Tuesday, April 20, 2010

Large-scale detection and analysis of RNA editing in grape mtDNA by RNA deep-sequencing

Large-scale detection and analysis of RNA editing in grape mtDNA by RNA deep-sequencing
Ernesto Picardi1, David S. Horner2, Matteo Chiara2, Riccardo Schiavon3, Giorgio Valle3 and Graziano Pesole1,4,*

1Dipartimento di Biochimica e Biologia Molecolare ‘E. Quagliariello’, Universit√† degli Studi di Bari, 70126 Bari, 2Dipartimento di Scienze Biomolecolari e Biotecnologie, Universit√† degli Studi di Milano, 20133 Milano, 3CRIBI, Universit√† degli Studi di Padova, viale G. Colombo 3, 35121 Padova and 4Istituto Tecnologie Biomediche del Consiglio Nazionale delle Ricerche, via Amendola 122/D, 70125 Bari, Italy

*To whom correspondence should be addressed. Tel: ; Fax: +39 080 544 3317; Email: graziano.pesole@biologia.uniba.it

Received September 7, 2009. Revised March 9, 2010. Accepted March 9, 2010.

RNA editing is a widespread post-transcriptional molecular phenomenon that can increase proteomic diversity, by modifying the sequence of completely or partially non-functional primary transcripts, through a variety of mechanistically and evolutionarily unrelated pathways. Editing by base substitution has been investigated in both animals and plants. However, conventional strategies based on directed Sanger sequencing are time-consuming and effectively preclude genome wide identification of RNA editing and assessment of partial and tissue-specific editing sites. In contrast, the high-throughput RNA-Seq approach allows the generation of a comprehensive landscape of RNA editing at the genome level. Short reads from Solexa/Illumina GA and ABI SOLiD platforms have been used to investigate the editing pattern in mitochondria of Vitis vinifera providing significant support for 401 C-to-U conversions in coding regions and an additional 44 modifications in non-coding RNAs. Moreover, 76% of all C-to-U conversions in coding genes represent partial RNA editing events and 28% of them were shown to be significantly tissue specific. Solexa/Illumina and SOLiD platforms showed different characteristics with respect to the specific issue of large-scale editing analysis, and the combined approach presented here reduces the false positive rate of discovery of editing events.

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