LoDEI: a robust and sensitive tool to detect transcriptome-wide differential A-to-I editing in RNA-seq data.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
23 Oct 2024
23 Oct 2024
Historique:
received:
24
04
2024
accepted:
02
10
2024
medline:
24
10
2024
pubmed:
24
10
2024
entrez:
23
10
2024
Statut:
epublish
Résumé
RNA editing is a highly conserved process. Adenosine deaminase acting on RNA (ADAR) mediated deamination of adenosine (A-to-I editing) is associated with human disease and immune checkpoint control. Functional implications of A-to-I editing are currently of broad interest to academic and industrial research as underscored by the fast-growing number of clinical studies applying base editors as therapeutic tools. Analyzing the dynamics of A-to-I editing, in a biological or therapeutic context, requires the sensitive detection of differential A-to-I editing, a currently unmet need. We introduce the local differential editing index (LoDEI) to detect differential A-to-I editing in RNA-seq datasets using a sliding-window approach coupled with an empirical q value calculation that detects more A-to-I editing sites at the same false-discovery rate compared to existing methods. LoDEI is validated on known and novel datasets revealing that the oncogene MYCN increases and that a specific small non-coding RNA reduces A-to-I editing.
Identifiants
pubmed: 39443485
doi: 10.1038/s41467-024-53298-y
pii: 10.1038/s41467-024-53298-y
doi:
Substances chimiques
Adenosine
K72T3FS567
Adenosine Deaminase
EC 3.5.4.4
Inosine
5A614L51CT
N-Myc Proto-Oncogene Protein
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
9121Subventions
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : SFB 960/3, Project B14
Informations de copyright
© 2024. The Author(s).
Références
Boccaletto, P. et al. MODOMICS: a database of RNA modification pathways. 2021 update. Nucleic Acids Res. 50, D231–D235 (2021).
doi: 10.1093/nar/gkab1083
pmcid: 8728126
Wiener, D. & Schwartz, S. The epitranscriptome beyond m6A. Nat. Rev. Genet. 22, 119–131 (2020).
doi: 10.1038/s41576-020-00295-8
pubmed: 33188361
Nishikura, K. Functions and regulation of RNA editing by ADAR deaminases. Annu. Rev. Biochem. 79, 321–349 (2010).
doi: 10.1146/annurev-biochem-060208-105251
pubmed: 20192758
pmcid: 2953425
Medina-Munoz, H. C. et al. Expanded palette of RNA base editors for comprehensive RBP-RNA interactome studies. Nat. Commun. 15, https://doi.org/10.1038/s41467-024-45009-4 (2024).
Monian, P. et al. Endogenous ADAR-mediated RNA editing in non-human primates using stereopure chemically modified oligonucleotides. Nat. Biotechnol. 40, 1093–1102 (2022).
doi: 10.1038/s41587-022-01225-1
pubmed: 35256816
Baker, A. R. & Slack, F. J. ADAR1 and its implications in cancer development and treatment. Trends Genet. 38, 821–830 (2022).
doi: 10.1016/j.tig.2022.03.013
pubmed: 35459560
pmcid: 9283316
Slotkin, W. & Nishikura, K. Adenosine-to-inosine RNA editing and human disease. Genome Med. 5, 105 (2013).
doi: 10.1186/gm508
pubmed: 24289319
pmcid: 3979043
Diaz Quiroz, J. F., Siskel, L. D. & Rosenthal, J. J. Site-directed A → I RNA editing as a therapeutic tool: moving beyond genetic mutations. RNA 29, 498–505 (2023).
doi: 10.1261/rna.079518.122
pubmed: 36669890
pmcid: 10019371
Nishikura, K. A-to-I editing of coding and non-coding RNAs by ADARs. Nat. Rev. Mol. Cell Biol. 17, 83–96 (2015).
doi: 10.1038/nrm.2015.4
pubmed: 26648264
pmcid: 4824625
Eisenberg, E. & Levanon, E. Y. A-to-I RNA editing—immune protector and transcriptome diversifier. Nat. Rev. Genet. 19, 473–490 (2018).
doi: 10.1038/s41576-018-0006-1
pubmed: 29692414
Wulff, B.-E., Sakurai, M. & Nishikura, K. Elucidating the inosinome: global approaches to adenosine-to-inosine RNA editing. Nat. Rev. Genet. 12, 81–85 (2010).
doi: 10.1038/nrg2915
pubmed: 21173775
pmcid: 3075016
Liddicoat, B. J. et al. RNA editing by ADAR1 prevents MDA5 sensing of endogenous dsRNA as nonself. Science 349, 1115–1120 (2015).
doi: 10.1126/science.aac7049
pubmed: 26275108
pmcid: 5444807
Gatsiou, A. et al. The RNA editor ADAR2 promotes immune cell trafficking by enhancing endothelial responses to interleukin-6 during sterile inflammation. Immunity 56, 979–997.e11 (2023).
doi: 10.1016/j.immuni.2023.03.021
pubmed: 37100060
Gan, W. L., Ng, L., Ng, B. Y. L. & Chen, L. Recent Advances in Adenosine-to-Inosine RNA Editing in Cancer 143–179 (Springer International Publishing, Cham, 2023).
