BMC Bioinformatics (Jul 2018)
Plant organelle RNA editing and its specificity factors: enhancements of analyses and new database features in PREPACT 3.0
Abstract
Abstract Background Gene expression in plant chloroplasts and mitochondria is affected by RNA editing. Numerous C-to-U conversions, accompanied by reverse U-to-C exchanges in some plant clades, alter the genetic information encoded in the organelle genomes. Predicting and analyzing RNA editing, which ranges from only few sites in some species to thousands in other taxa, is bioinformatically demanding. Results Here, we present major enhancements and extensions of PREPACT, a WWW-based service for analysing, predicting and cataloguing plant-type RNA editing. New features in PREPACT’s core include direct GenBank accession query input and options to restrict searches to candidate U-to-C editing or to sites where editing has been documented previously in the references. The reference database has been extended by 20 new organelle editomes. PREPACT 3.0 features new modules “EdiFacts” and “TargetScan”. EdiFacts integrates information on pentatricopeptide repeat (PPR) proteins characterized as site-specific RNA editing factors. PREPACT’s editome references connect into EdiFacts, linking editing events to specific co-factors where known. TargetScan allows position-weighted querying for sequence motifs in the organelle references, optionally restricted to coding regions or sequences around editing sites, or in queries uploaded by the user. TargetScan is mainly intended to evaluate and further refine the proposed PPR-RNA recognition code but may be handy for other tasks as well. We present an analysis for the immediate sequence environment of more than 15,000 documented editing sites finding strong and different bias in the editome data sets. Conclusions We exemplarily present the novel features of PREPACT 3.0 aimed to enhance the analyses of plant-type RNA editing, including its new modules EdiFacts integrating information on characterized editing factors and TargetScan aimed to analyse RNA editing site recognition specificities.
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