"Proteogenome is the combination of two words Proteomics and Genomics. Proteogenomicsrefers to the correlation of mass spectrometry-derived proteomic data to refine genomeannotation. The completion of a genome sequencing effort represents a milestone forunderstanding the genetic blueprint of any particular organism. However, to realize the fullbiological value of the sequenced genome requires accurate identification of the protein-codinggenes in each genome, as well as the nature of the functional protein products. Thisunderstanding has shifted attention from genome sequencing to genome annotation. Massspectrometry (MS)-based proteomics approaches directly measure peptides arising fromexpressed proteins, which allows for direct verification of coding regions of a genomic sequence.In addition to verifying protein-coding genes, these analyses can also benefit genome annotationby helping to identify missed protein-coding genes, confirm the expression of alternative splicevariants in eukaryotic genomes, and correct overestimated protein-coding potentials, particularlyin microbial genomes.Comparative Proteogenomics:Is a branch of proteogenomics that compares proteomic data from multiple related speciesconcurrently and exploits the homology between their proteins to improve annotations withhigher statistical confidence. In a sense – this is the approximate peptide matching problem.However, it needs to take residue conservation at different part of the proteins into account e.gsites which are post translationally modified must be preserved to maintain function.Metaproteomics:Metaproteomics (also Community Proteomics, Environmental Proteomics, or CommunityProteogenomics) is the study of all protein samples recovered directly from environmentalsamples. This involves simultaneous mapping of peptides to all known genomes and proteomesto get the identity of different organisms present in a sample. Concept of Proteogenomics:In a proteogenomic approach, genomic and transcriptomic data are used to generate customizedprotein sequence databases to help interpret proteomic data. In turn, the proteomic data provideprotein-level validation of the gene expression data and help refine gene models. The enhancedgene models can help improve protein sequence databases for traditional proteomic analysis.Figure 1: The concept of proteogenomicsMethodology adopted: In this approach, customized protein sequence databases generated using genomic andtranscriptomic information are used to help identify novel peptides (not present in referenceprotein sequence databases) from mass spectrometry-based proteomic data; in turn, theproteomic data can be used to provide protein-level evidence of gene expression and to helprefine gene models. In recent years, owing to the emergence of new sequencing technologiessuch as RNA-seq and dramatic improvements in the depth and throughput of mass spectrometry- based proteomics, the pace of proteogenomic research has greatly accelerated. Figure 2: Proteogenomics WorkflowRole of Proteogenome:1. Accurate prediction of Translation Start Site.2. Accurate prediction of programmed frameshifts.3. Accurate prediction of post translational modification.4. It has been applied to the identification of previously unidentified genes and thecorrection and validation of predicted genes in various organisms.5. It is an important tool for integrating protein-level information into the genomeannotation process and can greatly improve genome annotation quality "