Alpine ibex simulation files

Identifying local adaptation in bottlenecked species is essential for conservation management. Selection detection methods have an important role in species management plans, assessments of adaptive capacity, and looking for responses to climate change. Yet, the allele frequency changes exploited in selection detection methods are similar to those caused by the strong neutral genetic drift expected during a bottleneck. Consequently, it is often unclear what accuracy selection detection methods have across bottlenecked populations. In this study, simulations were used to explore if signals of selection could be confidently distinguished from genetic drift across 23 bottlenecked and reintroduced populations of Alpine ibex (Capra ibex). The meticulously recorded demographic history of the Alpine ibex was used to generate comprehensive simulated SNP data. The simulated SNPs were then used to benchmark the confidence we could place in outliers identified in empirical Alpine ibex RADseq derived SNP data. Within the simulated dataset, the false positive rates were high for all selection detection methods (Fst outlier scans and Genetic-Environment Association analyses) but fell substantially when two or more methods were combined. True positive rates were consistently low and became negligible with increased stringency. Despite finding many outlier loci in the empirical Alpine ibex SNPs, none could be distinguished from genetic drift-driven false positives. Unfortunately, the low true positive rate also prevents the exclusion of recent local adaptation within the Alpine ibex. The baselines and stringent approach outlined here should be applied to other bottlenecked species to ensure the risk of false positive, or negative, signals of selection are accounted for in conservation management plans.识别受种群瓶颈效应影响的物种的局部适应特征，对物种保护管理工作至关重要。选择检测方法在物种管理规划、种群适应能力评估以及气候变化响应探寻等研究中发挥着关键作用。然而，选择检测方法所利用的等位基因频率变化，与种群瓶颈期间常见的强烈中性遗传漂变所引发的频率变化极为相似。因此，在受种群瓶颈影响的种群中，选择检测方法的实际准确性往往难以确定。本研究以阿尔卑斯羱羊（Capra ibex）的23个受种群瓶颈影响且已重新引入的自然种群为研究对象，通过模拟实验探究能否可靠区分选择信号与遗传漂变信号。研究人员依托阿尔卑斯羱羊被详尽记录的种群动态历史，生成了全面的模拟单核苷酸多态性（Single Nucleotide Polymorphism, SNP）数据集。随后利用该模拟SNP数据集，对基于阿尔卑斯羱羊限制性位点相关DNA测序（Restriction-site Associated DNA Sequencing, RADseq）获得的实验SNP数据中所鉴定的异常位点的置信度进行基准评估。在模拟数据集内，所有选择检测方法（包括Fst异常值扫描与遗传-环境关联分析）的假阳性率均较高，但当结合两种及以上检测方法时，假阳性率会大幅降低。真阳性率则始终偏低，且随着筛选严谨性的提升，真阳性率会变得可忽略不计。尽管在实验阿尔卑斯羱羊SNP数据中发现了大量异常位点，但无一可被区分于遗传漂变驱动的假阳性信号。遗憾的是，较低的真阳性率也使得我们无法排除阿尔卑斯羱羊近期发生的局部适应事件。本文所提出的基准分析方案与严谨筛选方法，应被应用于其他受种群瓶颈影响的物种，以确保在保护管理规划中充分考虑选择信号假阳性（或假阴性）的风险。