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Models of archaic admixture and recent history from two-locus statistics

机译:来自两基因座统计的古混合物模型和近期历史

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摘要

We learn about population history and underlying evolutionary biology through patterns of genetic polymorphism. Many approaches to reconstruct evolutionary histories focus on a limited number of informative statistics describing distributions of allele frequencies or patterns of linkage disequilibrium. We show that many commonly used statistics are part of a broad family of two-locus moments whose expectation can be computed jointly and rapidly under a wide range of scenarios, including complex multi-population demographies with continuous migration and admixture events. A full inspection of these statistics reveals that widely used models of human history fail to predict simple patterns of linkage disequilibrium. To jointly capture the information contained in classical and novel statistics, we implemented a tractable likelihood-based inference framework for demographic history. Using this approach, we show that human evolutionary models that include archaic admixture in Africa, Asia, and Europe provide a much better description of patterns of genetic diversity across the human genome. We estimate that an unidentified, deeply diverged population admixed with modern humans within Africa both before and after the split of African and Eurasian populations, contributing 4 − 8% genetic ancestry to individuals in world-wide populations.
机译:我们通过遗传多态性模式了解种群历史和潜在的进化生物学。重建进化历史的许多方法都集中在数量有限的信息统计学上,这些统计学描述了等位基因频率的分布或连锁不平衡的模式。我们表明,许多常用的统计信息是广泛的两轨矩时刻系列的一部分,这些时刻的期望值可以在广泛的场景下(包括具有连续迁移和混合事件的复杂的多人口人口统计学特征)共同快速地计算出来。对这些统计数据的全面检查表明,广泛使用的人类历史模型无法预测连锁不平衡的简单模式。为了共同捕获古典统计和新颖统计中包含的信息,我们为人口历史记录实现了基于可预测的似然性推断框架。使用这种方法,我们表明,包括非洲,亚洲和欧洲的古老混合物在内的人类进化模型可以更好地描述整个人类基因组中遗传多样性的模式。我们估计,在非洲和欧亚人口分裂之前和之后,一个身份不明的,高度分歧的人口与非洲内部的现代人类交织在一起,为全世界人口的个体贡献了4 – 8%的遗传祖先。

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