Olga Tsoy1*, Zakaria Louadi2, Chit Tong Lio2, Jan Baumbach1, Olga Kalinina3,4, Alexander Gress3,4, Tim Kacprowski5,6, and Markus List2
1University of Hamburg, Notkestrasse 9, Hamburg, Germany
2Technical University of Munich, Maximus-von-Imhof-Forum 3, Freising, Germany
3Helmholtz Centre for Infection Research, Inhoffenstraße 7, Saarbrücken, Germany.
4Saarland University, Homburg, Germany
5PLRI of TU Braunschweig and MHH, Rebenring 56, Brunswick, Germany
6BRICS, TU Braunschweig, Rebenring 56, Brunswick, Germany
olga.tsoy [at] uni-hamburg.de
Abstract
Alternative splicing (AS) can impact protein structure and lead to protein-protein interaction (PPI) rewiring. Available PPI networks neglect alternative splicing isoforms: as interactions might happen only between a subset of isoforms, the PPI network contains both false-positive and false-negative interactions. Since it is not feasible to validate all isoform-isoform interactions experimentally, we present a set of tools to investigate AS on a network level: DIGGER to map splicing to the PPI network, as well as NEASE and Spycone to evaluate the functional consequences of network rewiring.
DIGGER (https://exbio.wzw.tum.de/digger) integrates PPIs, domain-domain, and residue-level interactions – the structures that might be spliced in or out and result in interaction gain or loss. Users can explore possible rewiring for an isoform or exon of interest and extract relevant subnetworks. NEASE (https://github.com/louadi/NEASE) identifies pathways that are significantly affected by network rewiring. NEASE extends classic gene set enrichment analysis by considering isoform-specific interactions affecting pathways. Spycone (https://github.com/yollct/spycone) addresses the time-course changes in AS. It searches for isoforms that demonstrate similar temporal splicing patterns and reflect the splicing co-regulation. Spycone further integrates gene set, network, and splicing-aware NEASE enrichment.
Overall, we offer a splicing-focused network analysis toolkit that allows for studying the mechanistic consequences of AS.
Keywords: bioinformatics, protein-protein interactions, alternative splicing, network enrichment, time series analysis
