CAREER: Identifying the Role of Tandem Repeats in Great Ape Adaptation through Undergraduate Team Research Using a Novel Statistical Framework

职业：通过本科团队研究使用新颖的统计框架确定串联重复在类人猿适应中的作用

• 批准号: 2144878
• 负责人: Rorianne Rohlfs
• 金额: $ 81.13万
• 依托单位: San Francisco State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2144878&HistoricalAwards=false
• 关键词: CAREER; Identifying; Role; Tandem; Repeats

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This project will substantially expand our ability to study rapid trait evolution. Rapid trait evolution results in dramatic differences between closely related species, such as chimpanzees and humans. The way genes are used (gene expression) has been implicated in such differences, but the genetic basis for altered gene expression is poorly understood. Until recently, because of limits in DNA sequencing techniques, a major source of genetic variation (tandem repeats) has been difficult to study. While sequencing technology has advanced so that we can produce these data, we still lack a way to analyze it. This project will create a new analysis tool and will demonstrate its use by studying great ape evolution, addressing longstanding biological problems such brain evolution. Further, this project will support the professional development of undergraduate and masters student scientists, mostly persons excluded due to ethnicity, race, and gender, improving the diversity, rigor, and relevance of science in the long term. Specifically, this project will complete the following objectives: (1) create TREVA, a statistical tool that uses tandem repeat (TR) variation data between and within species to test evolutionary hypotheses, in particular to identify TRs under balancing or directional selection; (2) apply TREVA to empirical data to determine how TR variation underlies adaptation in great apes; (3) identify genes impacted by TRs under selection and determine the downstream biological processes and traits under selection. This project will integrate education into research using three mechanisms. (1) The research will primarily be carried out by San Francisco State University (SFSU) undergraduates and master’s students. (2) The project will create the Computational Research Introductory Summer Program where SFSU masters students will be supported to mentor teams of novice SFSU undergraduates to learn computer science skills and apply them to original research projects. (3) Students performing the research will create video abstracts describing their work, which will be used in science classes nationally to engage students with diverse scientists.This project is co-funded by the Biological Anthropology program in the Division of Behavioral and Cognitive Sciences.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.

该奖项全部或部分由2021年美国救援计划法案（公法117-2）资助。该项目将大大扩展我们研究快速性状进化的能力。快速的性状进化导致了密切相关的物种之间的巨大差异，如黑猩猩和人类。基因的使用方式（基因表达）与这些差异有关，但对基因表达改变的遗传基础知之甚少。直到最近，由于DNA测序技术的限制，遗传变异的主要来源（串联重复序列）一直难以研究。虽然测序技术已经发展到我们可以产生这些数据，但我们仍然缺乏分析它的方法。该项目将创建一种新的分析工具，并将通过研究类人猿进化来展示其用途，解决长期存在的生物学问题，如大脑进化。此外，该项目将支持本科生和硕士生科学家的专业发展，主要是由于种族，种族和性别而被排除在外的人，长期改善科学的多样性，严谨性和相关性。 具体而言，该项目将完成以下目标：（1）创建TREVA，这是一种统计工具，使用物种之间和物种内的串联重复序列（TR）变异数据来检验进化假设，特别是确定平衡或定向选择下的TR;（2）将TREVA应用于经验数据，以确定TR变异如何成为类人猿适应的基础;（3）鉴定受选择中TR影响的基因，并确定选择中的下游生物学过程和性状。该项目将利用三种机制将教育纳入研究。(1)这项研究将主要由旧金山弗朗西斯科州立大学（SFSU）的本科生和硕士生进行。(2)该项目将创建计算研究入门暑期课程，SFSU硕士生将获得支持，指导SFSU本科生新手团队学习计算机科学技能并将其应用于原创研究项目。(3)进行研究的学生将创建描述他们工作的视频摘要，该项目将在全国范围内的科学课程中使用，让学生与不同的科学家接触。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查进行评估，被认为值得支持的搜索.