Simulation-based Benchmarking of Ancient Haplotype Inference for Detecting Population Structure.
Simulation-based Benchmarking of Ancient Haplotype Inference for Detecting Population Structure.
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用于检测种群结构的古代单倍型推断的基于模拟的基准测试。
DOI：
10.1101/2023.09.28.560049
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Huerta-Sanchez,Emilia
中科院分区：
文献类型：
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作者：
Tretmanis,JazepsMedina;Jay,Flora;Avila-Árcos,MaríaC;Huerta-Sanchez,Emilia
古基因组学数据告诉我们古代种群的运动、生长和关系。它还为我们提供了与医学相关的适应背景，这些适应是由于来自其他原始人的渗入而出现在现代人类身上的，它继续帮助我们描述人类的进化史。然而，古代DNA （aDNA）面临着一些实际挑战，因为各种因素，如脱氨，高度碎片化，aDNA的环境污染，以及可恢复的内源性DNA的低量，使得aDNA的恢复和分析比现代DNA更加困难。大多数关于aDNA的研究仅利用SNP数据，只有少数研究基于单倍型数据推断人类人口统计学历史，可能是因为单倍型估计（或分相）尚未在aDNA背景下进行系统评估。在这里，我们评估了aDNA的独特挑战如何影响分相质量。我们还开发了一个模拟aDNA的软件工具，考虑到aDNA的特征以及种群的进化史。我们测量了相位误差作为aDNA质量和人口统计历史的函数，发现只要污染和读取深度足够，即使对于非常古老的个体（过去约400代），也可以实现低相位误差。我们的研究结果表明，种群分裂或在参考种群和阶段性种群之间发生的瓶颈事件会影响相位质量，瓶颈导致最高的平均错误率。最后，我们发现使用估计的单倍型，即使不完全准确，在重建现代和古代种群分裂后的种群结构变化时，也优于使用模拟的基因型数据。
Paleogenomic data has informed us about the movements, growth, and relationships of ancient populations. It has also given us context for medically relevant adaptations that appear in present-day humans due to introgression from other hominids, and it continues to help us characterize the evolutionary history of humans. However, ancient DNA (aDNA) presents several practical challenges as various factors such as deamination, high fragmentation, environmental contamination of aDNA, and low amounts of recoverable endogenous DNA, make aDNA recovery and analysis more difficult than modern DNA. Most studies with aDNA leverage only SNP data, and only a few studies have made inferences on human demographic history based on haplotype data, possibly because haplotype estimation (or phasing) has not yet been systematically evaluated in the context of aDNA. Here, we evaluate how the unique challenges of aDNA can impact phasing quality. We also develop a software tool that simulates aDNA taking into account the features of aDNA as well as the evolutionary history of the population. We measured phasing error as a function of aDNA quality and demographic history, and found that low phasing error is achievable even for very ancient individuals (~ 400 generations in the past) as long as contamination and read depth are adequate. Our results show that population splits or bottleneck events occurring between the reference and phased populations affect phasing quality, with bottlenecks resulting in the highest average error rates. Finally, we found that using estimated haplotypes, even if not completely accurate, is superior to using the simulated genotype data when reconstructing changes in population structure after population splits between present-day and ancient populations.