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Integrating alternative splicing detection into gene prediction.

TitleIntegrating alternative splicing detection into gene prediction.
Publication TypeJournal Article
Year of Publication2005
AuthorsFoissac, S, Schiex, T
JournalBMC Bioinformatics
Volume6
Pagination25
Date Published2005 Feb 10
ISSN1471-2105
KeywordsAlgorithms, Alternative Splicing, Arabidopsis, Codon, Computer Graphics, Databases, Genetic, Databases, Nucleic Acid, Databases, Protein, DNA, Complementary, Exons, Expressed Sequence Tags, Gene Expression Profiling, Genes, Plant, Genome, Genome, Human, Genomics, Humans, Introns, Models, Genetic, Proteomics, RNA Splice Sites, Sequence Alignment, Sequence Analysis, Protein, Sequence Analysis, RNA, Software, Transcription, Genetic, User-Computer Interface
Abstract

BACKGROUND: Alternative splicing (AS) is now considered as a major actor in transcriptome/proteome diversity and it cannot be neglected in the annotation process of a new genome. Despite considerable progresses in term of accuracy in computational gene prediction, the ability to reliably predict AS variants when there is local experimental evidence of it remains an open challenge for gene finders.RESULTS: We have used a new integrative approach that allows to incorporate AS detection into ab initio gene prediction. This method relies on the analysis of genomically aligned transcript sequences (ESTs and/or cDNAs), and has been implemented in the dynamic programming algorithm of the graph-based gene finder EuGENE. Given a genomic sequence and a set of aligned transcripts, this new version identifies the set of transcripts carrying evidence of alternative splicing events, and provides, in addition to the classical optimal gene prediction, alternative optimal predictions (among those which are consistent with the AS events detected). This allows for multiple annotations of a single gene in a way such that each predicted variant is supported by a transcript evidence (but not necessarily with a full-length coverage).CONCLUSIONS: This automatic combination of experimental data analysis and ab initio gene finding offers an ideal integration of alternatively spliced gene prediction inside a single annotation pipeline.

DOI10.1186/1471-2105-6-25
Alternate JournalBMC Bioinformatics
PubMed ID15705189
PubMed Central IDPMC550657