Adaptive genetic variation is a function of both selective and neutral forces. To accurately identify adaptive loci, it is thus critical to account for demographic history. Theory suggests that signatures of selection can be inferred using the coalescent, following the premise that genealogies of selected loci deviate from neutral expectations. Here, we build on this theory to develop an analytical framework to identify loci under selection via explicit demographic models (LSD). Under this framework, signatures of selection are inferred through deviations in demographic parameters, rather than through summary statistics directly, and demographic history is accounted for explicitly. Leveraging the property of demographic models to incorporate directionality, we show that LSD can provide information on the environment in which selection acts on a population. This can prove useful in elucidating the selective processes underlying local adaptation, by characterizing genetic trade-offs and extending the concepts of antagonistic pleiotropy and conditional neutrality from ecological theory to practical application in genomic data. We implement LSD via approximate Bayesian computation and demonstrate, via simulations, that LSD (a) has high power to identify selected loci across a large range of demographic-selection regimes, (b) outperforms commonly applied genome-scan methods under complex demographies and (c) accurately infers the directionality of selection for identified candidates. Using the same simulations, we further characterize the behaviour of isolation-with-migration models conducive to the study of local adaptation under regimes of selection. Finally, we demonstrate an application of LSD by detecting loci and characterizing genetic trade-offs underlying flower colour in Antirrhinum majus.

中文翻译：

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通过明确的人口统计模型识别选择下的基因座

适应性遗传变异是选择性力量和中性力量的函数。因此，为了准确识别适应性位点，考虑人口统计历史至关重要。理论表明，在所选基因座的谱系偏离中性期望的前提下，可以使用聚结来推断选择的特征。在这里，我们基于这一理论开发了一个分析框架，通过显式人口统计模型（LSD）来识别选择下的基因座。在此框架下，选择的特征是通过人口统计参数的偏差来推断的，而不是直接通过汇总统计来推断，并且明确地考虑了人口统计历史。利用人口统计模型的特性来纳入方向性，我们证明 LSD 可以提供有关选择作用于人口的环境的信息。通过表征遗传权衡并将拮抗性多效性和条件中性的概念从生态理论扩展到基因组数据的实际应用，这可以证明有助于阐明局部适应的选择性过程。我们通过近似贝叶斯计算实现 LSD，并通过模拟证明 LSD (a) 具有很强的能力来识别大范围的人口统计选择制度中的选定基因座，(b) 在复杂的人口统计情况下优于常用的基因组扫描方法，并且（ c) 准确推断已确定候选人的选择方向。使用相同的模拟，我们进一步描述了有利于研究选择制度下的局部适应的迁移隔离模型的行为。最后，我们通过检测基因座并表征金鱼草花色的遗传权衡来展示 LSD 的应用。