Z02: Transcriptomics and proteomics platform

Long non-coding RNAs (lncRNAs) function via subcellular compartment-specific interactions with proteins and nucleic acids. RNA Binding Proteins (RBPs) form ribonucleoprotein (RNP) complexes that modulate several cellular processes, including gene transcription, chromatin and nuclear body formation or pre-mRNA splicing. Characterizing the interactions of lncRNAs with RBPs is crucial to infer their function and it is an overarching task of the TRR 267. The Z02 project provides state-of-the-art proteomics (Wittig) and machine learning approaches (Marsico) to characterize RNP complexes, determine the interactome of lncRNAs of interest and predict binding site locations at nucleotide resolution. During the previous funding period we contributed transcriptomics and proteomics to numerous projects of the consortium. A large fraction of the collaborations investigated the composition and dynamics of RNA-protein complexes. Annalisa Marsico is new to this consortium and brings 10-year experience in the development of tools and machine learning models to analyze and interpret large scale protein-RNA interaction data, from binding site prediction to subcellular-compartment specific functional annotation of lncRNAs. The mass spectrometry core unit in Frankfurt (Wittig) will provide standardized and novel procedures to (i) gain insights into the mode of action by isolating protein-bound lncRNAs, to identify the interacting proteins and characterize their RNA-binding domains and (ii) to study lncRNA-mediated proteome and protein complex remodeling in cells and tissues using deep proteome and complexome analysis. The Marsico lab in Munich will apply and further develop novel machine learning methods for the prediction of RBP-lncRNA regulatory interactions driving lncRNA molecular function, cellular localization and intron retention in the context of different projects inside the CRC. Predictions of RBP-RNA interaction sites and RNA motif analysis at single nucleotide resolution will aid several projects in designing targeted follow-up experiments. In silico identification of RNA motifs which mediate RBP-RNA interactions and function will enable prioritization of lncRNA-related functional genetic variants, and experimental validation using biochemical experiments in vitro. The results from the mass spectrometry data and computational predictions will be made available through a web portal representing an important resource for future studies.