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In situ Single-Cell Multi-Omic and Morphological Profiling in Mammalian Brains

哺乳动物大脑的原位单细胞多组学和形态学分析

基本信息

批准号：
10506297
负责人：
Chongyuan Luo
金额：
$ 180.95万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10506297
关键词：
3-Dimensional ATAC-seq Anatomy Atlases Axon Bar Codes Base of the Brain Benchmarking Brain Cell Nucleus Cells Cellular Morphology Censuses Characteristics Chemicals Chromatin Classification Cytosine DNA DNA Ligation DNA Modification Process Data Data Set Dendrites Development Disease Enhancers Epitopes Gene Expression Gene Expression Regulation Genetic Genomics Goals Human In Situ Individual Joints Label Ligation Lighting Measurement Mental disorders Methods Methylation Microglia Microscopy Modification Molecular Molecular Profiling Morphology Mosaicism Mus Neurodegenerative Disorders Neuroglia Neuronal Differentiation Neurons Oligonucleotides Pattern Physical shape Physiology Play Ploidies Population Positioning Attribute Property RNA Reaction Regulator Genes Regulatory Element Resolution Role Scanning Specificity Structure Synapses Systems Development Techniques Technology Tissues Transcriptional Regulation Writing Yang base brain cell brain tissue cell type data quality epigenome epigenomics genome-wide indexing innovation methylome multiple omics nervous system disorder novel photonics promoter relating to nervous system single cell technology tool transcriptome transcriptomics two-photon

项目摘要

PROJECT SUMMARY Single-cell technologies have revolutionized the characterization of mammalian brains allowing unbiased census of cell types and their transcriptomic and epigenomics signatures. However, the mapping of molecular signatures onto three-dimensional brain structures remains highly challenging since most single-cell methods can only analyze disassociated cells or nuclei. We propose to develop photonic-indexing sequencing (pi-seq) strategies for in situ spatial barcoding with single-cell resolution. The proposed pi-seq strategy writes high complexity molecular barcodes into the tissue using sequential ligation of DNA indices with the ligation reaction controlled by high-resolution patterned illumination. Chromatin accessibility and cytosine modifications are well-established epigenomics marks playing critical roles in transcription regulation in normal and disease tissues. We will integrate pi-seq with existing single-cell epigenomics techniques to develop methods for the spatial profiling of chromatin accessibility (pi-ATAC-seq) and methylcytosine (pi-mC-seq). We will further develop an in situ method pi-mCAT-seq to simultaneously profile RNA, methylcytosine, and chromatin accessibility at a single-cell resolution based upon our single-nucleus multi-omics method snmC2T-seq. The spatial specificity and data quality of pi-seq methods will be systematically evaluated using single-cell epigenomic datasets generated by BICCN. To connect molecular profiles with other defining properties of brain cell types such as morphology and synaptic connectivity, we will develop methods to integrate pi-seq with MORF (Mosaicism with Repeat Frameshift), a sparse and genetic labeling approach of neurons and glia to illuminate their complete morphologies (dendrites, axons, synapses). The proposed pi-seq methods will provide the tools to construct spatially resolved epigenomic atlas of mammalian brains and advance the study of gene regulation in brain development, function, and disease at the resolution of single cells.

项目概要单细胞技术彻底改变了哺乳动物大脑的特征，允许公正的普查细胞类型及其转录组学和表观基因组学特征。然而，分子特征的映射三维大脑结构仍然极具挑战性，因为大多数单细胞方法只能分析分离的细胞或细胞核。我们建议开发光子索引测序（pi-seq）策略用于具有单细胞分辨率的原位空间条形码。提出的pi-seq策略写复杂度高通过连续连接 DNA 索引并控制连接反应，将分子条形码植入组织中通过高分辨率图案照明。染色质可及性和胞嘧啶修饰已得到证实表观基因组学标志着在正常和疾病组织的转录调控中发挥着关键作用。我们将将 pi-seq 与现有的单细胞表观基因组学技术相结合，开发空间分析方法染色质可及性 (pi-ATAC-seq) 和甲基胞嘧啶 (pi-mC-seq)。我们将进一步开发一种原位方法 pi-mCAT-seq 可同时分析单细胞的 RNA、甲基胞嘧啶和染色质可及性基于我们的单核多组学方法 snmC2T-seq 的分辨率。空间特异性和数据 pi-seq方法的质量将使用由以下机构生成的单细胞表观基因组数据集进行系统评估 BICCN。将分子谱与脑细胞类型的其他定义特性（例如形态和突触连接，我们将开发将 pi-seq 与 MORF（Mosaicism with Repeat Frameshift），一种神经元和神经胶质细胞的稀疏遗传标记方法，以阐明它们的完整形态（树突、轴突、突触）。所提出的 pi-seq 方法将提供构建的工具哺乳动物大脑的空间解析表观基因组图谱并推进大脑基因调控的研究单细胞分辨率下的发育、功能和疾病。