Combining genomic and proteomic techniques can reveal important insights to unlock complex biological function. The exploration of methods for integrating large genomic and proteomic datasets is gaining traction due to improved bioinformatics and the public availability of well-organized, searchable data. Also, by merging RNA sequencing with mass spectrometry and improving bioinformatics, scientists can strategically select from a much broader range of investigational techniques and take advantage of complementary information. When one avenue of investigation closes, another may offer a new route to discovery—either building on previously inconclusive results or offering altogether new insights. Multiple studies in the past several years have demonstrated that transcriptional profiling data do not necessarily correlate with protein expression data, confirming that the two types of information are not duplicates but, instead, may be synergistic in terms of broadening our understanding of basic biology.1
In this brief overview, three recent examples illustrate how a “proteogenomics” approach can improve investigational power by enabling a progression of approaches that lead to actionable conclusions. When it comes to translational medicine, proteogenomics may provide better prospects for revealing biomarkers, assessing disease states, and identifying the complex mechanisms behind biological function (Figure 1).
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