当前位置: X-MOL 学术PLOS Genet. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Tracking human population structure through time from whole genome sequences.
PLOS Genetics ( IF 4.0 ) Pub Date : 2020-03-09 , DOI: 10.1371/journal.pgen.1008552
Ke Wang 1 , Iain Mathieson 2 , Jared O'Connell 3 , Stephan Schiffels 1
Affiliation  

The genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population’s history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyze the separation history between populations. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.



中文翻译:


从全基因组序列跟踪人类人口结构随时间的变化。



与许多物种一样,人类的遗传多样性是由人口分离、随后隔离和随后混合的复杂模式塑造的。这种模式至少可以追溯到古生物学记录中我们物种出现的时候,并在我们的基因组中留下了痕迹。从这些痕迹重建人群的历史是一个具有挑战性的问题。在这里,我们提出了一种基于多重顺序马尔可夫合并(MSMC)的新方法来分析种群之间的分离历史。我们的方法称为 MSMC-IM,使用改进的 MSMC (MSMC2) 实现来估计群体内和群体之间的合并率,然后将连续的分离-迁移模型拟合到这些速率以获得基因的时间依赖性估计流动。我们通过模拟表明,我们的方法可以识别涉及分裂后混合或古老渗入的复杂人口统计场景。我们将 MSMC-IM 应用到全球 15 个人群的全基因组序列中,追踪人类遗传多样性的过程。我们发现一些非洲人群之间存在极其深厚的血统痕迹,大约 1% 的血统可以追溯到一百万年前。

更新日期:2020-04-06
down
wechat
bug