From microevolutionary processes to macroevolutionary patterns: modelling long-term evolution driven by ecological adaptation

从微观进化过程到宏观进化模式：模拟生态适应驱动的长期进化

• 批准号: RGPIN-2018-04287
• 负责人: Doebeli, Michael
• 金额: $ 6.92万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=692544
• 关键词: microevolutionary; processes; macroevolutionary; patterns; modelling

Long-term patterns of evolution have captured the imagination of biologists for centuries, and understanding the “tree of life” is a fundamental problem in science. Macroevolutionary patterns such as stasis and adaptive radiations have been extensively analyzed, and it is generally thought that ecological adaptations play an important role for long-term evolution. However, ecological explanations for macroevolutionary patters are still mostly based on verbal theories. Macroevolutionary patterns ultimately result from microevolutionary processes. With the research proposed here, I intend to develop a mathematical theory for macroevolutionary dynamics and phylogenetic analysis that is derived from ecological birth-death processes. I propose to use this theory as a testing ground for existing comparative phylogenetic methods. Finally, I propose to apply novel computational tools to study macroevolution of ecologically important traits on large phylogenetic trees. Specifically: 1) I propose to use adaptive dynamics models incorporating diversification and extinction to classify salient patterns of macroevolutionary dynamics generated by different types of ecological interactions, for varying dimensions of phenotype space, and for different assumptions about the biogeography of the evolving communities. This will yield a general classification of the types of macroevolutionary patterns generated by mechanistic models for long-term evolution. In particular, it will enable a critical evaluation of salient verbal theories for macroevolution. 2) The adaptive dynamics models yield artificial phylogenetic trees that I propose to analyze using a variety of comparative phylogenetic methods in order to test which of these can best explain the phylogenies. This will allow for a comparison of inferences made from comparative methods with the actual ecological processes that generated the phylogenies. This work will also give important insights into the statistical properties of mechanistic models for macroevolution. 3) Microorganisms have shaped the chemistry of Earth's ecosystems, and determining the macroevolutionary patterns of metabolic functions in the prokaryotic tree of life is an important problem. Prokaryotic phylogenies can be extremely large, and their analysis requires novel computational tools. I propose to apply such tools to the problem of the evolution of protein superfamilies along the microbial tree of life.

几个世纪以来，长期的进化模式吸引了生物学家的想象，理解“生命之树”是科学中的一个基本问题。宏观进化模式（如暂停和适应性辐射）已经进行了广泛的分析，人们普遍认为生态适应性对长期进化起着重要作用。但是，宏观进化模式的生态解释仍然主要基于言语理论。宏观进化模式最终是由微进化过程引起的。通过此处提出的研究，我打算开发一种数学理论，用于宏观进化动力学和系统发育分析，该理论是从生态出生死亡过程中得出的。我建议将该理论用作现有比较系统发育方法的测试基础。最后，我建议应用新颖的计算工具来研究大型系统发育树上生态重要特征的宏观进化。具体来说：1）我建议使用结合多元化和扩展的自适应动力学模型，以分类由不同类型的生态相互作用产生的宏观进化动力学的显着模式，用于表型空间的不同维度，以及关于发展社区的生物地理学的不同假设。这将产生由机械模型产生的长期演化产生的宏观进化模式类型的一般分类。特别是，它将能够对宏观进化的显着言语理论进行批判性评估。 2）自适应动力学模型产生了人工系统发育树，我建议使用各种比较系统发育方法来分析，以测试其中哪种可以最好地解释系统发育。这将使比较方法的推论与产生系统发育的实际生态过程进行比较。这项工作还将为机械模型的统计特性提供重要的见解。3）微生物已经塑造了地球生态系统的化学，并确定生命原核生性树中代谢功能的宏观进化模式是重要的问题。核系统发育可能非常大，它们的分析需要新颖的计算工具。我建议将这种工具应用于蛋白质超家族在微生物生命树上的进化问题。