Université Montpellier 2, Montpellier, France.
Mol Ecol. 2013 Apr;22(8):2061-4. doi: 10.1111/mec.12241.
It is now common for population geneticists to estimate FST for a large number of loci across the genome, before testing for selected loci as being outliers to the FST distribution. One surprising result of such FST scans is the often high proportion (>1% and sometimes >10%) of outliers detected, and this is often interpreted as evidence for pervasive local adaptation. In this issue of Molecular Ecolog, Fourcade et al. (2013) observe that a particularly high rate of FST outliers has often been found in river organisms, such as fishes or damselflies, despite there being no obvious reason why selection should affect a larger proportion of the genomes of these organisms. Using computer simulations, Fourcade et al. (2013) show that the strong correlation in co-ancestry produced in long onedimensional landscapes (such as rivers, valleys, peninsulas, oceanic ridges or coastlines) greatly increases the neutral variance in FST, especially when the landscape is further reticulated into fractal networks. As a consequence, outlier tests have a high rate of false positives, unless this correlation can be taken into account. Fourcade et al.'s study highlights an extreme case of the general problem, first noticed by Robertson (1975a,b) and Nei & Maruyama (1975), that correlated co-ancestry inflates the neutral variance in FST when compared to its expectation under an island model of population structure. Similar warnings about the validity of outlier tests have appeared regularly since then but have not been widely cited in the recent genomics literature. We further emphasize that FST outliers can arise in many different ways and that outlier tests are not designed for situations where the genetic architecture of local adaptation involves many loci.
现在，群体遗传学家通常会在测试选定的局部位点是否为 FST 分布的异常值之前，对基因组中大量的位点进行 FST 估计。这种 FST 扫描的一个令人惊讶的结果是，经常会检测到大量的异常值（>1%，有时甚至>10%），这通常被解释为普遍存在局部适应的证据。在本期的《分子生态学》杂志上，Fourcade 等人（2013 年）观察到，尽管没有明显的理由表明选择应该影响这些生物的基因组更大比例，但河流生物（如鱼类或蜻蜓）中经常发现 FST 异常值的比例特别高。Fourcade 等人（2013 年）使用计算机模拟表明，在长一维景观（如河流、山谷、半岛、海洋脊或海岸线）中产生的强烈亲缘相关的强烈相关性极大地增加了 FST 的中性方差，尤其是当景观进一步呈分形网络状时。因此，除非可以考虑到这种相关性，否则异常值测试的假阳性率很高。Fourcade 等人的研究突出了一个极端情况，这是 Robertson（1975a，b）和 Nei 和 Maruyama（1975）首先注意到的问题，即与岛屿模型的种群结构相比，相关的亲缘相关会使 FST 的中性方差膨胀。自那时以来，类似的关于异常值测试有效性的警告经常出现，但在最近的基因组学文献中并没有被广泛引用。我们进一步强调，FST 异常值可能以许多不同的方式出现，并且异常值测试不是为涉及许多位点的局部适应的遗传结构的情况而设计的。
