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首页> 外文期刊>Genetics: A Periodical Record of Investigations Bearing on Heredity and Variation >Bayes Estimation of Species Divergence Times and Ancestral Population Sizes Using DNA Sequences From Multiple Loci
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Bayes Estimation of Species Divergence Times and Ancestral Population Sizes Using DNA Sequences From Multiple Loci

机译:使用多个位点的DNA序列进行物种发散时间和祖先种群大小的贝叶斯估计

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摘要

The effective population sizes of ancestral as well as modern species are important parameters in models of population genetics and human evolution. The commonly used method for estimating ancestral population sizes, based on counting mismatches between the species tree and the inferred gene trees, is highly biased as it ignores uncertainties in gene tree reconstruction. In this article, we develop a Bayes method for simultaneous estimation of the species divergence times and current and ancestral population sizes. The method uses DNA sequence data from multiple loci and extracts information about conflicts among gene tree topologies and coalescent times to estimate ancestral population sizes. The topology of the species tree is assumed known. A Markov chain Monte Carlo algorithm is implemented to integrate over uncertain gene trees and branch lengths (or coalescence times) at each locus as well as species divergence times. The method can handle any species tree and allows different numbers of sequences at different loci. We apply the method to published noncoding DNA sequences from the human and the great apes. There are strong correlations between posterior estimates of speciation times and ancestral population sizes. With the use of an informative prior for the human-chimpanzee divergence date, the population size of the common ancestor of the two species is estimated to be ~20,000, with a 95% credibility interval (8000, 40,000). Our estimates, however, are affected by model assumptions as well as data quality. We suggest that reliable estimates have yet to await more data and more realistic models.
机译:祖传以及现代物种的有效种群数量是种群遗传和人类进化模型的重要参数。基于对物种树和推断的基因树之间的不匹配进行计数的估算祖先种群大小的常用方法因其忽略了基因树重建的不确定性而存在很大的偏见。在本文中,我们开发了一种贝叶斯方法,用于同时估计物种发散时间以及当前和祖先种群的大小。该方法使用来自多个基因座的DNA序列数据,并提取有关基因树拓扑和合并时间之间的冲突的信息,以估计祖先种群的大小。物种树的拓扑假定是已知的。实施了马尔可夫链蒙特卡罗算法,以整合每个基因座上不确定的基因树和分支长度(或合并时间)以及物种发散时间。该方法可以处理任何物种树,并允许在不同位点使用不同数量的序列。我们将该方法应用于人类和大猿人发表的非编码DNA序列。在物种形成时间的后验估计与祖先种群规模之间有很强的相关性。利用人类黑猩猩分歧日期的先验信息,这两个物种的共同祖先的种群规模估计为〜20,000,可信区间为95%(8000,40,000)。但是,我们的估计受模型假设以及数据质量的影响。我们建议可靠的估计尚未等待更多的数据和更现实的模型。

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