Estimating effective population size trajectories from time-series identity-by-descent segments.

IF 5.1 3区 生物学 Q2 GENETICS & HEREDITY Genetics Pub Date : 2025-03-17 DOI:10.1093/genetics/iyae212
Yilei Huang, Shai Carmi, Harald Ringbauer
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Abstract

Long, identical haplotypes shared between pairs of individuals, known as identity-by-descent (IBD) segments, result from recently shared co-ancestry. Various methods have been developed to utilize IBD sharing for demographic inference in contemporary DNA data. Recent methodological advances have extended the screening for IBD segments to ancient DNA (aDNA) data, making demographic inference based on IBD also possible for aDNA. However, aDNA data typically have varying sampling times, but most demographic inference methods for modern data assume that sampling is contemporaneous. Here, we present Ttne (Time-Transect Ne), which models time-transect sampling to infer recent effective population size trajectories. Using simulations, we show that utilizing IBD sharing in time series increased resolution to infer recent fluctuations in effective population sizes compared with methods that only use contemporaneous samples. To account for IBD detection errors common in empirical analyses, we implemented an approach to estimate and model IBD detection errors. Finally, we applied Ttne to two aDNA time transects: individuals associated with the Copper Age Corded Ware Culture and Medieval England. In both cases, we found evidence of a growing population, a signal consistent with archaeological records.

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从时间序列下降身份段估计有效种群规模轨迹。
一对个体之间共享的长而相同的单倍型,被称为血统认同(IBD)片段,源于最近共享的共同祖先。已经开发了各种方法来利用IBD共享在当代DNA数据中进行人口统计推断。最近的方法进步已经将IBD片段的筛选扩展到古代DNA (aDNA)数据,使得基于IBD的人口统计学推断也可能用于aDNA。然而,aDNA数据通常有不同的采样时间,但大多数现代数据的人口统计学推断方法都假设采样是同期的。在这里,我们提出了Ttne(时间样带Ne),它对时间样带采样进行建模,以推断最近的有效种群规模轨迹。通过模拟,我们发现与仅使用同期样本的方法相比,在时间序列中使用IBD共享可以提高推断有效种群规模近期波动的分辨率。为了解释实证分析中常见的IBD检测误差,我们实施了一种方法来估计和建模IBD检测误差。最后,我们将Ttne应用于两个aDNA时间断面:与铜器时代绳纹器文化和中世纪英格兰相关的个体。在这两种情况下,我们都发现了人口增长的证据,这一信号与考古记录一致。
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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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