Multilevel selection 2: Estimating the genetic parameters determining inheritance and response to selection
Multilevel selection 2: Estimating the genetic parameters determining inheritance and response to selection
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DOI：
10.1534/genetics.106.062729
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发表时间：
2007-01-01
期刊：
影响因子：
3.3
通讯作者：
Van Arendonk, Johan A. M.
中科院分区：
文献类型：
--
作者：
Bijma, Piter;Muir, William M.;Van Arendonk, Johan A. M.
个体之间的相互作用是普遍的，无论是在动物和植物中，在自然和家庭人口中都是如此。通过自然选择或人工选择来理解这些相互作用对种群进化的影响，需要了解它们背后的可遗传成分。在这里，我们提出了一种统计方法来估计遗传参数，这些遗传参数决定了一般群体中个体之间相互作用影响的多水平性状选择的反应。我们应用这些方法来获得由于啄食行为导致高死亡率的蛋鸡群体中生存天数的遗传参数的估计。我们发现，可遗传变异比经典分析获得的遗传变异大三倍，这意味着由于社会相互作用，三分之二的完整可遗传变异对经典分析是隐藏的。因此，对适用于这一群体的多水平选择的预测反应比经典预测大三倍。这项工作与本期随附的一篇文章中提出的响应多级选择的数量遗传理论相结合，使选择方案的设计能够有效地减少牲畜和植物中的竞争交互作用，并能够预测社会交互对经历多级选择的自然种群进化的影响。
Interactions among individuals are universal, both in animals and in plants and in natural as well as domestic populations. Understanding the consequences of these interactions for the evolution of populations by either natural or artificial selection requires knowledge of the heritable components underlying them. Here we present statistical methodology to estimate the genetic parameters determining response to multilevel selection of traits affected by interactions among individuals in general populations. We apply these methods to obtain estimates of genetic parameters for survival, days in a population of layer chickens with high mortality due to pecking behavior. We find that heritable variation is threefold greater than that obtained from classical analyses, meaning that two-thirds of the full heritable variation is hidden to classical analysis due to social interactions. As a consequence, predicted responses to multilevel selection applied to this population are threefold greater than classical predictions. This work, combined with the quantitative genetic theory for response to multilevel selection presented in an accompanying article in this issue, enables the design of selection programs to effectively reduce competitive interactions in livestock and plants and the prediction of the effects of social interactions on evolution in natural populations undergoing multilevel selection.