Systematic approaches to deciphering regulation and function of RNA editing in brain

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Project Summary Recent advances in sequencing technologies and bioinformatic methodologies have enabled great progress in better understanding RNA processing, regulation and modification. RNA editing is a prevalent type of RNA modification where the RNA sequences are altered through insertion, deletion or substitution of nucleotides. In mammals, the most common type of RNA editing is adenosine to inosine (A-to-I) editing. A-to-I editing is essential for normal life and development. A handful of A-to-I editing sites have been discovered with critical roles in neuronal signaling, by modulating membrane excitability, neurotransmission plasticity and signal transduction. In addition, aberrant RNA editing has been implicated in human neuropsychiatric diseases, such as Autism, Alzheimer’s disease, depression, schizophrenia, and amyotrophic lateral sclerosis. While numerous RNA editing sites have been identified via RNA-sequencing (RNA-seq) and related technologies, major challenges exist in understanding the function and regulation of RNA editing. The vast majority of known human RNA editing sites reside in non- coding regions, such as introns and untranslated regions, 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 RNA editing on post- transcriptional regulation. The regulatory mechanisms of RNA editing are poorly characterized. Except the ADAR enzymes, few proteins and their mechanisms of action have been examined for RNA editing. A major challenge is the lack of efficient and systematic methods to pinpoint novel regulators. In this project, we propose to extend our recent success at developing bioinformatic and experimental frameworks to address the above challenges. We will capitalize on the large collection of RNA-seq data sets derived from postmortem brain samples. 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 the molecular function of RNA editing and related regulatory mechanisms. This work will allow a previously unattained level of understanding of the molecular basis of RNA editing and provide new insights to the involvement of RNA editing in human biology.