Promislow Daniel
Department of Genetics, University of Georgia, Athens, Georgia 30602-7223, USA.
Am Nat. 2005 May;165(5):515-23. doi: 10.1086/429161. Epub 2005 Feb 18.
Models for the evolution of phenotypic plasticity suggest when and why plasticity might evolve. However, relatively little is known about the genetic basis of plasticity. Molecular studies have recently demonstrated that gene networks can provide a powerful way to infer phenotype from genotype. Information on the structure of the yeast gene regulatory network was combined with data on variation in gene expression in yeast across multiple environments in order to explore the genetic basis of phenotypic plasticity. The phenotypic plasticity of a gene was positively correlated with the number of transcription factors regulating that gene and was significantly lower for transcription factors than for downstream, nonregulatory genes. Plasticity of a gene was also affected by the local substructure of the network in which it was found and by the gene's function. These results illustrate how network analyses can be used to understand the complex genetic architecture of quantitative traits.
表型可塑性进化模型表明可塑性何时以及为何会进化。然而,对于可塑性的遗传基础我们了解得相对较少。分子研究最近表明,基因网络能够提供一种从基因型推断表型的有力方法。将酵母基因调控网络结构的信息与酵母在多种环境下基因表达变化的数据相结合,以探索表型可塑性的遗传基础。一个基因的表型可塑性与调控该基因的转录因子数量呈正相关,并且转录因子的可塑性显著低于下游的非调控基因。一个基因的可塑性还受到其所在网络的局部子结构以及该基因功能的影响。这些结果说明了如何利用网络分析来理解数量性状的复杂遗传结构。