Prediction and Validation of Oligodendrocyte Gene Regulatory Network from Multi-Omics

多组学预测和验证少突胶质细胞基因调控网络

• 批准号: 10509768
• 负责人: John P Svaren
• 金额: $ 40.1万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10509768
• 关键词: Affect; Binding Sites; Biological; CHD7 gene; ChIP-seq; Cognition Disorders; Collaborations; Computer Models; Data; Data Set; Defect; Development; Developmental Disabilities; Disease; Enhancers; Gene Expression Regulation; Genes; Genetic; Genome; Genotype-Tissue Expression Project; Goals; Grant; Interruption; Laboratories; Link; Modeling; Mutation; Myelin; Myelin Sheath; Nerve; Oligodendroglia; Pathogenesis; Patients; Pelizaeus-Merzbacher Disease; Pilot Projects; Predictive Value; Regulation; Regulatory Element; Resolution; Resources; Role; Site; TCF7L2 gene; Testing; Untranslated RNA; Validation; Variant; autism spectrum disorder; computational pipelines; disorder risk; epigenome; epigenomics; functional genomics; gene regulatory network; genetic variant; genome sequencing; genome wide association study; improved; leukodystrophy; model development; mouse model; multiple omics; nervous system development; network models; risk variant; tool; transcription factor; white matter; white matter change; whole genome

PROJECT ABSTRACT Studies of several Intellectual/Developmental Disability (IDD) conditions have implicated white matter alterations in their pathogenesis, and mouse models of oligodendrocyte defects have validated mechanistic connections with cognitive disorders. In addition, many genetic causes of leukodystrophies have been identified, including mutations affecting the PLP1 gene in Pelizaeus-Merzbacher disease. However, due to the lack of tools to interpret significant variations in the noncoding genome, the ultimate influence of most genetic variants unfortunately remain uncharacterized. With the resources of PsychEncode and GTEx, a number of tools have emerged that can be integrated to create a network model of Transcription Factors (TFs) and their binding sites (TFBS), and several relevant datasets of the oligodendrocyte epigenome have emerged. The goal of this proposal is to integrate these epigenomic resources with newly available eQTL resources to develop a model that will improved predictive value in deciphering Whole Genome Sequencing (WGS) data from patients with a variety of developmental disabilities related to white matter changes. Along with creating the model, we will integrate motif analysis of known TFs involved in oligodendrocyte development (MYRF, SOX10, OLIG2, TCF4 and CHD7/8) to determine if variants alter transcription factor binding sites (TFBS) in oligodendrocyte-expressed genes. We anticipate that creation an improved oligodendrocyte GRN will lead to collaborative grant collaborations in several IDD conditions, such as Autism Spectrum Disorder (ASD), to elucidate the effects of noncoding changes in WGS and link them to perturbations in the oligodendrocyte network.

项目摘要