Evolutionary Dynamics and Diversity in High Dimensions

广泛的DNA测序揭示了物种内巨大的遗传多样性，包括自然界中单个细菌物种的本地种群的精细多样性，以及实验室中从单个克隆进化而来的种群。然而，由于突变、重组、选择、随机波动和空间扩散等进化过程，以及各亚型与变化的环境之间的生态相互作用，这种多样性的原因和统计特性还远未被理解。生物和环境的复杂性决定了生态进化动力学发生在高维空间。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，这些方面会产生。这将通过开发和分析简单的模型，一些实际过程的粗略近似值和其他试图利用高维方面提取一般特征的抽象漫画来完成。实验室实验和来自天然微生物群落的数据，其中一些PI已经并将继续参与，将激励一些建模和预测将与测序和其他数据进行比较。关于基因搭便车对基因组其他地方选择的统计结果的理论，有可能使更好地利用人类遗传多样性数据来推断人类种群的进化史和其他方面。教育方面的影响包括将生物学和定量科学结合起来的课程和课程的发展，以及对女学生和博士后的培训。对各种多样性来源之间的相互作用及其可观察结果的更好理论将促进对微生物短期进化的定性和定量理解。该项目将集中于确定遗传多样性的统计特性，当表型差异非常细微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史和生态学的情景。这将能够更有效地利用DNA测序数据，并激励哪些类型的数据将为未来的研究提供最多的信息。同样，它将有助于激发哪些结合了进化和生态方面的实验室实验可能对这些复杂的过程提供最大的启示。建模和分析将涉及发展一些新的统计动力学和渐近方法，以及探索粗糙漫画模型探索情景和发展直觉的潜力。

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.