Good Benjamin H, Walczak Aleksandra M, Neher Richard A, Desai Michael M
Departments of Organismic and Evolutionary Biology and of Physics, Harvard University, Cambridge, Massachusetts, United States of America; FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.
CNRS-Laboratoire de Physique Théorique de l'École Normale Supérieure, Paris, France.
PLoS Genet. 2014 Mar 27;10(3):e1004222. doi: 10.1371/journal.pgen.1004222. eCollection 2014 Mar.
Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a "linkage block"). We exploit this insensitivity in a new "coarse-grained" coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability.
普遍存在的自然选择能够强烈影响所观察到的遗传变异模式，但是当多个被选择的变异在基因组的邻近区域分离时，这些影响仍未得到充分理解。经典群体遗传学未能考虑连锁突变之间的干扰，随着被选择多态性密度的增加，这种干扰会变得越来越严重。在此，我们描述了一种当干扰普遍存在时出现的简单极限情况，其中单个突变的适应性效应发挥的作用相对较小。相反，类似于数量遗传学模型，分子进化由群体内适应性的方差决定，该方差是在基因组的一个有效无性片段（一个“连锁块”）上定义的。我们在一个新的“粗粒度”合并框架中利用这种不敏感性，该框架用数量较少但能产生相同适应性方差的强选择突变来近似许多弱选择突变的效应。当干扰普遍存在时，这种近似对于沉默位点变异性能产生准确且高效的预测。然而，这些结果表明，当干扰足够广泛时，解析个体选择压力的能力会降低，因为广泛的参数具有几乎相同的沉默位点变异性模式。
