The goal of this project is to systematically investigate how genetic variants affect post- transcriptional regulation in Alzheimer?s disease (AD). Recently, an increasing number of genetic variants have been cataloged that confer risks to AD. However, it remains a great challenge to identify causal variants and elucidate their potential function relevant to disease pathogenesis and progression. Compared to the progress in pinpointing genetic variants that alter transcriptional regulation or protein-coding sequences, how genetic variants may affect post-transcriptional processes is poorly understood. Many of the newly identified AD-associated variants reside in non-coding regions, such as introns and untranslated regions (UTRs), that may confer regulatory function to the related gene, especially at the level of post-transcriptional regulation. Therefore, there is a great demand for in-depth studies of the functional impacts of genetic variants on post-transcriptional regulation. In human, a myriad of processes mediate RNA expression at the post-transcriptional stage, such as splicing, editing, polyadenylation and mRNA decay. Post-transcriptional processes are extremely versatile, yet closely regulated, affecting most human genes. RNA-binding proteins (RBPs) are central players in post- transcriptional regulation, many of which are known to be involved in AD-related pathways. In this project, we will capitalize on the large collection of public data sets on RBP-RNA interaction profiling, RNA-Seq and genotyping data collected from AD and control subjects, and our in- house data generation. We will develop and apply novel methodologies to make full use of these data sets, complemented by further bioinformatic prediction and high-throughput experimental testing, to predict and validate genetic variants that alter gene expression post- transcriptionally in AD. This work will allow a previously unattained level of understanding of genetic variants in post-transcriptional regulation and provide new means to tackle the imperative task of functional interpretation of genetic variants in AD.
Post-transcriptional regulation can significantly alter gene expression and contribute to Alzheimer?s disease (AD) mechanisms. The proposed research aims to combine bioinformatic and experimental methods to study functional genetic mutations or polymorphisms that cause post-transcriptional changes in AD. This work will provide mechanistic basis for how genetic variations may contribute to AD, such that future interventions can target specific genes therapeutically.
