Abbreviations

Database-search algorithms are the primary workhorses for the identification of tandem mass spectra. However, these methods are limited to the identification of spectra whose peptides are present in the database, preventing the identification of peptides from mutated, or alternatively spliced sequences. A variety of methods have been developed to search a spectrum against a sequence allowing for variations. Some tools determine the sequence of the homologous protein in the related species, but do not report the peptide in the target organism. Other tools consider variations, including modifications, and mutations, in reconstructing the target sequence. However, these tools will not work if the template (homologous peptide) is missing in the database, and do not attempt to reconstruct the entire protein target sequence. De novo identification of peptide sequences is another possibility, as it does not require a protein database. However, the lack of database reduces the accuracy. We present a novel proteogenomic approach, GenoMS, that draws on the strengths of database and de novo peptide identification methods. Protein sequence templates, i.e. proteins or genomic sequences that are similar to the target protein are identified using the database search tool InsPecT. The templates are then used to recruit, align, and de novo sequence regions of the target protein that have diverged from the database, or are missing. We used GenoMS to reconstruct the full sequence of an antibody, using spectra acquired from multipl