Bioinformatics Resources for RNA Editing

Maria Angela Diroma; Loredana Ciaccia; Graziano Pesole; Ernesto Picardi

doi:10.1007/978-1-0716-0787-9_11

Bioinformatics Resources for RNA Editing

Methods Mol Biol. 2021:2181:177-191. doi: 10.1007/978-1-0716-0787-9_11.

Authors

Maria Angela Diroma¹, Loredana Ciaccia², Graziano Pesole^{1

2}, Ernesto Picardi^{3

4}

Affiliations

¹ Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari, Italy.
² Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari "A. Moro", Bari, Italy.
³ Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari, Italy. ernesto.picardi@uniba.it.
⁴ Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari "A. Moro", Bari, Italy. ernesto.picardi@uniba.it.

PMID: 32729081
DOI: 10.1007/978-1-0716-0787-9_11

Abstract

RNA editing is a widespread co/posttranscriptional mechanism affecting primary RNAs by specific nucleotide modifications, which plays relevant roles in molecular processes including regulation of gene expression and/or processing of noncoding RNAs (ncRNAs). In recent years, the detection of editing sites has been greatly improved through the availability of high-throughput RNA sequencing technologies. Several pipelines, employing various read mappers and variant callers with a wide range of adjustable parameters, are currently available for the detection of RNA editing events. Hereafter, we describe some of the most recent and popular tools and provide guidelines for the detection of RNA editing in massive transcriptome data.

Keywords: A-to-I editing; Bioinformatics; Deep sequencing; RNA editing; RNA-Seq; Transcriptome.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Computational Biology / methods*
Computational Biology / standards
High-Throughput Nucleotide Sequencing
Humans
Practice Guidelines as Topic
RNA Editing / physiology*
Sequence Analysis, RNA
Transcriptome