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RNA Editing pp 193-212 | Cite as

High-Throughput Sequencing to Detect DNA-RNA Changes

  • Claudio Lo Giudice
  • Graziano Pesole
  • Ernesto PicardiEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 2181)

Abstract

手机体育投注平台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.

Key words

RNA editing Next-generation sequencing Transcriptomics Epigenetics RNA-Seq DNA-Seq 

Notes

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.

References

  1. 1.
    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
  2. 2.
    Nishikura K (2010) Functions and regulation of RNA editing by ADAR deaminases. Annu Rev Biochem 79:321–349.  
  3. 3.
    Maas S, Kawahara Y, Tamburro KM, Nishikura K (2006) A-to-I RNA editing and human disease. RNA Biol 3(1):1–9.  
  4. 4.
    Kung CP, Maggi LB Jr, Weber JD (2018) The role of RNA editing in cancer development and metabolic disorders. Front Endocrinol 9:762.  
  5. 5.
    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
  6. 6.
    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
  7. 7.
    Diroma MA, Ciaccia L, Pesole G, Picardi E (2019) Elucidating the editome: bioinformatics approaches for RNA editing detection. Brief Bioinform 20(2):436–447.  
  8. 8.
    Picardi E, Pesole G (2013) REDItools: high-throughput RNA editing detection made easy. Bioinformatics 29(14):1813–1814
  9. 9.
    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
  10. 10.
    Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14):1754–1760
  11. 11.
    Wu TD, Nacu S (2010) Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 26(7):873–881
  12. 12.
    Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12(4):357–360
  13. 13.
    Ramaswami G, Li JB (2014) RADAR: a rigorously annotated database of A-to-I RNA editing. Nucleic Acids Res 42(Database issue):D109–D113
  14. 14.
    Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9(4):357–359
  15. 15.
    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
  16. 16.
    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
  17. 17.
    Wang L, Wang S, Li W (2012) RSeQC: quality control of RNAseq experiments. Bioinformatics (Oxford, England) 28(16):2184–2185.  
  18. 18.
    Kent WJ (2002) BLAT—the BLAST-like alignment tool. Genome Res 12(4):656–664.  
  19. 19.
    Wang M, Kong L (2019) pblat: a multithread blat algorithm speeding up aligning sequences to genomes. BMC Bioinform 20(1):28.  
  20. 20.
    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
  21. 21.
    Hatem A, Bozdag D, Toland AE, Catalyurek UV (2013) Benchmarking short sequence mapping tools. BMC Bioinformatics 14:184

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2021

Authors and Affiliations

  • Claudio Lo Giudice
    • 1
  • Graziano Pesole
    • 1
    • 2
  • Ernesto Picardi
    • 1
    • 2
    Email author
  1. 1.Institute of Biomembranes, Bioenergetics and Molecular BiotechnologiesNational Research CouncilBariItaly
  2. 2.Department of Biosciences, Biotechnology and BiopharmaceuticsUniversity of BariBariItaly

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