School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia.
BMC Evol Biol. 2013 Nov 7;13:244. doi: 10.1186/1471-2148-13-244.
A major goal of molecular evolution is to determine how natural selection has shaped the evolution of a gene. One approach taken by methods such as KA/KS and the McDonald-Kreitman (MK) test is to compare the frequency of non-synonymous and synonymous changes. These methods, however, rely on the assumption that a change in frequency of one mutation will not affect changes in frequency of other mutations.
We demonstrate that linkage between sites can bias measures of selection based on synonymous and non-synonymous changes. Using forward simulation of a Wright-Fisher process, we show that hitch-hiking of deleterious mutations with advantageous mutations can lead to overestimation of the number of adaptive substitutions, while background selection and clonal interference can distort the site frequency spectrum to obscure the signal for positive selection. We present three diagnostics for detecting these effects of linked selection and apply them to the human influenza (H3N2) hemagglutinin gene.
Various forms of linked selection have characteristic effects on MK-type statistics. The extent of background selection, hitch-hiking and clonal interference can be evaluated using the diagnostic statistics presented here. The diagnostics can also be used to determine how well we expect the MK statistics to perform and whether one form of the statistic may be preferable to another.
分子进化的主要目标之一是确定自然选择如何塑造基因的进化。KA/KS 和 McDonald-Kreitman (MK) 检验等方法采用的一种方法是比较非同义突变和同义突变的频率。然而，这些方法依赖于一个假设，即一个突变频率的变化不会影响其他突变频率的变化。
我们证明了位点之间的连锁可以偏置基于同义突变和非同义突变的选择度量。我们使用 Wright-Fisher 过程的正向模拟表明，有利突变与有害突变的连锁漂变可能导致对适应性替代数量的高估，而背景选择和克隆干扰会扭曲位点频率谱，掩盖正选择的信号。我们提出了三种用于检测连锁选择这些影响的诊断方法，并将其应用于人类流感 (H3N2) 血凝素基因。
各种形式的连锁选择对 MK 型统计数据有特征性影响。可以使用此处提出的诊断统计数据来评估背景选择、连锁漂变和克隆干扰的程度。这些诊断还可以用于确定我们对 MK 统计数据的期望程度，以及一种统计数据是否可能优于另一种。
