运动中的古DNA：通过整合考古基因组学与考古学研究过去的人类流动与互动
Ancient DNA in motion: Studying past human mobility and interactions by integrating archaeogenetics and archaeology
浏览论文内容
中文总结 AI 辅助
该研究整合考古基因组学与考古学，阐述古DNA数据用于探究人类流动的方法、工具及证据，分析不同流动模式的推断，结合多学科证据构建过去人类流动模型并呼吁跨领域整合。
中文摘要 AI 辅助
本文概述了考古基因组学数据如何用于探究过去的人类流动，以及如何将其与考古学研究相结合，以重建不同尺度下的人类流动模型。我们首先阐释了清晰的流动术语与理论方法的重要性，探讨了迁移、基因混合、祖先来源、替代等术语。随后描述了从古DNA数据推断过去人类流动的理论原理与最先进工具，包括探索性方法与形式化建模，以及利用多类证据的相关性，这些证据涵盖等位基因频率模式、单倍型共享、遗传亲缘关系和单亲遗传标记。我们还讨论了这些方法在推断不同流动模式时的优势与局限性，例如被称为迁移的大规模长距离流动，以及我们认为构成过去人类流动主体、可能在塑造文化景观中占主要份额的小规模短距离流动。此外，我们阐述了性别偏向流动事件的推断方法。最后，我们呈现了基因组数据与考古学、生物考古学及历史证据联合分析的实例，证明了跨学科分析在构建全面的过去人类流动模型方面的潜力。本文呼吁各领域进一步整合。
英文摘要
Here, we present an overview of how archaeogenomic data can be used to investigate past mobilities and how it can be integrated with archaeological research to reconstruct models of human mobility at different scales. We first seek to explain the importance of a clear terminological and theoretical approach to mobility, discussing terms such as migration, admixture, ancestry, and replacement. We then describe the theoretical principles and state-of-the-art tools for inferring past mobility from ancient DNA data, including exploratory approaches and formal modeling, and the relevance of using diverse lines of evidence including allele-frequency patterns, haplotype-sharing, genetic relatedness, and uniparental markers. We further discuss the power and limitations of these methods for inferring different modes of mobility, such as large-scale and long-distance mobility, which we refer to as migration, and also small-scale and short-distance movements, which we argue constituted the bulk of past human mobility and may have had the major share in shaping cultural landscapes. We also describe inference of sex-biased mobility events. Finally, we present examples of joint analyses of genomic data with archaeological, bioarchaeological and historical evidence, demonstrating the potential of interdisciplinary analyses in building comprehensive models of past mobilities. We finish by calling for further integration across fields.
