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迈向进化适应理论。

Towards a theory of evolutionary adaptation.

作者信息

Hartl D L, Taubes C H

机构信息

Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.

出版信息

Genetica. 1998;102-103(1-6):525-33.

PMID:9720296
Abstract

Most theoretical models in population genetics fail to deal in a realistic manner with the process of mutation. They are consequently not informative about the central evolutionary problem of the origin, progression, and limit of adaptation. Here we present an explicit distribution of phenotypes expected in an ensemble of populations under a mutation-selection-drift model that allows mutations with a distribution of adaptive values to occur randomly in time. The model of mutation is a geometrical model in which the effect of a new mutation is determined by a random angle in n dimensional space and in which the adaptive value (fitness) of an organism decreases as the square of the deviation of its phenotype from an optimum. Each new mutation is subjected to random genetic drift and fixed or lost according to its selective value and the effective population number. Time is measured in number of fixation events, so that, at any point in time, each population is regarded as genetically homogeneous. In this mutation-selection-drift model, among an ensemble of populations, the equilibrium average phenotype coincides with the optimum because the distribution of positive and negative deviations from the optimum is symmetrical. However, at equilibrium the mean of the absolute value of the deviation from the optimum equals square root of n-/8Ns), where n is the dimensionality of the trait space, N is the effective population size, and s is the selection coefficient against a mutation whose phenotype deviates by one unit from the optimum. Furthermore, at equilibrium, the average fitness across the ensemble of populations equals 1 - (n + 1)/8N. When n is sufficiently large, there is a strong mutation pressure toward the fixation of slightly deleterious mutations. This feature relates our model to the nearly neutral theory of molecular evolution.

摘要

群体遗传学中的大多数理论模型都未能以现实的方式处理突变过程。因此,它们对于适应的起源、发展和极限这一核心进化问题并无助益。在此,我们给出了一个在突变 - 选择 - 漂变模型下,预期在一组群体中出现的表型的显式分布,该模型允许具有适应值分布的突变在时间上随机发生。突变模型是一个几何模型,其中新突变的效应由n维空间中的一个随机角度决定,并且生物体的适应值(适合度)随着其表型与最优值的偏差的平方而降低。每个新突变都经历随机遗传漂变,并根据其选择值和有效种群数量被固定或丢失。时间以固定事件的数量来衡量,因此,在任何时间点,每个群体都被视为基因同质的。在这个突变 - 选择 - 漂变模型中,在一组群体中,平衡平均表型与最优值一致,因为与最优值的正偏差和负偏差的分布是对称的。然而,在平衡时,与最优值的偏差的绝对值的平均值等于(\sqrt{n/8Ns}),其中n是性状空间的维度,N是有效种群大小, s是针对其表型与最优值偏差一个单位的突变的选择系数。此外,在平衡时,整个群体集合的平均适合度等于(1-(n + 1)/8N)。当n足够大时,存在一种强烈的突变压力促使轻微有害突变固定下来。这一特征将我们的模型与分子进化的近中性理论联系起来。

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