RESEARCH-PGR: Illuminating the Plant Protein Interactome with Genome-wide Signatures of Coevolution

研究-PGR：用协同进化的全基因组特征阐明植物蛋白相互作用组

• 批准号: 2114641
• 负责人: Daniel Sloan
• 金额: $ 53.14万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2114641&HistoricalAwards=false
• 关键词: RESEARCH; PGR; Illuminating; Plant; Protein

Sequencing plant genomes has unlocked a massive catalog of genes and yet our ability to understand the specific role of each gene lags far behind, meaning functions have only been assigned to a fraction of known plant genes. Individual genes rarely work alone, and a critical aspect of a given gene's function is its interacting partners. Deciphering genetic interactions throughout plant genomes will advance our understanding of the function of a large number of uncharacterized genes; however, most existing methods for identifying genetic interactions are laborious, expensive, and difficult to scale to the entire genome. This project will develop scalable, efficient computational analyses tailored to identifying genetic interactions based on gene-specific rates of evolution across plant genomes. These computational tools will serve as resources applicable to any group of plants and be used to generate databases of genetic interactions for several scientifically and agriculturally important plant groups, which plant geneticists and molecular biologists can search to identify new functions for genes of interest. The results will also be used to probe the emergent properties of entire networks of genetic interactions, which will illuminate the higher-level functional architecture of plant genomes. The impact of these resources will be maximized by offering workshops that will provide training to researchers interested in using these tools and by engaging with first-year undergraduates to broaden participation in the field of computational biology.Genetic interactions are an important indicator of gene function but the existing tools for identifying the genome-wide assemblage of interactions (i.e., the interactome) in plants provide only a partial view. The phylogenetic signature of evolutionary rate covariation (ERC) between interacting proteins has been successfully applied on small sets of genes in plants to demonstrate coevolution between known subunits within enzyme complexes and on a genome-wide all-by-all basis in non-plant lineages to discover novel interaction partners. However, ERC has never been applied at genome-wide scale in plants, likely due to phylogenetic challenges caused by the especially frequent gene and genome duplication that occur in plants. This project will develop a novel pipeline tailored to ERC analyses of plant genomes, which will employ existing theory on reconciling complex histories of duplication across gene trees. This pipeline will be used to perform ERC analyses at multiple levels of plant evolution and compile the results to generate a web-based plant interactome database, which can be queried for specific genetic interactions. Further, the resulting ERC-based interaction data will be integrated with existing binding assay and coexpression-based interactions to functionally validate ERC results. Finally, network analytics will identify modules of interacting cofunctional proteins and determine how network structure is driven by gene function. This work will create a resource that will empower genome biologists to add a needed layer of information to genome annotation efforts and provide molecular biologists with a wealth of ready-to-test functional hypotheses. All project outcomes will be freely accessible through CyVerse and long-term repositories such as GitHub and Dryad.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.

对植物基因组进行测序已经解锁了大量的基因目录，但我们理解每个基因的具体作用的能力远远落后，这意味着功能只被分配给一小部分已知的植物基因。单个基因很少单独工作，给定基因功能的一个关键方面是其相互作用的伙伴。破译整个植物基因组中的遗传相互作用将促进我们对大量未表征基因的功能的理解;然而，大多数用于识别遗传相互作用的现有方法都是费力的，昂贵的，并且难以扩展到整个基因组。该项目将开发可扩展的，高效的计算分析，以确定基于跨植物基因组的基因特异性进化速率的遗传相互作用。这些计算工具将作为适用于任何植物群的资源，并用于生成几个在科学和农业上重要的植物群的遗传相互作用数据库，植物遗传学家和分子生物学家可以搜索这些数据库，以确定感兴趣基因的新功能。研究结果还将用于探索整个遗传相互作用网络的涌现特性，这将阐明植物基因组的更高层次功能结构。这些资源的影响将通过提供讲习班，为有兴趣使用这些工具的研究人员提供培训，并通过与一年级本科生接触，扩大对计算生物学领域的参与，以最大限度地发挥作用。遗传相互作用是基因功能的重要指标，但现有的用于识别全基因组相互作用组合的工具（即，植物中的相互作用组）仅提供了部分视图。相互作用的蛋白质之间的进化速率协变（ERC）的系统发育签名已成功地应用于植物中的小组基因，以证明酶复合物内的已知亚基之间的协同进化，并在非植物谱系的全基因组的基础上，发现新的相互作用伙伴。然而，ERC从未在植物的全基因组范围内应用，这可能是由于植物中特别频繁的基因和基因组复制所引起的系统发育挑战。该项目将开发一种针对植物基因组ERC分析的新型管道，该管道将采用现有理论来协调基因树之间复杂的重复历史。该管道将用于在植物进化的多个水平上进行ERC分析，并编译结果以生成基于网络的植物相互作用组数据库，该数据库可以查询特定的遗传相互作用。此外，所得的基于ERC的相互作用数据将与现有的结合测定和基于共表达的相互作用整合，以在功能上验证ERC结果。最后，网络分析将识别相互作用的共功能蛋白质模块，并确定基因功能如何驱动网络结构。这项工作将创建一个资源，使基因组生物学家能够为基因组注释工作添加所需的信息层，并为分子生物学家提供大量随时可以测试的功能假设。所有项目成果将通过CyVerse和GitHub和Dryad等长期存储库免费访问。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标准进行评估，被认为值得支持。