What we do
Individual cells of a body exhibit a stunning diversity of phenotypes, despite carrying a largely identical genetic makeup. This is due to the distinct ways in which the same genetic information can be read, interpreted and translated into function. At the RNA Regulatory Networks (RRN) Group at the Biozentrum in Basel we combine computational modelling with big data and experimental analysis to discover and understand the regulatory networks governing the interpretation of genetic information at the level of tissues and single cells.
Highlights 2017
Main highlights from our work in 2017 are the development of a few tools to analyze the regulation of 3' end processing and generation of alternative 3' untranslated regions. As these regions carry sequencing elements that are bound by RNA-binding proteins to modulate the stability, translation and localization of mRNAs, 3' UTRs are very important for the regulation of many aspects of gene expression. Recently, we have developed the PAQR method for quantifying poly(A) site usage from RNA-seq data and the KAPAC method to infer sequence motifs that best explain global changes in poly(A) site usage between samples. With these tools, we have started to unravel the regulation of 3' end processing in human cancer.
Main publications 2017
- Gruber AJ et al. Discovery of physiological and cancer-related regulators of 3′ UTR processing with KAPAC. bioRxiv 195958 2017
- Riba A et al. Explicit Modeling of siRNA-Dependent On-and Off-Target Repression Improves the Interpretation of Screening Results. Cell Systems 2017 2(4): 182-193. e4.
- Gumienny R et al. High-throughput identification of C/D box snoRNA targets with CLIP and RiboMeth-seq. Nucleic Acids Res. 45(5): 2341-2353. 2017
