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

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。这个项目将大大扩展我们研究性状快速进化的能力。性状的快速进化导致了近亲物种之间的巨大差异，比如黑猩猩和人类。基因的使用方式（基因表达）与这些差异有关，但基因表达改变的遗传基础却知之甚少。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。虽然测序技术的进步使我们能够产生这些数据，但我们仍然缺乏分析数据的方法。该项目将创造一种新的分析工具，并将通过研究类人猿的进化来证明其用途，解决诸如大脑进化等长期存在的生物学问题。此外，该项目将支持本科生和硕士生的专业发展，主要是由于民族，种族和性别而被排除的人，从长远来看，提高科学的多样性，严谨性和相关性。具体而言，本项目将完成以下目标：(1)创建TREVA，这是一个统计工具，使用物种之间和物种内部的串联重复序列（TR）变异数据来测试进化假设，特别是识别平衡或定向选择下的TR；(2)将TREVA应用于经验数据，以确定类人猿TR变异对适应的影响；(3)鉴定受选择TRs影响的基因，确定下游生物过程和选择性状。该项目将通过三种机制将教育与研究结合起来。(1)研究将主要由旧金山州立大学（SFSU）的本科生和硕士生进行。(2)本项目将设立计算研究暑期导论课程，支持旧金山外国语大学硕士生指导旧金山外国语大学本科生新手团队学习计算机科学技能，并将其应用于原创性研究项目。(3)进行研究的学生将制作视频摘要，描述他们的工作，这些视频摘要将在全国的科学课上使用，使学生与不同的科学家互动。本项目由行为与认知科学部生物人类学项目共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.