Modelling the Population Genetics of Non-Equilibrium Molecular Evolution: Understanding The Forces that Shape The Genome

模拟非平衡分子进化的群体遗传学：了解塑造基因组的力量

• 批准号: RGPIN-2020-06317
• 负责人: deKoning, APJason
• 金额: $ 2.4万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=744255
• 关键词: Modelling; Population; Genetics; Non; Equilibrium

Thanks to transformational technological advances in the past decade, whole genome sequencing has become feasible in many species and populations (e.g., the Vertebrate Genomes Project is sequencing 70,000 vertebrate genomes). Such data resources present next-level opportunities to "read evolution's laboratory notebook", and to make more powerful and richer inferences about patterns of genome sequence variations and their causes, about the natural history of selection, the sequence variations that `work', and about the tree of life itself. However, substantial conceptual and computational challenges impede the full utilization of such data at present. Objectives The overarching aim of our research program is to understand, model, and infer the forces that shaped the evolution of vertebrate genomes. Significant recent effort has been expended in developing models of molecular evolution with an explicit population genetic basis, however, current models make a variety of simplifying assumptions inherited from theoretical population genetics that were popularized largely because they led to convenient mathematics in an era that predates modern computers (e.g., infinite sites and weak mutation). These assumptions may not always be justified in natural populations, and an important direction is thus to unshackle our models from such antiquated assumptions. Scientific Approach In a series of recent papers we demonstrated how general computational approaches for algebraically exact analysis of any Markov chain model in population genetics can be made feasible and highly efficient. These approaches allowed us to make a detailed theoretical analysis of the rate of substitution without classical assumptions, which showed that several predictions of the neutral theory of molecular evolution break down in populations with large but biologically relevant population mutation rates. In this research, we will determine if these predictions hold in natural populations. We will first translate our theoretical developments into models useful for analysing across-species sequence evolution, including time heterogeneity at both phylo- and population-genetic scales. We will use these and other approaches to test two main hypotheses: 1) The rate of substitution disobeys traditional weak-mutation theory when the population mutation rate parameter, theta, is as small as 0.05; and 2) Temporal variation in population size across a phylogeny can induce large-scale phylogenetic artifacts. Impact If validated, the impact of this work may be substantial for studies of molecular and genome evolution, phylogenetics, and in population and evolutionary genetics. In particular, nearly all methods for inferring the strength and direction of natural selection will need modification to apply to populations in vulnerable parameter ranges. We hope that the models developed will advance us along the path towards meaningfully more mechanistic models of molecular evolution.

由于过去十年中的变革性技术进步，全基因组测序在许多物种和种群中已经变得可行（例如，脊椎动物基因组计划正在对70，000个脊椎动物基因组进行测序）。这些数据资源提供了下一个层次的机会，可以“阅读进化的实验室笔记本”，并对基因组序列变异的模式及其原因、选择的自然历史、“起作用”的序列变异以及生命之树本身做出更有力和更丰富的推断。然而，大量的概念和计算挑战阻碍了充分利用这些数据目前。我们的研究计划的首要目标是理解，建模，并推断形成脊椎动物基因组进化的力量。最近的重大努力已经花费在开发具有明确的群体遗传基础的分子进化模型上，然而，当前的模型做出了从理论群体遗传学继承的各种简化假设，这些假设在很大程度上是因为它们在现代计算机之前的时代导致了方便的数学（例如，无限位点和弱突变）。这些假设在自然种群中可能并不总是合理的，因此一个重要的方向是从这些过时的假设中解放我们的模型。科学方法在最近的一系列论文中，我们展示了如何使群体遗传学中任何马尔可夫链模型的代数精确分析的通用计算方法变得可行和高效。这些方法使我们能够在没有经典假设的情况下对取代率进行详细的理论分析，这表明分子进化中性理论的几个预测在具有大但生物相关的群体突变率的群体中失败。在这项研究中，我们将确定这些预测是否适用于自然人群。我们将首先将我们的理论发展转化为有用的模型，用于分析跨物种序列的演变，包括在phylo和种群遗传尺度的时间异质性。我们将使用这些和其他方法来测试两个主要的假设：1）当种群突变率参数θ小到0.05时，取代率不服从传统的弱突变理论; 2）种群大小在一个系统发育中的时间变化可以诱导大规模的系统发育假象。影响如果得到验证，这项工作的影响可能是实质性的分子和基因组进化，遗传学，在人口和进化遗传学的研究。特别是，几乎所有推断自然选择的强度和方向的方法都需要修改，以适用于脆弱参数范围内的种群。我们希望，这些模型将推动我们沿着更有意义的分子进化机制模型的道路前进。