
Pratibha Singh
Assistant researcher

Discriminative prediction of A-To-I RNA editing events from DNA sequence
Author
Summary, in 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.
Department/s
- Diabetes - Molecular Metabolism
- Genomics, Diabetes and Endocrinology
- Breastcancer-genetics
- Centre for Analysis and Synthesis
- EXODIAB: Excellence of Diabetes Research in Sweden
Publishing year
2016-10-01
Language
English
Publication/Series
PLoS ONE
Volume
11
Issue
10
Document type
Journal article
Publisher
Public Library of Science (PLoS)
Topic
- Cell and Molecular Biology
Status
Published
Research group
- Diabetes - Molecular Metabolism
- Genomics, Diabetes and Endocrinology
ISBN/ISSN/Other
- ISSN: 1932-6203