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. 2010 Aug 24:6:400.
doi: 10.1038/msb.2010.59.

Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line

Christine Vogel  1 , Raquel de Sousa Abreu, Daijin Ko, Shu-Yun Le, Bruce A Shapiro, Suzanne C Burns, Devraj Sandhu, Daniel R Boutz, Edward M Marcotte, Luiz O Penalva
Affiliations

Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line

Christine Vogel et al. Mol Syst Biol. .

Abstract

Transcription, mRNA decay, translation and protein degradation are essential processes during eukaryotic gene expression, but their relative global contributions to steady-state protein concentrations in multi-cellular eukaryotes are largely unknown. Using measurements of absolute protein and mRNA abundances in cellular lysate from the human Daoy medulloblastoma cell line, we quantitatively evaluate the impact of mRNA concentration and sequence features implicated in translation and protein degradation on protein expression. Sequence features related to translation and protein degradation have an impact similar to that of mRNA abundance, and their combined contribution explains two-thirds of protein abundance variation. mRNA sequence lengths, amino-acid properties, upstream open reading frames and secondary structures in the 5' untranslated region (UTR) were the strongest individual correlates of protein concentrations. In a combined model, characteristics of the coding region and the 3'UTR explained a larger proportion of protein abundance variation than characteristics of the 5'UTR. The absolute protein and mRNA concentration measurements for >1000 human genes described here represent one of the largest datasets currently available, and reveal both general trends and specific examples of post-transcriptional regulation.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of methods. We measured absolute mRNA and protein concentrations in cellular lysate from the Daoy medulloblastoma cell line. We integrated transcript level information with data on sequence characteristics to explain variation in protein abundance. All sequence characteristics analyzed are listed in the Supplementary information. MARS, Multivariate Adaptive Regression Splines.
Figure 2
Figure 2
Human protein and mRNA concentrations. Left: protein and mRNA concentrations correlate significantly at a log–log scale (N=512, R2=0.29, Rs=0.46 with P-value<2.2e−16). Right: genes with extremely high (red) or low (green) protein-per-mRNA ratios are likely regulated at the level of translation or protein stability. Source data is available for this figure at www.nature.com/msb.
Figure 3
Figure 3
Combined contributions. (A) Predicted protein abundance using the entire, combined MARS model, R2=0.67 (log scale, P-value<0.001). (B) Contributions of different feature groups to explanation of protein abundance variation. Yellow, green, blue: length, composition, structure and other characteristics of the coding sequence, 5′UTR and 3′UTR, respectively. