Silva Nuno Miguel, Rio Jeremy, Currat Mathias
AGP lab, Department of Genetics & Evolution - Anthropology Unit, University of Geneva, Geneva, Switzerland.
Institute of Genetics and Genomics in Geneva (IGE3), University of Geneva, Geneva, Switzerland.
BMC Genet. 2017 Dec 15;18(1):114. doi: 10.1186/s12863-017-0575-6.
Recent advances in sequencing technologies have allowed for the retrieval of ancient DNA data (aDNA) from skeletal remains, providing direct genetic snapshots from diverse periods of human prehistory. Comparing samples taken in the same region but at different times, hereafter called "serial samples", may indicate whether there is continuity in the peopling history of that area or whether an immigration of a genetically different population has occurred between the two sampling times. However, the exploration of genetic relationships between serial samples generally ignores their geographical locations and the spatiotemporal dynamics of populations. Here, we present a new coalescent-based, spatially explicit modelling approach to investigate population continuity using aDNA, which includes two fundamental elements neglected in previous methods: population structure and migration. The approach also considers the extensive temporal and geographical variance that is commonly found in aDNA population samples.
We first showed that our spatially explicit approach is more conservative than the previous (panmictic) approach and should be preferred to test for population continuity, especially when small and isolated populations are considered. We then applied our method to two mitochondrial datasets from Germany and France, both including modern and ancient lineages dating from the early Neolithic. The results clearly reject population continuity for the maternal line over the last 7500 years for the German dataset but not for the French dataset, suggesting regional heterogeneity in post-Neolithic migratory processes.
Here, we demonstrate the benefits of using a spatially explicit method when investigating population continuity with aDNA. It constitutes an improvement over panmictic methods by considering the spatiotemporal dynamics of genetic lineages and the precise location of ancient samples. The method can be used to investigate population continuity between any pair of serial samples (ancient-ancient or ancient-modern) and to investigate more complex evolutionary scenarios. Although we based our study on mitochondrial DNA sequences, diploid molecular markers of different types (DNA, SNP, STR) can also be simulated with our approach. It thus constitutes a promising tool for the analysis of the numerous aDNA datasets being produced, including genome wide data, in humans but also in many other species.
测序技术的最新进展使得从骨骼遗骸中获取古代DNA数据(aDNA)成为可能,从而提供了来自人类史前不同时期的直接遗传快照。比较在同一地区但不同时间采集的样本(以下称为“系列样本”),可以表明该地区的人口历史是否具有连续性,或者在两次采样时间之间是否发生了基因不同的人群的移民。然而,对系列样本之间遗传关系的探索通常忽略了它们的地理位置和人群的时空动态。在这里,我们提出了一种新的基于合并的、空间明确的建模方法,以使用aDNA研究人口连续性,该方法包括先前方法中被忽视的两个基本要素:种群结构和迁移。该方法还考虑了aDNA种群样本中常见的广泛的时间和地理差异。
我们首先表明,我们的空间明确方法比以前的(随机交配)方法更保守,在测试人口连续性时应优先使用,特别是在考虑小的和孤立的种群时。然后,我们将我们的方法应用于来自德国和法国的两个线粒体数据集,这两个数据集都包括可追溯到新石器时代早期的现代和古代谱系。结果清楚地表明,德国数据集在过去7500年中母系没有人口连续性,但法国数据集则不然,这表明新石器时代后迁徙过程存在区域异质性。
在这里,我们展示了在使用aDNA研究人口连续性时使用空间明确方法的好处。通过考虑遗传谱系的时空动态和古代样本的精确位置,它构成了对随机交配方法的改进。该方法可用于研究任何一对系列样本(古代-古代或古代-现代)之间的人口连续性,并研究更复杂的进化场景。虽然我们的研究基于线粒体DNA序列,但不同类型的二倍体分子标记(DNA、SNP、STR)也可以用我们的方法进行模拟。因此,它构成了一个有前途的工具,可用于分析正在产生的大量aDNA数据集,包括人类但也包括许多其他物种的全基因组数据。