Bhate, A., Sun, T. & Li, J. B. ADAR1: a new target for immuno-oncology therapy. Mol. Cell 73, 866–868 (2019).
doi: 10.1016/j.molcel.2019.02.021
pubmed: 30849393
Bahn, J. H. et al. Accurate identification of A-to-I RNA editing in human by transcriptome sequencing. Genome Res. 22, 142–150 (2011).
doi: 10.1101/gr.124107.111
pubmed: 21960545
Hung, T. et al. The Ro60 autoantigen binds endogenous retroelements and regulates inflammatory gene expression. Science 350, 455–459 (2015).
doi: 10.1126/science.aac7442
pubmed: 26382853
pmcid: 4691329
Liang, Y., Chen, F., Wang, K. & Lai, L. Base editors: development and applications in biomedicine. Front. Med. 17, 359–387 (2023).
doi: 10.1007/s11684-023-1013-y
pubmed: 37434066
Picardi, E. & Pesole, G. REDItools: high-throughput RNA editing detection made easy. Bioinformatics 29, 1813–1814 (2013).
doi: 10.1093/bioinformatics/btt287
pubmed: 23742983
Flati, T. et al. HPC-REDItools: a novel HPC-aware tool for improved large scale RNA-editing analysis. BMC Bioinform. 21, https://doi.org/10.1186/s12859-020-03562-x (2020).
Zhang, Q. & Xiao, X. Genome sequence-independent identification of RNA editing sites. Nat. Methods 12, 347–350 (2015).
doi: 10.1038/nmeth.3314
pubmed: 25730491
pmcid: 4382388
Ramaswami, G. & Li, J. B. RADAR: a rigorously annotated database of A-to-I RNA editing. Nucleic Acids Res. 42, D109–D113 (2013).
doi: 10.1093/nar/gkt996
pubmed: 24163250
pmcid: 3965033
Picardi, E., D’Erchia, A. M., Giudice, C. L. & Pesole, G. REDIportal: a comprehensive database of A-to-I RNA editing events in humans. Nucleic Acids Res. 45, D750–D757 (2016).
doi: 10.1093/nar/gkw767
pubmed: 27587585
pmcid: 5210607
Freund, E. C. et al. Unbiased identification of trans regulators of ADAR and A-to-I RNA editing. Cell Rep. 31, 107656 (2020).
doi: 10.1016/j.celrep.2020.107656
pubmed: 32433965
pmcid: 7306178
John, D., Weirick, T., Dimmeler, S. & Uchida, S. RNAEditor: easy detection of RNA editing events and the introduction of editing islands. Brief. Bioinform. bbw087 https://doi.org/10.1093/bib/bbw087 (2016).
Kofman, E., Yee, B., Medina-Munoz, H. C. & Yeo, G. W. FLARE: a fast and flexible workflow for identifying RNA editing foci. BMC Bioinform. 24, https://doi.org/10.1186/s12859-023-05452-4 (2023).
Roth, S. H., Levanon, E. Y. & Eisenberg, E. Genome-wide quantification of ADAR adenosine-to-inosine RNA editing activity. Nat. Methods 16, 1131–1138 (2019).
doi: 10.1038/s41592-019-0610-9
pubmed: 31636457
Piechotta, M., Wyler, E., Ohler, U., Landthaler, M. & Dieterich, C. JACUSA: site-specific identification of RNA editing events from replicate sequencing data. BMC Bioinform. 18, https://doi.org/10.1186/s12859-016-1432-8 (2017).
