Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
BMC Evol Biol. 2012 Sep 6;12:173. doi: 10.1186/1471-2148-12-173.
Changes in gene regulatory networks drive the evolution of phenotypic diversity both within and between species. Rewiring of transcriptional networks is achieved either by changes to transcription factor binding sites or by changes to the physical interactions among transcription factor proteins. It has been suggested that the evolution of cooperative binding among factors can facilitate the adaptive rewiring of a regulatory network.
We use a population-genetic model to explore when cooperative binding of transcription factors is favored by evolution, and what effects cooperativity then has on the adaptive re-writing of regulatory networks. We consider a pair of transcription factors that regulate multiple targets and overlap in the sets of target genes they regulate. We show that, under stabilising selection, cooperative binding between the transcription factors is favoured provided the amount of overlap between their target genes exceeds a threshold. The value of this threshold depends on several population-genetic factors: strength of selection on binding sites, cost of pleiotropy associated with protein-protein interactions, rates of mutation and population size. Once it is established, we find that cooperative binding of transcription factors significantly accelerates the adaptive rewiring of transcriptional networks under positive selection. We compare our qualitative predictions to systematic data on Saccharomyces cerevisiae transcription factors, their binding sites, and their protein-protein interactions.
Our study reveals a rich set of evolutionary dynamics driven by a tradeoff between the beneficial effects of cooperative binding at targets shared by a pair of factors, and the detrimental effects of cooperative binding for non-shared targets. We find that cooperative regulation will evolve when transcription factors share a sufficient proportion of their target genes. These findings help to explain empirical pattens in datasets of transcription factors in Saccharomyces cerevisiae and, they suggest that changes to physical interactions between transcription factors can play a critical role in the evolution of gene regulatory networks.
基因调控网络的变化推动了物种内和物种间表型多样性的进化。转录网络的重新布线要么通过改变转录因子结合位点来实现，要么通过改变转录因子蛋白之间的物理相互作用来实现。有人认为，因子之间协同结合的进化可以促进调控网络的适应性重新布线。
我们使用群体遗传模型来探索转录因子的协同结合何时受到进化的青睐，以及协同作用随后对调控网络的适应性重写有什么影响。我们考虑一对调节多个靶标的转录因子，它们在调节的靶基因集合中重叠。我们表明，在稳定选择下，只要它们的靶基因之间的重叠量超过一个阈值，转录因子之间的协同结合就会受到青睐。这个阈值的值取决于几个群体遗传因素：结合位点的选择强度、与蛋白质-蛋白质相互作用相关的多效性成本、突变率和种群大小。一旦建立起来，我们发现，转录因子的协同结合显著加速了正选择下转录网络的适应性重写。我们将我们的定性预测与酿酒酵母转录因子及其结合位点和蛋白质-蛋白质相互作用的系统数据进行了比较。
我们的研究揭示了一组丰富的进化动态，这些动态是由一对因子共享的靶标上协同结合的有益效应与非共享靶标上协同结合的有害效应之间的权衡驱动的。我们发现，当转录因子共享足够比例的靶基因时，协同调节将进化。这些发现有助于解释酿酒酵母转录因子数据集的经验模式，并且表明转录因子之间物理相互作用的改变可以在基因调控网络的进化中发挥关键作用。
