Buzbas Erkan Ozge, Joyce Paul, Rosenberg Noah A
Department of Human Genetics, University of Michigan, USA.
Theor Popul Biol. 2011 May;79(3):102-13. doi: 10.1016/j.tpb.2011.01.002. Epub 2011 Jan 26.
Existing inference methods for estimating the strength of balancing selection in multi-locus genotypes rely on the assumption that there are no epistatic interactions between loci. Complex systems in which balancing selection is prevalent, such as sets of human immune system genes, are known to contain components that interact epistatically. Therefore, current methods may not produce reliable inference on the strength of selection at these loci. In this paper, we address this problem by presenting statistical methods that can account for epistatic interactions in making inference about balancing selection. A theoretical result due to Fearnhead (2006) is used to build a multi-locus Wright-Fisher model of balancing selection, allowing for epistatic interactions among loci. Antagonistic and synergistic types of interactions are examined. The joint posterior distribution of the selection and mutation parameters is sampled by Markov chain Monte Carlo methods, and the plausibility of models is assessed via Bayes factors. As a component of the inference process, an algorithm to generate multi-locus allele frequencies under balancing selection models with epistasis is also presented. Recent evidence on interactions among a set of human immune system genes is introduced as a motivating biological system for the epistatic model, and data on these genes are used to demonstrate the methods.
现有的用于估计多位点基因型中平衡选择强度的推断方法依赖于这样一个假设,即基因座之间不存在上位性相互作用。已知平衡选择普遍存在的复杂系统,如人类免疫系统基因集,包含上位性相互作用的成分。因此,当前方法可能无法对这些基因座处的选择强度做出可靠推断。在本文中,我们通过提出在推断平衡选择时能够考虑上位性相互作用的统计方法来解决这个问题。利用Fearnhead(2006)的一个理论结果构建了一个允许基因座间存在上位性相互作用的多位点平衡选择的赖特 - 费希尔模型。研究了拮抗和协同类型的相互作用。通过马尔可夫链蒙特卡罗方法对选择和突变参数的联合后验分布进行采样,并通过贝叶斯因子评估模型的合理性。作为推断过程的一个组成部分,还提出了一种在具有上位性的平衡选择模型下生成多位点等位基因频率的算法。引入了一组人类免疫系统基因之间相互作用的最新证据,作为上位性模型的一个具有启发性的生物系统,并使用这些基因的数据来演示这些方法。