Collaborative Research: RESEARCH-PGR: Uncovering latent vascular function in maize

合作研究：RESEARCH-PGR：揭示玉米的潜在血管功能

• 批准号: 2211435
• 负责人: George Chuck
• 金额: $ 43.95万
• 依托单位: University of California-Berkeley
• 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: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2211435&HistoricalAwards=false
• 关键词: Collaborative; Research; RESEARCH; PGR; Uncovering

Because of its utility as a source of food, animal feed, fuel, and other bioproducts, maize (Zea mays subsp. mays) production is valued at over $83 billion annually in the US. The increased frequency of extreme weather events like drought and flooding threaten American businesses and communities that depend on maize production. Researchers from Oregon State University (PI Leiboff) and the University of California, Berkeley (Co-PI Chuck) are working together to understand the mechanisms that regulate the maize vascular system to prepare our nation’s most important crop for climate change. In a recent breakthrough, Co-PI Chuck showed that amongst the complex network of seemingly identical veins within a maize plant, there are specialized veins with unique functions in surviving drought and accommodating plant microbes. By applying cutting edge techniques in single cell genomics, mutant mapping, and machine learning, PI Leiboff and Co-PI Chuck will uncover the secret genetics that define these specialized veins and provide tools for the rapid improvement of the maize vascular system by precision breeding. The PIs will use techniques developed by this research to provide rural and urban high school teachers with low-cost smartphone microscope kits that will improve high school student engagement with the life sciences. Data from this research will be used to produce a free educational resource, “Teaching with Single Cell Genomics” providing university educators with lesson plans, animations, multimedia presentations, and a supplemental textbook to ensure that our next generation of undergraduates in biology receive training in this revolutionary new technology.The dynamic production of the dense network of veins is critical for efficient photosynthesis in C4 grasses. Grasses produce this network through reiterative developmental programs that maintain physiological functions as tissues grow or encounter new environments. Although the products of these programs are similar in structure, these repeated events provide a unique opportunity for specialization amongst tissues generated at different times and locations. This research explores the biological question of how similar tissues within an organism can be constructed for different purposes. Maize is an ideal experimental system for studying dynamic vascular events because of its high vein density and predictable developmental sequence of initiating leaf vein subtypes. The PIs will test the hypothesis that spatiotemporal gene regulation leads to unique development and physiology amongst veins in the same plant. This research will leverage state-of-the-art advances in single cell transcriptomics to track and identify key fate-determining factors in developing leaf vein subtypes amongst all developing leaf cells. Next, researchers will collaboratively apply genomics to accelerate the mapping and functional characterization of maize specialized vascular mutants. By constructing a neural network machine learning model, this work will predict vascular phenotypes from tens of thousands of cleared leaf images to perform a GWAS of a 942-inbred mapping panel, dissecting the genetic architecture of specialized vascular development and spatiotemporal gene expression changes between alleles. Data derived from these aims will inform the precision breeding of specialized vascular traits for the continued improvement of maize to meet global demand for food, feed, and fuel.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.

由于其作为食物、动物饲料、燃料和其他生物产品的来源的效用，玉米（Zea mays subsp.在美国，每年的产量价值超过830亿美元。干旱和洪水等极端天气事件的频率增加威胁着依赖玉米生产的美国企业和社区。来自俄勒冈州州立大学（PI Leiboff）和加州大学伯克利分校（Co-PI Chuck）的研究人员正在共同努力，了解调节玉米维管系统的机制，为我国最重要的作物应对气候变化做好准备。在最近的一项突破中，Co-PI Chuck表明，在玉米植株内看似相同的静脉的复杂网络中，有一些特殊的静脉在干旱中生存和容纳植物微生物方面具有独特的功能。通过在单细胞基因组学、突变体定位和机器学习中应用尖端技术，PI Leiboff和Co-PI Chuck将揭开定义这些特殊静脉的秘密遗传学，并为通过精确育种快速改善玉米维管系统提供工具。PI将使用本研究开发的技术，为农村和城市高中教师提供低成本的智能手机显微镜套件，以提高高中生对生命科学的参与度。这项研究的数据将用于制作免费的教育资源，“单细胞基因组学教学”，为大学教育工作者提供教案，动画，多媒体演示和补充教科书，以确保我们的下一代生物学本科生接受这一革命性新技术的培训。密集的静脉网络的动态生产对于C4草的高效光合作用至关重要。草通过重复的发育程序产生这种网络，这些程序在组织生长或遇到新环境时维持生理功能。虽然这些程序的产品在结构上是相似的，但这些重复的事件为在不同时间和地点产生的组织之间的专业化提供了独特的机会。这项研究探索了生物学问题，即生物体内相似的组织如何被构建用于不同的目的。玉米具有较高的叶脉密度和可预测的起始叶脉亚型发育顺序，是研究动态维管事件的理想实验系统。PI将测试时空基因调控导致同一植物中的静脉之间的独特发育和生理学的假设。这项研究将利用单细胞转录组学的最新进展来跟踪和确定所有发育中的叶细胞中发育中的叶脉亚型的关键命运决定因素。接下来，研究人员将合作应用基因组学来加速玉米专用维管突变体的定位和功能表征。通过构建神经网络机器学习模型，这项工作将从数万张清晰的叶片图像中预测维管表型，以执行942个近交系映射面板的GWAS，剖析特化维管发育的遗传结构和等位基因之间的时空基因表达变化。从这些目标中获得的数据将为精确育种专门的维管性状提供信息，以持续改进玉米，满足全球对食品，饲料和燃料的需求。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。