Integrating single-cell connectivity, gene expression, and function in zebra finches

整合斑胸草雀的单细胞连接、基因表达和功能

• 批准号: 10657971
• 负责人: JUSTUS M KEBSCHULL
• 金额: $ 38.69万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10657971
• 关键词: Acoustics; Address; Adult; Animal Model; BRAIN initiative; Bar Codes; Behavior; Behavior Control; Behavioral; Biological Models; Brain; Brain Mapping; Brain Stem; Brain region; Cell Nucleus; Cells; Collaborations; Communication; Complement; Complex; Courtship; DNA sequencing; Data; Development; Electrophysiology (science); Fostering; Foundations; Functional Imaging; Future; Gene Expression; Generations; Genes; Genetic Transcription; Goals; Histologic; Human; Image; In Situ; Individual; Investigation; Knowledge; Laboratory mice; Learning; Link; Maps; Measurement; Measures; Methods; Microscope; Mission; Modeling; Motor; Motor Skills; Multiplexed Analysis of Projections by Sequencing; Names; Neurons; Nucleic Acids; Optical Methods; Output; Pattern; Production; Property; Prosencephalon; RNA; Research; Resolution; Role; Sampling; Songbirds; Speech; Structure; System; Techniques; Technology; Testing; Tissue imaging; Tissues; Translating; United States National Institutes of Health; Update; Virus; Work; cell type; experimental study; flexibility; in situ sequencing; in vivo; in vivo imaging; insight; male; model organism; motor behavior; motor control; multimodality; multiple omics; neural circuit; next generation; novel; preservation; single-cell RNA sequencing; stem; support tools; tool; transcriptomics; tutoring; two-photon; vocal learning; zebra finch

PROJECT SUMMARY The courtship song of male zebra finches is a classical model for learning complex motor behaviors and shows important parallels to human speech and communication. Male zebra finches learn a song from an adult tutor and then reproduce this song throughout adulthood. The zebra finch model offers outstanding behavioral control that permits the investigation of general principles of the circuit basis of vocal learning and motor control. Many highly interconnected brain regions across the zebra finch brain, ranging from forebrain to brainstem motor nuclei, form a song control system required for song learning and song production. A major bottleneck in understanding this system stems from unknown connectivity properties in the songbird brain and little knowledge of how these connectivity properties interface with transcriptomic and functional diversity of individual neurons to produce robust behavioral output. BRAIN Initiative supported tools have revolutionized research in the laboratory mouse by addressing this same bottleneck. However, these technologies are currently limited to a small set of model systems and not yet adapted to the zebra finch. We recently developed a novel class of flexible, high-throughput connectivity mapping tools for investigating neural circuit function. Our strategy relies on nucleic acid barcodes to translate neuronal connectivity into a format that can be read out by DNA sequencing and can bridge connectomics, transcriptomics, and functional data with single-cell resolution. Importantly, our tools are virus-based and can therefore be applied across species. To enable a multi-modal investigation of the circuit function of integrated cell types in the zebra finch song control system, and in particular the song nucleus HVC, in this capacity-building proposal we will adapt our next-generation connectomics and spatial transcriptomics tools to the zebra finch. In Aim 1, we bring the single-cell tracing method MAPseq and its combination with single-cell RNA sequencing to the zebra finch to discover, in an unbiased way, the multi-omic cell type identities in HVC. In Aim 2, we first optimize in situ sequencing method BARseq for zebra finches to map endogenous gene expression and barcodes in space. We then establish a pipeline to routinely register functional imaging data of HVC with BARseq images to interrogate the interaction of neuronal activity, gene expression, and long-range connectivity at the resolution of single cells for hundreds of cells per experiment. Successful completion of these aims paves the way for integrative TargetedBCP R01 projects conducted in collaboration between the Kebschull and Long labs. These projects will update existing models of song learning in the zebra finch by incorporating long-range connectivity and transcriptomic cell identity information that is critical for achieving a mechanistic understanding of circuit function. Our first target will test two competing hypotheses about how the connectomic and transcriptomic features of HVC neurons determine network properties that give rise to acoustic structure in the songbird brain.

项目摘要 雄性斑胸草雀的求偶歌是学习复杂运动行为和表演的经典模型 与人类语言和交流的重要相似之处。雄性斑胸草雀从成年导师那里学一首歌 然后在整个成年期都重复这首歌。斑胸草雀模型提供了出色的行为控制 这使得研究发声学习和运动控制的电路基础的一般原理成为可能。许多 斑胸草雀大脑中高度互联的大脑区域，从前脑到脑干运动区 细胞核，形成一个歌曲控制系统所需的歌曲学习和歌曲生产。的一大瓶颈 对这个系统的理解源于鸣禽大脑中未知的连接特性， 这些连接特性如何与单个神经元的转录组和功能多样性相互作用 产生强大的行为输出。BRAIN Initiative支持的工具彻底改变了 实验室老鼠通过解决同样的瓶颈。然而，这些技术目前仅限于 这是一个小型的模式系统，还没有适应斑胸草雀。我们最近开发了一种新型的 灵活、高通量的连接映射工具，用于研究神经回路功能。我们的策略是 将神经元连接转换成可以通过DNA测序读出的格式 并且可以桥接连接组学、转录组学和具有单细胞分辨率的功能数据。重要的是我们的 工具是基于病毒的，因此可以跨物种应用。为了实现多模式调查， 斑胸草雀鸣唱控制系统中集成细胞类型的电路功能，特别是 在这个能力建设提案中，我们将调整我们的下一代连接组学， 和空间转录组学工具。在目标1中，我们提出了单细胞追踪方法， MAPseq及其与单细胞RNA测序的结合，以公正的方式发现斑胸草雀， HVC中的多组细胞类型身份。目的二首先优化了斑马的原位测序方法BARseq 雀类来绘制空间中的内源基因表达和条形码。然后我们建立一个管道， 将HVC的功能成像数据与BARseq图像配准以询问神经元活动的相互作用， 基因表达，以及每个细胞数百个细胞的单细胞分辨率下的远程连接。 实验这些目标的成功完成为综合TargetedBCP R01项目铺平了道路 在Kebschull和Long实验室的合作下进行。这些项目将更新现有的 斑胸草雀通过长距离连接和转录组细胞特性的学习 这些信息对于实现电路功能的机械理解至关重要。我们的第一个目标将测试 关于HVC神经元的连接组和转录组特征如何决定HVC神经元的两个相互竞争的假设， 这些网络特性导致鸣禽大脑中的声学结构。