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.

该奖项是根据2021年《美国救援计划法》的全部或部分资助的（公共法117-2）。该项目将大大扩展我们研究快速特质进化的能力。快速特征的演化导致紧密相关的物种（例如黑猩猩和人类）之间存在巨大差异。使用基因的方式（基因表达）已在这种差异中暗示，但是基因表达改变的遗传基础是很差的。直到最近，由于DNA测序技术的局限性，很难研究遗传变异（串联重复）的主要来源。在测序技术已经进步以便我们可以生成这些数据的同时，我们仍然缺乏分析数据的方法。该项目将创建一个新的分析工具，并通过研究伟大的猿类进化来证明其使用，从而解决了大脑进化等长期存在的生物学问题。此外，该项目将支持本科和硕士学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，从而改善了长期科学的多样性，严格和相关性。具体而言，该项目将完成以下目标：（1）创建Treva，一种统计工具，该工具使用串联重复（TR）变化数据在物种之间和内部进行进化假设，尤其是为了识别平衡或方向选择下的TR； （2）将treva应用于经验数据，以确定TR变异是如何在大猿中适应的基础； （3）确定在选择下受到TR的影响的基因，并确定下游的生物学过程和所选择的特征。该项目将使用三种机制将教育纳入研究。 （1）这项研究将由旧金山州立大学（SFSU）本科生和硕士学生进行。 （2）该项目将创建计算研究介绍性夏季计划，其中SFSU硕士学生将受到新颖SFSU本科生的指导团队的支持，以学习计算机科学技能并将其应用于原始研究项目。 （3）进行研究的学生将创建描述其工作的视频摘要，该摘要将在全国范围内与我们的科学家吸引学生。该项目由生物人类学计划共同资助了行为和认知科学的部门，该奖项反映了NSF的法定任务，并通过评估了基金会的智力效果，并诚实地对其进行了评估。