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阈值性状的选择水平。

Levels of selection on threshold characters.

作者信息

Moorad Jacob A, Linksvayer Timothy A

机构信息

Department of Genetics, University of Georgia, Athens, Georgia 30602, USA.

出版信息

Genetics. 2008 Jun;179(2):899-905. doi: 10.1534/genetics.108.086959. Epub 2008 May 27.

Abstract

Threshold models are useful for understanding the evolution of dimorphic traits with polygenic bases. Selection for threshold characters on individuals is expected to be frequency dependent because of the peculiar way that selection views underlying genetic and environmental factors. Selection among individuals is inefficient because individual phenotypes fall into only two discrete categories that map imperfectly to the underlying genes. Incidence, however, can be continuously distributed among groups, making among-group selection relatively more efficient. Differently put, the group-mean phenotype can be a better predictor of an individual's genotype than that individual's own phenotype. Because evolution in group-structured populations is governed by the balance of selection within and between groups, we can expect threshold traits to evolve in fundamentally different ways when group mean fitness is a function of morph frequency. We extend the theory of selection on threshold traits to include group selection using contextual analysis. For the simple case of linear group-fitness functions, we show that the group-level component of selection, like the individual-level component, is frequency dependent. However, the conditions that determine which component dominates when levels of selection are in conflict (as described by Hamilton's rule) are not frequency dependent. Thus, enhanced group selection is not an inherent property of threshold characters. Nevertheless, we show that predicting the effects of multiple levels of selection on dimorphic traits requires special considerations of the threshold model.

摘要

阈值模型有助于理解具有多基因基础的二态性状的进化。由于选择看待潜在遗传和环境因素的特殊方式,对个体阈值性状的选择预期是频率依赖的。个体间的选择效率低下,因为个体表型仅分为两个离散类别,与潜在基因的映射并不完美。然而,发病率在群体间可以连续分布,使得群体间选择相对更有效。换句话说,群体平均表型可能比个体自身表型更能预测个体的基因型。由于群体结构种群中的进化受群体内部和群体之间选择平衡的支配,当群体平均适合度是形态频率的函数时,我们可以预期阈值性状会以根本不同的方式进化。我们使用情境分析将阈值性状的选择理论扩展到包括群体选择。对于线性群体适合度函数的简单情况,我们表明选择的群体水平成分与个体水平成分一样,是频率依赖的。然而,当选择水平发生冲突时(如汉密尔顿法则所述),决定哪个成分占主导的条件并非频率依赖的。因此,增强的群体选择并非阈值性状的固有属性。尽管如此,我们表明预测多层次选择对二态性状的影响需要对阈值模型进行特殊考虑。

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