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Λ-不对称 Moran 模型的祖先选择图。

The ancestral selection graph for a Λ-asymmetric Moran model.

机构信息

Instituto de Matematicas, Universidad Nacional Autonoma de Mexico (UNAM), Cuernavaca, Mexico; Department of Statistics, University of California at Berkeley, United States of America.

Institut für Mathematik, Johann Wolfgang Goethe-Universität, 60325 Frankfurt am Main, Germany.

出版信息

Theor Popul Biol. 2024 Oct;159:91-107. doi: 10.1016/j.tpb.2024.02.010. Epub 2024 Mar 13.

Abstract

Motivated by the question of the impact of selective advantage in populations with skewed reproduction mechanisms, we study a Moran model with selection. We assume that there are two types of individuals, where the reproductive success of one type is larger than the other. The higher reproductive success may stem from either more frequent reproduction, or from larger numbers of offspring, and is encoded in a measure Λ for each of the two types. Λ-reproduction here means that a whole fraction of the population is replaced at a reproductive event. Our approach consists of constructing a Λ-asymmetric Moran model in which individuals of the two populations compete, rather than considering a Moran model for each population. Provided the measure are ordered stochastically, we can couple them. This allows us to construct the central object of this paper, the Λ-asymmetric ancestral selection graph, leading to a pathwise duality of the forward in time Λ-asymmetric Moran model with its ancestral process. We apply the ancestral selection graph in order to obtain scaling limits of the forward and backward processes, and note that the frequency process converges to the solution of an SDE with discontinuous paths. Finally, we derive a Griffiths representation for the generator of the SDE and use it to find a semi-explicit formula for the probability of fixation of the less beneficial of the two types.

摘要

受到具有偏态繁殖机制的群体中选择优势影响的问题的启发,我们研究了具有选择的 Moran 模型。我们假设存在两种类型的个体,其中一种类型的繁殖成功率大于另一种类型。较高的繁殖成功率可能源于更频繁的繁殖,也可能源于更多的后代,并且用两个类型中的每一个的一个度量 Λ 来编码。这里的 Λ-繁殖意味着在繁殖事件中整个种群的一部分被替换。我们的方法包括构建一个 Λ-不对称 Moran 模型,其中两个种群的个体相互竞争,而不是为每个种群考虑 Moran 模型。如果度量是随机排序的,我们可以将它们耦合起来。这使我们能够构建本文的中心对象,即 Λ-不对称祖先选择图,从而导致随时间向前的 Λ-不对称 Moran 模型与其祖先过程之间的路径对偶性。我们应用祖先选择图来获得向前和向后过程的缩放极限,并注意到频率过程收敛到具有不连续路径的 SDE 的解。最后,我们为 SDE 的生成器推导出 Griffiths 表示,并使用它找到两种类型中较不利类型的固定概率的半显式公式。

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