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Discriminative prediction of A-To-I RNA editing events from DNA sequence

  • Jiangming Sun
  • Yang De Marinis
  • Peter Osmark
  • Pratibha Singh
  • Annika Bagge
  • Berengere Valtat
  • Petter Vikman
  • Peter Spégel
  • Hindrik Mulder
Publishing year: 2016-10-01
Language: English
Publication/Series: PLoS ONE
Volume: 11
Issue: 10
Document type: Journal article
Publisher: Public Library of Science

Abstract english

RNA editing is a post-transcriptional alteration of RNA sequences that, via insertions, deletions or base substitutions, can affect protein structure as well as RNA and protein expression. Recently, it has been suggested that RNA editing may be more frequent than previously thought. A great impediment, however, to a deeper understanding of this process is the paramount sequencing effort that needs to be undertaken to identify RNA editing events. Here, we describe an in silico approach, based on machine learning, that ameliorates this problem. Using 41 nucleotide long DNA sequences, we show that novel A-to-I RNA editing events can be predicted from known A-to-I RNA editing events intra- and interspecies. The validity of the proposed method was verified in an independent experimental dataset. Using our approach, 203 202 putative A-to-I RNA editing events were predicted in the whole human genome. Out of these, 9% were previously reported. The remaining sites require further validation, e.g., by targeted deep sequencing. In conclusion, the approach described here is a useful tool to identify potential A-to-I RNA editing events without the requirement of extensive RNA sequencing.


  • Cell and Molecular Biology


  • Molecular Metabolism
  • Diabetes and Endocrinology
  • ISSN: 1932-6203
Peter Spegel
E-mail: peter [dot] spegel [at] chem [dot] lu [dot] se


Centre for Analysis and Synthesis


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