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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.

项目总结