Bell G
Department of Biology, McGill University, Montréal, Québec, Canada H3A 181.
Cold Spring Harb Symp Quant Biol. 2009;74:139-44. doi: 10.1101/sqb.2009.74.003. Epub 2009 Aug 10.
The traditional view is that evolution proceeds very slowly, over immense periods of time, driven by weak selection acting on innumerable genes of small effect. Recent studies of rapid evolution, in the laboratory and in the field, have given a radically different picture. Although beneficial mutations tend to be small in effect when they first appear, those that survive to spread and become fixed are usually among the minority with large effect. Hence, although hundreds of loci of small effect may contribute to variation in character state, adaptation is predominantly caused by alleles of large effect. This leads to the hope that the particular mutations responsible for adaptation to altered conditions of life can be identified and characterized. This has been achieved in some cases and may soon become routine. Furthermore, it raises the possibility that adaptive change can be predicted from a knowledge of genetics and ecology. Experimental evolution suggests that any given selection line that is adapting to changed conditions will follow one of a few themes (broadly speaking, loci), each of which may have many variations (mutations within the locus producing similar phenotypes). Hence, evolutionary change can be predicted only within limits, even in principle. Nevertheless, recent attempts to predict how very simple genomes change have been surprisingly successful, and we may be close to a new predictive understanding of the genetic basis of adaptation.
传统观点认为,进化进程非常缓慢,历经漫长的时间,由作用于无数微小效应基因的微弱选择所驱动。近期在实验室和野外对快速进化的研究呈现出截然不同的景象。尽管有益突变最初出现时效应往往较小,但那些存活下来得以传播并固定下来的突变通常属于效应较大的少数突变。因此,尽管数百个微小效应的基因座可能会导致性状状态的变异,但适应主要是由效应较大的等位基因引起的。这使得人们希望能够识别并表征那些导致适应生活条件改变的特定突变。在某些情况下已经实现了这一点,并且可能很快会成为常规操作。此外,这还增加了从遗传学和生态学知识预测适应性变化的可能性。实验进化表明,任何适应变化条件的给定选择系将遵循少数几个主题(广义而言,基因座)之一,每个主题可能有许多变体(基因座内产生相似表型的突变)。因此,即使原则上,进化变化也只能在一定范围内被预测。然而,最近预测非常简单的基因组如何变化的尝试取得了惊人的成功,我们可能即将对适应的遗传基础有新的预测性理解。