Nature Communications · 2018 · 153 citations · 57 references
Life SciencesBiochemistryMolecular BiologyGenomicsProteomicsProteomics InformaticsBottom-up ProteomicsCancer ProteomicsMass Spectrometry Data AnalysisMass Spectrometry-based ProteomicsPeptide IdentificationProtein IdentificationMass Spectrum InterpretationPeptide SequencingProteogenomicsSingle-nucleotide Polymorphisms
Proteogenomics enable the discovery of novel peptides (from unannotated genomic protein-coding loci) and single amino acid variant peptides (derived from single-nucleotide polymorphisms and mutations). Increasing the reliability of these identifications is crucial to ensure their usefulness for genome annotation and potential application as neoantigens in cancer immunotherapy. We here present integrated proteogenomics analysis workflow (IPAW), which combines peptide discovery, curation, and validation. IPAW includes the SpectrumAI tool for automated inspection of MS/MS spectra, eliminating false identifications of single-residue substitution peptides. We employ IPAW to analyze two proteomics data sets acquired from A431 cells and five normal human tissues using extended (pH range, 3-10) high-resolution isoelectric focusing (HiRIEF) pre-fractionation and TMT-based peptide quantitation. The IPAW results provide evidence for the translation of pseudogenes, lncRNAs, short ORFs, alternative ORFs, N-terminal extensions, and intronic sequences. Moreover, our quantitative analysis indicates that protein production from certain pseudogenes and lncRNAs is tissue specific.
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