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在费希尔适应几何模型中有益突变的适合度效应分布。

The distribution of fitness effects among beneficial mutations in Fisher's geometric model of adaptation.

作者信息

Orr H Allen

机构信息

Department of Biology, University of Rochester, Rochester, NY 14627, USA.

出版信息

J Theor Biol. 2006 Jan 21;238(2):279-85. doi: 10.1016/j.jtbi.2005.05.001. Epub 2005 Jun 28.

Abstract

Recent models of adaptation at the DNA sequence level assume that the fitness effects of new mutations show certain statistical properties. In particular, these models assume that the distribution of fitness effects among new mutations is in the domain of attraction of the so-called Gumbel-type extreme value distribution. This assumption has not, however, been justified on any biological or theoretical grounds. In this note, I study random mutation in one of the simplest models of mutation and adaptation-Fisher's geometric model. I show that random mutation in this model yields a distribution of mutational effects that belongs to the Gumbel type. I also show that the distribution of fitness effects among rare beneficial mutations in Fisher's model is asymptotically exponential. I confirm these analytic findings with exact computer simulations. These results provide some support for the use of Gumbel-type extreme value theory in studies of adaptation and point to a surprising connection between recent phenotypic- and sequence-based models of adaptation: in both, the distribution of fitness effects among rare beneficial mutations is approximately exponential.

摘要

近期在DNA序列水平上的适应性模型假定新突变的适合度效应具有某些统计学特性。特别地,这些模型假定新突变之间适合度效应的分布处于所谓的耿贝尔型极值分布的吸引域内。然而,这一假定尚未基于任何生物学或理论依据得到论证。在本注释中,我研究了最简单的突变与适应性模型之一——费希尔几何模型中的随机突变。我表明该模型中的随机突变产生了属于耿贝尔类型的突变效应分布。我还表明费希尔模型中罕见有益突变的适合度效应分布渐近呈指数分布。我通过精确的计算机模拟证实了这些分析结果。这些结果为在适应性研究中使用耿贝尔型极值理论提供了一些支持,并指出了近期基于表型和基于序列的适应性模型之间令人惊讶的联系:在这两种模型中,罕见有益突变的适合度效应分布都近似呈指数分布。

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