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Elucidation of the RNA Recognition Code for Pentatricopeptide Repeat Proteins Involved in Organelle RNA Editing in Plants

Overview of attention for article published in PLOS ONE, March 2013
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Title
Elucidation of the RNA Recognition Code for Pentatricopeptide Repeat Proteins Involved in Organelle RNA Editing in Plants
Published in
PLOS ONE, March 2013
DOI 10.1371/journal.pone.0057286
Pubmed ID
Authors

Yusuke Yagi, Shimpei Hayashi, Keiko Kobayashi, Takashi Hirayama, Takahiro Nakamura

Abstract

Pentatricopeptide repeat (PPR) proteins are eukaryotic RNA-binding proteins that are commonly found in plants. Organelle transcript processing and stability are mediated by PPR proteins in a gene-specific manner through recognition by tandem arrays of degenerate 35-amino-acid repeating units, the PPR motifs. However, the sequence-specific RNA recognition mechanism of the PPR protein remains largely unknown. Here, we show the principle underlying RNA recognition for PPR proteins involved in RNA editing. The distance between the PPR-RNA alignment and the editable C was shown to be conserved. Amino acid variation at 3 particular positions within the motif determined recognition of a specific RNA in a programmable manner, with a 1-motif to 1-nucleotide correspondence, with no gap sequence. Data from the decoded nucleotide frequencies for these 3 amino acids were used to assign accurate interacting sites to several PPR proteins for RNA editing and to predict the target site for an uncharacterized PPR protein.

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Geographical breakdown

Country Count As %
United States 2 1%
Poland 1 <1%
Germany 1 <1%
Australia 1 <1%
Unknown 149 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 22%
Researcher 29 19%
Student > Master 23 15%
Student > Bachelor 12 8%
Student > Doctoral Student 12 8%
Other 22 14%
Unknown 22 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 69 45%
Biochemistry, Genetics and Molecular Biology 46 30%
Chemistry 4 3%
Unspecified 3 2%
Chemical Engineering 2 1%
Other 10 6%
Unknown 20 13%