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Bioinformatics Advance Access published online on April 3, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn113
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© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

ASPicDB: A database resource for alternative splicing analysis

T Castrignanò 1, M D'Antonio 1, A Anselmo 2, D Carrabino 1, De Meo A D'Onorio 1, AM D'Erchia 3, F Licciulli 4, M Mangiulli 3, F Mignone 2, G Pavesi 2, E Picardi 3, A Riva 3,5, R Rizzi 6, P Bonizzoni 6 and Graziano Pesole 3,4,*

1 Consorzio Interuniversitario per le Applicazioni di Supercalcolo per Universitàa e Ricerca, CASPUR, Rome, Italy,
2 University of Milan, Dipartimento di Scienze Biomolecolari e Biotecnologie, via Celoria 26, Milan 20133, Italy
3 University of Bari, Dipartimento di Biochimica e Biologia Molecolare, via Orabona, 4, Bari 70126, Italy
4 Istituto Tecnologie Biomediche del Consiglio Nazionale delle Ricerche, via Amendola 122/D, Bari 70126, Italy
5 Department of Molecular Genetics and Microbiology, University of Florida, PO Box 103610, Gainesville, FL 32610-3610, USA
6 DISCo, University of Milan Bicocca, via Bicocca degli Arcimboldi, 8, Milan, 20135, Italy

*To whom correspondence should be addressed. Prof. Grazino Pesole, E-mail: graziano.pesole{at}biologia.uniba.it


  Abstract

Motivation: Alternative splicing has recently emerged as a key mechanism responsible for the expansion of transcriptome and proteome complexity in human and other organisms. Although several online resources devoted to alternative splicing analysis are available they may suffer are available they may suffer from limitations related both to the computational methodologies adopted and to the extent of the annotations they provide that prevent the full exploitation of the available data. Furthermore, current resources provide limited query and download facilities.

Results: ASPicDB is a database designed to provide access to reliable annotations of the alternative splicing pattern of human genes and to the functional annotation of predicted splicing isoforms. Splice site detection and full-length transcript modeling have been carried out by a genome-wide application of the ASPic algorithm, based on the multiple alignment of gene-related transcripts (typically a Unigene cluster) to the genomic sequences, a strategy that greatly improves prediction accuracy compared to methods based on independent and progressive alignments.

Enhanced query and download facilities for annotations and sequences allow users to select and extract specific sets of data related to genes, transcripts and introns fulfilling a combination of user-defined criteria. Several tabular and graphical views of the results are presented, providing a comprehensive assessment of the functional implication of alternative splicing in the gene set under investigation.

ASPicDB, which is regularly updated on a monthly basis, also includes information on tissue-specific splicing patterns of normal and cancer cells, based on available EST sequences and their library source annotation.

ASPicDB is regularly updated on a monthly basis with the latest releases of NCBI Entrez Gene and Unigene databases.

Availability: www.caspur.it/ASPicDB

Contact: graziano.pesole{at}biologia.uniba.it

Associate Editor: Prof. Alfonso Valencia

Received on November 30, 2007; revised on February 26, 2008; accepted on March 28, 2008

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