Valentin Schneider-Lunitz, Jorge Ruiz-Orera, Norbert Hubner, Sebastiaan van Heesch
RNA-binding proteins (RBPs) can regulate more than a single aspect of RNA metabolism. We searched for such previously undiscovered multifunctionality within a set of 143 RBPs, by defining the predictive value of RBP abundance for the transcription and translation levels of known RBP target genes across 80 human hearts. This led us to newly associate 27 RBPs with cardiac translational regulation in vivo.
RNA-protein interactions are crucial for a wide range of processes in multiple subcellular compartments, including RNA transcription, splicing, editing, transport, stability, localization, and translation. Using state-of-the-art mass spectrometry-based approaches, recent studies have identified up to thousands of potential RNA-binding proteins (RBPs), although for many their precise roles remain unknown.
Materials and methods
Ribosome profiling and RNA sequencing data analysis
We re-analyzed ribosome profiling (Ribo-seq) and matched RNA-seq datasets from 80 human hearts that we generated and published previously (EGA accession code: EGAS00001003263). In short, Ribo-seq reads were clipped for residual adapters using FASTX toolkit. Reads mapping to the mitochondrial RNA, ribosomal RNA and tRNA sequences were removed from downstream analysis.
Target gene enrichment
To identify RBPs that are putative modulators of target gene mRNA abundance and/or TE, we calculated the frequency with which target genes supported with CLIP-seq data correlated significantly with each RBP.
Increasing evidence suggests that RBPs can act as multifunctional gene expression regulators. Here, we built an in-silico method for the large-scale analysis of RBP-driven regulation using correlation as a proxy for mRNA abundance and translational efficiency (TE) of target genes across 80 human heart samples.
Citation: Schneider-Lunitz V, Ruiz-Orera J, Hubner N, van Heesch S (2021) Multifunctional RNA-binding proteins influence mRNA abundance and translational efficiency of distinct sets of target genes. PLoS Comput Biol 17(12): e1009658. https://doi.org/10.1371/journal.pcbi.1009658
Editor: Greg Tucker-Kellogg, National University of Singapore, SINGAPORE
Received: August 2, 2021; Accepted: November 18, 2021; Published: December 8, 2021.
Copyright: © 2021 Schneider-Lunitz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: This study includes no newly generated data deposited in external repositories. Accession numbers for all data used in this study have been reported within the Materials and Methods section with reference to the studies that generated and published the data. All scripts generated for the analyses are available via the GitHub development platform at: https://github.com/vschnei/Dual-function_RBP_manuscript_analysis.
Funding: This work was supported by the European Union’s Horizon 2020 research and innovation programme [European Research Council (ERC) advanced grant, grant agreement n° AdG788970 to N.H.; https://erc.europa.eu]; the Leducq Foundation [11 CVD-01 to N.H.; https://www.fondationleducq.org]; and the "Bundesministerium für Bildung und Forschung" [grant CaRNAtion to N.H; https://www.dfg.de]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.