Analysis of causal genetic variants in pre-mRNA processing using ENCODE data

描述(由申请人提供)：项目摘要本项目的目标是从功能上注释信使核糖核酸加工的调节中的遗传变异，这是对目前ENCODE数据分析重点的扩展和补充。最近，在构建疾病基因组或跨种群的遗传变异目录方面取得了巨大的成功。下一个重大挑战是识别因果变异，并阐明它们在生物学和疾病过程中的潜在功能。为此，研究人员一直致力于研究位于蛋白质编码、启动子和剪接位点区域的变体，因为它们对基因表达有明显的影响。然而，许多新发现的疾病相关变异存在于其他非编码区，如内含子，可能赋予相关基因调控功能。这些变种的机制一直很难破译。据估计，其中许多基因可能在转录后水平发挥作用，从而影响mRNA的加工。在人类中，mRNA的加工是极其多样的，但受到严格的调控，大多数基因至少参与了一种替代的加工途径。尽管这很重要，但如何准确识别这些过程中的功能性遗传变异仍然是该领域的一个关键问题。为了解决这个问题，大量的ENCODE表达和蛋白质结合数据是一个宝贵的资源。我们将开发新的分析策略，充分利用ENCODE和其他公开可用的数据集，并辅之以进一步的生物信息学预测和实验验证。这项工作将使对受基因调控的mRNA加工事件的检测达到前所未有的水平，并提供新的手段来解决基因变体的功能注释这一紧迫任务。

DESCRIPTION (provided by applicant): Project Summary The goal of this project is to functionally annotate genetic variants in the regulation of mRNA processing, which extends and complements the current focus of ENCODE data analysis. Recently, tremendous success has been achieved in constructing a catalog of genetic variants in disease genomes or across population. The next great challenge is to identify causal variants and elucidate their potential function in biological and disease processes. To this end, research efforts have been directed to studying variants located in protein-coding, promoter, and splice site regions due to their apparent impacts on gene expression. However, many of the newly identified disease-associated variants reside in other non-coding regions, such as introns, that may confer regulatory function to the related gene. The mechanisms of these variants have been hard to decipher. It is expected that many of them may function at the post-transcriptional level, thus affecting mRNA processing. In human, mRNA processing is extremely versatile, yet closely regulated, with most genes involved in at least one of the alternative processing pathways. Despite the importance, how to accurately identify functional genetic variants in these processes remains a key question in the field. To address this question, the large collection of ENCODE expression and protein-binding data represent an invaluable resource. We will develop novel analysis strategies to make full use of the ENCODE and other publicly available data sets, complemented by further bioinformatic prediction and experimental validations. This work will allow a previously unattained level of detection of genetically regulated mRNA processing events and provide new means to tackle the imperative task of functional annotations of genetic variants.