Novel methods to detect and interpret splicing quantitative trait loci

家长补助金摘要 几乎所有与复杂疾病相关的遗传变异都是非编码的。许多非编码 疾病风险变异影响基因表达的幅度。然而，我们发现 mRNA剪接是遗传变异和复杂疾病之间的额外主要联系。 因此，了解遗传变异如何以及哪些影响RNA剪接可以极大地帮助 我们对非编码变异影响的理解。尽管RNA剪接的重要性 在介导疾病的遗传风险中，确定细胞中mRNA含量的主要测定法 或组织，多聚腺苷酸化mRNA的RNA-seq，主要捕获稳态mRNA同种型， 这不仅反映了RNA剪接，也反映了其他过程，如RNA衰变。此外，RNA- seq提供的关于RNA同种型生物发生途径的信息很少。然而，其他分析 超越RNA-seq，报告RNA剪接的途径， 衰减是非常缺乏的，这大大削弱了我们解释如何，以及哪些， 遗传变异影响RNA剪接。我们建议首先开发一系列新的基因组 检测以监测剪接途径，然后利用这些检测来确定 基因变异的影响我们将优化这些方法，以产生数据集来研究 遗传变异以前所未有的细节影响mRNA剪接的机制。 具体来说，为了实现我们的目标，我们建议i）开发全基因组检测来监测 以新的方式剪接，ii）使用这些测定法寻找剪接定量trail基因座，和iii） 通过一种综合的方法来解释遗传学的功能机制， 变体影响剪接。在这个项目结束时，我们将开发出基因组分析方法， 和计算方法，使我们能够深入了解 将序列变异与剪接变异并最终与疾病联系起来。

Summary of Parent Grant Nearly all genetic variants associated with complex disease are noncoding. Many noncoding disease risk variants affect the amplitude of gene expression. However, we have identified mRNA splicing as an additional primary link between genetic variants and complex diseases. Thus, an understanding of how, and which, genetic variants affect RNA splicing can greatly aid our understanding of the impact of noncoding variants. Despite the importance of RNA splicing in mediating genetic risk for disease, the dominant assay to determine mRNA content in a cell or tissue, RNA-seq of polyadenylated mRNA, primarily captures steady-state mRNA isoforms, which reflect not only RNA splicing but also other processes such as RNA decay. Further, RNA- seq provides little information on the pathway of RNA isoform biogenesis. Yet, other assays beyond RNA-seq that report on the pathway of RNA splicing and in a manner independent of decay are sorely lacking, significantly compromising our ability to account for how, and which, genetic variants affect RNA splicing. We propose to first develop a battery of novel genomic assays to monitor the pathway of splicing and then exploit these assays to define the impact of genetic variation on splicing. We will optimize such approaches to yield datasets to study the mechanisms by which genetic variants affect mRNA splicing at unprecedented detail. Specifically, to achieve our goals, we propose i) to develop genome-wide assays to monitor splicing in novel ways, ii) to search for splicing quantitative trail loci using these assays, and iii) to account through an integrated approach for the functional mechanisms by which genetic variants affect splicing. At the conclusion of this project, we will have developed genomic assays and computational approaches that allow us to reach a deep understanding of the mechanisms that link sequence variation to variation in splicing and ultimately to disease.