NSF Postdoctoral Fellowship in Biology FY 2021: Understanding the Demographic History of Populations using Identity-by-Descent

2021 财年 NSF 生物学博士后奖学金：使用血统身份了解人口的人口统计历史

• 批准号: 2109515
• 负责人: Jazlyn Mooney
• 金额: $ 13.8万
• 依托单位: Mooney, Jazlyn
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2109515&HistoricalAwards=false
• 关键词: NSF; Postdoctoral; Fellowship; Biology; FY

This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2021, Broadening Participation of Groups Under-represented in Biology. The Fellowship supports a research and training plan for the fellow that will increase the participation of groups underrepresented in biology. This project will expand the fellow’s skills in mathematics and will advance the fellow’s research on understudied population makeup in the field of genomics. The goals of this project are to deliver insights about the historical processes that affect different types of shared genomic segments in the human genome. In particular, this work seeks to deepen knowledge of African American demographic and genetic history in the field of genomics by using mathematical and statistical models. The fellow’s work contributes to increasing the representation of diverse populations in genomics, and addressing imbalances in current genomics data sets. The project will promote the fellow’s activities in teaching, mentoring, and working within the Stanford postdoctoral community.This project will expand upon the fellow’s previous research, while enabling the fellow to develop skills in theoretical population genetics and stochastic simulation. The project will deliver insights about the underlying demographic processes that affect the length distribution of runs of homozygosity (ROH) and identical-by-descent (IBD) segments in the human genome, and it will provide historically relevant information about admixed populations. First, forward-in-time simulations will be used to generate a spectrum of demographic histories to determine the expected length distribution and genomic burden of IBD and ROH. Next, the simulated models will be applied to empirical data to assess model accuracy and to assess possible demographic histories of understudied populations. Lastly, the fellow will use a mechanistic model of admixture to estimate the number of distinct genealogical ancestors from a source population that are required to generate current admixture fractions in an admixed individual. This admixture model will be applied to African American populations to estimate the expected number of African and European individuals that contributed to the genomes of modern admixed individuals. This project will bridge the fields of anthropology, biology, and statistics by using mathematical models to understand how populations evolve over time and to understand the evolutionary forces acting on modern genomes. In addition to academic research, the fellow will continue teaching, cultivating relationships with other underrepresented students in STEM through mentorship, and active participation in diversity efforts at Stanford.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项行动资助了2021财年的NSF生物学博士后研究奖学金，扩大了生物学中代表性不足的群体的参与。该研究金支持研究员的研究和培训计划，以增加在生物学方面代表性不足的群体的参与。该项目将扩大研究员的数学技能，并将推动研究员在基因组学领域对未充分研究的人口构成的研究。该项目的目标是提供有关影响人类基因组中不同类型共享基因组片段的历史过程的见解。特别是，这项工作旨在通过使用数学和统计模型加深对基因组学领域的非裔美国人人口和遗传历史的了解。该研究员的工作有助于增加基因组学中不同人群的代表性，并解决当前基因组学数据集的不平衡问题。该项目将促进该研究员在斯坦福大学博士后社区内的教学、指导和工作活动。该项目将扩展该研究员先前的研究，同时使该研究员能够发展理论群体遗传学和随机模拟方面的技能。该项目将提供有关影响人类基因组中纯合性（ROH）和血统相同（IBD）片段长度分布的潜在人口统计过程的见解，并将提供有关混合人群的历史相关信息。首先，将使用时间向前模拟来生成人口统计学历史谱，以确定IBD和ROH的预期长度分布和基因组负担。接下来，模拟模型将应用于经验数据，以评估模型的准确性，并评估未充分研究的人群可能的人口统计学历史。最后，该研究员将使用混合物的机械模型来估计在混合个体中产生当前混合物分数所需的来自源种群的不同系谱祖先的数量。该混合模型将应用于非裔美国人群体，以估计对现代混合个体的基因组有贡献的非洲和欧洲个体的预期数量。该项目将通过使用数学模型来理解人口如何随着时间的推移而进化，并了解作用于现代基因组的进化力量，从而连接人类学，生物学和统计学领域。除了学术研究，该研究员将继续教学，通过指导培养与其他在STEM领域代表性不足的学生的关系，并积极参与斯坦福大学的多样性工作。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响力审查标准进行评估，被认为值得支持。