Abstract
RNA editing is a widespread post-transcriptional mechanism able to modify transcripts through insertions/deletions or base substitutions. It is prominent in mammals, in which millions of adenosines are deaminated to inosines by members of the ADAR family of enzymes. A-to-I RNA editing has a plethora of biological functions, but its detection in large-scale transcriptome datasets is still an unsolved computational task. To this aim, we developed REDItools, the first software package devoted to the RNA editing profiling in RNA-sequencing (RNAseq) data. It has been successfully used in human transcriptomes, proving the tissue and cell type specificity of RNA editing as well as its pervasive nature. Outcomes from large-scale REDItools analyses on human RNAseq data have been collected in our specialized REDIportal database, containing more than 4.5 million events. Here we describe in detail two bioinformatic procedures based on our computational resources, REDItools and REDIportal. In the first procedure, we outline a workflow to detect RNA editing in the human cell line NA12878, for which transcriptome and whole genome data are available. In the second procedure, we show how to identify dysregulated editing at specific recoding sites in post-mortem brain samples of Huntington disease donors. On a 64-bit computer running Linux with ≥32 GB of random-access memory (RAM), both procedures should take ~76 h, using 4 to 24 cores. Our protocols have been designed to investigate RNA editing in different organisms with available transcriptomic and/or genomic reads. Scripts to complete both procedures and a docker image are available at https://github.com/BioinfoUNIBA/REDItools.
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Data availability
Example datasets that include NA12878 RNAseq/WGS reads and RNAseq reads from BioProject PRJNA316625 are freely available at the ENA database (https://www.ebi.ac.uk/ena) or the SRA archive (https://www.ncbi.nlm.nih.gov/sra).
Code availability
REDItools source code is available at the GitHub website (https://github.com/BioinfoUNIBA/REDItools) under the MIT License. The code in this protocol has been peer reviewed.
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Acknowledgements
We kindly thank the ReCaS computing center at University of Bari for computational and technical assistance. We also acknowledge the PRACE project 2016163924 for computing resources. This work was supported by Elixir IIB and PRACE projects 2016163924 and 2018194670.
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G.P. and E.P. conceived the project. C.L.G. and E.P. designed and wrote the full analysis pipeline. C.L.G. performed extensive user testing of the software. M.A.T. created the docker image and implemented the statistical tests to calculate differential RNA editing. E.P. wrote the manuscript with input and editing from all authors.
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Peer review information Nature Protocols thanks Trees-Juen Chuang, Erez Levanon and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Key references using this protocol
D’Erchia, A. M. et al. Sci. Rep. 7, 10046 (2017): https://doi.org/10.1038/s41598-017-10488-7
Picardi, E., Horner, D. S. and Pesole, G. RNA 23, 860–865 (2017): https://doi.org/10.1261/rna.058271.116
Rossetti, C. et al. Leukemia 31, 2824–2832 (2017): https://doi.org/10.1038/leu.2017.134
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Lo Giudice, C., Tangaro, M.A., Pesole, G. et al. Investigating RNA editing in deep transcriptome datasets with REDItools and REDIportal. Nat Protoc 15, 1098–1131 (2020). https://doi.org/10.1038/s41596-019-0279-7
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DOI: https://doi.org/10.1038/s41596-019-0279-7
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