CAGEE: Computational analysis of gene expression evolution

CAGEE：基因表达进化的计算分析

• 批准号: 2146866
• 负责人: Matthew Hahn
• 金额: $ 89.25万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2146866&HistoricalAwards=false
• 关键词: CAGEE; Computational; analysis; gene; expression

Biological advances have revealed that many traits are controlled by the amount of a gene produced in each cell, not just the sequence of each gene and protein. Genes can differ in these expression levels between different tissues within the same organism or between species in the same tissue. Understanding how these levels change—and how they control the appearance and function of organisms—is a key challenge for current research. This project will develop new methods for understanding gene expression changes between tissues and species, as well as how these changes are coordinated. The research applies new statistical approaches to produce open-source software for carrying out the analyses. The software will allow all scientists to be able to use these new tools on multiple platforms, contributing to the national cyberinfrastructure. This work also will improve and accelerate research with multiple societal benefits, including enabling new biological discoveries. This project will support the training of a postdoctoral researcher, graduate students, and undergraduates from groups that are underrepresented in science and technology careers. A classroom lesson plan and computer lab on understanding evolutionary trees will be developed and distributed to partner institutions.Changes in gene expression have been shown to be responsible for many differences between species, and recent technological advances mean that such data are easy to collect, even in non-model organisms. By measuring expression levels of the same gene in multiple species, we can begin to understand the history of changes in gene expression across organisms. By measuring expression in thousands of genes, we can further understand the mechanisms and modes by which gene expression evolves. This research develops a new software package (CAGEE) for studying gene expression evolution across a phylogenetic tree. The statistical approach developed here also makes it possible to study multiple tissues or sexes in a single framework, allowing us to make statistically rigorous inferences about differences in the rates of evolution among samples. Integrating these tools into a single software package available on multiple platforms enables these methods to be applied by a wide group of users.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.

生物学进步表明，许多特征受每个细胞中产生的基因的量控制，而不仅仅是每个基因和蛋白质的序列。基因在同一生物体内或同一组织中物种之间的不同组织之间的这些表达水平上可能有所不同。了解这些水平如何改变以及它们如何控制生物的外观和功能，这是当前研究的关键挑战。该项目将开发新的方法来理解组织和物种之间的基因表达变化，以及这些变化的协调方式。该研究采用新的统计方法来生产开源软件以进行分析。该软件将允许所有科学家能够在多个平台上使用这些新工具，从而有助于国家网络基础设施。这项工作还将通过多种社会利益改善和加速研究，包括实现新的生物学发现。该项目将支持博士后研究人员，研究生和本科生的培训，这些群体在科学和技术职业中的人数不足。关于了解进化树的课堂课程计划和计算机实验室将开发并分发给合作伙伴机构。基因表达的变换已被证明是物种之间许多差异的原因，而最近的技术进步意味着即使在非模型生物体中，这种数据也很容易收集。通过测量多种物种中同一基因的表达水平，我们可以开始了解跨生物体基因表达变化的历史。通过测量成千上万基因中的表达，我们可以进一步了解基因表达演化的机制和模式。这项研究开发了一个新的软件包（CAGEE），用于研究跨系统发育树的基因表达演化。这里开发的统计方法还可以在一个框架中研究多个时间或性别，从而使我们能够对样本之间进化速率的差异进行统计上的严格推断。将这些工具集成到多个平台上可用的单个软件包中，使这些方法能够由广泛的用户应用。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响审查标准，通过评估被认为是宝贵的支持。