权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

RNA regulatory networks in neuronal cell type diversity and function

神经元细胞类型多样性和功能中的 RNA 调控网络

基本信息

批准号：
10342485
负责人：
Chaolin Zhang
金额：
$ 62.5万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-12-01 至 2026-11-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10342485
关键词：
ANK3 gene Action Potentials Affect Alternative Splicing Axon Behavior Biological Models Brain Cells Classification Clustered Regularly Interspaced Short Palindromic Repeats Complex Computer Analysis Data Data Set Disease ES Cell Line Electrophysiology (science)Elements Exons Experimental Models GTP-Binding Protein alpha Subunits, Gs Ganglia Gene Expression Gene Expression Regulation Genes Genetic Transcription Glutamates Goals Human In Vitro Interneurons Knock-out Mammals Medial Messenger RNA Methods Modeling Molecular Molecular Profiling Morphology Motor Neurons Mus Mutagenesis Nervous system structure Neurons Organ Population Process Property Protein Family Protein Isoforms Proteins RNA RNA Splicing RNA-Binding Proteins RNA-Protein Interaction Regulation Regulator Genes Reporter Research Resources Rest Rodent Role Sampling Specific qualifier value Spinal Structure System Taxonomy Testing Tissues To specify Transcript Validation Variant Work base cell type clinically relevant deep learning deep learning model driving force embryonic stem cell excitatory neuron in silico in vivo in vivo Model inhibitory neuron innovation insight interdisciplinary approach mRNA Precursor machine learning method molecular marker mouse model neural circuit neurodevelopment neuronal excitability novel programs single-cell RNA sequencing statistical and machine learning stem cell differentiation success transcriptome transcriptome sequencing transcriptomics

项目摘要

PROJECT SUMMARY RNA regulatory networks in neuronal cell type diversity and function The mammalian brain is probably the most complex organ in the body and its proper function requires coordination of many diverse types of excitatory and inhibitory neurons that form distinct functional circuitries. Characterization of neuronal cell types is fundamental to understand not only how the brain works, but also how specific cell types are selectively affected in multiple neuronal disorders and how this process can be reversed. A large number of neuronal cell types were recently defined based on their gene expression profiles in bulk and single cells, and these cell types are organized into a hierarchical cell taxonomy. Alternative splicing is a mechanism to generate multiple transcript and protein variants with distinct functions, thus providing a major driving force of the molecular diversity in mammals. The overarching goal of my research group is to understand the contribution of alternative splicing and the underlying RNA-regulatory networks in the brain and brain-related disorders. Previous work from multiple groups, including ours, unambiguously demonstrated that the brain has unique splicing-regulatory programs compared to non-neuronal tissues. Our studies also revealed the establishment of a pan-neuronal splicing program regulated by multiple RNA-binding proteins (RBPs) during neural development, and demonstrated the important role of the Rbfox protein family in regulating axonal maturation and neuronal excitability. However, how alternative splicing contributes to the distinct molecular profiles of diverse neuronal cell types in the cortex is currently poorly understood. We hypothesize that the transcriptome diversity generated by highly regulated alternative exons is a major component that specifies neuronal cell type identity and function. In this application, we describe our preliminary analysis of neuronal cell type-specific alternative splicing regulation in mouse cortex, which provides strong support for the following specific aims we would like to pursue: 1) Perform systematic analysis of neuronal cell type-specific alternative splicing to identify novel neuronal subclasses and regulators using deep sc-RNA-seq data. 2) Validate our computational predictions and characterize mechanisms of neuronal cell type-specific splicing regulation and function using two complementary model systems: the distinction of two major subclasses of GABAergic interneurons originating from caudal (CGE) and medial (MGE) ganglionic eminences, and a GABAergic neuron- specific microexon in Ank3/Ankyrin G. To achieve our goal, we will use a multidisciplinary approach that integrates cutting-edge statistical an machine learning methods and multiple in vitro and in vivo experimental models. This study will generate a global and mechanistic view of precise alternative splicing regulation across diverse neuronal cell types and illuminate its impact on neuronal structural and functional properties.

项目总结