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Systematic identification and characterization of RNA editing in prostate tumors.


ABSTRACT: RNA editing modifies the sequence of primary transcripts, potentially resulting in profound effects to RNA structure and protein-coding sequence. Recent analyses of RNA sequence data are beginning to provide insights into the distribution of RNA editing across the entire transcriptome, but there are few published matched whole genome and transcriptome sequence datasets, and designing accurate bioinformatics methodology has proven highly challenging. To further characterize the RNA editome, we analyzed 16 paired DNA-RNA sequence libraries from prostate tumor specimens, employing a comprehensive strategy to rescue low coverage sites and minimize false positives. We identified over a hundred thousand putative RNA editing events, a third of which were recurrent in two or more samples, and systematically characterized their type and distribution across the genome. Within genes the majority of events affect non-coding regions such as introns and untranslated regions (UTRs), but 546 genes had RNA editing events predicted to result in deleterious amino acid alterations. Finally, we report a potential association between RNA editing of microRNA binding sites within 3' UTRs and increased transcript expression. These results provide a systematic characterization of the landscape of RNA editing in low coverage sequence data from prostate tumor specimens. We demonstrate further evidence for RNA editing as an important regulatory mechanism and suggest that the RNA editome should be further studied in cancer.

SUBMITTER: Mo F 

PROVIDER: S-EPMC4103770 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Systematic identification and characterization of RNA editing in prostate tumors.

Mo Fan F   Wyatt Alexander W AW   Sun Yue Y   Brahmbhatt Sonal S   McConeghy Brian J BJ   Wu Chunxiao C   Wang Yuzhuo Y   Gleave Martin E ME   Volik Stanislav V SV   Collins Colin C CC  

PloS one 20140718 7


RNA editing modifies the sequence of primary transcripts, potentially resulting in profound effects to RNA structure and protein-coding sequence. Recent analyses of RNA sequence data are beginning to provide insights into the distribution of RNA editing across the entire transcriptome, but there are few published matched whole genome and transcriptome sequence datasets, and designing accurate bioinformatics methodology has proven highly challenging. To further characterize the RNA editome, we an  ...[more]

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