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利用稀疏数据估计移动性:在人类遗传变异中的应用。

Estimating mobility using sparse data: Application to human genetic variation.

机构信息

Research Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, United Kingdom;

Research Laboratory for Archaeology & the History of Art, University of Oxford, Oxford OX1 3QY, United Kingdom.

出版信息

Proc Natl Acad Sci U S A. 2017 Nov 14;114(46):12213-12218. doi: 10.1073/pnas.1703642114. Epub 2017 Oct 30.

Abstract

Mobility is one of the most important processes shaping spatiotemporal patterns of variation in genetic, morphological, and cultural traits. However, current approaches for inferring past migration episodes in the fields of archaeology and population genetics lack either temporal resolution or formal quantification of the underlying mobility, are poorly suited to spatially and temporally sparsely sampled data, and permit only limited systematic comparison between different time periods or geographic regions. Here we present an estimator of past mobility that addresses these issues by explicitly linking trait differentiation in space and time. We demonstrate the efficacy of this estimator using spatiotemporally explicit simulations and apply it to a large set of ancient genomic data from Western Eurasia. We identify a sequence of changes in human mobility from the Late Pleistocene to the Iron Age. We find that mobility among European Holocene farmers was significantly higher than among European hunter-gatherers both pre- and postdating the Last Glacial Maximum. We also infer that this Holocene rise in mobility occurred in at least three distinct stages: the first centering on the well-known population expansion at the beginning of the Neolithic, and the second and third centering on the beginning of the Bronze Age and the late Iron Age, respectively. These findings suggest a strong link between technological change and human mobility in Holocene Western Eurasia and demonstrate the utility of this framework for exploring changes in mobility through space and time.

摘要

迁移是塑造遗传、形态和文化特征时空变化模式的最重要过程之一。然而,考古学和群体遗传学领域中推断过去迁移事件的当前方法要么缺乏时间分辨率,要么缺乏对潜在迁移的正式量化,不适合空间和时间稀疏采样的数据,并且只允许在不同时期或地理区域之间进行有限的系统比较。在这里,我们提出了一种过去迁移的估计量,通过明确链接空间和时间上的特征分化来解决这些问题。我们使用时空显式模拟来证明该估计量的有效性,并将其应用于来自西欧亚的大量古代基因组数据。我们确定了从更新世晚期到铁器时代人类迁移的一系列变化。我们发现,与旧石器时代晚期的狩猎采集者相比,新石器时代的欧洲农民的流动性要高得多。我们还推断出,这种全新世的流动性增加至少发生了三个不同的阶段:第一个阶段集中在新石器时代初期的人口扩张,第二个阶段和第三个阶段分别集中在青铜时代和铁器时代晚期的开始。这些发现表明,在全新世的欧洲西部,技术变革和人类迁移之间存在着很强的联系,并证明了该框架在探索空间和时间上的迁移变化方面的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fb5/5699029/4d489cf8708d/pnas.1703642114fig01.jpg

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