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RNA. 2013 Jun;19(6):725-32. doi: 10.1261/rna.037903.112. Epub 2013 Apr 18.

Analysis and design of RNA sequencing experiments for identifying RNA editing and other single-nucleotide variants.

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Department of Integrative Biology and Physiology, Bioinformatics Interdepartmental Program, and the Molecular Biology Institute, University of California, Los Angeles, California 90095, USA.


RNA-sequencing (RNA-Seq) technologies hold enormous promise for novel discoveries in genomics and transcriptomics. In the past year, a surge of reports has analyzed RNA-Seq data to gain a global view of the RNA editome. Opposing results have been presented, giving rise to extensive debate surrounding one of the first such studies in which a daunting list of all 12 types of RNA-DNA differences (RDDs) were identified. Although a consensus is forming that some of the initial "paradigm-shifting" results of this study may be questionable, recent reports on this topic differed in terms of the number and relative abundance of each type of RDD. Many outstanding issues exist, most importantly, the choice of bioinformatic approaches. Here we discuss the critical data analysis and experimental design issues of such studies to enable improved systematic investigation of the largely unexplored frontier of single-nucleotide variants in RNA.


RNA editing; RNA-Seq; RNA–DNA difference; mapping error; read mapping

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