Wagner Günter P, Altenberg Lee
Center for Computational Ecology, Department of Biology, Yale University, New Haven, Connecticut, 06511.
Hawaii Institute of Geophysics and Planetology, University of Hawaii at Manoa, Manoa, Hawaii, 96822.
Evolution. 1996 Jun;50(3):967-976. doi: 10.1111/j.1558-5646.1996.tb02339.x.
The problem of complex adaptations is studied in two largely disconnected research traditions: evolutionary biology and evolutionary computer science. This paper summarizes the results from both areas and compares their implications. In evolutionary computer science it was found that the Darwinian process of mutation, recombination and selection is not universally effective in improving complex systems like computer programs or chip designs. For adaptation to occur, these systems must possess "evolvability," i.e., the ability of random variations to sometimes produce improvement. It was found that evolvability critically depends on the way genetic variation maps onto phenotypic variation, an issue known as the representation problem. The genotype-phenotype map determines the variability of characters, which is the propensity to vary. Variability needs to be distinguished from variations, which are the actually realized differences between individuals. The genotype-phenotype map is the common theme underlying such varied biological phenomena as genetic canalization, developmental constraints, biological versatility, developmental dissociability, and morphological integration. For evolutionary biology the representation problem has important implications: how is it that extant species acquired a genotype-phenotype map which allows improvement by mutation and selection? Is the genotype-phenotype map able to change in evolution? What are the selective forces, if any, that shape the genotype-phenotype map? We propose that the genotype-phenotype map can evolve by two main routes: epistatic mutations, or the creation of new genes. A common result for organismic design is modularity. By modularity we mean a genotype-phenotype map in which there are few pleiotropic effects among characters serving different functions, with pleiotropic effects falling mainly among characters that are part of a single functional complex. Such a design is expected to improve evolvability by limiting the interference between the adaptation of different functions. Several population genetic models are reviewed that are intended to explain the evolutionary origin of a modular design. While our current knowledge is insufficient to assess the plausibility of these models, they form the beginning of a framework for understanding the evolution of the genotype-phenotype map.
进化生物学和进化计算机科学。本文总结了这两个领域的研究结果并比较了它们的意义。在进化计算机科学中发现,突变、重组和选择的达尔文过程在改进诸如计算机程序或芯片设计等复杂系统方面并非普遍有效。为了实现适应性,这些系统必须具备“可进化性”,即随机变异有时能产生改进的能力。研究发现,可进化性关键取决于遗传变异映射到表型变异的方式,这一问题被称为表征问题。基因型 - 表型映射决定了性状的变异性,即变异的倾向。变异性需要与变异区分开来,变异是个体之间实际出现的差异。基因型 - 表型映射是诸如遗传稳态、发育限制、生物多功能性、发育解离性和形态整合等各种生物现象背后的共同主题。对于进化生物学而言,表征问题具有重要意义:现存物种是如何获得允许通过突变和选择实现改进的基因型 - 表型映射的?基因型 - 表型映射在进化过程中能够改变吗?塑造基因型 - 表型映射的选择力量(如果有的话)是什么?我们提出,基因型 - 表型映射可以通过两条主要途径进化:上位性突变或新基因的产生。生物体设计的一个常见结果是模块化。我们所说的模块化是指一种基因型 - 表型映射,其中服务于不同功能的性状之间几乎没有多效性效应,多效性效应主要出现在属于单个功能复合体一部分的性状之间。这样的设计预计通过限制不同功能适应性之间的干扰来提高可进化性。本文回顾了几个群体遗传模型,这些模型旨在解释模块化设计的进化起源。虽然我们目前的知识不足以评估这些模型的合理性,但它们构成了理解基因型 - 表型映射进化框架的开端。