Clade size distribution under neutral evolutionary models

IF 1.2 4区 生物学 Q4 ECOLOGY Theoretical Population Biology Pub Date : 2024-02-15 DOI:10.1016/j.tpb.2024.02.004
Antonio Di Nunzio, Filippo Disanto
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Abstract

Given a labeled tree topology t, consider a population P of k leaves chosen among those of t. The clade of P is the minimal subtree of t containing P and its size is given by the number of leaves in the clade. When t is selected under the Yule or uniform distribution among the labeled topologies of size n, we study the “clade size” random variable determining closed formulas for its probability mass function, its mean, and its variance. Our calculations show that for large n the clade size tends to be smaller under the uniform model than under the Yule model, with a larger variability in the first scenario for values of k5. We apply our probability formulas to investigate set-theoretic relationships between the clades of two populations in a random tree, determining how likely one clade is contained in or it is equal to the other. Our study relates to earlier calculations for the probability that under the Yule model the clade size of P equals the size of P – that is, the population P forms a monophyletic group – and extends known results for the probability that the minimal (non-trivial) clade containing a random taxon has a given size.

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中性进化模型下的支系规模分布
P 的支系是包含 P 的 t 的最小子树,其大小由支系中叶子的数量决定。当 t 是根据 Yule 分布或均匀分布从大小为 n 的标注拓扑中选出时,我们研究了 "支系大小 "随机变量,并确定了其概率质量函数、均值和方差的封闭公式。我们的计算表明,对于大 n,统一模型下的支系大小往往小于尤勒模型下的支系大小,而对于 k≥5 的值,第一种情况下的变异性更大。我们应用我们的概率公式来研究随机树中两个种群的支系之间的集合论关系,确定一个支系包含在另一个支系中或与另一个支系相等的可能性有多大。我们的研究与早先计算的 Yule 模型下 P 的支系大小等于 P 的大小(即种群 P 形成一个单系群)的概率有关,并扩展了包含随机类群的最小(非三系)支系具有给定大小的概率的已知结果。
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来源期刊
Theoretical Population Biology
Theoretical Population Biology 生物-进化生物学
CiteScore
2.50
自引率
14.30%
发文量
43
审稿时长
6-12 weeks
期刊介绍: An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena. Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.
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