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2/2 - Cell Type and Region-Specific Regulatory Networks in Human Brain Development and Disorders

2/2 - 人脑发育和疾病中的细胞类型和区域特异性调节网络

基本信息

批准号：
10430082
负责人：
MATTHEW W. STATE
金额：
$ 45.19万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-15 至 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10430082
关键词：
7q11.23 ATAC-seq Address Age Archives Autopsy Biological Models Brain Brain Diseases Brain region Cell Nucleus Cell physiology Cells Chromatin Remodeling Factor Code Collection Communities Complex Coupled Data Data Set Development Diagnosis Dimensions Disease Elements Etiology Fluorescence Freezing Functional disorder Genes Genetic Genetic Transcription Genomics Heterogeneity Human Joints Knowledge Link Macaca Maps Modality Molecular Molecular Profiling Nature Neurons Pathway interactions Patients Pattern Population Post-Transcriptional Regulation Protein Analysis Protein Isoforms Proteome Proteomics Regulator Genes Regulatory Element Resources Risk Role Sampling Sorting - Cell Movement Surveys Syndrome Time Tissues Transgenic Mice Untranslated RNA Validation Variant Work autism spectrum disorder base candidate selection cell type experimental study functional genomics genetic architecture genetic regulatory protein genomic data improved induced pluripotent stem cell insight member mouse model neurodevelopment neurogenomics neuropsychiatric disorder neuropsychiatry novel postnatal development postnatal human prenatal risk variant sample archive single-cell RNA sequencing spatiotemporal transcription factor transcriptome sequencing

项目摘要

ABSTRACT Recent advances in genetics and genomics have identified hundreds of coding variants that increase risk for major neuropsychiatric disorders, such autism spectrum disorder. Work to clarify the contribution of non- coding variants is also underway and is expected to accelerate rapidly in the next few years. While these advances have considerably improved our understanding of the genetic landscape neuropsychiatric disorders, a deeper understanding of molecular pathophysiology is still missing. This knowledge gap is due to, in part, the heterogeneity of risk loci involved, their potential roles in regulating expression of a large number of genes, the pleiotropic nature of risk genes, and the high likelihood that neuropsychiatric disorders result from dysfunctional circuitry involving multiple cell types and brain regions, altogether making the identification of molecular and cellular mechanisms underlying a disease problematic, especially in the context of the protractive and complex nature of brain development. Therefore, the discovery and characterization of the full spectrum of functional genomic elements active in the human brain, as well as their activity/expression patterns across the spatiotemporal dimensions, is essential for clarifying when, where, and what cell types are relevant to the etiology and treatment of neuropsychiatric disorders. This is particularly so in the context of non-coding variants, which are difficult to annotate, yet potentially hold the promise of providing highly specific spatial, temporal, and cell type specific information. To address this knowledge gap and to continue our contributions to the PsychENCODE Consortium, we propose four specific aims that identify gene regulatory and cell type-specific mechanisms of human neurodevelopment. In Aim 1, we identify functional genomic elements across single cells (nuclei), cell types, regions and developmental time points of neurotypical human and macaque postmortem brains. In Aim 2, we map the spatio-temporal proteome of neurotypical human and macaque postmortem brains. In Aim 3, we perform integrative identification of functional genomic elements and proteomics in diseased brains and iPSC-derived neural cells. In Aim 4, we integrate results from Aims 1-3, as well as with independent genetic datasets of neuropsychiatric populations, to identify non-coding elements, genes, or molecular pathways that will lead to a better understanding of the underlying pathophysiological mechanisms of neuropsychiatric disorders. Finally, these mechanisms will be functionally characterized in model systems. Data from this proposal will also serve as a critical new resource for members of the community, with which they can intersect their results and draw deeper and more meaningful conclusions, especially as the wealth of genomic data from neuropsychiatric disorders continues to accumulate.

摘要