Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions.
Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions.
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根据 X 染色体和常染色体血统比例准确估计性别偏见混合物的挑战。
DOI：
10.1016/j.ajhg.2022.12.012
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发表时间：
2023
影响因子：
9.8
通讯作者：
Lachance,Joseph
中科院分区：
文献类型：
--
作者：
Pfennig,Aaron;Lachance,Joseph
性别偏见的混合物可以从祖先特异性的X染色体和常染色体的比例推断。在《美国人类遗传学杂志》上发表的一篇论文中，Micheletti等人1使用这种方法量化了跨大西洋奴隶贸易后男性和女性的贡献。使用23andMe的大型数据集，他们得出结论，非洲人和欧洲人对美洲基因库的贡献比以前认为的更有性别偏见。我们表明，极端的性别特异性的贡献，可以归因于未分配的遗传祖先，以及性别偏见的混合物的简单模型的局限性。Micheletti等人的研究中未分配的祖先比例。根据染色体类型和地理区域的不同，从0.1%到21%不等。敏感性分析说明了这种未分配的祖先如何产生错误的性别偏见模式，以及数学模型在推断平均祖先比例时对轻微的抽样误差高度敏感，从而需要置信区间。因此，未分配的祖先和模型的敏感性有效地禁止米切莱蒂等人的许多地理区域的估计性别偏见的解释。此外，Micheletti et al.一个单一的混合物事件的假设模型。通过模拟，我们发现违反人口统计学假设，如随后的基因流动和/或性别特异性交配，可能混淆了Micheletti等人的分析，但未指定的祖先可能是更重要的混杂因素。我们的研究结果强调了使用完整的祖先信息，足够大的样本量和适当的模型时，推断性别偏见的人口统计模式的重要性。这篇论文是对Micheletti等人的回应，1发表于美国人类遗传学杂志。另见Micheletti等人的答复，2在这个问题上发表。
Sex-biased admixture can be inferred from ancestry-specific proportions of X chromosome and autosomes. In a paper published in theAmerican Journal of Human Genetics, Micheletti et al.1used this approach to quantify male and female contributions following the transatlantic slave trade. Using a large dataset from 23andMe, they concluded that African and European contributions to gene pools in the Americas were much more sex biased than previously thought. We show that the reported extreme sex-specific contributions can be attributed to unassigned genetic ancestry as well as the limitations of simple models of sex-biased admixture. Unassigned ancestry proportions in the study by Micheletti et al. ranged from ∼1% to 21%, depending on the type of chromosome and geographic region. A sensitivity analysis illustrates how this unassigned ancestry can create false patterns of sex bias and that mathematical models are highly sensitive to slight sampling errors when inferring mean ancestry proportions, making confidence intervals necessary. Thus, unassigned ancestry and the sensitivity of the models effectively prohibit the interpretation of estimated sex biases for many geographic regions in Micheletti et al. Furthermore, Micheletti et al. assumed models of a single admixture event. Using simulations, we find that violations of demographic assumptions, such as subsequent gene flow and/or sex-specific assortative mating, may have confounded the analyses of Micheletti et al., but unassigned ancestry was likely the more important confounding factor. Our findings underscore the importance of using complete ancestry information, sufficiently large sample sizes, and appropriate models when inferring sex-biased patterns of demography. This Matters Arising paper is in response to Micheletti et al.,1published inAmerican Journal of Human Genetics. See also the response by Micheletti et al.,2published in this issue.