Division of Ecology and Evolutionary Biology, Graduate School of Life Sciences, Tohoku University, Sendai, Japan.
PLoS Comput Biol. 2010 Aug 5;6(8):e1000873. doi: 10.1371/journal.pcbi.1000873.
Various characteristics of complex gene regulatory networks (GRNs) have been discovered during the last decade, e.g., redundancy, exponential indegree distributions, scale-free outdegree distributions, mutational robustness, and evolvability. Although progress has been made in this field, it is not well understood whether these characteristics are the direct products of selection or those of other evolutionary forces such as mutational biases and biophysical constraints. To elucidate the causal factors that promoted the evolution of complex GRNs, we examined the effect of fluctuating environmental selection and some intrinsic constraining factors on GRN evolution by using an individual-based model. We found that the evolution of complex GRNs is remarkably promoted by fixation of beneficial gene duplications under unpredictably fluctuating environmental conditions and that some internal factors inherent in organisms, such as mutational bias, gene expression costs, and constraints on expression dynamics, are also important for the evolution of GRNs. The results indicate that various biological properties observed in GRNs could evolve as a result of not only adaptation to unpredictable environmental changes but also non-adaptive processes owing to the properties of the organisms themselves. Our study emphasizes that evolutionary models considering such intrinsic constraining factors should be used as null models to analyze the effect of selection on GRN evolution.
在过去的十年中,人们发现了复杂基因调控网络(GRN)的各种特性,例如冗余、指数性入度分布、无标度性出度分布、突变稳健性和可进化性。尽管在这个领域已经取得了进展,但人们并不清楚这些特性是选择的直接产物,还是突变偏向和生物物理限制等其他进化力量的产物。为了阐明促进复杂 GRN 进化的因果因素,我们通过使用基于个体的模型,考察了环境选择的波动和一些内在约束因素对 GRN 进化的影响。我们发现,在不可预测的环境条件下,有益基因重复的固定对复杂 GRN 的进化有显著的促进作用,而且生物体固有的一些内在因素,如突变偏向、基因表达成本以及对表达动态的限制,对于 GRN 的进化也很重要。结果表明,GRN 中观察到的各种生物学特性的进化不仅是对不可预测的环境变化的适应的结果,也是由于生物体自身的特性导致的非适应性过程的结果。我们的研究强调,应该使用考虑这些内在约束因素的进化模型作为零模型来分析选择对 GRN 进化的影响。