High resolution neuronal lineage tracing

高分辨率神经元谱系追踪

基本信息

批准号：
10042321
负责人：
Claude Desplan
金额：
$ 43.15万
依托单位：
NEW YORK UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-01 至 2022-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10042321
关键词：
Address Adult Algorithms Atlases Bar Codes Behavioral Benchmarking Biological Biological Models Biology Birth Order Brain CRISPR/Cas technology Cell Death Cell Lineage Cell division Cells Chromium Cicatrix Clustered Regularly Interspaced Short Palindromic Repeats Complex DNA DNA Sequence Alteration Data Data Set Development Developmental Biology Dissection Drosophila genus Evaluation Evolution Genetic Genomics Grain Guide RNA Image Individual Knowledge Label Libraries Mammals Maps Measurement Methods Mitotic Modeling Molecular Motion Mus Mushroom Bodies Mutation Nature Nervous system structure Neurobiology Neuroglia Neurons Optic Lobe Outcome Pattern Play Preparation Procedures Process Protocols documentation Publishing Recovery Research Resolution Resources Retina Role Site Structure System Technology Testing Time Tissues Transcript Transgenic Organisms Trees Validation Work base cell type cost efficient design detector experimental study fly in silico in vivo insight interest nerve stem cell neuroepithelium neurogenesis neuron development new technology next generation overexpression precursor cell premature progenitor reconstruction relating to nervous system single cell mRNA sequencing single cell sequencing spatiotemporal stem cells synthetic biology tool transcriptome transcriptome sequencing transcriptomics

项目摘要

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.

项目摘要神经元祖细胞如何产生巨大的神经元和神经胶质细胞类型是基本的仍然尚未解决的主题。果蝇一直是研究这些复合物的关键模型系统神经系统中神经发生和研究的问题已导致了几个重要的概念适用于哺乳动物。这些包括时间和空间图案，细胞死亡，神经和/或神经胶质规范和不对称细胞分裂。然而，其神经元谱系的完整解决仍然难以捉摸。在这个提案我们将利用从合成生物学得出的强大遗传工具来重建整个单细胞分辨率下多个大脑结构的神经元谱系。我们将开发转基因苍蝇可以通过单细胞转录组学对谱系进行自主记录和分析。我们假设这一点我们对成人脑发育的结构和分子性质的了解将为我们提供独特的知识优势不仅可以重建果蝇大脑的整个谱系树，还可以形成新的假设关于每个大脑结构如何从前体细胞中非常忠实，均匀地形成。 AIM 1果蝇中进行性血统记录器的发展。目前尚无建立果蝇神经系统中基于CRISPR的谱系方法。我们将适应果蝇的格式塔谱系进展过程中的DNA“疤痕”，并通过发育逐渐记录了这种谱系。我们将使用遗传工具来获得对我们的谱系测量结果的时空控制，并用于用于计算机建模条形码结构以优化系统的活动。我们将使用足够的目标站点生成苍蝇捕获神经元发育过程中产生的整个神经元多样性。我们将经验评估该技术的不同版本，并为单细胞谱系跟踪选择最佳的版本。目标2定义成人大脑中神经元的出生顺序和克隆关系。我们将谱系跟踪通过神经元发育，同时对单细胞的转录组进行测序。这应该允许我们使用单细胞地图集鉴定不同的神经亚型。我们将表征血统每个单元格的信息，并将其与能够重建多树谱系的已发布方法结合确定我们数据中的不同谱系关系。我们将建立在神经元的刻板印象上开发以完善这种结构并重建神经元谱系 AIM 3对重建的神经元谱系的实验验证。我们将利用我们的先验知识神经元发展与事后验证相结合，以基准我们的血统重建。我们将首先将我们对果蝇局部运动探测器的谱系重建与他们已知的简单和定义明确的血统。我们将使用特定区域的GAL4线来谱系跟踪不同的子区域神经上皮之后是FACS和单细胞测序，以识别这些区域中出生的神经元。对我们重建树中这些关系的评估将为我们的谱系树提供进一步的验证。