NSF Postdoctoral Fellowship in Biology FY 2013

2013 财年 NSF 生物学博士后奖学金

• 批准号: 1308885
• 负责人: Jamie Oaks
• 金额: $ 20.7万
• 依托单位: Oaks Jamie R
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1308885&HistoricalAwards=false
• 关键词: NSF; Postdoctoral; Fellowship; Biology; FY

Developing novel methods for testing models of shared evolutionary historyUnderstanding the processes that generate biodiversity is a fundamental goal of biology. To achieve this goal, it will be critical to account for mechanisms that influence the evolution of entire communities of co-occurring species, such as changes to the environment. The advancement of next-generation sequencing (NGS) technology provides opportunities to examine evolutionary history in unprecedented detail using genome-wide data from multiple species. However, there are currently no methods for analyzing NGS data in a comparative framework to test hypotheses about shared evolutionary history. The goal of this project is to develop Bayesian statistical models that can utilize NGS data for estimating the temporal pattern of speciation events across co-distributed taxa. These novel methods will be applied to NGS data from species across West-Central Africa to infer the effect of past aridifi cation cycles on the diversifi cation ofAfro-tropical rainforest fauna.Broader impacts include the development of novel computational tools made freely available as open-source software. These tools will be of general interest across multiple disciplines, including biodiversity science and evolutionary medicine, by providing statistical approaches to estimate models of co-diversifi cation across landscapes and co-evolutionary dynamics between host taxa and their associated microbiomes. The former is critical for understanding global biodiversity, and the latter is important for understanding the evolutionary history and assembly of host-associated microbiota, including pathogens. Training objectives include mastering the mathematical, computational, and bioinformatic skills necessary for advancing research at the nexus of mathematics, statistics, and biology. This project will also use an evidence-based approach to develop classroom strategies for improving undergraduate education in the foundational concepts of evolution and the scienti fic method. This project will follow the principles of Open Notebook Science; all progress will be recorded in real time via version-control software and made publicly available on the Internet.

开发新的方法来测试共同进化历史的模型理解产生生物多样性的过程是生物学的一个基本目标。为了实现这一目标，解释影响整个共生物种群落进化的机制，如环境变化，将是至关重要的。下一代测序（NGS）技术的进步提供了使用来自多个物种的全基因组数据以前所未有的细节检查进化史的机会。然而，目前还没有在比较框架中分析NGS数据的方法来检验关于共同进化史的假设。本项目的目标是建立贝叶斯统计模型，利用NGS数据估计共分布分类群中物种形成事件的时间模式。这些新方法将应用于来自西非和中非物种的NGS数据，以推断过去干旱化周期对非洲热带雨林动物多样性的影响。更广泛的影响包括以开源软件的形式免费提供的新型计算工具的发展。这些工具将在包括生物多样性科学和进化医学在内的多个学科中引起普遍的兴趣，通过提供统计方法来估计宿主分类群及其相关微生物群之间的景观共同多样性模型和共同进化动态。前者对于理解全球生物多样性至关重要，后者对于理解宿主相关微生物群（包括病原体）的进化史和组装至关重要。培训目标包括掌握数学、计算和生物信息学技能，这些技能是推进数学、统计学和生物学研究所必需的。该项目还将采用循证方法来制定课堂策略，以改善进化论基本概念和科学方法的本科教育。本项目将遵循Open Notebook Science的原则；所有的进展都将通过版本控制软件实时记录下来，并在互联网上公开。