Fischer Eva K, Ghalambor Cameron K, Hoke Kim L
*Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA.
Department of Biology, Colorado State University, 1878 Campus Delivery, Fort Collins, CO 80523, USA.
Integr Comp Biol. 2016 Nov;56(5):877-888. doi: 10.1093/icb/icw087. Epub 2016 Jul 8.
Theoretical and empirical work has described a range of scenarios in which plasticity may shape adaptation to a novel environment. For example, recent studies have implicated a role for both adaptive and non-adaptive plasticity in facilitating adaptive evolution, yet we lack a broad mechanistic framework to predict under what conditions each scenario is likely to dominate evolutionary processes. We propose that such a framework requires understanding how transcriptional, protein, and developmental networks change in response to different rearing environments across evolutionary time scales. Our central argument is that these hierarchical networks generate and maintain phenotypic variation in populations, both by buffering organisms from developmental noise and mutational inputs and by exhibiting flexible responses to environmental cues. These network properties in turn lead to predictions about how plasticity should influence adaptive evolution. Because buffering mechanisms allow the build-up of cryptic genetic variation (i.e., genetic variation without phenotypic consequences), the initial response of individuals colonizing novel environments should be a release of genetic and phenotypic variation that selection acts upon; some of which is adaptive and some of which is not. Thus, in the early stages of adaptation, strong selection against maladaptive phenotypes should result in rapid evolution acting on standing cryptic variation. However, over longer time scales, evolutionary change should largely be compensatory, to rebuild robust developmental processes and promote integrated phenotypes. We argue that considering how hierarchical networks respond over developmental and evolutionary time encompasses a more mechanistic understanding of the genotype-phenotype map, and will result in a more predictive framework for understanding the role of plasticity in adaptive evolution.
理论和实证研究描述了一系列可塑性可能影响对新环境适应的情景。例如，最近的研究表明，适应性和非适应性可塑性在促进适应性进化中都发挥了作用，但我们缺乏一个广泛的机制框架来预测每种情景在何种条件下可能主导进化过程。我们提出，这样一个框架需要理解转录、蛋白质和发育网络在跨越进化时间尺度的不同饲养环境下是如何变化的。我们的核心观点是，这些层次网络通过缓冲生物体免受发育噪声和突变输入的影响，以及通过对环境线索表现出灵活反应，在种群中产生并维持表型变异。这些网络特性进而导致了关于可塑性应如何影响适应性进化的预测。由于缓冲机制允许隐性遗传变异（即没有表型后果的遗传变异）的积累，定殖于新环境的个体的初始反应应该是释放可供选择作用的遗传和表型变异；其中一些是适应性的，一些是非适应性的。因此，在适应的早期阶段，对非适应性表型的强烈选择应导致对现存隐性变异的快速进化作用。然而，在更长的时间尺度上，进化变化在很大程度上应该是补偿性的，以重建稳健的发育过程并促进整合的表型。我们认为，考虑层次网络在发育和进化时间上的反应，包含了对基因型-表型图谱更具机制性的理解，并将产生一个更具预测性的框架，用于理解可塑性在适应性进化中的作用。
