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

• 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
• 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

 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.

 描述（由申请人提供）：已鉴定出大量导致精神疾病的突变。然而，这些突变导致这些疾病的机制仍然未知。整合大型和异构数据集的计算方法将在预测精神疾病突变背后的分子机制方面发挥关键作用。在我们最近的研究中（Lin et al，Neuron，2015），我们证明了时空蛋白质相互作用网络如何帮助识别可能参与调节16p11.2拷贝数变异缺失和重复携带者大脑大小的途径。在这里，我们建议使用类似的方法来构建异构体水平的共表达和蛋白质相互作用网络，用于预测自闭症谱系障碍（ASD）患者的从头剪接位点突变的功能影响。目前在ASD患者中确定了超过80种剪接位点从头突变，但对于这些突变中的任何一种都没有建立单一的疾病机制。我们假设，亚型水平的网络将为我们提供一个更详细和更现实的图片的过程中被破坏的ASD突变在大脑中。为了验证这一假设，我们提出了一种综合方法，该方法结合了网络生物学，CRISPR/Cas技术，转录组学和蛋白质组学方法，以预测和验证剪接位点突变对人类（iPSC）和ASD动物模型中细胞和分子途径的影响。该项目的最终目标是预测和验证受ASD从头剪接位点突变影响的特定途径。我们将通过以下具体目标实现这一目标：（1）构建和分析大脑共表达和物理相互作用蛋白质的亚型水平网络;（2）将从头ASD突变映射到亚型水平网络上，以预测其功能影响;（3）在神经元和动物模型中使用CRISPR/Cas技术验证被破坏的网络和途径。拟议的研究将发现和表征从头剪接位点ASD突变破坏的细胞和分子过程。本研究中确定的途径可能代表未来治疗干预的重要新靶点。