Trans-acting RNA binding proteins regulate alternative polyadenylation
Alternative PolyAdenylation (APA) is a key post-transcriptional regulatory mechanism that varies the 3’UTR length of the majority of mRNAs, leading to modification of transcript stability, cellular localisation, and translation efficiency. However, the underlying mechanisms that lead to APA are not yet fully understood. We have discovered that the RNA-binding protein (RBP) Elav/HuR family regulates the mechanism of neuronal APA and alternative splicing. We hypothesise that this is a general mechanism involving other RBPs. Our understanding of how RBPs control mammalian APA is currently very limited, and the role of RBP-controlled APA in complex tissue organisation and function, and local cell-cell interactions, has not been previously investigated. We combine single-cell assays, CRISPR gene knockouts in transgenic CD8+ T cells, computational analysis and machine learning models to understand the functional and phenotypic implications of new roles of trans-acting RBPs in regulating APA in immune cell differentiation. We further integrate state-of-the-art high-resolution spatial transcriptomics (ST) high-throughput assays and advanced machine learning models to discover the diversity of APA isoforms and trans-acting RBPs across retinal cell types to uncover the RBP regulatory code of APA in spatio-temporal stress responses and cell-cell interactions.
A/Prof Jean Wen leads the “Computational Biology of RNAs and Functional Genomics” group at The John Curtin School of Medical Research (JCSMR), ANU. Her research portfolio is focused on exploring diverse modes of gene regulation through RNA processing, regulation, and evolution in biological systems and human diseases. She is an ANU PhD graduate with a background in Bioinformatics, Computer Science and Engineering. She has trained in leading institutions in the world, including the Bioinformatics Center at Copenhagen University, Denmark, and Memorial Sloan-Kettering Cancer Center (MSKCC), New York. In late 2017, Dr Wen was awarded a prestigious ARC Future Fellowship and returned to ANU to establish her independent group. Dr Wen’s computational RNA biology group explores diverse modes of gene regulation through RNAs, including endogenous small interfering RNAs, highly conserved structural RNAs, microRNAs, RNA binding protein interactions, and RNA 3’ end processing. Wen’s group integrates advanced machine learning techniques, such as deep learning and state-of-the-art high-throughput genome-wide data analysis, including single-cell and spatial transcriptome analysis, to quantitively model RNA-mediated gene regulatory interactions. The group aims to deduce their role in regulating gene expression and cellular identity and their potential use for RNA-based biotechnologies and therapeutics.