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一种基于溯祖理论的DNA序列混合估计方法。

A coalescent-based estimator of admixture from DNA sequences.

作者信息

Wang Jinliang

机构信息

Institute of Zoology, Zoological Society of London, London NW1 4RY, United Kingdom.

出版信息

Genetics. 2006 Jul;173(3):1679-92. doi: 10.1534/genetics.105.054130. Epub 2006 Apr 19.

Abstract

A variety of estimators have been developed to use genetic marker information in inferring the admixture proportions (parental contributions) of a hybrid population. The majority of these estimators used allele frequency data, ignored molecular information that is available in markers such as microsatellites and DNA sequences, and assumed that mutations are absent since the admixture event. As a result, these estimators may fail to deliver an estimate or give rather poor estimates when admixture is ancient and thus mutations are not negligible. A previous molecular estimator based its inference of admixture proportions on the average coalescent times between pairs of genes taken from within and between populations. In this article I propose an estimator that considers the entire genealogy of all of the sampled genes and infers admixture proportions from the numbers of segregating sites in DNA sequence samples. By considering the genealogy of all sequences rather than pairs of sequences, this new estimator also allows the joint estimation of other interesting parameters in the admixture model, such as admixture time, divergence time, population size, and mutation rate. Comparative analyses of simulated data indicate that the new coalescent estimator generally yields better estimates of admixture proportions than the previous molecular estimator, especially when the parental populations are not highly differentiated. It also gives reasonably accurate estimates of other admixture parameters. A human mtDNA sequence data set was analyzed to demonstrate the method, and the analysis results are discussed and compared with those from previous studies.

摘要

已经开发出多种估计方法,用于利用遗传标记信息推断杂交群体的混合比例(亲本贡献)。这些估计方法大多使用等位基因频率数据,忽略了微卫星和DNA序列等标记中可用的分子信息,并假设自混合事件以来不存在突变。因此,当混合事件发生时间久远且突变不可忽略时,这些估计方法可能无法给出估计值,或者给出的估计值相当不准确。之前的一种分子估计方法是基于从群体内部和群体之间选取的基因对之间的平均合并时间来推断混合比例。在本文中,我提出了一种估计方法,该方法考虑所有采样基因的完整谱系,并根据DNA序列样本中的分离位点数量推断混合比例。通过考虑所有序列的谱系而非序列对,这种新的估计方法还允许对混合模型中的其他有趣参数进行联合估计,例如混合时间、分化时间、群体大小和突变率。对模拟数据的比较分析表明,新的合并估计方法通常比之前的分子估计方法能更好地估计混合比例,尤其是当亲本群体差异不大时。它还能对其他混合参数给出合理准确的估计。对一个人类线粒体DNA序列数据集进行了分析以演示该方法,并对分析结果进行了讨论,并与之前研究的结果进行了比较。

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A coalescent-based estimator of admixture from DNA sequences.一种基于溯祖理论的DNA序列混合估计方法。
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