Combadão Jaime, Campos Paulo R A, Dionisio Francisco, Gordo Isabel
Instituto Gulbenkian de Ciência, Oeiras, Portugal.
Genet Res. 2007 Feb;89(1):7-18. doi: 10.1017/S0016672307008658.
Muller's ratchet is an evolutionary process that has been implicated in the extinction of asexual species, the evolution of non-recombining genomes, such as the mitochondria, the degeneration of the Y chromosome, and the evolution of sex and recombination. Here we study the speed of Muller's ratchet in a spatially structured population which is subdivided into many small populations (demes) connected by migration, and distributed on a graph. We studied different types of networks: regular networks (similar to the stepping-stone model), small-world networks and completely random graphs. We show that at the onset of the small-world network - which is characterized by high local connectivity among the demes but low average path length - the speed of the ratchet starts to decrease dramatically. This result is independent of the number of demes considered, but is more pronounced the larger the network and the stronger the deleterious effect of mutations. Furthermore, although the ratchet slows down with increasing migration between demes, the observed decrease in speed is smaller in the stepping-stone model than in small-world networks. As migration rate increases, the structured populations approach, but never reach, the result in the corresponding panmictic population with the same number of individuals. Since small-world networks have been shown to describe well the real contact networks among people, we discuss our results in the light of the evolution of microbes and disease epidemics.
穆勒棘轮效应是一个进化过程,它与无性物种的灭绝、非重组基因组(如线粒体)的进化、Y染色体的退化以及性别和重组的进化有关。在这里,我们研究了穆勒棘轮效应在空间结构化种群中的速度,该种群被细分为许多通过迁移相连的小种群(群落),并分布在一个图上。我们研究了不同类型的网络:规则网络(类似于踏脚石模型)、小世界网络和完全随机图。我们表明,在小世界网络开始时——其特征是群落之间的局部连通性高但平均路径长度低——棘轮效应的速度开始急剧下降。这一结果与所考虑的群落数量无关,但网络越大且突变的有害影响越强,这种结果就越明显。此外,尽管随着群落之间迁移的增加,棘轮效应会减缓,但在踏脚石模型中观察到的速度下降比在小世界网络中要小。随着迁移率的增加,结构化种群接近但永远不会达到具有相同个体数量的相应随机交配种群的结果。由于小世界网络已被证明能很好地描述人与人之间的实际接触网络,我们根据微生物和疾病流行的进化来讨论我们的结果。