Evidence map›Paper›PMID 15826309›Full record

ArticleBMC bioinformatics2005

PREP-Mt: predictive RNA editor for plant mitochondrial genes.

Jeffrey P Mower

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

90 citing papers in PubMed, 189 citations in OpenAlex.

  1. Article
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  6. The First Complete Mitochondrial Genome ofCurrent issues in molecular biology · 2026
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  11. Comparative chloroplast genomics of sixFrontiers in plant science · 2026
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  14. Assembly and Analysis of the Mitochondrial Genome ofPlants (Basel, Switzerland) · 2025
    Article
  15. Article
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  20. Article

30 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Jeffrey P MowerDepartment of Biology, Indiana University, Bloomington, IN 47405, USA. jpmower@indiana.edu
Indiana University Bloomington · US

Funding

TRANSFER OF ORGANELLE GENES TO THE NUCLEUSR01GM035087 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PALMER, JEFFREY D · 1985 to 2004
$1.8M
NIGMS NIH HHS R01 GM035087NIGMS NIH HHS R01-GM-35087
6 · The paper itself

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.

Indexed as

Genes, PlantGenome, PlantRNA EditingAmino Acid SequenceBase SequenceBinding SitesChloroplastsComputational BiologyConserved SequenceCytidineDatabases, ProteinDNADNA, PlantMitochondrial ProteinsModels, StatisticalMolecular Sequence DataCytidineDNADNA, PlantMitochondrial ProteinsPlant ProteinsRNARNA, ChloroplastRNA, Mitochondrial

Identifiers

PMID15826309
PMCPMC1087475
OpenAlexW2152334724

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.