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2
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3
Assortative mating by population of origin in a mechanistic model of admixture.起源人群的混合机制模型中的交配组合。
Theor Popul Biol. 2020 Aug;134:129-146. doi: 10.1016/j.tpb.2020.02.004. Epub 2020 Apr 7.
4
Native American admixture recapitulates population-specific migration and settlement of the continental United States.美洲原住民的混合再现了美国大陆特定人群的迁移和定居。
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8
Beyond 2/3 and 1/3: The Complex Signatures of Sex-Biased Admixture on the X Chromosome.超越三分之二与三分之一:X染色体上性别偏向性混合的复杂特征
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9
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准确估计 X 染色体和常染色体祖先比例的性别偏倚混合所面临的挑战。

Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions.

机构信息

School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.

School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.

出版信息

Am J Hum Genet. 2023 Feb 2;110(2):359-367. doi: 10.1016/j.ajhg.2022.12.012.

DOI:10.1016/j.ajhg.2022.12.012
PMID:36736293
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9943719/
Abstract

Sex-biased admixture can be inferred from ancestry-specific proportions of X chromosome and autosomes. In a paper published in the American Journal of Human Genetics, Micheletti et al. used 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., published in American Journal of Human Genetics. See also the response by Micheletti et al., published in this issue.

摘要

性染色体和常染色体上的祖先特异性比例可以推断出性别偏向的混合。在《美国人类遗传学杂志》上发表的一篇论文中,Micheletti 等人使用这种方法来量化跨大西洋奴隶贸易后男性和女性的贡献。他们利用 23andMe 的大型数据集得出结论,非洲和欧洲对美洲基因库的贡献比之前认为的更具性别偏向。我们表明,报告的极端性别特异性贡献可以归因于未分配的遗传祖先以及性别偏向混合的简单模型的局限性。Micheletti 等人研究中的未分配祖先比例取决于染色体类型和地理区域,范围从 1%到 21%不等。敏感性分析说明了未分配的祖先如何会产生错误的性别偏差模式,以及当推断平均祖先比例时,数学模型对轻微的抽样误差非常敏感,因此需要置信区间。因此,未分配的祖先和模型的敏感性实际上禁止了对 Micheletti 等人研究中许多地理区域的估计性别偏差进行解释。此外,Micheletti 等人假设了单一混合事件的模型。通过模拟,我们发现违反人口假设,例如随后的基因流动和/或性别特定的交配选择,可能会使 Micheletti 等人的分析复杂化,但未分配的祖先很可能是更重要的混杂因素。我们的研究结果强调了在推断性别偏向的人口统计学模式时使用完整的祖先信息、足够大的样本量和适当的模型的重要性。这篇“争议解决论文”是对 Micheletti 等人在《美国人类遗传学杂志》上发表的文章的回应。也可以看到 Micheletti 等人在本期杂志上发表的回应。