title: An integrated mass-spectrometry pipeline identifies novel protein coding-regions in the human genome.
abstract: BACKGROUND
  Most protein mass spectrometry (MS) experiments rely on searches against a database of known or predicted proteins, limiting their ability as a gene discovery tool.
  
  
  RESULTS
  Using a search against an in silico translation of the entire human genome, combined with a series of annotation filters, we identified 346 putative novel peptides [False Discovery Rate (FDR)<5%] in a MS dataset derived from two human breast epithelial cell lines. A subset of these were then successfully validated by a different MS technique. Two of these correspond to novel isoforms of Heterogeneous Ribonuclear Proteins, while the rest correspond to novel loci.
  
  
  CONCLUSIONS
  MS technology can be used for ab initio gene discovery in human data, which, since it is based on different underlying assumptions, identifies protein-coding genes not found by other techniques. As MS technology continues to evolve, such approaches will become increasingly powerful.
authors.affiliation: Applied Computational Biology and Bioinformatics Group, Cancer Research UK, Paterson Institute for Cancer Research, The University of Manchester, Manchester, United Kingdom.
authors.forename: Danny A
authors.initials: DA
authors.lastname: Bitton
authors.forename: Duncan L
authors.initials: DL
authors.lastname: Smith
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Connolly
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Scutt
authors.forename: Crispin J
authors.initials: CJ
authors.lastname: Miller
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D045744:Cell Line, Tumor; D015894:Genome, Human; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D008969:Molecular Sequence Data; D017386:Sequence Homology, Amino Acid