Abstract

BackgroundRNA editing is a type of post-transcriptional modification of RNA and belongs to the class of mechanisms that contribute to the complexity of transcriptomes. C-to-U RNA editing is commonly observed in plant mitochondria and chloroplasts. The in vivo mechanism of recognizing C-to-U RNA editing sites is still unknown. In recent years, many efforts have been made to computationally predict C-to-U RNA editing sites in the mitochondria of seed plants, but there is still no algorithm available for C-to-U RNA editing site prediction in the chloroplasts of seed plants.ResultsIn this paper, we extend our algorithm CURE, which can accurately predict the C-to-U RNA editing sites in mitochondria, to predict C-to-U RNA editing sites in the chloroplasts of seed plants. The algorithm achieves over 80% sensitivity and over 99% specificity. We implement the algorithm as an online service called CURE-Chloroplast .ConclusionCURE-Chloroplast is an online service for predicting the C-to-U RNA editing sites in the chloroplasts of seed plants. The online service allows the processing of entire chloroplast genome sequences. Since CURE-Chloroplast performs very well, it could be a helpful tool in the study of C-to-U RNA editing in the chloroplasts of seed plants.

Highlights

  • RNA editing is a type of post-transcriptional modification of RNA and belongs to the class of mechanisms that contribute to the complexity of transcriptomes

  • RNA editing is a kind of RNA processing that can alter the genetic information of RNA via insertion, deletion or substitution of single or multiple nucleotides

  • Because the dataset was significantly unbalanced, we provided the positive predictive value (PPV) and Matthew's correlation coefficient (MCC) values as measures of performance on the unbalanced dataset

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Summary

Results

We extend our algorithm CURE, which can accurately predict the C-to-U RNA editing sites in mitochondria, to predict C-to-U RNA editing sites in the chloroplasts of seed plants. The algorithm achieves over 80% sensitivity and over 99% specificity. We implement the algorithm as an online service called CURE-Chloroplast http://bioinfo.au.tsinghua.edu.cn/pure

Conclusion
Background
Results and Discussion
Handa H
17. Shikanai T
32. Mower JP
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