A novel computational strategy to identify A-to-I RNA editing sites by RNA-Seq data: de novo detection in human spinal cord tissue

• Published in: PloS one Vol. 7; no. 9; p. e44184
• Main Authors: Picardi, Ernesto, Gallo, Angela, Galeano, Federica, Tomaselli, Sara, Pesole, Graziano
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 05.09.2012; Public Library of Science (PLoS)
• Subjects: Acids; Adenosine; Adenosine - genetics; Algorithms; Bioinformatics; Biology; Brain; Brain - metabolism; Cell adhesion & migration; Computation; Computational Biology - methods; Computational neuroscience; Data processing; Databases, Genetic; Deregulation; DNA sequencing; Editing; Enzymes; Exome; Gene expression; Gene Expression Regulation; Gene mapping; Gene sequencing; Genes; Genome, Human; Genomes; Genomics; Homeostasis; Humans; Inosine - genetics; Laboratories; Messenger RNA; Molecular biology; Mutation; Nervous system diseases; Neurodegenerative diseases; Neurodegenerative Diseases - metabolism; Neurological diseases; Post-transcription; Proteins; Reproducibility of Results; Ribonucleic acid; RNA; RNA Editing; RNA sequencing; Software; Spinal cord; Spinal Cord - metabolism; Spinal Cord - pathology; Transcription (Genetics); Transcriptome; Italy
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0044184

RNA editing is a post-transcriptional process occurring in a wide range of organisms. In human brain, the A-to-I RNA editing, in which individual adenosine (A) bases in pre-mRNA are modified to yield inosine (I), is the most frequent event. Modulating gene expression, RNA editing is essential for cellular homeostasis. Indeed, its deregulation has been linked to several neurological and neurodegenerative diseases. To date, many RNA editing sites have been identified by next generation sequencing technologies employing massive transcriptome sequencing together with whole genome or exome sequencing. While genome and transcriptome reads are not always available for single individuals, RNA-Seq data are widespread through public databases and represent a relevant source of yet unexplored RNA editing sites. In this context, we propose a simple computational strategy to identify genomic positions enriched in novel hypothetical RNA editing events by means of a new two-steps mapping procedure requiring only RNA-Seq data and no a priori knowledge of RNA editing characteristics and genomic reads. We assessed the suitability of our procedure by confirming A-to-I candidates using conventional Sanger sequencing and performing RNA-Seq as well as whole exome sequencing of human spinal cord tissue from a single individual.