Ancestral inference on gene trees under selection
Ancestral inference on gene trees under selection
复制标题
DOI：
10.1016/j.tpb.2004.06.006
复制
发表时间：
2004-11-01
影响因子：
1.4
通讯作者：
Griffiths, RC
中科院分区：
文献类型：
--
作者：
Coop, G;Griffiths, RC
自然选择在多大程度上塑造了种群内的多样性，这是种群遗传学的一个关键问题。因此，人们对量化选择的强度很感兴趣。这里描述了一种全似然方法，用于推断在原本中性的完全连锁的位点序列中的单个位点的选择。进化的合并模型被用来模拟具有所选位置分离的DNA序列样本的祖先。对于选择的和中性的位点，突变模型是无限多个位点的模型，其中在位点上没有反向或平行突变。在这种突变模式下，根据样本序列上的突变构型，可以构建一个独特的完美的系统发育树--基因树。该方法具有通用性，可用于任何双等位基因选择方案。选择是通过对所选和中性等位基因类的频率进行随机建模来结合的，然后使用细分种群模型，将随时间变化的种群频率视为可变的种群大小。然后使用重要性抽样算法在与数据一致的合并树空间上进行探索。该方法被应用于模拟数据集和Verrelli等人提出的基因树。(2002)。(C)2004 Elsevier Inc.保留所有权利。
The extent to which natural selection shapes diversity within populations is a key question for population genetics. Thus, there is considerable interest in quantifying the strength of selection. A full likelihood approach for inference about selection at a single site within an otherwise neutral fully linked sequence of sites is described here. A coalescent model of evolution is used to model the ancestry of a sample of DNA sequences which have the selected site segregating. The mutation model, for the selected and neutral sites, is the infinitely many-sites model where there is no back or parallel mutation at sites. A unique perfect phylogeny, a gene tree, can be constructed from the configuration of mutations on the sample sequences under this model of mutation. The approach is general and can be used for any bi-allelic selection scheme. Selection is incorporated through modelling the frequency of the selected and neutral allelic classes stochastically back in time, then using a subdivided population model considering the population frequencies through time as variable population sizes. An importance sampling algorithm is then used to explore over coalescent tree space consistent with the data. The method is applied to a simulated data set and the gene tree presented in Verrelli et al. (2002). (C) 2004 Elsevier Inc. All rights reserved.