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Open Access Database

Ontology-oriented retrieval of putative microRNAs in Vitis vinifera via GrapeMiRNA: a web database of de novo predicted grape microRNAs

Barbara Lazzari1*, Andrea Caprera1, Alessandro Cestaro2, Ivan Merelli3, Marcello Del Corvo1, Paolo Fontana2, Luciano Milanesi3, Riccardo Velasco2 and Alessandra Stella14

Author Affiliations

1 Technology Park Lodi, Località Cascina Codazza, Via Einstein, 26900 Lodi, Italy

2 IASMA Research Center, Via E. Mach 1, 38010 San Michele all'Adige (TN), Italy

3 Institute for Biomedical Technologies (CNR), via Fratelli Cervi 93, 20090 Segrate (MI), Italy

4 Institute of Agricultural Biology and Biotechnology (CNR), via Bassini 15, 20133 Milan, Italy

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BMC Plant Biology 2009, 9:82  doi:10.1186/1471-2229-9-82

Published: 29 June 2009

Abstract

Background

Two complete genome sequences are available for Vitis vinifera Pinot noir. Based on the sequence and gene predictions produced by the IASMA, we performed an in silico detection of putative microRNA genes and of their targets, and collected the most reliable microRNA predictions in a web database. The application is available at http://www.itb.cnr.it/ptp/grapemirna/ webcite.

Description

The program FindMiRNA was used to detect putative microRNA genes in the grape genome. A very high number of predictions was retrieved, calling for validation. Nine parameters were calculated and, based on the grape microRNAs dataset available at miRBase, thresholds were defined and applied to FindMiRNA predictions having targets in gene exons. In the resulting subset, predictions were ranked according to precursor positions and sequence similarity, and to target identity. To further validate FindMiRNA predictions, comparisons to the Arabidopsis genome, to the grape Genoscope genome, and to the grape EST collection were performed. Results were stored in a MySQL database and a web interface was prepared to query the database and retrieve predictions of interest.

Conclusion

The GrapeMiRNA database encompasses 5,778 microRNA predictions spanning the whole grape genome. Predictions are integrated with information that can be of use in selection procedures. Tools added in the web interface also allow to inspect predictions according to gene ontology classes and metabolic pathways of targets. The GrapeMiRNA database can be of help in selecting candidate microRNA genes to be validated.