Theunert Christoph, Racimo Fernando, Slatkin Montgomery
Department of Integrative Biology, University of California, Berkeley, California 94720
Department of Evolutionary Genetics, Max-Planck Institute for Evolutionary Anthropology, Leipzig, Germany, and.
Genetics. 2017 Jun;206(2):1025-1035. doi: 10.1534/genetics.117.200600. Epub 2017 Apr 10.
Here, we develop and test a method to address whether DNA samples sequenced from a group of fossil hominin bone or tooth fragments originate from the same individual or from closely related individuals. Our method assumes low amounts of retrievable DNA, significant levels of sequencing error, and contamination from one or more present-day humans. We develop and implement a maximum likelihood method that estimates levels of contamination, sequencing error rates, and pairwise relatedness coefficients in a set of individuals. We assume that there is no reference panel for the ancient population to provide allele and haplotype frequencies. Our approach makes use of single nucleotide polymorphisms (SNPs) and does not make assumptions about the underlying demographic model. By artificially mating genomes from the 1000 Genomes Project, we determine the numbers of individuals at a given genomic coverage that are required to detect different levels of genetic relatedness with confidence.
在此,我们开发并测试了一种方法,以确定从一组化石古人类骨骼或牙齿碎片中测序得到的DNA样本是来自同一个体还是来自亲缘关系密切的个体。我们的方法假定可检索到的DNA量很少、测序错误水平较高,并且存在来自一个或多个现代人类的污染。我们开发并实施了一种最大似然法,该方法可估计一组个体中的污染水平、测序错误率和成对相关性系数。我们假定没有古代人群的参考面板来提供等位基因和单倍型频率。我们的方法利用单核苷酸多态性(SNP),并且不对潜在的人口模型做任何假设。通过人工配对来自千人基因组计划的基因组,我们确定了在给定基因组覆盖率下,能够自信地检测到不同程度遗传相关性所需的个体数量。