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

Evaluating the effect of splicing mutations on isoform networks in autism

评估剪接突变对自闭症亚型网络的影响

基本信息

批准号：
9101077
负责人：
LILIA M IAKOUCHEVA
金额：
$ 42.04万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-05-01 至 2021-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9101077
关键词：
16p11.2 Animal Model Attention Autistic Disorder Binding Biology Brain CRISPR/Cas technology Cells Copy Number Polymorphism Data Data Set Databases Development Disease Exhibits Future Gene Expression Genes Genotype-Tissue Expression Project Goals Human Information Networks Maps Mental disorders Methods Modeling Molecular Mutate Mutation Neurons Pathway interactions Patients Play Post-Translational Protein Processing Process Property Protein Isoforms Proteins Proteomics RNA Splicing Reading Reporting Risk Role Site Specificity Splice-Site Mutation Technology Testing Therapeutic Intervention Tissues Transcript Work Yang autism spectrum disorder base brain size disease-causing mutation exome follow-up genome sequencing human disease induced pluripotent stem cell insight interest molecular phenotype mouse model mutant nerve stem cell protein expression protein protein interaction public health relevance transcriptome sequencing transcriptomics whole genome

项目摘要

DESCRIPTION (provided by applicant): A large number of mutations contributing to psychiatric disorders have been identified. However, the mechanisms by which these mutations cause these diseases are still unknown. Computational approaches that integrate large and heterogeneous datasets will play crucial role in predicting molecular mechanisms behind psychiatric disease mutations. In our recent study (Lin et al, Neuron, 2015) we demonstrated how spatio-temporal protein interaction networks could help to identify a pathway that is likely involved in regulating brain size in the 16p11.2 copy number variant deletion and duplication carriers. Here, we propose to use similar approaches to construct the isoform-level co-expression and protein interaction networks for predicting functional impact of the de novo splice site mutations from the patients with autism spectrum disorder (ASD). More than 80 splice site de novo mutations are currently identified in the ASD patients, but not a single disease mechanism is established for any of these mutations. We hypothesize that isoform-level networks will provide us with a more detailed and realistic picture of the processes that are disrupted by the ASD mutations in the brain. To test this hypothesis, we propose an integrative approach that combines network biology, CRISPR/Cas technology, transcriptomic and proteomic methods to predict and validate the impact of splice site mutations on cellular and molecular pathways in the human (iPSCs) and animal models of ASD. The ultimate goal of this project is to predict and validate specific pathways that are impacted by the de novo ASD splice site mutations. We will achieve this goal through the following specific aims: (1) Build and analyze isoform-level networks of brain co-expressed and physically interacting proteins; (2) Map de novo ASD mutations onto isoform-level networks to predict their functional impact; (3) Validate the disrupted networks and pathways using CRISPR/Cas technology in neuronal and animal models. The proposed study will discover and characterize cellular and molecular processes that are disrupted by the de novo splice site ASD mutations. The pathways identified in this study could represent important new targets for future therapeutic intervention.