Tran, S. S., Zhou, Q. & Xiao, X. Statistical inference of differential RNA-editing sites from RNA-sequencing data by hierarchical modeling. Bioinformatics 36, 2796–2804 (2020).
doi: 10.1093/bioinformatics/btaa066
pubmed: 32003773
pmcid: 8453238
Hwang, T. et al. Dynamic regulation of RNA editing in human brain development and disease. Nat. Neurosci. 19, 1093–1099 (2016).
doi: 10.1038/nn.4337
pubmed: 27348216
Han, L. et al. The genomic landscape and clinical relevance of A-to-I RNA editing in human cancers. Cancer Cell 28, 515–528 (2015).
doi: 10.1016/j.ccell.2015.08.013
pubmed: 26439496
pmcid: 4605878
Piechotta, M., Naarmann-de Vries, I. S., Wang, Q., Altmüller, J. & Dieterich, C. RNA modification mapping with JACUSA2. Genome Biol. 23, https://doi.org/10.1186/s13059-022-02676-0 (2022).
Giudice, C. L. et al. Quantifying RNA editing in deep transcriptome datasets. Front. Genet. 11, https://doi.org/10.3389/fgene.2020.00194 (2020).
Storey, J. D. & Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl Acad. Sci. USA 100, 9440–9445 (2003).
doi: 10.1073/pnas.1530509100
pubmed: 12883005
pmcid: 170937
Efron, B. Large-scale simultaneous hypothesis testing. J. Am. Stat. Assoc. 99, 96–104 (2004).
doi: 10.1198/016214504000000089
John, M. et al. Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributions. Bioinformatics 38, ii5–ii12 (2022).
doi: 10.1093/bioinformatics/btac455
pubmed: 36124808
pmcid: 9486594
Quinones-Valdez, G. et al. Regulation of RNA editing by RNA-binding proteins in human cells. Commun. Biol. 2, https://doi.org/10.1038/s42003-018-0271-8 (2019).
Roth, S. H. et al. Increased RNA editing may provide a source for autoantigens in systemic lupus erythematosus. Cell Rep. 23, 50–57 (2018).
doi: 10.1016/j.celrep.2018.03.036
pubmed: 29617672
pmcid: 5905401
Shi, Y. et al. Aberrant splicing in neuroblastoma generates RNA-fusion transcripts and provides vulnerability to spliceosome inhibitors. Nucleic Acids Res. 49, 2509–2521 (2021).
doi: 10.1093/nar/gkab054
pubmed: 33555349
pmcid: 7969022
Weigert, N. et al. Detection of a 7SL RNA-derived small non-coding RNA using Molecular Beacons in vitro and in cells. Biol. Chem. 404, 1123–1136 (2023).
doi: 10.1515/hsz-2023-0185
pubmed: 37632732
Pecori, R. et al. ADAR RNA editing on antisense RNAs results in apparent U-to-C base changes on overlapping sense transcripts. Front. Cell Dev. Biol. 10, https://doi.org/10.3389/fcell.2022.1080626 (2023).
Zhang, F., Lu, Y., Yan, S., Xing, Q. & Tian, W. SPRINT: an SNP-free toolkit for identifying RNA editing sites. Bioinformatics 33, 3538–3548 (2017).
doi: 10.1093/bioinformatics/btx473
pubmed: 29036410
pmcid: 5870768
Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766–D773 (2018).
doi: 10.1093/nar/gky955
pmcid: 6323946
Goldstein, B. et al. A-to-I RNA editing promotes developmental stage-specific gene and lncRNA expression. Genome Res. 27, 462–470 (2016).
doi: 10.1101/gr.211169.116
pubmed: 28031250
Mölder, F. et al. Sustainable data analysis with Snakemake. F1000Research 10, 33 (2021).
doi: 10.12688/f1000research.29032.2
pubmed: 34035898
pmcid: 8114187
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10 (2011).
doi: 10.14806/ej.17.1.200
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2012).
doi: 10.1093/bioinformatics/bts635
pubmed: 23104886
pmcid: 3530905
Torkler, P. et al. LoDEI: A Robust and Sensitive Tool to Detect Transcriptome-wide Differential A-to-I Editing in RNA-seq Data, Local Differential Editing Index—Results https://doi.org/10.5281/zenodo.12748069 (2024).
Torkler, P. et al. LoDEI: A Robust and Sensitive Tool to Detect Transcriptome-wide Differential A-to-I Editing in RNA-seq Data https://github.com/rna-editing1/lodei , https://zenodo.org/doi/10.5281/zenodo.13838679 (2024).
Torkler, P. et al. LoDEI: A Robust and Sensitive Tool to Detect Transcriptome-wide Differential A-to-I Editing in RNA-seq Data, Local Differential Editing Index—Test Dataset https://doi.org/10.5281/zenodo.12748864 (2024).
Bland, J. M. & Altman, D. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 327, 307–310 (1986).
doi: 10.1016/S0140-6736(86)90837-8