APEXdb: A Comprehensive Dataset for APEX-Dependent RNA Proximity Biotinylation

APEXdb is the first publicly available, curated dataset dedicated to APEX-dependent proximity biotinylation strategies. This resource serves as a centralized hub for researchers to explore protein-RNA interactions and evaluate the spatial transcriptome within various cellular contexts. Resource Overview PLANSdb aggregates and annotates all currently available data regarding RNAs identified as interactors or neighbors of specific APEX-tagged protein baits. By compiling disparate experimental results into a unified framework, you can: Search for specific protein-RNA interactions Assess the specificity of identified interactors Distinguish between promiscuous "background" RNAs and biologically significant specific interactions Data Composition and Metadata To ensure reproducibility and facilitate cross-study comparisons, every entry in PLANSdb is enriched with comprehensive experimental metadata, including: Bait Information: Type of tag used and its specific cellular localization Biological Context: Cell line utilized and the specific stress conditions applied during the experiment Technical Specifications: Type of starting material for sequencing and the sequencing platform adopted Integration and Future Growth PLANSdb is not a static resource. It integrates novel data generated within this project and is designed for continuous expansion. Our team will regularly incorporate new datasets as they are produced, ensuring that the community has access to the most up-to-date proximity labeling information available. At the moment data from the following published works is integrated: Padrón, Alejandro et al. “Proximity RNA Labeling by APEX-Seq Reveals the Organization of Translation Initiation Complexes and Repressive RNA Granules.” Molecular cell vol. 75,4 (2019): 875-887.e5. doi:10.1016/j.molcel.2019.07.030 Barutcu, A Rasim et al. “Systematic mapping of nuclear domain-associated transcripts reveals speckles and lamina as hubs of functionally distinct retained introns.” Molecular cell vol. 82,5 (2022): 1035-1052.e9. doi:10.1016/j.molcel.2021.12.010 Fazal, Furqan M et al. “Atlas of Subcellular RNA Localization Revealed by APEX-Seq.” Cell vol. 178,2 (2019): 473-490.e26. doi:10.1016/j.cell.2019.05.027