Alternative splicing of CD19 mRNA in pediatric leukemia and CART-19 therapy resistance - Regulators, genetic variants and cryptic isoforms

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Alternative splicing increases protein diversity in eukaryotic cells, and plays an important role in development and tissue identity, but also in diseases such as cancer. Splicing reactions are catalysed by the spliceosome and modulated by auxiliary RNA-binding proteins (RBPs) which recognise nearby RNA sequences and guide spliceosome activity. The rules how multiple protein complexes dynamically interact on pre-mRNA sequence to control splicing (splice code) remain poorly understood.In this project, we employ a systems approach to better understand the splice code. As a prototypical example, we study the alternative splicing of the MSTR1 gene which is frequently altered in cancer and promotes tumour invasiveness. The developed tools will be extended to other interesting splicing scenarios, e.g. Alu exonisation.To study the determinants of splicing, we established a random mutagenesis screen in which we generate a library of more than 5,500 MST1R minigene variants, each containing on average three point mutations. We then transfect the library into HEK293T cells and assess splicing changes using targeted RNA-seq. Bioinformatics analyses will yield the frequency of five canonical splice isoforms for each of the mutants and will additionally detect novel splicing events arising from cryptic splice sites. These complex splicing patterns will be interpreted using mathematical models to infer changes in the kinetics of individual splice rates and to identify causative mutations. Taken together, Aim 1 will yield a compendium of cis-regulatory elements in MSTR1.In Aim 2, we plan to characterise how auxiliary RBPs and core splicing factors interpret the pre-mRNA sequence to establish context-specific splicing patterns. To this end, we will perform a knockdown screen in which we deplete 44 RBPs with a known role in MSTR1 splicing, and assess splicing patterns in each of the 5,500 minigene variants. Modelling of this comprehensive data set will reveal how RBPs impact on specific splice rates, which cis-regulatory elements they bind to, and how they assemble into larger RBP complexes. The resulting network will be subjected to a bioinformatics analysis to integrate prior knowledge, and selected interactions will be validated using pull-down experiments.In Aim 3, bioinformatics and genome-wide experimental approaches (RNA-seq, iCLIP) will be combined to assess whether determinants of MSTR1 splicing can be transferred to a global scale, thus providing general insights into the rules of splicing. A dynamic mathematical model of MSTR1 splicing will be derived to describe how RBP expression patterns influence splicing decisions. In conclusion, we propose a systematic approach to study prototypical splicing events with the potential to transfer the knowledge to a genome-wide scale. Our research provides insights into the modulation of disease-relevant splicing events by single-nucleotide polymorphisms (SNPs) and by the RBP content of the cell.