Prioritization of splicing-altering genetic variants in Alzheimer's disease

项目摘要 该项目的目标是开发允许计算机预测的计算管道 阿尔茨海默病中干扰前-mRNA剪接及相关通路的功能性遗传变异 疾病(AD)。最近，在建立一个目录方面取得了巨大的成功。 不同患者队列中AD基因组中的遗传变异。下一个巨大的挑战是 确定因果变异并阐明其与疾病过程相关的潜在功能。至 为此，研究工作一直致力于研究位于蛋白质编码中的变体， 启动子和剪接位点区域，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体驻留在其他非编码区， 例如内含子，可以赋予相关基因调控功能。它的作用机制 这些变种一直很难破译。预计其中许多可能会在 转录后水平，从而影响mRNA的表达。在人类中，有无数的过程 在转录后阶段调节RNA的表达，其中之一是剪接。拼接 是哺乳动物基因表达的必要步骤，选择性剪接影响大多数人类 基因。最近的文献报道，RNA剪接是GVS和疾病之间的主要联系。 一般来说，据估计，导致人类基因突变的点突变有15%-60% 疾病破坏了剪接，突显了这一监管步骤的重要性。在AD中，异常 已在许多功能关键基因中检测到剪接，其中一些基因受 GVS。尽管剪接很重要，但如何准确识别剪接中的功能遗传变异 监管仍然是该领域的一个关键问题。为了解决这个问题，大量的 从AD和对照组收集的RNA-Seq和基因分型数据集代表着 无价的资源。我们将开发和应用新的方法来充分利用这些 数据集，辅以进一步的生物信息学预测和实验验证。这 这项工作将使对剪接中的遗传变异的理解达到前所未有的水平 规范，并提供新的方法来解决功能注释的紧迫任务 AD中的遗传变异。

Project Summary The goal of this project is to develop computational pipelines that allow in silico prediction of functional genetic variants that disrupt pre-mRNA splicing and related pathways in Alzheimer's disease (AD). Recently, tremendous success has been achieved in constructing a catalog of genetic variants in AD genomes of various patient cohorts. The next great challenge is to identify causal variants and elucidate their potential function relevant to 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, one of which being splicing. Splicing is an essential step of mammalian gene expression and alternative splicing affects most human genes. Recent literature reported that RNA splicing is a primary link between GVs and disease. In general, it was estimated that 15-60% of point mutations that result in human genetic diseases disrupt splicing, highlighting the importance of this regulatory step. In AD, aberrant splicing has been detected in many functionally critical genes, some of which are modulated by GVs. Despite the importance, how to accurately identify functional genetic variants in splicing regulation remains a key question in the field. To address this question, the large collection of RNA-Seq and genotyping data sets collected from AD and control subjects represent an invaluable resource. We will develop and apply novel methodologies to make full use of these data sets, complemented by further bioinformatic prediction and experimental validations. This work will allow a previously unattained level of understanding of genetic variants in splicing regulation and provide new means to tackle the imperative task of functional annotations of genetic variants in AD.