Analysis of functional genetic variants in RNA processing and expression

项目摘要 该项目的目标是对转录后基因变异进行功能性注释。 对RNA表达的调节，这是对ENCODE当前重点的扩展和补充 数据分析。最近，在建立一个目录方面取得了巨大的成功。 疾病基因组或种群中的遗传变异。下一个巨大的挑战是 识别因果变异并阐明其在生物学和疾病中的潜在功能 流程。为此，研究工作一直致力于研究位于 蛋白质编码区、启动子区和剪接区对基因的明显影响 表情。然而，许多新发现的与疾病相关的变异存在于其他 非编码区，如内含子，可赋予相关基因调节功能。 这些变种的机制一直很难破译。预计他们中的许多人 可能在转录后水平发挥作用，从而影响mRNA的表达。在人类中，一个 在转录后阶段，有无数的过程调节RNA的表达，如剪接， 编辑、多聚腺苷酸化和信使核糖核酸衰变。转录后调控是极其多样的， 然而，它受到严格的监管，影响了大多数人类基因。尽管很重要，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。至 解决这个问题，大量的ENCODE表达和蛋白质结合数据 是一种无价的资源。我们将开发新的方法，充分利用 编码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。这项工作将使以前从未达到的水平 理解RNA表达和转录后调控中的遗传变异 为解决基因变异的功能注释这一紧迫任务提供了新的手段。

Project Summary The goal of this project is to functionally annotate genetic variants in post-transcriptional regulation of RNA expression, 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 expression. In human, a myriad of processes mediate RNA expression at the post-transcriptional stage, such as splicing, editing, polyadenylation and mRNA decay. Post-transcriptional regulation is extremely versatile, yet closely regulated, affecting most human genes. 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 methodologies 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 understanding of genetic variants in post-transcriptional regulation of RNA expression and provide new means to tackle the imperative task of functional annotations of genetic variants.