An integrated mass-spectrometry pipeline identifies novel protein coding-regions in the human genome.
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.
Bitton
Danny A
DA
Applied Computational Biology and Bioinformatics Group, Cancer Research UK, Paterson Institute for Cancer Research, The University of Manchester, Manchester, United Kingdom.
Smith
Duncan L
DL
Connolly
Yvonne
Y
Scutt
Paul J
PJ
Miller
Crispin J
CJ
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