantly with latitudinally varying abiotic factors in the less structured southern populations. This suggests that the degree of connectivity driven by kelp rafting over the southern scale may be insufficient to counteract local adaptation in this species. Our study supports the expectation that genome scans may be prone to errors in highly structured populations. Nonetheless, it also empirically demonstrates that careful statistical controls enable the identification of candidate loci that invite more detailed investigations. Ultimately, genome scans are valuable tools to help guide further research aiming to determine the potential of non-model species to adapt to future environments.
摘要：
对未来环境条件的遗传适应对于帮助物种随着气候变化而持续生存至关重要。基因组扫描是理解适应性景观的强大工具，使我们能够将遗传多样性与环境梯度相关联，同时从适应性变异中解开中性。然而,低基因流动会导致局部适应和高度结构化的种群，并且是基因组扫描的主要混杂因素，导致候选基因座数量膨胀。这里,我们比较了海洋软体动物（Onithochitonneglectus）中的候选基因座检测，利用种群之间遗传结构水平的自然地理对比。O.neglectus是新西兰特有的，分布在从亚热带北部到亚南极南部的整个环境梯度中。由于一种沉思的发展模式，人口往往是局部孤立的。然而,在漂流海带上搭便车的成年人增加了南部人口之间的连通性。我们对异常值（Bayescan和PCAdapt）和两个基因型-环境关联（GEA）测试（BayeScEnv和RDA）进行了两次基因组扫描。为了限制误报问题，我们使用q值的几何平均值合并结果,并对随机环境变量进行关联检验.这种新颖的方法是以前广泛使用的严格和宽松方法之间的折衷，并允许我们将候选基因座分类为低置信度或高置信度。异常值的基因组扫描在强和中等结构的群体中检测到大量显著的异常值。在强种群结构的背景下，未检测到高置信度GEA基因座。然而,在结构较少的南部人群中，有86个高置信度基因座主要与纬度变化的非生物因素相关。这表明，由南方海带漂流驱动的连通性程度可能不足以抵消该物种的局部适应。我们的研究支持这样的预期，即基因组扫描在高度结构化的人群中可能容易出错。尽管如此，它还从经验上证明，仔细的统计控制可以识别出邀请更详细调查的候选基因座。最终,基因组扫描是有价值的工具，可以帮助指导旨在确定非模型物种适应未来环境的潜力的进一步研究。
