Abstract
The advent of deep sequencing technologies has greatly improved the study of complex eukaryotic genomes and transcriptomes, allowing the investigation of posttranscriptional molecular mechanisms as alternative splicing and RNA editing at unprecedented throughput and resolution. The most prevalent type of RNA editing in higher eukaryotes is the deamination of adenosine to inosine (A-to-I) in double-stranded RNAs. Depending on the RNA type or the RNA region involved, A-to-I RNA editing contributes to the transcriptome and proteome diversity.
Hereafter, we present an easy and reproducible computational protocol for the identification of candidate RNA editing sites in humans using deep transcriptome (RNA-Seq) and genome (DNA-Seq) sequencing.
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References
Benne R, Van den Burg J, Brakenhoff JP, Sloof P, Van Boom JH, Tromp MC (1986) Major transcript of the frameshifted coxII gene from trypanosome mitochondria contains four nucleotides that are not encoded in the DNA. Cell 46(6):819–826
Nishikura K (2010) Functions and regulation of RNA editing by ADAR deaminases. Annu Rev Biochem 79:321–349. https://doi.org/10.1146/annurev-biochem-060208-105251
Maas S, Kawahara Y, Tamburro KM, Nishikura K (2006) A-to-I RNA editing and human disease. RNA Biol 3(1):1–9. https://doi.org/10.4161/rna.3.1.2495
Kung CP, Maggi LB Jr, Weber JD (2018) The role of RNA editing in cancer development and metabolic disorders. Front Endocrinol 9:762. https://doi.org/10.3389/fendo.2018.00762
Picardi E, Manzari C, Mastropasqua F, Aiello I, D’Erchia AM, Pesole G (2015) Profiling RNA editing in human tissues: towards the inosinome Atlas. Sci Rep 5:14941
Ramaswami G, Lin W, Piskol R, Tan MH, Davis C, Li JB (2012) Accurate identification of human Alu and non-Alu RNA editing sites. Nat Methods 9(6):579–581
Diroma MA, Ciaccia L, Pesole G, Picardi E (2019) Elucidating the editome: bioinformatics approaches for RNA editing detection. Brief Bioinform 20(2):436–447. https://doi.org/10.1093/bib/bbx129
Picardi E, Pesole G (2013) REDItools: high-throughput RNA editing detection made easy. Bioinformatics 29(14):1813–1814
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1):15–21
Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14):1754–1760
Wu TD, Nacu S (2010) Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 26(7):873–881
Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12(4):357–360
Ramaswami G, Li JB (2014) RADAR: a rigorously annotated database of A-to-I RNA editing. Nucleic Acids Res 42(Database issue):D109–D113
Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9(4):357–359
Li R, Yu C, Li Y, Lam TW, Yiu SM, Kristiansen K, Wang J (2009) SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 25(15):1966–1967
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Genome Project Data Processing S (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25(16):2078–2079
Wang L, Wang S, Li W (2012) RSeQC: quality control of RNAseq experiments. Bioinformatics (Oxford, England) 28(16):2184–2185. https://doi.org/10.1093/bioinformatics/bts356
Kent WJ (2002) BLAT—the BLAST-like alignment tool. Genome Res 12(4):656–664. https://doi.org/10.1101/gr.229202
Wang M, Kong L (2019) pblat: a multithread blat algorithm speeding up aligning sequences to genomes. BMC Bioinform 20(1):28. https://doi.org/10.1186/s12859-019-2597-8
Baruzzo G, Hayer KE, Kim EJ, Di Camillo B, FitzGerald GA, Grant GR (2017) Simulation-based comprehensive benchmarking of RNA-seq aligners. Nat Methods 14(2):135–139
Hatem A, Bozdag D, Toland AE, Catalyurek UV (2013) Benchmarking short sequence mapping tools. BMC Bioinformatics 14:184
Acknowledgments
We kindly thank Elixir-IIB (the Italian Infrastructure for Bioinformatics), the EPITRAN project (the European Epitranscriptomics Network), and the Bari ReCaS DataCenter. This work was supported by PRACE project no. 2018194670 to E.P.
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Lo Giudice, C., Pesole, G., Picardi, E. (2021). High-Throughput Sequencing to Detect DNA-RNA Changes. In: Picardi, E., Pesole, G. (eds) RNA Editing. Methods in Molecular Biology, vol 2181. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0787-9_12
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DOI: https://doi.org/10.1007/978-1-0716-0787-9_12
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