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Front Bioeng Biotechnol. 2014 Dec 05;2:64. doi: 10.3389/fbioe.2014.00064. eCollection 2014.

Uncovering RNA Editing Sites in Long Non-Coding RNAs.

Frontiers in bioengineering and biotechnology

Ernesto Picardi, Anna Maria D'Erchia, Angela Gallo, Antonio Montalvo, Graziano Pesole

Affiliations

  1. Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari , Bari , Italy ; Institute of Biomembranes and Bioenergetics , Bari , Italy.
  2. RNA Editing Laboratory, Oncohaematology Department, IRCCS Ospedale Pediatrico Bambino Gesù , Rome , Italy.
  3. Department of Molecular Biology, Faculty of Medicine, University of Cantabria , Santander , Spain ; University Hospital Marqués de Valdecilla , Santander , Spain.

PMID: 25538940 PMCID: PMC4257104 DOI: 10.3389/fbioe.2014.00064

Abstract

RNA editing is an important co/post-transcriptional molecular process able to modify RNAs by nucleotide insertions/deletions or substitutions. In human, the most common RNA editing event involves the deamination of adenosine (A) into inosine (I) through the adenosine deaminase acting on RNA proteins. Although A-to-I editing can occur in both coding and non-coding RNAs, recent findings, based on RNA-seq experiments, have clearly demonstrated that a large fraction of RNA editing events alter non-coding RNAs sequences including untranslated regions of mRNAs, introns, long non-coding RNAs (lncRNAs), and low molecular weight RNAs (tRNA, miRNAs, and others). An accurate detection of A-to-I events occurring in non-coding RNAs is of utmost importance to clarify yet unknown functional roles of RNA editing in the context of gene expression regulation and maintenance of cell homeostasis. In the last few years, massive transcriptome sequencing has been employed to identify putative RNA editing changes at genome scale. Despite several efforts, the computational prediction of A-to-I sites in complete eukaryotic genomes is yet a challenging task. We have recently developed a software package, called REDItools, in order to simplify the detection of RNA editing events from deep sequencing data. In the present work, we show the potential of our tools in recovering A-to-I candidates from RNA-Seq experiments as well as guidelines to improve the RNA editing detection in non-coding RNAs, with specific attention to the lncRNAs.

Keywords: A-to-I editing; RNA editing; RNA-Seq; lncRNA; long non-coding RNA; ncRNA; transcriptome

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