An explanation for the sister repulsion phenomenon in Patterson's f-statistics.

IF 3.3 3区 生物学 Q2 GENETICS & HEREDITY
Genetics Pub Date : 2024-11-06 DOI:10.1093/genetics/iyae144
Gözde Atağ, Shamam Waldman, Shai Carmi, Mehmet Somel
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引用次数: 0

Abstract

Patterson's f-statistics are among the most heavily utilized tools for analyzing genome-wide allele frequency data for demographic inference. Beyond studying admixture, f3- and f4-statistics are also used for clustering populations to identify groups with similar histories. However, previous studies have noted an unexpected behavior of f-statistics: multiple populations from a certain region systematically show higher genetic affinity to a more distant population than to their neighbors, a pattern that is mismatched with alternative measures of genetic similarity. We call this counter-intuitive pattern "sister repulsion". We first present a novel instance of sister repulsion, where genomes from Bronze Age East Anatolian sites show higher affinity toward Bronze Age Greece rather than each other. This is observed both using f3- and f4-statistics, contrasts with archaeological/historical expectation, and also contradicts genetic affinity patterns captured using principal components analysis or multidimensional scaling on genetic distances. We then propose a simple demographic model to explain this pattern, where sister populations receive gene flow from a genetically distant source. We calculate f3- and f4-statistics using simulated genetic data with varying population genetic parameters, confirming that low-level gene flow from an external source into populations from 1 region can create sister repulsion in f-statistics. Unidirectional gene flow between the studied regions (without an external source) can likewise create repulsion. Meanwhile, similar to our empirical observations, multidimensional scaling analyses of genetic distances still cluster sister populations together. Overall, our results highlight the impact of low-level admixture events when inferring demographic history using f-statistics.

帕特森 f 统计中姊妹排斥现象的解释。
Patterson 的 f 统计量是用于分析全基因组等位基因频率数据以进行人口推断的最常用工具之一。除了研究混杂外,f3 和 f4 统计量还用于聚类,以确定具有相似历史的群体。然而,以往的研究注意到了 f 统计量的一种意想不到的行为:来自某一地区的多个种群系统性地表现出与较远种群的遗传亲和性高于与邻近种群的遗传亲和性,这种模式与遗传相似性的其他衡量标准不匹配。我们称这种反直觉模式为 "姊妹排斥"。我们首先介绍了姊妹排斥的一个新实例,即青铜时代东安纳托利亚遗址的基因组与青铜时代希腊的亲和力更高,而不是相互亲和力更高。这是用 f3- 和 f4 统计法观察到的,与考古学/历史学的预期相反,也与用主成分分析或遗传距离多维缩放捕捉到的遗传亲和模式相矛盾。随后,我们提出了一个简单的人口统计模型来解释这种模式,即姐妹种群接受来自遗传上遥远来源的基因流。我们利用不同种群遗传参数的模拟遗传数据计算了f3-和f4-统计量,证实了来自外部的低水平基因流进入来自一个地区的种群会在f-统计量中产生姊妹排斥。研究区域之间的单向基因流动(无外部来源)同样会产生排斥。同时,与我们的经验观察相似,遗传距离的多维比例分析仍然会将姊妹种群聚集在一起。总之,我们的研究结果凸显了利用 f 统计量推断人口历史时低水平混杂事件的影响。
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来源期刊
Genetics
Genetics GENETICS & HEREDITY-
CiteScore
6.90
自引率
6.10%
发文量
177
审稿时长
1.5 months
期刊介绍: GENETICS is published by the Genetics Society of America, a scholarly society that seeks to deepen our understanding of the living world by advancing our understanding of genetics. Since 1916, GENETICS has published high-quality, original research presenting novel findings bearing on genetics and genomics. The journal publishes empirical studies of organisms ranging from microbes to humans, as well as theoretical work. While it has an illustrious history, GENETICS has changed along with the communities it serves: it is not your mentor''s journal. The editors make decisions quickly – in around 30 days – without sacrificing the excellence and scholarship for which the journal has long been known. GENETICS is a peer reviewed, peer-edited journal, with an international reach and increasing visibility and impact. All editorial decisions are made through collaboration of at least two editors who are practicing scientists. GENETICS is constantly innovating: expanded types of content include Reviews, Commentary (current issues of interest to geneticists), Perspectives (historical), Primers (to introduce primary literature into the classroom), Toolbox Reviews, plus YeastBook, FlyBook, and WormBook (coming spring 2016). For particularly time-sensitive results, we publish Communications. As part of our mission to serve our communities, we''ve published thematic collections, including Genomic Selection, Multiparental Populations, Mouse Collaborative Cross, and the Genetics of Sex.
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