Models to infer evolution in declining populations and across space

推断人口减少和跨空间进化的模型

• 批准号: RGPIN-2021-03207
• 负责人: Osmond, Matthew
• 金额: $ 2.77万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742435
• 关键词: Models; infer; evolution; declining; populations

Evolution, demography, and genetics interact to form a complex system that determines the fate of populations. Better understanding this complex system (population biology) holds intrinsic value -- e.g., unraveling the evolutionary history of our species -- and guides practical attempts to conserve biodiversity, improve crops, and control pests and pathogens. The long-term vision of my research program is to develop deeper intuition and novel insights about population biology using mathematical models, which are essential for both complex reasoning and inference from vast amounts of data (e.g., thousands of genomes). Within this broader framework of theoretical population biology, this proposal seeks to address two fundamental questions, using a combination of mathematical modelling, computer simulation, and genomic data. 1) How does evolution affect declining populations? We are in the midst of what is perhaps a sixth mass extinction, with many populations in demographic decline. At the same time we are also barraged by pathogens and pests that we attempt to extinguish. How are these demographic declines impacted by evolution? Theory suggests that evolution will have one of two contrasting effects on declining populations: i) increasing genetic drift leading to an extinction vortex and ii) rapid adaptive evolution rescuing populations from extinction. How can we tell which, if either, is acting on natural populations? This proposal outlines two novel methods for inferring how evolution acts in declining populations, both building on recent developments in population genetics. One uses small changes in allele frequencies across the genome to jointly estimate a changing population size and relative strength of adaptation vs drift. The other reconstructs recent demography and selection from genome-wide genealogies. Both promise large advances over current summary statistic approaches. 2) How do populations move and adapt across the landscape? Present-day genetic patterns have been shaped by selection and the geographic movements of ancestors, so how do we extract information about past selection and dispersal from contemporary genomes? The newfound ability to infer gene genealogies at every site in the genome (tree-sequences) for a large number of samples opens up many new ways to approach this problem. This proposal describes four new methods that capitalize on the massive amount of information contained in tree-sequences to infer past selection and dispersal. The first derives the likely locations of genetic ancestors and uses these to deduce large scale geographic histories, such as admixture between glacial refugia. The second extends this method to detect ongoing expansions and contractions of species' ranges. The third jointly estimates selection and dispersal to describe the spatial spread of beneficial alleles. And the fourth aims to reconstruct the evolution of phenotypic clines, such as the latitudinal gradient in human height.

进化、人口统计学和遗传学相互作用，形成了一个决定人口命运的复杂系统。更好地理解这个复杂的系统（种群生物学）具有内在价值-例如，解开我们物种的进化历史--并指导保护生物多样性、改良作物、控制害虫和病原体的实际尝试。我的研究计划的长期愿景是使用数学模型开发关于种群生物学的更深层次的直觉和新颖的见解，这对于复杂的推理和从大量数据中进行推断至关重要（例如，数以千计的基因组）。在这个更广泛的理论种群生物学的框架内，这个建议试图解决两个基本问题，使用数学建模，计算机模拟和基因组数据的组合。1)进化如何影响人口减少？我们正处于可能是第六次大规模灭绝的过程中，许多人口在人口下降。与此同时，我们也受到我们试图消灭的病原体和害虫的袭击。这些人口下降是如何受到进化的影响的？理论表明，进化将对下降的种群产生两种截然不同的影响之一：i）增加遗传漂变导致灭绝漩涡，ii）快速适应性进化拯救种群免于灭绝。我们怎么知道哪一个，如果有的话，是作用于自然种群？该提案概述了两种新的方法来推断进化如何在下降的人口中发挥作用，这两种方法都建立在人口遗传学的最新发展基础上。一种是利用基因组中等位基因频率的微小变化来联合估计不断变化的种群规模和适应与漂移的相对强度。另一个重建了最近的人口统计学和全基因组谱系的选择。这两种方法都比目前的汇总统计方法有很大的进步。2)人口如何在整个景观中移动和适应？今天的遗传模式是由选择和祖先的地理迁移塑造的，那么我们如何从当代基因组中提取关于过去选择和传播的信息呢？新发现的推断大量样本基因组（树状序列）中每个位点基因谱系的能力为解决这个问题开辟了许多新途径。 该提案描述了四种新方法，利用树序列中包含的大量信息来推断过去的选择和扩散。第一种方法得出遗传祖先的可能位置，并利用这些来推断大规模的地理历史，如冰川避难所之间的混合。第二个扩展了这种方法，以检测正在进行的扩张和收缩的物种的范围。第三个联合估计选择和扩散来描述有益等位基因的空间分布。第四个目标是重建表型渐变的进化，例如人类身高的纬度梯度。