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跨环境突变的适应性效应:基于适应性景观模型的一项调查

The fitness effect of mutations across environments: a survey in light of fitness landscape models.

作者信息

Martin Guillaume, Lenormand Thomas

机构信息

Centre d'Ecologie Fonctionnelle et Evolutive, CNRS UMR 5175, 1919 Rte de Mende, 34 293 Montpellier, France.

出版信息

Evolution. 2006 Dec;60(12):2413-27.

Abstract

The fitness effects of mutations on a given genotype are rarely constant across environments to which this genotype is more or less adapted, that is, between more or less stressful conditions. This can have important implications, especially on the evolution of ecological specialization. Stress is thought to increase the variance of mutations' fitness effects, their average, or the number of expressed mutations. Although empirical evidence is available for these three mechanisms, their relative magnitude is poorly understood. In this paper, we propose a simple approach to discriminate between these mechanisms, using a survey of empirical measures of mutation effects in contrasted environments. This survey, across various species and environments, shows that stress mainly increases the variance of mutations' effects on fitness, with a much more limited impact on their average effect or on the number of expressed mutations. This pattern is consistent with a simple model in which fitness is a Gaussian function of phenotypes around an environmentally determined optimum. These results suggest that a simple, mathematically tractable landscape model may not be quantitatively as unrealistic as previously suggested. They also suggest that mutation parameter estimates may be strongly biased when measured in stressful environments.

摘要

对于某一特定基因型而言,突变的适应性效应在该基因型或多或少适应的不同环境中,即在压力程度不同的条件下,很少会保持恒定。这可能具有重要意义,特别是对生态特化的进化而言。压力被认为会增加突变适应性效应的方差、其平均值或表达突变的数量。尽管有关于这三种机制的实证证据,但对它们的相对大小却知之甚少。在本文中,我们提出了一种简单的方法来区分这些机制,即通过对不同环境中突变效应的实证测量进行调查。这项涵盖各种物种和环境的调查表明,压力主要增加了突变对适应性的效应的方差,而对其平均效应或表达突变的数量影响要小得多。这种模式与一个简单模型一致,在该模型中,适应性是围绕环境决定的最优值的表型的高斯函数。这些结果表明,一个简单的、数学上易于处理的景观模型在定量方面可能并不像之前认为的那样不切实际。它们还表明,在压力环境中进行测量时,突变参数估计可能会有很大偏差。

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