Simultaneous high-throughput functional, transcriptomic and connectivity profiling using FUNseq

项目摘要 在大脑倡议的推动下，最近的技术进步产生了表征AC-AC的新方法。 整个大脑中神经元的活性、转录组和微观解剖，并增加了吞吐量 这些技术的数量级。目前可以记录POPU的同时活动- 大分子激光照射清醒行为动物体内数万个神经元的实验研究 fi视野多光子成像或高密度硅探测器，以及新的机器学习方法正在实现 比以往任何时候都更全面的功能表征。转录前fi铃声可以完成 在体外培养的数万或数十万个神经元的规模。最后对轴突前区的微尺度解剖进行了研究。 整个大脑的投射和连接也可以在同一个神经元的数万个神经元中进行评估 动物使用高密度电子显微镜重建局部电路，或(如我们这里建议的)RNA条形码 局部和远程轴突投射的方法。这些技术中的每一种都可以为用户提供 关于神经元的多样性及其组织成具有特殊fic功能的规范电路的重要线索， 转录性，或轴突投射fiLes。虽然这些技术都是独立推进的， 它们仍然有效地彼此孤立，排除了相同神经元的多模式特征 同样的动物。发展一个全面的管道，以表征转录，轴突投射和 我们在这里建议做的活体功能fi指纹将使细胞类型组成的协同分析成为可能 跨越这些多个维度。最后，由于这种方法的低成本和高吞吐量，实验结果表明，该方法是可行的。 使用这种新型管道的实验可以在不同的动物身上重复多次，以回答紧迫的问题 关于神经元的功能、结构和转录组之间的关系如何在发育过程中发生变化 精神或疾病状态。在这项计划中，我们将利用我们团队在体内功能方面的综合专业知识 成像和机器学习用于表征初级视觉神经元的复杂功能特性 小鼠的大脑皮质，以及皮扎多开发的结合转录前fi林的新测序技术 使用RNA条形码以轴突分辨率测量整个大脑中的单个神经元投射模式。

Project Summary Recent advances in technology driven by the BRAIN Initiative have yielded new methods for characterizing the ac- tivity, transcriptome, and microscale anatomy of neurons throughout the brain, and have increased the throughput of these techniques by orders of magnitude. It is currently possible to record the simultaneous activity of popu- lations of neurons on the order of tens of thousands of neurons in awake behaving animals in vivo using large field of view multiphoton imaging or high density silicon probes, and new machine learning methods are enabling more comprehensive functional characterization than ever before. Transcriptomic profiling can be accomplished at scales of tens or hundreds of thousands of neurons in vitro. Finally the microscale anatomy of axonal pro- jections and connections across the brain can also be assessed in tens of thousands of neurons in the same animal using dense electron microscopy reconstruction for local circuits, or (as we propose here) RNA barcoding methods for local and long-range axonal projections. Each of these techniques on their own can provide im- portant clues about the diversity of neurons and their organization into canonical circuits with specific functional, transcriptomic, or axonal projection profiles. While these techniques are all being pushed forward independently, they remain effectively siloed from each other, precluding multi-modal characterization of the same neurons in the same animal. Developing a comprehensive pipeline to characterize transcriptomic, axonal projections and in vivo functional fingerprints as we propose to do here would enable synergistic analyses of cell-type composition across these multiple dimensions. Finally, because of the low cost and high throughput of this approach, experi- ments using this novel pipeline could be repeated many times in different animals to answer pressing questions about how the relationship between the function, structure, and transcriptome of neurons changes across devel- opmental or disease states. In this proposal, we will leverage our team's combined expertise in in vivo functional imaging and Machine Learning to characterize the complex functional properties of neurons in primary visual cortex of the mouse, and novel sequencing techniques developed by PI Zador to combine transcriptomic profiling with RNA barcoding to measure single-neuron projection patterns throughout the brain at axonal resolution.