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Editing site recognition and nucleotide insertion are separable processes in Physarum mitochondria.

Center for RNA Molecular Biology, Case Western Reserve University, 2109 Adelbert Road, School of Medicine, Cleveland, OH 44106, USA.
The EMBO Journal (Impact Factor: 10.75). 12/2002; 21(22):6154-61. DOI: 10.1093/emboj/cdf610
Source: PubMed

ABSTRACT Insertional RNA editing in Physarum polycephalum is a complex process involving the specific addition of non-templated nucleotides to nascent mitochondrial transcripts. Since all four ribonucleotides are substrates for the editing activity(s), both the site of insertion and the identity of the nucleotide to be added at a particular position must be specified, but the signals for these events have yet to be elucidated. Here we report the occurrence of sporadic errors in RNAs synthesized in vitro. These mistakes, which include omission of encoded nucleotides as well as misinsertions, occur only on templates that support editing. The pattern of these misediting events indicates that editing site recognition and nucleotide addition are separable events, and that the recognition step involves features of the mitochondrial template that are required for editing. The larger deletions lack all templated nucleotides between editing sites, suggesting that the transcription/editing apparatus can "jump" from one insertion site to another, perhaps mediated by interactions with editing determinants, while smaller omissions most likely reflect misalignment of the transcript upon resumption of templated RNA synthesis.

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    ABSTRACT: Mitochondrial gene expression in the acellular slime mold Physarum polycephalum requires a diverse array of RNA editing events. Virtually all transcripts encoded in the organelle are subject to changes at the RNA level, including both mRNAs and stable RNAs. Roughly 500 editing events involving nucleotide insertion or deletion have been confirmed thus far; these occur co-transcriptionally. Base changes also occur in Physarum mitochondria, but these are much rarer and occur post-transcriptionally. This chapter focuses on the experimental approaches used to dissect the unique mechanism of insertion/deletion editing in Physarum mitochondria.
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    ABSTRACT: RNA editing describes the process in which individual or short stretches of nucleotides in a messenger or structural RNA are inserted, deleted, or substituted. A high level of RNA editing has been observed in the mitochondrial genome of Physarum polycephalum. The most frequent editing type in Physarum is the insertion of individual Cs. RNA editing is extremely accurate in Physarum; however, little is known about its mechanism. Here, we demonstrate how analyzing two organisms from the Myxomycetes, namely Physarum polycephalum and Didymium iridis, allows us to test hypotheses about the editing mechanism that can not be tested from a single organism alone. First, we show that using the recently determined full transcriptome information of Physarum dramatically improves the accuracy of computational editing site prediction in Didymium. We use this approach to predict genes in the mitochondrial genome of Didymium and identify six new edited genes as well as one new gene that appears unedited. Next we investigate sequence conservation in the vicinity of editing sites between the two organisms in order to identify sites that harbor the information for the location of editing sites based on increased conservation. Our results imply that the information contained within only nine or ten nucleotides on either side of the editing site (a distance previously suggested through experiments) is not enough to locate the editing sites. Finally, we show that the codon position bias in C insertional RNA editing of these two organisms is correlated with the selection pressure on the respective genes thereby directly testing an evolutionary theory on the origin of this codon bias. Beyond revealing interesting properties of insertional RNA editing in Myxomycetes, our work suggests possible approaches to be used when finding sequence motifs for any biological process fails.
    PLoS Computational Biology 02/2012; 8(2):e1002400. DOI:10.1371/journal.pcbi.1002400 · 4.83 Impact Factor

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