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Computational Detection of Plant RNA Editing Events

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RNA Editing

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2181))

Abstract

Computers are able to systematically exploit RNA-seq data allowing us to efficiently detect RNA editing sites in a genome-wide scale. This chapter introduces a very flexible computational framework for detecting RNA editing sites in plant organelles. This framework comprises three major steps: RNA-seq data processing, RNA read alignment, and RNA editing site detection. Each step is discussed in sufficient detail to be implemented by the reader. As a study case, the framework will be used with publicly available sequencing data to detect C-to-U RNA editing sites in the coding sequences of the mitochondrial genome of Nicotiana tabacum.

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Author information

Authors and Affiliations

  1. Facultad de Ciencias Agrarias, IBAM, Universidad Nacional de Cuyo, CONICET, Almirante Brown, Argentina

    Alejandro A. Edera & M. Virginia Sanchez-Puerta

  2. Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Cuyo, Mendoza, Argentina

    M. Virginia Sanchez-Puerta

Authors
  1. Alejandro A. Edera
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  2. M. Virginia Sanchez-Puerta
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Corresponding author

Correspondence to Alejandro A. Edera .

Editor information

Editors and Affiliations

  1. Department of Biosciences, Biotechnology and Biopharmaceutics, Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, University of Bari “Aldo Moro”, Bari, Italy, Bari, Italy

    Ernesto Picardi

  2. Department of Biosciences, Biotechnology and Biopharmaceutics, Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, University of Bari “Aldo Moro”, Bari, Italy, Bari, Italy

    Graziano Pesole

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Edera, A.A., Sanchez-Puerta, M.V. (2021). Computational Detection of Plant RNA Editing Events. 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_2

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  • DOI: https://doi.org/10.1007/978-1-0716-0787-9_2

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0786-2

  • Online ISBN: 978-1-0716-0787-9

  • eBook Packages: Springer Protocols

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