Albrecht Elias, Pelz Konstantin, Gress Alexander, Trung Hieu Nguyen, Kalinina Olga V, Kacprowski Tim, Baumbach Jan, List Markus, Tsoy Olga
Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Maximus-von-Imhof Forum 3, 85354 Freising, Germany.
Institute for Computational Systems Biology, University of Hamburg, Albert-Einstein-Ring 8-10, 22761 Hamburg, Germany.
Nucleic Acids Res. 2025 Jul 7;53(W1):W245-W252. doi: 10.1093/nar/gkaf384.
Changes in alternative splicing between groups or conditions contribute to protein-protein interaction rewiring, a consequence often neglected in data analysis. The web server and database DIGGER overcomes this limitation by augmenting a protein-protein interaction network with domain-domain interactions and splicing information. Here, we present DIGGER 2.0, which now features both experimental and newly added predicted domain-domain interactions. In addition to the human interactome, DIGGER 2.0 adds support for mouse as an important model organism. Additionally, we integrated the splicing analysis tool NEASE, which allows users to perform online splicing- and interactome-informed enrichment analysis on RNA-seq data. In two application cases (multiple sclerosis and mice models of cardiac diseases), we show the utility of DIGGER 2.0 for deeper exploration and functional interpretation of changes in alternative splicing in human and mouse disorders. DIGGER 2.0 is available at https://exbio.wzw.tum.de/digger/.
不同组或条件之间的可变剪接变化会导致蛋白质-蛋白质相互作用的重新连接，这一结果在数据分析中常常被忽视。网络服务器和数据库DIGGER通过用结构域-结构域相互作用和剪接信息扩充蛋白质-蛋白质相互作用网络，克服了这一局限性。在此，我们展示了DIGGER 2.0，它现在兼具实验性的以及新添加的预测结构域-结构域相互作用。除了人类相互作用组，DIGGER 2.0还增加了对作为重要模式生物的小鼠的支持。此外，我们整合了剪接分析工具NEASE，它允许用户对RNA测序数据进行在线剪接和相互作用组信息富集分析。在两个应用案例（多发性硬化症和心脏病小鼠模型）中，我们展示了DIGGER 2.0在深入探索和功能解释人类和小鼠疾病中可变剪接变化方面的效用。可通过https://exbio.wzw.tum.de/digger/获取DIGGER 2.0。
