Reading tree leaves: inferring speciation anfd extinction processes using phylogenies.

IF 4.7 2区 生物学 Q1 BIOLOGY Philosophical Transactions of the Royal Society B: Biological Sciences Pub Date : 2025-02-13 Epub Date: 2025-02-20 DOI:10.1098/rstb.2023.0309
Bruce Rannala, Ziheng Yang
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Abstract

The birth-death process (BDP) is widely used in evolutionary biology as a model for generating phylogenetic trees of species. The generalized birth-death process (GBDP) allows rate variation over time, with speciation and extinction rates to be arbitrary functions of time. Here we review the probability theory underpinning the GBDP as a model of cladogenesis and recent findings concerning its identifiability. The GBDP with arbitrary continuous rate functions has been shown to be non-identifiable from lineage-through-time data: even with species phylogenies of infinite size the parameters cannot be estimated. However, a restricted class of BDPs with piecewise-constant rates has been shown to be identifiable. We review and illustrate these results using simple examples and discuss their implications for biologists interested in inferring the past tempo and mode of evolution using reconstructed phylogenetic trees.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

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解读树叶:用系统发生学推断物种形成和灭绝过程。
在进化生物学中,生-死过程被广泛用于生成物种系统发育树的模型。广义出生-死亡过程(GBDP)允许速率随时间变化,物种形成和灭绝速率是时间的任意函数。在这里,我们回顾了作为分支发生模型的GBDP的概率论和最近关于其可识别性的发现。具有任意连续速率函数的GBDP已被证明是无法从谱系-时间数据中识别的:即使具有无限大小的物种系统发育,参数也无法估计。然而,具有分段恒定速率的一类有限的bdp已被证明是可识别的。我们用简单的例子来回顾和说明这些结果,并讨论它们对利用重建的系统发育树来推断过去的进化速度和模式的生物学家的意义。这篇文章是主题“进化的数学理论”的一部分:追溯到100年前的系统发育模型。
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来源期刊
CiteScore
11.80
自引率
1.60%
发文量
365
审稿时长
3 months
期刊介绍: The journal publishes topics across the life sciences. As long as the core subject lies within the biological sciences, some issues may also include content crossing into other areas such as the physical sciences, social sciences, biophysics, policy, economics etc. Issues generally sit within four broad areas (although many issues sit across these areas): Organismal, environmental and evolutionary biology Neuroscience and cognition Cellular, molecular and developmental biology Health and disease.
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