Models to infer evolution in declining populations and across space

进化、人口学和遗传学相互作用，形成了一个复杂的系统，决定了种群的命运。更好地理解这一复杂系统(种群生物学)具有内在价值--例如，揭开我们物种的进化史--并指导保护生物多样性、改良作物以及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(例如，数千个基因组)进行推断都是必不可少的。在这一更广泛的理论种群生物学框架内，这项建议试图结合数学建模、计算机模拟和基因组数据来解决两个基本问题。1)进化对人口减少有何影响？我们正处于可能是第六次大规模灭绝的过程中，许多人口处于人口下降的状态。与此同时，我们也被我们试图消灭的病原体和害虫所包围。这些人口数量的下降是如何受到进化的影响的？理论表明，进化将对衰落的种群产生两种截然不同的影响之一：i)不断增加的遗传漂移导致灭绝漩涡；ii)快速适应性进化将种群从灭绝中拯救出来。我们怎么知道哪一个在对自然人口起作用呢？这项建议概述了两种新的方法来推断进化如何在种群减少中发挥作用，这两种方法都建立在种群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学和从全基因组谱系中进行的选择。这两种方法都承诺比目前的汇总统计方法有很大进步。2)人口如何在这片土地上迁徙和适应？今天的遗传模式是由选择和祖先的地理运动塑造的，那么我们如何从当代基因组中提取关于过去选择和扩散的信息？新发现的为大量样本推断基因组(树序列)中每个位置的基因谱系的能力开辟了许多新的方法来解决这个问题。这项建议描述了四种新的方法，它们利用树序列中包含的大量信息来推断过去的选择和扩散。第一种方法推导出基因祖先的可能位置，并利用这些位置来推断大规模的地理历史，例如冰川避难所之间的混合。第二种方法将该方法扩展到检测物种范围的持续扩展和收缩。第三种是联合估计选择和扩散来描述有利等位基因的空间分布。第四个目标是重建表型跃层的演化，例如人类身高的纬度梯度。

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.