Retention Time and Fragmentation Predictors Increase Confidence in Identification of Common Variant Peptides

Precision medicine focuses on adapting care to the individual
profile
of patients, for example, accounting for their unique genetic makeup.
Being able to account for the effect of genetic variation on the proteome
holds great promise toward this goal. However, identifying the protein
products of genetic variation using mass spectrometry has proven very
challenging. Here we show that the identification of variant peptides
can be improved by the integration of retention time and fragmentation
predictors into a unified proteogenomic pipeline. By combining these
intrinsic peptide characteristics using the search-engine post-processor
Percolator, we demonstrate improved discrimination power between correct
and incorrect peptide-spectrum matches. Our results demonstrate that
the drop in performance that is induced when expanding a protein sequence
database can be compensated, hence enabling efficient identification
of genetic variation products in proteomics data. We anticipate that
this enhancement of proteogenomic pipelines can provide a more refined
picture of the unique proteome of patients and thereby contribute
to improving patient care.