A model in two acts: a commentary on 'A model detectable alleles in a finite population' by Timoko Ohta and Motoo Kimura.

J. Hey
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引用次数: 1

Abstract

In the early 1970s, protein electrophoresis was the primary tool geneticists used to discover and measure allelic variation in natural populations. It was a relatively simple and inexpensive technique and, most importantly, it permitted the detection of multiple alleles regardless of polymorphism levels. This was a critical point because before the age of protein electrophoresis, segregating alleles were usually discovered only in cases where clearly discrete patterns of phenotypic variation were first observed. With protein electrophoresis a geneticist’s ability to identify multiple alleles did not depend on a prior indication of the presence of genetic variation (Hubby & Lewontin, 1966; Lewontin, 1974). The purpose of the short paper that Tomoko Ohta and her mentor Motoo Kimura published in Genetical Research in 1973 was to devise a mutation model that was explicitly appropriate for protein electrophoretic data and that would permit such data to be analysed with regard to questions on the relative roles of natural selection and genetic drift. As data on electrophoretic alleles began to accumulate, it was discovered that individuals were heterozygous, and many species were polymorphic, at a substantial fraction of the proteins that could be surveyed. These numbers on heterozygosity and polymorphism immediately began to feed a long-standing hunger, that had built up from decades of sophisticated modelling, for data on such topics as mutation rates, genetic load, the rate of neutral mutations, and the relative roles of natural selection and genetic drift in shaping levels and patterns of variation. Ohta and Kimura were the primary theoreticians of the neutral theory of molecular evolution and they had a very strong interest (as did most population geneticists of that age) in understanding how well the neutral theory explained the levels of polymorphism discovered by electrophoresis. The models they developed focused on amounts and patterns of genetic variation, and they tended to include explicitly a neutral mutation rate as well as assumptions about the nature of the mutation process. One prediction of the neutral theory was that the number of alleles in a population was expected to co-vary strongly with the effective population size. Earlier in 1964, Kimura and James Crow had developed the infinite alleles model, in which every mutation gives rise to a new allele (Kimura & Crow, 1964), and under this model the number of neutral alleles varies linearly with both effective population size and neutral mutation rate. Ohta and Kimura’s key idea in 1973 was a mutation model that explicitly gave rise to new allelic states in single steps that differed in net protein charge. Because four of the amino acids are normally charged at physiological pH, the surface of a soluble protein will carry a charge that affects its behaviour in gel electrophoresis, and mutations that raise or lower this charge will increase or decrease the rate of electrophoresis. In Ohta and Kimura’s model, which later came to be known as the ‘stepwise mutation model ’ (Kimura & Ohta, 1978) and also sometimes the ‘ ladder model ’, a protein may mutate to a different allelic state in +1 and x1 steps. Importantly, unlike the infinite sites model, it was possible under this model for two proteins to be identical in kind (i.e. have the same net charge), and not be identical by virtue of common descent from an ancestral gene of the same allelic state (i.e. identity by descent). Ohta and Kimura were a virtual dynamic duo of differential equations, and in this paper as in many others they took a diffusion equation approach. Their primary target was an expression for the effective number of alleles in a population, ne. Under the infinite sites model, Kimura and Crow had shown that ne=1+4Neu (Kimura & Crow, 1964). But under the stepwise model, Ohta and Kimura found that ne= ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
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两种行为的模型:对Timoko Ohta和Motoo Kimura的“有限种群中可检测的等位基因模型”的评论。
在20世纪70年代早期,蛋白质电泳是遗传学家用来发现和测量自然种群中等位基因变异的主要工具。这是一种相对简单和廉价的技术,最重要的是,它允许检测多个等位基因,而不管多态性水平如何。这是一个关键点,因为在蛋白质电泳时代之前,分离等位基因通常只在首次观察到明显离散的表型变异模式的情况下发现。通过蛋白质电泳,遗传学家识别多个等位基因的能力不依赖于遗传变异存在的先前指示(Hubby & Lewontin, 1966;Lewontin, 1974)。1973年,Tomoko Ohta和她的导师Motoo Kimura在《遗传学研究》上发表了一篇简短的论文,目的是设计一个明确适用于蛋白质电泳数据的突变模型,并允许对这些数据进行分析,以解决自然选择和遗传漂变的相对作用问题。随着电泳等位基因的数据开始积累,人们发现个体是杂合的,许多物种是多态的,在可以调查的蛋白质的很大一部分上。这些关于杂合性和多态性的数据立即开始满足长期以来的需求,这种需求是几十年来建立的复杂模型,对突变率、遗传负荷、中性突变率以及自然选择和遗传漂变在形成变异水平和模式方面的相对作用等主题的数据的需求。Ohta和Kimura是分子进化中性理论的主要理论家,他们(和那个时代的大多数群体遗传学家一样)对理解中性理论如何很好地解释电泳发现的多态性水平有着浓厚的兴趣。他们建立的模型关注的是基因变异的数量和模式,而且它们倾向于明确地包括一个中性的突变率,以及对突变过程本质的假设。中性理论的一个预测是,一个群体中等位基因的数量预计与有效群体规模密切相关。早在1964年,Kimura和James Crow就提出了无限等位基因模型,即每次突变都会产生一个新的等位基因(Kimura & Crow, 1964),在该模型下,中性等位基因的数量随有效种群规模和中性突变率呈线性变化。1973年,Ohta和Kimura的关键思想是一个突变模型,该模型明确地在单个步骤中产生新的等位基因状态,这些等位基因的净蛋白质电荷不同。由于四种氨基酸通常在生理pH值下带电,因此可溶性蛋白质的表面会携带影响其在凝胶电泳中的行为的电荷,而增加或降低这种电荷的突变会增加或减少电泳速率。Ohta和Kimura的模型后来被称为“逐步突变模型”(Kimura & Ohta, 1978),有时也被称为“阶梯模型”,在该模型中,蛋白质可能在+1和x1步中突变为不同的等位基因状态。重要的是,与无限位点模型不同,在该模型下,两种蛋白质在种类上是相同的(即具有相同的净电荷),并且由于具有相同等位基因状态的祖先基因的共同血统而不相同(即通过血统而相同)。Ohta和Kimura是微分方程的虚拟动态二人组,在这篇论文中,和其他许多论文一样,他们采用了扩散方程的方法。他们的主要目标是表达一个群体中等位基因的有效数量。在无限位点模型下,Kimura和Crow证明了ne=1+4Neu (Kimura & Crow, 1964)。但是在逐步模型下,Ohta和Kimura发现ne= ffffffffffffffffffffffffffffffffffi
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Wild populations are smaller than we think: a commentary on 'Effective population size/adult population size ratios in wildlife: a review' by Richard Frankham. Impact of selection on effective population size: a commentary on 'Inbreeding in artificial selection programmes' by Alan Robertson. Hybrid dysgenesis: from darkness into light: a commentary on 'Hybrid dysgenesis in Drosophila melanogaster: rules of inheritance of female sterility' by William R. Engels. A model in two acts: a commentary on 'A model detectable alleles in a finite population' by Timoko Ohta and Motoo Kimura. Estimating the recombination parameter: a commentary on 'Estimating the recombination parameter of a finite population model without selection' by Richard R. Hudson.
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