Proteogenomics

Proteogenomics is an interdisciplinary field that integrates proteomics and genomics to improve genome annotation and enable discovery of novel protein-coding events. In bottom-up proteomics, tandem mass spectrometry identifies peptides that can be mapped back to a genome or transcriptome. By combining these data, researchers can validate predicted genes, refine exon–intron boundaries, and discover translation events not captured by conventional annotation, such as alternative start sites, alternative splicing, or translation of previously annotated noncoding regions.

Proteogenomic workflows typically start with genomic and transcriptomic data to generate a protein sequence database, often including six-frame translations or sample-specific transcript-derived databases. Mass spectra are searched against this database with controls for false discovery rate. The resulting peptide-to-genome mappings provide evidence for gene models and can reveal novel coding sequences, noncanonical isoforms, single amino acid variants, and gene fusions. Integrating ribosome profiling data or RNA-Seq improves confidence and context.

Applications include improved genome annotation in non-model organisms, cancer research for identifying tumor-specific neoantigens or personalized proteomes, and studies in plants and microbes. It also supports discovery of proteoforms, proteolytic processing, and post-translational modifications in the genomic frame, helping to link genomic variation with functional protein consequences.

Challenges include managing large, sample-specific databases, distinguishing true translation from noise, biases in proteomics data, and ensuring reproducibility. Rigorous statistical validation and orthogonal evidence are essential, as well as developing standardized pipelines and user-friendly tools to make proteogenomics broadly accessible.