Isoform-level probabilistic transcriptome-wide association to undercover neurogenetic mechanisms underlying complex psychiatric traits

同种型水平的概率转录组范围与复杂精神特征背后的秘密神经发生机制的关联

• 批准号: 10738989
• 负责人: Michael Gandal
• 金额: $ 63.29万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-03 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10738989
• 关键词: Address; Adult; Affect; Alternative Splicing; Area; Biological; Biological Process; Brain; CRISPR/Cas technology; Candidate Disease Gene; Cell Line; Cells; Chromosome Mapping; Communities; Complex; Data; Development; Disease; Ensure; Event; Exhibits; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Risk; Genetic Variation; Genets; Genome engineering; Genomic approach; Genomics; Genotype; Heritability; Human; Individual; Intervention; Knock-in; Link; Linkage Disequilibrium; Maps; Mental disorders; Methods; Neurobiology; Neurons; Pathogenesis; Pattern; Phenotype; Protein Isoforms; Proteomics; Quality Control; Quantitative Trait Loci; RNA; RNA Splicing; Regulation; Reporting; Reproducibility of Results; Resolution; Resources; Risk; Sampling; Schizophrenia; Science; Signal Transduction; Specificity; TCF7L2 gene; Techniques; Therapeutic Intervention; Tissue-Specific Gene Expression; Tissues; Transcript; Uncertainty; Variant; Work; autism spectrum disorder; candidate validation; cell type; differential expression; disorder risk; fetal; functional genomics; genetic variant; genome resource; genome wide association study; genome-wide; genomic data; genomic locus; insight; nerve stem cell; neurobiological mechanism; neurogenetics; neuropsychiatry; new therapeutic target; novel; precision medicine; repaired; risk variant; targeted treatment; therapeutic development; trait; transcriptome; transcriptome sequencing; transcriptomic profiling; transcriptomics

PROJECT SUMMARY/ABSTRACT As large-scale genome-wide association studies (GWAS) rapidly identify associations with neurodevelopmental and psychiatric traits, the major defining challenge of the post-GWAS era is to rigorously define the neurobiological mechanisms underlying disease-associated genetic variation at scale. To this end, we and others have recently developed methods to directly integrate GWAS results with large-scale tissue-specific expression quantitative trait loci (eQTL) reference panels, enabling a transcriptome-wide association study (TWAS) – a powerful approach to identify genes whose expression is associated with genetic risk for disease. In parallel, emerging evidence has strongly implicated alternative splicing – a form of genetic regulation capable of generating an exponential number of unique RNA transcript isoforms from a single gene – as an important mechanism that exhibits dynamic patterns across development and is disrupted in the brains on individuals affected by psychiatric diseases, including autism and schizophrenia. Yet, no studies have systematically characterized the genetic regulation of isoform expression in human brain or its association with genetic risk for psychiatric disorders. This proposal seeks to develop a novel, isoform-level TWAS approach (iso-TWAS) to identify transcript-isoforms whose cis-regulated expression is associated with psychiatric disease risk. We will compile a large-scale functional genomic reference panel incorporating genotype and isoform quantifications from RNA-seq data of more than 3800 human brain samples, which we will leverage to perform iso-TWAS along with traditional gene-level TWAS for a host of neuropsychiatric traits. We will directly integrate isoform quantification uncertainties as well as probabilistic fine-mapping within our iso-TWAS framework, in order to ensure the robustness of resulting associations. We hypothesize that isoform-level characterization will provide substantially greater resolution to detect candidate biological mechanisms underlying psychiatric GWAS loci. Finally, predicted SNP-isoform-disease associations will be experimentally validated using genome-engineering in primary human neural progenitor cell (phNPC) lines followed by long-read RNA-sequencing and detailed cellular phenotyping. Together, these studies will systematically characterize a critical, yet underexplored area of genomic regulation in human brain, thereby providing novel insights into psychiatric disease mechanisms and identifying potential neurobiological targets for therapeutic development and intervention.

项目摘要/摘要 随着大规模基因组关联研究（GWAS）迅速识别与神经发育的关联 和精神科特征，后GWAS时代的主要决定性挑战是严格定义 在大规模上与疾病相关的遗传变异的神经生物学机制。为此，我们和其他人 最近开发了将GWAS结果与大规模组织特异性表达直接整合的方法 定量性状基因座（EQTL）参考面板，使整个转录组的关联研究（TWA） - A 识别其表达与疾病遗传风险相关的基因的强大方法。并联， 新兴证据强烈暗示替代剪接 - 一种能够的遗传调节形式 从单个基因产生指数级的唯一RNA转录本亚型 - 作为重要的 跨发育范围表现出动态模式并在大脑中破坏了个体的机制 受自闭症和精神分裂症在内的精神病影响。然而，没有研究有系统地 表征了人脑中同工型表达的遗传调节或其与遗传风险的关联 精神疾病。该提议旨在开发一种小说，同工级的两种方法（ISO-TWA） 识别其顺式调节表达与精神病风险有关的转录物相类型。我们将 编译编码基因型和同工型定量的大规模功能基因组参考面板 从3800多个人脑样品的RNA-seq数据中，我们将利用这些数据来执行ISO-TWAS 具有传统的基因级别TWA，具有许多神经精神特征。我们将直接整合同工型 在我们的ISO-TWAS框架内进行量化不确定性以及概率的精细映射，以便 确保产生关联的鲁棒性。我们假设同工型级特征将提供 大幅更大的分辨率来检测精神病基因座基因座基础的候选生物学机制。 最后，将使用基因组工程来实验验证预测的SNP-异型 - 疾病联合关联 在原代人神经祖细胞（PHNPC）线中，然后进行了长阅读的RNA测序和详细 细胞表型。总之，这些研究将系统地表征一个关键但毫无疑问的区域 人脑中基因组调节，从而提供了对精神病机制和 确定潜在的神经生物学靶标，以进行热发育和干预。