School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, New South Wales, Australia.
PLoS Comput Biol. 2010 Feb 12;6(2):e1000672. doi: 10.1371/journal.pcbi.1000672.
Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model), genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters.
在细菌染色体上，编码蛋白质的基因通常在共同途径附近彼此相邻。已经提出了几种解释来解释这些结构的进化。例如，自然选择可能通过多种机制直接有利于基因簇，例如增加核心调控的效率。另一种替代的和有争议的假设是自私操纵子模型，该模型断言基因簇的排列更容易转移到其他物种，从而提高了簇的生存机会。根据另一种假设（持续模型），紧密接近的基因不太可能被缺失破坏。在这里，我们开发计算模型来研究基因簇进化和持续存在的条件。首先，我们通过重新实现模拟并在广泛的条件下运行来检查自私操纵子模型。其次，我们引入并研究了一种 Moran 过程，其中存在基因聚类的自然选择，并且通过基因组倒位事件发生重排。最后，我们开发并研究了一个包括选择和倒位的模型，该模型跟踪重排的发生和固定。令人惊讶的是，在广泛的条件下，基因簇未能进化。促进基因簇进化的因素包括途径中基因数量少、种群数量大，以及在自私操纵子模型中，水平转移率高。这里的计算分析表明，只要满足某些条件，基因簇的进化就可以在直接选择和间接选择下发生。在这些条件下，自私操纵子模型仍然是解释基因簇进化的可行模型。
