RBPbase v0.2.0 alpha

A COMPREHENSIVE DATABASE OF EUKARYOTIC RNA-BINDING PROTEINS (RBP) WITH THEIR RBP ANNOTATIONS


Welcome to RBPbase, a database that integrates high-throughput RNA-binding protein (RBP) detection studies. For context, we recommend our review on RNA-binding proteins [1], and the technical descriptions of RNA interactome capture (RIC) [2,3,4], a mass spectrometry (MS) based protocol. The latest refinements of this protocol include enhanced RIC (eRIC) [5] and many others which can be found under tab 'Studies'.


We accelerated the release of this first public version in response to the SARS-CoV-2 crisis. We will continuously introduce refinements and welcome feedback. While no SARS-CoV-2 RNA interactome is currently available, SARS-CoV-2 proteomics are already underway. Since SARS-CoV-2 is an RNA virus, it is expected to intensively use host RBPs for its replicative cycle. We hope that RBPbase will help to identify relevant host proteins as RBPs, which could be helpful for understanding viral biology and ultimately the design of therapeutic strategies. To support SARS-CoV-2 research the database also provides annotations for 332 experimentally validated SARS-CoV-2-human protein-protein interactions (PPIs) [6].


In these early versions, RBPbase functions as a table browser with search, filtering and downloading functions. We are committed adding latest high-throughput RBP interaction studies and annotations. In near future, RBPbase will get more sophisticated analysis and plotting functions to analyse your RIC studies here. Stay tuned.



            

References:
[1] Hentze, M.W., Castello, A., Schwarzl, T. and Preiss, T., 2018. A brave new world of RNA-binding proteins. Nature Reviews Molecular Cell Biology, 19(5), p.327. https://doi.org/10.1038/nrm.2017.130
[2] Baltz, A.G., Munschauer, M., Schwanh├Ąusser, B., Vasile, A., Murakawa, Y., Schueler, M., Youngs, N., Penfold-Brown, D., Drew, K., Milek, M. and Wyler, E., 2012. The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. Molecular cell, 46(5), pp.674-690. https://doi.org/10.1016/j.molcel.2012.05.021
[3] Castello, A., Fischer, B., Eichelbaum, K., Horos, R., Beckmann, B.M., Strein, C., Davey, N.E., Humphreys, D.T., Preiss, T., Steinmetz, L.M. and Krijgsveld, J., 2012. Insights into RNA biology from an atlas of mammalian mRNA-binding proteins. Cell, 149(6), pp.1393-1406. https://doi.org/10.1016/j.cell.2012.04.031
[4] Castello, A., Horos, R., Strein, C., Fischer, B., Eichelbaum, K., Steinmetz, L.M., Krijgsveld, J. and Hentze, M.W., 2013. System-wide identification of RNA-binding proteins by interactome capture. Nature protocols, 8(3), p.491. https://doi.org/10.1038/nprot.2013.020
[5] Perez-Perri, J.I., Rogell, B., Schwarzl, T., Stein, F., Zhou, Y., Rettel, M., Brosig, A. and Hentze, M.W., 2018. Discovery of RNA-binding proteins and characterization of their dynamic responses by enhanced RNA interactome capture. Nature communications, 9(1), pp.1-13. https://doi.org/10.1038/s41467-018-06557-8
[6] Gordon, D.E., Jang, G.M., Bouhaddou, M., Xu, J., Obernier, K., O'meara, M.J., Guo, J.Z., Swaney, D.L., Tummino, T.A., Huttenhain, R. and Kaake, R.M., 2020. A SARS-CoV-2-human protein-protein interaction map reveals drug targets and potential drug-repurposing. BioRxiv. https://doi.org/10.1101/2020.03.22.002386

About

Impressum


This database is hosted and maintained by

Hentze Group
European Molecular Biology Laboratory (EMBL)
Thomas Schwarzl, PhD, Staff Scientist in Hentze and Huber Group
Meyerhofstra├če 1
69117 Heidelberg.

Please contact biohentze@embl.de for support or inqueries.

FAQ

Frequently asked questions


Is the input data, code or shiny app available?

All code for the backend data generation can be found in this git repository: https://git.embl.de/schwarzl/rbpbasebackend . The shiny app and Dockerfile can be found in this git repository: https://git.embl.de/schwarzl/rbpbase

Why summarizing by gene identifiers and not protein identifiers?

The common identifiers were individually selected for each organism. Because protein identifiers are very unstable, gene identifiers were used to summarize reported RBPs. If any isoform of a protein was reported, the gene was marked as RNA-binding. To account for different genomic locations, unique identifiers were created from the reported gene names. If any of the gene identifiers was reported to be RNA-binding, the unique identifier was marked as RNA-binding. Genes without gene names kept their genomic identifier.

What Ensembl versions are the identified based on?

The identifiers are based on Ensembl ID version 92

How was the homology mapping done?

Homology mapping was done with EggNog database[1]. It will be revised soon.

Why is RBPbase a table browser and not a relational database?

The userbase, use cases and R/Shiny specific properties prefer precompiled tables with optional analytic or display features.

[1] Jensen, L.J., Julien, P., Kuhn, M., von Mering, C., Muller, J., Doerks, T. and Bork, P., 2007. eggNOG: automated construction and annotation of orthologous groups of genes. Nucleic acids research, 36(suppl_1), pp.D250-D254. https://doi.org/10.1093/nar/gkm796

Acknowledgements

Thank you very much


Eva Schitter for the work on homology mapping during an intership at the Hentze lab.


Wolfgang Huber for advice and feedback.


Josep Manel Andres Moscardo and EMBL IT Services for hosting the Shiny App and EMBL Bio-IT for hosting Gitlab services.