ArticleBMC bioinformatics2005
PREP-Mt: predictive RNA editor for plant mitochondrial genes.
Article in BMC bioinformatics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers.
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Who cites it
90 citing papers in PubMed, 189 citations in OpenAlex.
- Article
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- Artificial intelligence and first-principle methods in protein redesign: A marriage of convenience?Protein science : a publication of the Protein Society · 2025Article
- Assembly and Analysis of the Mitochondrial Genome ofPlants (Basel, Switzerland) · 2025Article
- Characterization and Analysis of the Complete Mitochondrial Genome ofCurrent issues in molecular biology · 2025Article
- Article
- Assembly and comparative analysis of the complete mitochondrial genome of Lactuca sativa var. ramosa Hort.Scientific reports · 2025Article
- Assembly and analysis of the first complete mitochondrial genome sequencing of main Tea-oil Camellia cultivars Camellia drupifera (Theaceae): revealed a multi-branch mitochondrial conformation for Camellia.BMC plant biology · 2025Article
- Complete sequencing of the mitochondrial genome of tea plantFrontiers in plant science · 2025Article
- Assembly and comparative analysis of the complete mitochondrial genome ofFrontiers in plant science · 2025Article
30 more citing papers are in PubMed but not listed here.
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
backgroundIn plants, RNA editing is a process that converts specific cytidines to uridines and uridines to cytidines in transcripts from virtually all mitochondrial protein-coding genes. There are thousands of plant mitochondrial genes in the sequence databases, but sites of RNA editing have not been determined for most. Accurate methods of RNA editing site prediction will be important in filling in this information gap and could reduce or even eliminate the need for experimental determination of editing sites for many sequences. Because RNA editing tends to increase protein conservation across species by "correcting" codons that specify unconserved amino acids, this principle can be used to predict editing sites by identifying positions where an RNA editing event would increase the conservation of a protein to homologues from other plants. PREP-Mt takes this approach to predict editing sites for any protein-coding gene in plant mitochondria.
resultsTo test the general applicability of the PREP-Mt methodology, RNA editing sites were predicted for 370 full-length or nearly full-length DNA sequences and then compared to the known sites of RNA editing for these sequences. Of 60,263 cytidines in this test set, PREP-Mt correctly classified 58,994 as either an edited or unedited site (accuracy = 97.9%). PREP-Mt properly identified 3,038 of the 3,698 known sites of RNA editing (sensitivity = 82.2%) and 55,956 of the 56,565 known unedited sites (specificity = 98.9%). Accuracy and sensitivity increased to 98.7% and 94.7%, respectively, after excluding the 489 silent editing sites (which have no effect on protein sequence or function) from the test set.
conclusionThese results indicate that PREP-Mt is effective at identifying C to U RNA editing sites in plant mitochondrial protein-coding genes. Thus, PREP-Mt should be useful in predicting protein sequences for use in molecular, biochemical, and phylogenetic analyses. In addition, PREP-Mt could be used to determine functionality of a mitochondrial gene or to identify particular sequences with unusual editing properties. The PREP-Mt methodology should be applicable to any system where RNA editing increases protein conservation across species.
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