评估古代DNA采样策略用于人类自然选择的推理,使用等位基因频率时间序列数据
Lucas Anchieri1,2, Carlos Eduardo G Amorim3, Samuel Neuenschwander1,4
1Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.
Genome biology and evolution
|February 2, 2026
概括
在古代人类DNA (aDNA) 中检测自然选择是可行的,尽管数据稀疏,但强选择 (s ≥0.02) 和~100个样本是可行的. ApproxWF表现最好,虚假阳性很低,用于强大的选择推理的功率很高.
科学领域:
- 人口遗传学 人口遗传学
- 古遗传学是古遗传学的一部分.
- 进化生物学 进化生物学
背景情况:
- 古代人类的基因组数据使得使用时间序列进行自然选择估计.
- 现有的方法是用大样本大小验证的,而不是稀疏的古代DNA (aDNA) 数据.
- aDNA数据带来了诸如高缺失率和不同时间点的样本大小等挑战.
研究的目的:
- 使用aDNA类时间序列数据集的基准选择推断方法.
- 用稀疏的数据和小样本大小来评估方法性能.
- 确定检测古人类群体中选择的可行性.
主要方法:
- 使用DNA类时间序列数据集进行了广泛的模拟.
- 基准测试使用了四种方法:ApproxWF,BMWS,Slattice和Sr.
- 测试各种采样方案和选择系数 (s).
主要成果:
- 选择检测是可能的强选择 (s ≥ 0.02) 的~100个样本,假设恒定的有效人口大小 (Ne).
- 与其他方法相比,ApproxWF在模拟中表现出卓越的性能.
- 观察到低虚假阳性率 (<6%) 和高功率 (>90%) 检测强选择.
- 跨时间点均的数据采样提高了估计准确度.
结论:
- 从稀疏的DNA数据推断自然选择是可以实现的,特别是在强选择方面.
- 建议使用ApproxWF来分析DNA时间序列数据.
- 未来的研究应该专注于数据在时间上的均分布,以提高准确性.
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