| Summary: | Next-generation sequencing techniques have considerably increased the number of completely sequenced eukaryotic genomes. These genomes are mostly automatically annotated, and ab initio gene prediction is commonly combined with homology-based search approaches and often supported by transcriptomic data. The latter in particular improve the prediction of intron splice sites and untranslated regions. However, correct prediction of translation initiation sites (TIS), alternative splice junctions, and protein-coding potential remains challenging. Here, we present an advanced proteogenomics approach, namely, the combination of proteogenomics and de novo peptide sequencing analysis, in conjunction with Blast2GO and phylostratigraphy. Using the model fungus Sordaria macrospora as an example, we provide a comprehensive view of the proteome that not only increases the functional understanding of this multicellular organism at different developmental stages but also immensely enhances the genome annotation quality.Proteogenomics combines proteomics, genomics, and transcriptomics and has considerably improved genome annotation in poorly investigated phylogenetic groups for which homology information is lacking. Furthermore, it can be advantageous when reinvestigating well-annotated genomes. Here, we applied an advanced proteogenomics approach, combining standard proteogenomics with peptide de novo sequencing, to refine annotation of the well-studied model fungus Sordaria macrospora. We investigated samples from different developmental and physiological conditions, resulting in the detection of 104 so-far hidden proteins and annotation changes in 575 genes, including 389 splice site refinements. Significantly, our approach provides peptide-level evidence for 113 single-amino-acid variations and 15 C-terminal protein elongations originating from A-to-I RNA editing, a phenomenon recently detected in fungi. Coexpression and phylostratigraphic analysis of the refined proteome suggest that new functions in evolutionarily young genes correlate with distinct developmental stages. In conclusion, our advanced proteogenomics approach supports and promotes functional studies of fungal model systems.
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