Evolutionary Dynamics and Diversity in High Dimensions

高维的进化动力学和多样性

• 批准号: 1607606
• 负责人: Daniel Fisher
• 金额: $ 90万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-15 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1607606&HistoricalAwards=false
• 关键词: Evolutionary; Dynamics; Diversity; Dimensions

Extensive DNA sequencing has revealed a tremendous amount of genetic diversity within species, including fine-scale diversity within local populations of single bacterial species in nature, as well as in populations evolved from a single clone in the laboratory. Yet the causes and statistical properties of this diversity are far from understood, with the evolutionary processes of mutation, recombination, selection, stochastic fluctuations, and spatial dispersal all playing roles, as well as the ecological interactions between subtypes and changing environments. The complexities of the organisms and environments mean that the eco-evo dynamics takes place in high-dimensional space. The primary goal of this project is to study various aspects of the evolutionary and ecological dynamics focussing on the statistical properties of the diversity, including aspects not previously studied, that these give rise to. This will be done by developing and analyzing simple models, some rough approximations of the actual processes and others abstract caricatures that endeavor to make use of the high-dimensional aspects to extract general features. Laboratory experiments and data from natural microbial communities, some of which the PI has been and will continue to be involved with, will motivate some of the modeling and the predictions will be compared with sequencing and other data. The theory to be developed on the statistical consequences of genetic hitchhiking on selection elsewhere in the genome has the potential to enable better use of human genetic diversity data to infer evolutionary history, and other aspects, of human populations. The educational impacts include development of courses and curricula bringing together biology and the quantitative sciences as well as training of women students and postdocs. Better theory on the interplay between various sources of diversity and their observable consequences will advance both qualitative and quantitative understanding of short term microbial evolution. The project will focus on identifying statistical properties of genetic diversity that can most effectively distinguish between scenarios for evolutionary history and ecology when the phenotypic differences are subtle enough that they cannot be readily observed. This will enable more effective use of DNA sequencing data and motivate which types of data would be most informative for future studies. Likewise, it will will help motivate which laboratory experiments that combine evolutionary and ecological aspects experiments might shed most light on these complex processes. The modeling and analysis will involve developing some new statistical dynamical and asymptotic methods, as well as exploring the potential of crude caricature models to explore scenarios and develop intuition.

广泛的 DNA 测序揭示了物种内大量的遗传多样性，包括自然界中单一细菌物种的局部种群内的精细多样性，以及从实验室中的单个克隆进化而来的种群。然而，这种多样性的原因和统计特性尚不清楚，突变、重组、选择、随机波动和空间分散的进化过程以及亚型和不断变化的环境之间的生态相互作用都在发挥作用。生物体和环境的复杂性意味着生态进化动力学发生在高维空间中。该项目的主要目标是研究进化和生态动力学的各个方面，重点关注多样性的统计特性，包括以前未研究过的方面。这将通过开发和分析简单模型、实际过程的一些粗略近似以及其他抽象漫画来完成，这些模型致力于利用高维方面来提取一般特征。实验室实验和来自自然微生物群落的数据（其中一些 PI 已经并将继续参与）将激发一些建模，并且预测将与测序和其他数据进行比较。根据遗传搭便车对基因组其他部分选择的统计后果而开发的理论有可能更好地利用人类遗传多样性数据来推断人类群体的进化历史和其他方面。教育影响包括开发将生物学和定量科学结合在一起的课程和课程，以及对女学生和博士后的培训。关于各种多样性来源及其可观察后果之间相互作用的更好理论将促进对短期微生物进化的定性和定量理解。该项目将侧重于确定遗传多样性的统计特性，当表型差异足够微妙以至于无法轻易观察到时，这些特性可以最有效地区分进化历史和生态学的情景。这将使 DNA 测序数据的使用更加有效，并激发哪些类型的数据对未来的研究最有帮助。同样，它将有助于激发将进化和生态方面的实验结合起来的实验室实验可能最能阐明这些复杂的过程。建模和分析将涉及开发一些新的统计动力学和渐近方法，以及探索原始漫画模型探索场景和发展直觉的潜力。