CRCNS US-German Research Proposal - The diversification of retinal ganglion cells: A combined transcriptomic, genome engineering and imaging approach

CRCNS 美国-德国研究提案 - 视网膜神经节细胞的多样化：转录组学、基因组工程和成像相结合的方法

• 批准号: 2309039
• 负责人: Karthik Shekhar
• 金额: $ 73.28万
• 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: 2023
• 资助国家: 美国
• 起止时间: 2023-11-01 至 2028-10-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2309039&HistoricalAwards=false
• 关键词: CRCNS; US; German; Research; Proposal

The brain contains a multitude of types of neuronal cells that assemble into elaborate circuits that underlie sensation, perception, and behavior. A fundamental question in neuroscience is how the developing brain generates such an impressive array of diverse neuronal types. Specifically, the grand challenge is to determine the networks of genes whose activity restricts immature “precursor” neurons to adopt specific terminal fates. The neural retina, which is an outpost of the brain residing in the back of the eye, is an ideal system for addressing this question due to its experimental accessibility and well-defined census of neuronal diversity in several species. Pioneering studies beginning in the 1980s used the then available experimental tools in frogs, rodents and fish to gain valuable insights into the process by which retinal cells become restricted to broadly defined “classes”. However, some retinal classes contain several (20-50) distinct neuronal types, and how cells commit to specific types within a class is unknown, and cannot be studied using classical tools. This project brings together an experimental neuroscientist and computational researcher to address this question combining several recently developed technologies to study the process of cell-type specification in the retina of the zebrafish in unprecedented detail. The approaches developed in this work will be useful for understanding neuronal development and maturation in other brain regions and species, and pinpoint the genes whose dysregulation may lead to developmental abnormalities. The project will combine high-throughput single-nucleus RNA-sequencing (snRNA-seq), advanced computational methods, genome engineering and live imaging to understand how ~35-50 types of retinal ganglion cells (RGCs), the output neurons of the eye, emerge in the developing and growing zebrafish retina. By leveraging the experimental advantages of zebrafish, which permits direct live imaging of developing cells in vivo, the researchers will study how postmitotic neuronal differentiation unfolds at a level of detail that is not possible in mice, the most commonly used vertebrate model. We will map the transcriptional landscapes of differentiating RGCs using snRNA-seq profiles collected at six developmental stages of zebrafish,and use computational methods to reconstruct lineage relationships among transcriptional clusters across development. To test predictions from genomic analysis, the researchers will label molecularly defined immature RGCs by CRISPR/Cas9-based genome engineering and image them to visualize their initial differentiation and transdifferentiation from embryonic stages into adulthood. Taken together, the efforts will lead to new insights into the patterning of a complex neurobiological system.This project is funded jointly by the Neural Systems Cluster in the Directorate for Biological Sciences and the Engineering Biology and Health Cluster in the Directorate for Engineering. A companion project is being funded by the German Federal Ministry of Education and Research (BMBF).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.

大脑包含多种类型的神经细胞，这些细胞组装成构成感觉、感知和行为的复杂电路。具体来说，最大的挑战是发育中的大脑如何产生如此多的不同神经类型。确定其活动限制未成熟“前体”神经元采取特定最终命运的基因网络，神经视网膜是位于眼睛后部的大脑前哨，是解决这个问题的理想系统。 20 世纪 80 年代开始的开创性研究利用当时可用的青蛙、啮齿动物和鱼类实验工具，对视网膜细胞被限制为广泛定义的过程获得了宝贵的见解。然而，一些视网膜类别包含几种（20-50）种不同的神经类型，并且细胞如何致力于类别中的特定类型是未知的，并且无法使用经典工具进行研究。神经科学家和计算研究人员结合了几种最近开发的技术来解决这个问题，以前所未有的细节研究斑马鱼视网膜中的细胞类型规范过程，这项工作中开发的方法将有助于理解其他大脑的神经发育和成熟。该项目将结合高通量单核 RNA 测序 (snRNA-seq)、先进的计算方法、基因组工程和实时成像，以了解其失调可能导致发育异常的基因。研究人员利用斑马鱼的实验优势，可以对体内发育的细胞进行直接实时成像，在发育和生长的斑马鱼视网膜中出现约 35-50 种视网膜神经节细胞（RGC），即眼睛的输出神经元。我们将研究有丝分裂后神经元分化如何在小鼠（最常用的脊椎动物模型）中以不可能的细节水平展开，我们将使用 RGC 的分化图谱来绘制转录图谱。为了测试基因组分析的预测，研究人员将通过基于 CRISPR/Cas9 的基因组工程和分子标记来标记分子定义的未成熟 RGC，并在斑马鱼的六个发育阶段收集 snRNA-seq 图谱，并使用计算方法重建转录簇之间的谱系关系。对它们进行成像，以可视化它们从胚胎阶段到成年期的初始分化和转分化。总之，这些努力将为复杂的神经生物学系统的模式带来新的见解。该项目由神经学联合资助。生物科学理事会的系统集群和工程理事会的工程生物学和健康集群有一个配套项目由德国联邦教育和研究部 (BMBF) 资助。该奖项反映了 NSF 的法定使命，并被视为值得通过使用基金会的智力优点和更广泛的影响审查标准进行评估来支持。