Adapting Biosystems

适应生物系统

• 批准号: CRC-2021-00052
• 负责人: Pennell, Matthew
• 金额: $ 1.51万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 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=755734
• 关键词: Adapting; Biosystems

A major goal of my research is to understand the processes that generate diversity in the number of lineages. This is a primary challenge in the field of macroevolution, where I got my start in research; we are only beginning to be able to explain why some branches of the Tree of Life are so much more diverse than others. I have previously identified some fundamental regularities in the processes that shape biodiversity across disparate groups of organisms and across disparate time scales; in my research group, we are looking to understand the evolutionary and ecological mechanisms that might explain these regularities. I have also identified some fundamental limits to how much scientists can learn about the processes that generate biodiversity from molecular data alone and have shown that in some cases, researchers may have been pushing these limits. In the next phase of my research, I aim to extend our previous insights and quantify hard bounds on what information we can extract from molecular datasets regarding several other evolutionary phenomena that are of broad interest to researchers. This work will help us determine exactly what we can hope to learn (and exactly what we cannot), to develop novel strategies for making the most of available data, and to identify inferences for which will require additional types of data. These results are also relevant to the study of disease dynamics. The fact that for rapidly evolving pathogens, such SARS-CoV2, genetic diversity accumulates on the time-scale of epidemics, means we can potentially estimate epidemiological parameters such as R0 using molecular phylogenies. As the tools used to study viral lineage diversity are very similar to those used to study organismal diversity, I am extending our macroevolutionary work to quantify the information content of viral phylogenies. This will provide a better measure of our confidence in epidemiological inferences. Alongside this work, I am developing novel approaches for better integrating molecular data with more conventional case count data so that these different types of information can reciprocally inform one another. I also plan to use macroevolutionary tools to reconstruct the diversification of B-cell (antibody) sequences. Working with immunologists, I am developing new statistical techniques for measuring the evolution of an individuals B-cell repertoire as well as precisely defining what we can and cannot learn from purely sequence-based approaches.

我研究的一个主要目标是了解产生谱系数量多样性的过程。这是宏观进化领域的主要挑战，我也是从宏观进化开始研究的；我们才刚刚开始能够解释为什么生命之树的一些分支比其他分支更加多样化。我以前已经确定了在不同的生物群体和不同的时间尺度上形成生物多样性的过程中的一些基本规律；在我的研究小组中，我们正在寻求理解可能解释这些规律的进化和生态机制。我还指出了一些基本的限制，即科学家只能从分子数据中了解产生生物多样性的过程，并表明在某些情况下，研究人员可能已经突破了这些限制。在我研究的下一阶段，我的目标是扩展我们以前的见解，并量化我们可以从分子数据集中提取的信息的硬性界限，这些信息涉及研究人员广泛感兴趣的其他几个进化现象。这项工作将帮助我们准确地确定我们希望学到什么（以及我们不能学到什么），制定新的策略来充分利用现有数据，并确定需要额外类型数据的推论。这些结果也与疾病动力学的研究有关。对于快速进化的病原体，如SARS-CoV2，遗传多样性在流行病的时间尺度上积累，这意味着我们可以利用分子系统发育来估计R0等流行病学参数。由于用于研究病毒谱系多样性的工具与用于研究生物多样性的工具非常相似，我正在扩展我们的宏观进化工作，以量化病毒系统发育的信息内容。这将更好地衡量我们对流行病学推断的信心。除了这项工作，我正在开发新的方法来更好地整合分子数据与更传统的病例计数数据，使这些不同类型的信息可以相互通知。我还计划使用宏观进化工具来重建b细胞（抗体）序列的多样化。与免疫学家合作，我正在开发新的统计技术来测量单个b细胞库的进化，以及精确地定义我们可以从纯粹的基于序列的方法中学到什么和不能学到什么。