High resolution neuronal lineage tracing

项目摘要 神经元祖细胞如何产生大量的神经元和神经胶质细胞类型的多样性是一个基本的 这个问题在很大程度上尚未解决。果蝇一直是研究这些复杂系统的关键模式系统 神经发生的问题及其神经系统的研究促成了几个重要的概念 适用于哺乳动物。这些包括时间和空间模式、细胞死亡、神经和/或神经胶质特化 和不对称的细胞分裂。然而，其神经元谱系的完全分辨率仍然难以捉摸。在这 我们将利用来自合成生物学的强大遗传工具来重建整个 在单细胞分辨率下的多个脑结构的神经元谱系。我们将培育转基因果蝇， 可以通过单细胞转录组学自主记录和分析谱系。我们假设 我们对成人大脑发育的结构和分子性质的了解将为我们提供一个独特的 这不仅有利于重建果蝇大脑的整个谱系树，而且有利于形成新的假设 关于每个大脑结构是如何从前体细胞忠实而均匀地形成的。 目的1建立果蝇谱系记录仪。目前没有建立 果蝇神经系统中基于CRISPR的谱系方法我们将在果蝇中调整GESTALT， 在谱系进展过程中给DNA留下“疤痕”，并通过发育逐步记录这一谱系。我们将 使用遗传工具来获得对我们的谱系测量的时空控制，并使用计算机建模， 条形码结构，以优化系统的活动。我们将产生足够多的目标点， 捕获神经元发育过程中产生的整个神经元多样性。我们将根据经验评估 不同版本的技术，并选择最好的一个单细胞谱系跟踪。 目的2明确成人脑神经元的出生顺序和克隆关系。我们将血统追溯 同时对单个细胞的转录组进行测序。这应该 让我们能够用单细胞图谱来识别不同的神经亚型。我们将描述血统 并且联合收割机将其与能够重建多树谱系的公开方法相结合 来识别我们数据中不同的血统关系。我们将建立在神经元的刻板模式， 发展，以改善这种结构和重建神经元谱系 目的3实验验证神经元谱系的重建。我们将利用我们的先验知识， 神经元发育与事后验证相结合，以基准我们的谱系重建。我们将 首先将我们对果蝇局部运动检测器的谱系重建与已知的简单和 明确的血统。我们将使用区域特异性Gal 4系来谱系追踪细胞的不同亚区。 然后通过流式细胞术和单细胞测序来鉴定在这些区域中产生的神经元。 在我们重建的树中评估这些关系将为我们的谱系树提供进一步的验证。

Project Summary How neuronal progenitor cells produce an enormous diversity of neuronal and glial cell types is a fundamental topic that remains largely unresolved. Drosophila has been a pivotal model system to study these complex questions of neurogenesis and research in its nervous system has contributed to several important concepts that apply to mammals. These include temporal and spatial patterning, cell death, neural and/or glial specification and asymmetric cell division. Nevertheless, the full resolution of its neuronal lineages remains elusive. In this proposal we will take advantage of powerful genetic tools derived from synthetic biology to reconstruct the entire neuronal lineage of multiple brain structures at single cell resolution. We will develop transgenic flies in which lineages can be autonomously recorded and analyzed through single cell transcriptomics. We hypothesize that our knowledge on the structure and molecular nature of adult brain development will provide us with a unique advantage to not only reconstruct the entire lineage tree of the Drosophila brain, but also to form new hypotheses on how each of the brain structures form very faithfully and uniformly from precursor cells. Aim 1 Development of a progressive lineage recorder in Drosophila. There are currently no established CRISPR-based lineage methods in the Drosophila nervous system. We will adapt GESTALT in Drosophila to `scar' the DNA during lineage progression and progressively record this lineage through development. We will use genetic tools to gain spatio-temporal control over our lineage measurements and use in silico modeling of the barcode structure to optimize the activity of the system. We will generate flies with enough target sites to capture the entire neuronal diversity generated during neuronal development. We will empirically evaluate different versions of the technology and select the best one for single cell lineage tracing. Aim 2 Defining neuronal birth order and clonal relationships in the adult brain. We will lineage trace through the neuronal development while simultaneous sequencing the transcriptome of single cells. This should allow us to identify the different neural subtypes using our single cell atlas. We will characterize the lineage information per cell and combine this with the published methods capable of reconstructing multi-tree lineages to identify different lineage relationships in our data. We will build on the stereotypical mode of neuronal development to refine this structure and reconstruct the neuronal lineages Aim 3 Experimental validation of the reconstructed neuronal lineages. We will use our prior knowledge of neuronal development in combination with post hoc validation to benchmark our lineage reconstruction. We will first compare our lineage reconstruction of the local motion detectors in Drosophila to their known simple and well-defined lineage. We will use region-specific Gal4 lines to lineage trace different subregions of the neuroepithelium followed by FACS and single cell sequencing to identify the neurons born in these regions. Evaluation of those relationships in our reconstructed tree will provide further validation for our lineage trees.