title: A new approach that allows identification of intron-split peptides from mass spectrometric data in genomic databases.
abstract: We present a new approach that allows the identification of intron-split peptides from mass spectrometric data in genomic databases. Our algorithm uses small regions of peptide sequence information which are automatically deduced from de novo amino acid sequence predictions together with the molecular mass information of the precursor ion. The sequence predictions are based on selected collision-induced mass spectrometric fragmentation spectra. Fragments of the predicted amino acid sequence are aligned with each of the six frames of the translated genome and the precursor mass information is used to assemble the corresponding tryptic peptides using the sequence as a matrix. Hereby, intron-split peptides can be gathered and in turn verified by mass spectrometric data interpretation tools such as Sequest.
authors.affiliation: Lehrstuhl für Pflanzenphysiologie, Friedrich-Schiller-Universität Jena, Dornburger Str. 159, 07743 Jena, Germany.
authors.forename: Jens
authors.initials: J
authors.lastname: Allmer
authors.forename: Christine
authors.initials: C
authors.lastname: Markert
authors.forename: Einar J
authors.initials: EJ
authors.lastname: Stauber
authors.forename: Michael
authors.initials: M
authors.lastname: Hippler
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D030541:Databases, Genetic; D016678:Genome; D007438:Introns; D013058:Mass Spectrometry / Q000379:methods*; D010455:Peptides / Q000737:chemistry* / Q000235:genetics*
chemical_list: D010455:Peptides