PDF(Pubmed)
Abstract：
Inferring the demographic history of populations provides fundamental insights into species dynamics and is essential for developing a null model to accurately study selective processes. However, background selection and selective sweeps can produce genomic signatures at linked sites that mimic or mask signals associated with historical population size change. While the theoretical biases introduced by the linked effects of selection have been well established, it is unclear whether ancestral recombination graph (ARG)-based approaches to demographic inference in typical empirical analyses are susceptible to misinference due to these effects. To address this, we developed highly realistic forward simulations of human and Drosophila melanogaster populations, including empirically estimated variability of gene density, mutation rates, recombination rates, purifying, and positive selection, across different historical demographic scenarios, to broadly assess the impact of selection on demographic inference using a genealogy-based approach. Our results indicate that the linked effects of selection minimally impact demographic inference for human populations, although it could cause misinference in populations with similar genome architecture and population parameters experiencing more frequent recurrent sweeps. We found that accurate demographic inference of D. melanogaster populations by ARG-based methods is compromised by the presence of pervasive background selection alone, leading to spurious inferences of recent population expansion, which may be further worsened by recurrent sweeps, depending on the proportion and strength of beneficial mutations. Caution and additional testing with species-specific simulations are needed when inferring population history with non-human populations using ARG-based approaches to avoid misinference due to the linked effects of selection.
摘要：
推断种群的人口统计学历史提供了对物种动态的基本见解，对于开发空模型以准确研究选择过程至关重要。然而,背景选择和选择性扫描可以在链接位点产生基因组特征,模拟或掩盖与历史种群数量变化相关的信号.虽然选择的关联效应引入的理论偏见已经得到了很好的确立，目前尚不清楚,在典型的实证分析中,基于ARG的人口统计学推断方法是否容易受到这些影响的误判.为了解决这个问题，我们开发了人类和果蝇种群的高度逼真的正向模拟，包括经验估计的基因密度变异性，突变率,重组率，净化和正选择，在不同的历史人口情况下，使用基于家谱的方法广泛评估选择对人口统计推断的影响。我们的结果表明，选择的关联效应对人口统计学推断的影响最小，尽管它可能会在具有相似基因组结构和种群参数的种群中引起错误的推断，这些种群经历了更频繁的反复扫描。我们发现，通过基于ARG的方法对D.melanogaster种群进行准确的人口统计学推断会受到普遍背景选择的影响，导致最近人口扩张的虚假推论，而反复的扫荡可能会进一步恶化，取决于有益突变的比例和强度。当使用基于ARG的方法推断非人类种群的种群历史时，需要谨慎并进行针对特定物种的模拟的额外测试，以避免由于选择的关联效应而导致的错误推断。
