Software

CURE-Chloroplast: A chloroplast C-to-U RNA editing predictor for seed plants

Pufeng Du^†, Liyan Jia^† and Yanda Li^*

• * Corresponding author: Yanda Li daulyd@tsinghua.edu.cn

• † Equal contributors

Author Affiliations

MOE Key Laboratory of Bioinformatics and Bioinformatics Div. TNLIST/Department of Automation, Tsinghua University, Beijing 100084, PR China

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BMC Bioinformatics 2009, 10:135 doi:10.1186/1471-2105-10-135

Published: 8 May 2009

Abstract

Background

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. 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.

Results

In 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 http://bioinfo.au.tsinghua.edu.cn/pure webcite.

Conclusion

CURE-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.