Martin Guillaume, Elena Santiago F, Lenormand Thomas
Centre d'écologie fonctionnelle et évolutive-Centre National de la Recherche Scientifique UMR 5175, 1919 Route de Mende, 34293 Montpellier, France.
Nat Genet. 2007 Apr;39(4):555-60. doi: 10.1038/ng1998. Epub 2007 Mar 18.
How do the fitness effects of several mutations combine? Despite its simplicity, this question is central to the understanding of multilocus evolution. Epistasis (the interaction between alleles at different loci), especially epistasis for fitness traits such as reproduction and survival, influences evolutionary predictions "almost whenever multilocus genetics matters". Yet very few models have sought to predict epistasis, and none has been empirically tested. Here we show that the distribution of epistasis can be predicted from the distribution of single mutation effects, based on a simple fitness landscape model. We show that this prediction closely matches the empirical measures of epistasis that have been obtained for Escherichia coli and the RNA virus vesicular stomatitis virus. Our results suggest that a simple fitness landscape model may be sufficient to quantitatively capture the complex nature of gene interactions. This model may offer a simple and widely applicable alternative to complex metabolic network models, in particular for making evolutionary predictions.
多个突变的适应性效应是如何组合的?尽管这个问题很简单,但它是理解多位点进化的核心。上位性(不同位点等位基因之间的相互作用),尤其是对繁殖和生存等适应性性状的上位性,“几乎在多位点遗传学起作用的时候”都会影响进化预测。然而,很少有模型试图预测上位性,而且没有一个模型经过实证检验。在这里,我们表明,基于一个简单的适应性景观模型,可以从单突变效应的分布预测上位性的分布。我们表明,这一预测与针对大肠杆菌和RNA病毒水疱性口炎病毒所获得的上位性实证测量结果密切匹配。我们的结果表明,一个简单的适应性景观模型可能足以定量捕捉基因相互作用的复杂本质。该模型可能为复杂的代谢网络模型提供一种简单且广泛适用的替代方案,特别是用于进行进化预测。