ABC inference of multi-population divergence with admixture from unphased population genomic data.
ABC inference of multi-population divergence with admixture from unphased population genomic data.
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DOI：
10.1111/mec.12881
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发表时间：
2014-09
影响因子：
4.9
通讯作者：
Hickerson MJ
中科院分区：
文献类型：
--
作者：
Robinson JD;Bunnefeld L;Hearn J;Stone GN;Hickerson MJ
快速发展的测序技术和不断下降的成本使得在非模型系统中从群体水平的样本中收集基因组规模的数据成为可能。根据这些数据集，历史人口统计学的推理工具目前还不发达。特别是，近似贝叶斯计算（ABC）还没有被产生这些数据的研究人员广泛接受。在这里，我们展示了ABC的承诺，现在可以通过目前的基因组测序技术从非模型类群的大型数据集的分析。我们开发和测试的ABC框架模型选择和参数估计，历史上的三个人口的分歧与混合物。然后，我们探索不同的采样制度，以说明如何采样更多的位点，更长的位点或更多的个人影响模型选择和参数估计的质量在这个ABC框架。我们的研究结果表明，随着测序位点的数量和/或长度的增加，推理得到了很大的改善，而通过大量的个人抽样获得的好处较少。最佳的采样策略，我们的推理模型包括至少2000个位点，每个约2 kb的长度，每个人口从5个二倍体个体采样，虽然具体的策略是模型和问题的依赖。我们通过基于模拟的交叉验证测试了我们的ABC方法，并使用先前分析的橡树瘿蜂Biorhiza pallida的数据来说明其应用。
Rapidly developing sequencing technologies and declining costs have made it possible to collect genome-scale data from population-level samples in nonmodel systems. Inferential tools for historical demography given these data sets are, at present, underdeveloped. In particular, approximate Bayesian computation (ABC) has yet to be widely embraced by researchers generating these data. Here, we demonstrate the promise of ABC for analysis of the large data sets that are now attainable from nonmodel taxa through current genomic sequencing technologies. We develop and test an ABC framework for model selection and parameter estimation, given histories of three-population divergence with admixture. We then explore different sampling regimes to illustrate how sampling more loci, longer loci or more individuals affects the quality of model selection and parameter estimation in this ABC framework. Our results show that inferences improved substantially with increases in the number and/or length of sequenced loci, while less benefit was gained by sampling large numbers of individuals. Optimal sampling strategies given our inferential models included at least 2000 loci, each approximately 2 kb in length, sampled from five diploid individuals per population, although specific strategies are model and question dependent. We tested our ABC approach through simulation-based cross-validations and illustrate its application using previously analysed data from the oak gall wasp, Biorhiza pallida.
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影响因子：
4.5
作者：
Gutenkunst RN;Hernandez RD;Williamson SH;Bustamante CD
通讯作者：
Bustamante CD
影响因子：
3.7
作者：
Baird NA;Etter PD;Atwood TS;Currey MC;Shiver AL;Lewis ZA;Selker EU;Cresko WA;Johnson EA
通讯作者：
Johnson EA
影响因子：
3.3
作者：
He, Qixin;Edwards, Danielle L.;Knowles, L. Lacey
通讯作者：
Knowles, L. Lacey
影响因子：
3.3
作者：
Fraisse, Christelle;Roux, Camille;Bierne, Nicolas
通讯作者：
Bierne, Nicolas
影响因子：
3
作者：
Huang W;Takebayashi N;Qi Y;Hickerson MJ
通讯作者：
Hickerson MJ