Genome annotation procedures can benefit from information provided by proteomics in various ways. Detection of sample- or patient specific alterations of protein sequences in the form of single amino acid variants (SAAVs) require dedicated analysis and validation procedures. In this work, proteogenomics methods were established that enable proteomics analysis of organisms void of reference sequence databases and that can universally be used to refine genome annotations based on protein level information as well as for identification of SAAVs. First, a de novo peptide sequencing method was established to improve database-free peptide identification. The applicability of de novo peptide sequencing to differentiate species of foraminifera (unicellular protists) based on their proteome was assessed and a homology-based strategy was employed to quantify the proteomic response of the foraminifera A. lobifera to heat stress. Next, the proteomic landscape of the freshwater snail R. auricularia was charted and a combination of de novo peptide sequencing and searches against the newly sequenced genome enabled an automated refinement of the annotation. The genome annotation of the model fungus S. macrospora was subjected to similar refinements. Remarkably, de novo peptide sequencing enabled to our knowledge the first ever confirmation of A-to-I RNA editing in fungi on the protein level. Finally, a proteogenomics approach was employed to analyze liver metastases retrieved from patients suffering from colorectal cancer. This enabled the identification of multiple SAAVs such as the prognostic KRAS G12V mutation. These discoveries were further validated and quantified by a targeted MS assay using of stable-isotope labeled standard (SIS) peptides.weiterlesen