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.

项目总结 雄斑雀的求爱歌声是学习复杂运动行为和表演的经典模式 与人类的语言和交流有着重要的相似之处。雄性斑马雀从成年家教那里学到一首歌 然后在成年后重现这首歌。斑马雀模型提供出色的行为控制 这使得研究声乐学习和运动控制的电路基础的一般原理成为可能。许多 斑马雀大脑中高度相互连接的脑区，从前脑到脑干运动 核团，形成歌曲学习和歌曲产生所需的歌曲控制系统。一个主要的瓶颈是 对这一系统的理解源于鸣禽大脑中未知的连接特性和很少的知识 这些连接属性如何与单个神经元的转录和功能多样性相互作用 以产生健壮的行为输出。由Brain Initiative支持的工具已经彻底改变了 通过解决这个同样的瓶颈来实验小鼠。然而，这些技术目前仅限于 一组小的模型系统，还不适应斑马雀。我们最近开发了一类新的 灵活、高通量的连接映射工具，用于研究神经电路功能。我们的战略依赖于 在核酸条形码上将神经元连接转换为可通过DNA测序读取的格式 并且可以用单细胞分辨率连接连接、转录和功能数据。重要的是，我们的 工具是以病毒为基础的，因此可以跨物种应用。启用多模式调查 斑马雀鸣唱控制系统中集成单元类型的电路功能，特别是 宋核HVC，在这个能力建设方案中，我们将适配我们的下一代连接 和空间转录工具给斑马雀。在目标1中，我们提出了单细胞示踪方法 MAPseq和它与单细胞RNA测序相结合的方法，以一种公正的方式发现， HVC中多染色体细胞类型的同一性。在目标2中，我们首先优化了斑马的BARseq原位测序方法 雀类在太空中绘制内源基因表达和条形码的地图。然后我们建立一条管道，例行地 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， 基因表达和远距离连接，分辨率为单个细胞，每个细胞数百个 做实验。这些目标的成功完成为综合目标BCP R01项目铺平了道路 由凯布舒尔实验室和朗实验室合作进行。这些项目将更新现有的 斑马雀通过结合远程连接和转录细胞识别而进行的歌曲学习 对实现对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神经元的连接和转录特征如何决定的两个相互竞争的假说 在鸣禽大脑中产生声学结构的网络特性。