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

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。该项目将极大地扩展我们研究快速性状进化的能力。快速的特征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)与这种差异有关，但基因表达改变的遗传基础却鲜为人知。直到最近，由于DNA测序技术的限制，遗传变异的一个主要来源(串联重复序列)一直很难研究。虽然测序技术已经进步，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，解决大脑进化等长期存在的生物学问题来展示其用途。此外，该项目将支持本科生和硕士生科学家的专业发展，他们大多是因种族、种族和性别而被排除在外的人，从长远来看，提高科学的多样性、严谨性和相关性。具体地说，这个项目将完成以下目标：(1)创建Treva，这是一个使用物种之间和物种内的串联重复(TR)变异数据来测试进化假说的统计工具，特别是在平衡或定向选择下确定TR的进化假说；(2)将Treva应用于经验数据，以确定大猩猩的TRR变异如何构成适应的基础；(3)确定被选择的TRs影响的基因，并确定被选择的下游生物过程和特征。该项目将使用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)的本科生和硕士研究生进行。(2)该项目将创建计算研究入门暑期项目，在该项目中，SFSU硕士学生将得到支持，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)进行这项研究的学生将制作描述他们工作的视频摘要，并将在全国范围内的科学课堂上使用，让学生与不同的科学家接触。该项目由行为和认知科学部门的生物人类学项目共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.