进化增强了突变的鲁棒性并抑制了新表型的出现：一种研究进化的新计算方法
Evolution enhances mutational robustness and suppresses the emergence of a new phenotype: A new computational approach for studying evolution
摘要：
本文的目的有两个方面。首先，我们提出了一种新的计算方法来研究进化的特殊性。其次，我们将这种方法应用到一个基因调控网络（GRNs）模型中，并探讨了突变鲁棒性和双稳态的演化。生命系统通过进化过程发展了它们的功能。为了从理论上理解这一过程的特殊性，进化模拟（ES）本身是不够的，因为ES的结果取决于进化途径。我们需要一个参照系来进行比较。用于此目的的适当参考系统是随机取样基因型的集合。然而，通过简单的随机抽样产生高适应度基因型是困难的，因为这样的基因型是罕见的。在这项研究中，我们使用统计物理学中发展的多规范蒙特卡罗方法来构建一个参考系综的GRNs和ES的结果进行比较。我们得到了以下结果。首先，突变的鲁棒性显着高于在相同的健身水平在ES比在参考集成。第二，一个新的表型，双稳态的出现，在进化中被推迟。第三，与非突变组相比，突变组的GRNs包含许多突变脆弱的GRNs。这表明，延迟出现的双稳态是突变选择机制的结果。
英文摘要：
The aim of this paper is two-fold. First, we propose a new computational method to investigate the particularities of evolution. Second, we apply this method to a model of gene regulatory networks (GRNs) and explore the evolution of mutational robustness and bistability. Living systems have developed their functions through evolutionary processes. To understand the particularities of this process theoretically, evolutionary simulation (ES) alone is insufficient because the outcomes of ES depend on evolutionary pathways. We need a reference system for comparison. An appropriate reference system for this purpose is an ensemble of the randomly sampled genotypes. However, generating high-fitness genotypes by simple random sampling is difficult because such genotypes are rare. In this study, we used the multicanonical Monte Carlo method developed in statistical physics to construct a reference ensemble of GRNs and compared it with the outcomes of ES. We obtained the following results. First, mutational robustness was significantly higher in ES than in the reference ensemble at the same fitness level. Second, the emergence of a new phenotype, bistability, was delayed in evolution. Third, the bistable group of GRNs contains many mutationally fragile GRNs compared with those in the non-bistable group. This suggests that the delayed emergence of bistability is a consequence of the mutation-selection mechanism.
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