Nijhout H F, Berg A M, Gibson W T
Department of Biology, Duke University, Durham, NC 27708, USA.
Evol Dev. 2003 May-Jun;5(3):281-94. doi: 10.1046/j.1525-142x.2003.03035.x.
Evolvability is a function of the way genetic variation interacts with the mechanisms that produce the phenotype. We explore an explicitly mechanistic way of studying the evolvability of phenotypes that are produced by a relatively simple genetic mechanism, the mitogen-activated protein kinase (MAPK) cascade. We developed a quantitative model of MAPK activation that can be used to study the effects of genetic variation on the various components of this signaling cascade. We show how some standard tools of applied mathematics, such as steady-state formulations and nondimensionalization, can be used to elucidate the relative importance of variation in each gene of this mechanism. We also give insights into non-intuitive patterns of dependence and trade-off among the genes. The mechanism produces several different phenotypes (ultrasensitivity to stimulation, switch-like behavior, amount of MAPK-PP delivered, persistence of MAPK-PP activity), each of which is sensitive to different (but partially overlapping) combinations of genes. We show that the mechanism imposes clear limitations on the evolvability of each of the different phenotypes of the pathway, even in the presence of genetic variation in the components of the mechanism. This approach to the study of evolvability is generally applicable and complements the traditional approach through statistical genetics by providing a mechanistic understanding of the genetic interactions that produce the phenotype.
可进化性是遗传变异与产生表型的机制相互作用方式的一种函数。我们探索了一种明确的机械方式来研究由相对简单的遗传机制——丝裂原活化蛋白激酶(MAPK)级联反应所产生的表型的可进化性。我们开发了一个MAPK激活的定量模型,可用于研究遗传变异对该信号级联反应各个组成部分的影响。我们展示了一些应用数学的标准工具,如稳态公式和无量纲化,如何能够用来阐明该机制中每个基因变异的相对重要性。我们还深入探讨了基因之间非直观的依赖模式和权衡关系。该机制产生了几种不同的表型(对刺激的超敏感性、开关样行为、MAPK-PP的传递量、MAPK-PP活性的持续性),每种表型对不同(但部分重叠)的基因组合敏感。我们表明,即使在该机制的组成部分存在遗传变异的情况下,该机制对该信号通路不同表型中的每一种的可进化性都施加了明确的限制。这种研究可进化性的方法普遍适用,并通过提供对产生表型的遗传相互作用的机械理解,对传统的统计遗传学方法起到补充作用。