A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiency of protein identification and enables the discovery of alternative translation start sites.

摘要: Next-generation transcriptome sequencing is increasingly integrated with MS to enhance MS-based protein and peptide identification. Recently, a breakthrough in analysis was achieved the development of ribosome profiling (ribo-seq). This technology based on deep ribosome-protected mRNA fragments, thereby enabling direct observation vivo synthesis at transcript level. In order explore impact ribo-seq-derived sequence search space MS/MS spectrum identification, we performed comprehensive proteome study human cancer cell line, using both shotgun N-terminal proteomics, next profiling, which used delineate (alternative) translational reading frames. By including protein-level evidence sample-specific genetic variation alternative translation, this strategy improved identification score 69 proteins identified 22 new experiment. Furthermore, discovered 18 translation start sites proteomics data observed correlation between quantitative measures ribo-seq Pearson coefficient ranging from 0.483 0.664. Overall, demonstrated benefits for believe approach could develop into common practice next-generation proteomics.