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费舍尔几何模型下选定突变的特性和基因型景观

Properties of selected mutations and genotypic landscapes under Fisher's geometric model.

作者信息

Blanquart François, Achaz Guillaume, Bataillon Thomas, Tenaillon Olivier

机构信息

Bioinformatics Research Centre, University of Aarhus, 8000C, Aarhus, Denmark.

出版信息

Evolution. 2014 Dec;68(12):3537-54. doi: 10.1111/evo.12545. Epub 2014 Nov 17.

Abstract

The fitness landscape-the mapping between genotypes and fitness-determines properties of the process of adaptation. Several small genotypic fitness landscapes have recently been built by selecting a handful of beneficial mutations and measuring fitness of all combinations of these mutations. Here, we generate several testable predictions for the properties of these small genotypic landscapes under Fisher's geometric model of adaptation. When the ancestral strain is far from the fitness optimum, we analytically compute the fitness effect of selected mutations and their epistatic interactions. Epistasis may be negative or positive on average depending on the distance of the ancestral genotype to the optimum and whether mutations were independently selected, or coselected in an adaptive walk. Simulations show that genotypic landscapes built from Fisher's model are very close to an additive landscape when the ancestral strain is far from the optimum. However, when it is close to the optimum, a large diversity of landscape with substantial roughness and sign epistasis emerged. Strikingly, small genotypic landscapes built from several replicate adaptive walks on the same underlying landscape were highly variable, suggesting that several realizations of small genotypic landscapes are needed to gain information about the underlying architecture of the fitness landscape.

摘要

适应度景观——基因型与适应度之间的映射——决定了适应过程的特性。最近,通过选择少数有益突变并测量这些突变的所有组合的适应度,构建了几个小型基因型适应度景观。在此,我们根据费希尔适应几何模型,对这些小型基因型景观的特性生成了几个可检验的预测。当祖先菌株远离适应度最优值时,我们通过分析计算所选突变的适应度效应及其上位性相互作用。平均而言,上位性可能为负或为正,这取决于祖先基因型与最优值的距离,以及突变是独立选择的,还是在适应性进化中共同选择的。模拟表明,当祖先菌株远离最优值时,基于费希尔模型构建的基因型景观非常接近加性景观。然而,当它接近最优值时,会出现具有大量粗糙度和符号上位性的多种不同景观。引人注目的是,在相同基础景观上通过多次重复适应性进化构建的小型基因型景观高度可变,这表明需要多个小型基因型景观的实现来获取有关适应度景观潜在结构的信息。

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