Ciliberti S, Martin O C, Wagner A
Unité Mixte Recherche 8565, Laboratoire de Physique Théorique et Modèles Statistiques, Université Paris-Sud and Centre National de la Recherche Scientifique, F-91405 Orsay, France.
Proc Natl Acad Sci U S A. 2007 Aug 21;104(34):13591-6. doi: 10.1073/pnas.0705396104. Epub 2007 Aug 9.
The history of life involves countless evolutionary innovations, a steady stream of ingenuity that has been flowing for more than 3 billion years. Very little is known about the principles of biological organization that allow such innovation. Here, we examine these principles for evolutionary innovation in gene expression patterns. To this end, we study a model for the transcriptional regulation networks that are at the heart of embryonic development. A genotype corresponds to a regulatory network of a given topology, and a phenotype corresponds to a steady-state gene expression pattern. Networks with the same phenotype form a connected graph in genotype space, where two networks are immediate neighbors if they differ by one regulatory interaction. We show that an evolutionary search on this graph can reach genotypes that are as different from each other as if they were chosen at random in genotype space, allowing evolutionary access to different kinds of innovation while staying close to a viable phenotype. Thus, although robustness to mutations may hinder innovation in the short term, we conclude that long-term innovation in gene expression patterns can only emerge in the presence of the robustness caused by connected genotype graphs.
生命的历史涉及无数的进化创新，这是一股源源不断的创造力，已经流淌了超过30亿年。对于允许这种创新的生物组织原理，我们知之甚少。在这里，我们研究基因表达模式进化创新的这些原理。为此，我们研究了作为胚胎发育核心的转录调控网络模型。一个基因型对应于一个给定拓扑结构的调控网络，一个表型对应于一个稳态基因表达模式。具有相同表型的网络在基因型空间中形成一个连通图，其中两个网络如果仅相差一个调控相互作用，则它们是直接邻居。我们表明，在这个图上的进化搜索可以到达彼此差异极大的基因型，就好像它们是在基因型空间中随机选择的一样，这使得进化能够在保持接近可行表型的同时获得不同类型的创新。因此，尽管对突变的稳健性可能在短期内阻碍创新，但我们得出结论，基因表达模式的长期创新只能在由连通基因型图引起的稳健性存在的情况下出现。
