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.

项目概要 雄性斑胸草雀的求爱歌曲是学习复杂运动行为和表演的经典模型 与人类言语和交流有重要相似之处。雄性斑胸草雀向成人导师学习歌曲 然后在整个成年时期重复这首歌。斑胸草雀模型具有出色的行为控制能力 这使得研究声音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连的大脑区域，从前脑到脑干运动 核，形成歌曲学习和歌曲制作所需的歌曲控制系统。一个主要瓶颈是 对这个系统的理解源于鸣禽大脑中未知的连接特性和知之甚少 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 产生稳健的行为输出。 BRAIN Initiative 支持的工具彻底改变了该领域的研究 实验室小鼠通过解决同样的瓶颈。然而，这些技术目前仅限于 一小组模型系统，尚未适应斑胸草雀。我们最近开发了一类新颖的 用于研究神经回路功能的灵活、高通量连接映射工具。我们的策略依赖于 核酸条形码将神经元连接转化为可通过 DNA 测序读出的格式 并能以单细胞分辨率连接连接组学、转录组学和功能数据。重要的是，我们的 工具是基于病毒的，因此可以跨物种应用。为了能够进行多模式调查 斑胸草雀鸣叫控制系统中集成细胞类型的电路功能，特别是 宋核 HVC，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 以及斑胸草雀的空间转录组学工具。在目标1中，我们引入了单细胞追踪方法 MAPseq 及其与斑胸草雀单细胞 RNA 测序的结合，以公正的方式发现， HVC 中的多组学细胞类型身份。在目标2中，我们首先优化斑马的原位测序方法BARseq 雀类绘制空间内源基因表达和条形码图。然后我们建立一个管道来定期 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的远程连接 实验。成功完成这些目标为综合 TargetedBCP R01 项目铺平了道路 Kebschull 和 Long 实验室合作进行。这些项目将更新现有的模型 通过结合远程连接和转录组细胞身份来进行斑胸草雀的鸣叫学习 对于实现电路功能的机械理解至关重要的信息。我们的第一个目标将测试 关于 HVC 神经元的连接组学和转录组学特征如何决定的两个相互竞争的假设 网络特性在鸣禽大脑中产生声学结构。