The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Translating mRNAs strongly correlate to proteins in a multivariate manner and their translation ratios are phenotype specific
Open accessAbstract
As a well-known phenomenon, total mRNAs poorly correlate to proteins in their abundances as reported. Recent findings calculated with bivariate models suggested even poorer such correlation, whereas focusing on the translating mRNAs (ribosome nascent-chain complex-bound mRNAs, RNC-mRNAs) subset. In this study, we analysed the relative abundances of mRNAs, RNC-mRNAs and proteins on genome-wide scale, comparing human lung cancer A549 and H1299 cells with normal human bronchial epithelial (HBE) cells, respectively. As discovered, a strong correlation between RNC-mRNAs and proteins in their relative abundances could be established through a multivariate linear model by integrating the mRNA length as a key factor. The R(2) reached 0.94 and 0.97 in A549 versus HBE and H1299 versus HBE comparisons, respectively. This correlation highlighted that the mRNA length significantly contributes to the translational modulation, especially to the translational initiation, favoured by its correlation with the mRNA translation ratio (TR) as observed. We found TR is highly phenotype specific, which was substantiated by both pathway analysis and biased TRs of the splice variants of BDP1 gene, which is a key transcription factor of transfer RNAs. These findings revealed, for the first time, the intrinsic and genome-wide translation modulations at translatomic level in human cells at steady-state, which are tightly correlated to the protein abundance and functionally relevant to cellular phenotypes.
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Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling
Ingolia, N. T., Ghaemmaghami, S., Newman, J. R. S., & Weissman, J. S. (2009) · Science · doi:10.1126/science.1168978 · Cited by 3,853
Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells
Taniguchi, Y., Choi, P. J., Li, G.-W., Chen, H., Babu, M., Hearn, J., Emili, A., & Xie, X. S. (2010) · Science · doi:10.1126/science.1188308 · Cited by 1,982
Correlation of mRNA and protein in complex biological samples
Maier, T., Güell, M., & Serrano, L. (2009) · FEBS Letters · doi:10.1016/j.febslet.2009.10.036 · Cited by 1,802
Comparing protein abundance and mRNA expression levels on a genomic scale
Greenbaum, D. (2003) · Genome biology · doi:10.1186/gb-2003-4-9-117 · Cited by 1,692
Lu, P., Vogel, C., Wang, R., Yao, X., & Marcotte, E. M. (2007) · Nature Biotechnology · doi:10.1038/nbt1270 · Cited by 1,139
Deep proteome and transcriptome mapping of a human cancer cell line
Nagaraj, N., Wisniewski, J. R., Geiger, T., Cox, J., Kircher, M., Kelso, J., Pääbo, S., & Mann, M. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.81 · Cited by 979
Concordant Regulation of Translation and mRNA Abundance for Hundreds of Targets of a Human microRNA
Hendrickson, D. G., Hogan, D. J., McCullough, H. L., Myers, J. W., Herschlag, D., Ferrell, J. E., & Brown, P. O. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000238 · Cited by 418
Defining the transcriptome and proteome in three functionally different human cell lines
Lundberg, E., Fagerberg, L., Klevebring, D., Matic, I., Geiger, T., Cox, J., Älgenäs, C., Lundeberg, J., Mann, M., & Uhlen, M. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.106 · Cited by 373
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Alternative mRNA transcription, processing, and translation: insights from RNA sequencing
de Klerk, E., & ‘t Hoen, P. A. C. (2015) · Trends in Genetics · doi:10.1016/j.tig.2015.01.001 · Cited by 350
Mao, Y., Liu, H., Liu, Y., & Tao, S. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku159 · Cited by 90
ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data
Teng, P.-N., Schaaf, J. P., Abulez, T., Hood, B. L., Wilson, K. N., Litzi, T. J., Mitchell, D., Conrads, K. A., Hunt, A. L., Olowu, V., et al. (2024) · iScience · doi:10.1016/j.isci.2024.109198 · Cited by 21
Metadata
- Authors
- Wang, T., Cui, Y., Jin, J., Guo, J., Wang, G., Yin, X., He, Q.-Y., & Zhang, G.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-03-20
- Volume
- 41
- Issue
- 9
- Pages
- 4743-4754
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W1980599684
- Cited by
- 210
- References
- 12
- FWCI
- 4.30
- Type
- journal article
- Language
- en
- Open access
- gold
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