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Updated: May 5, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Systematic analyses of the transcriptome, translatome, and proteome provide a global view and potential strategy for
Cheng Chang1, Liwei Li, Chengpu Zhang
1State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Engineering Research Center for Protein Drugs, National Center for Protein Sciences, Beijing Institute of Radiation Medicine , 27 Taiping Road, Beijing 102206, P. R. China.
Abstract:
To estimate the potential of the state-of-the-art proteomics technologies on full coverage of the encoding gene products, the Chinese Human Chromosome Proteome Consortium (CCPC) applied a multiomics strategy to systematically analyze the transciptome, translatome, and proteome of the same cultured hepatoma cells with varied metastatic potential qualitatively and quantitatively. The results provide a global view of gene expression profiles. The 9064 identified high confident proteins covered 50.2% of all gene products in the translatome. Those proteins with function of adhesion, development, reproduction, and so on are low abundant in transcriptome and translatome but absent in proteome. Taking the translatome as the background of protein expression, we found that the protein abundance plays a decisive role and hydrophobicity has a greater influence than molecular weight and isoelectric point on protein detectability. Thus, the enrichment strategy used for low-abundant transcription factors helped to identify missing proteins. In addition, those peptides with single amino acid polymorphisms played a significant role for the disease research, although they might negligibly contribute to new protein identification. The proteome raw and metadata of proteome were collected using the iProX submission system and submitted to ProteomeXchange (PXD000529, PXD000533, and PXD000535). All detailed information in this study can be accessed from the Chinese Chromosome-Centric Human Proteome Database.
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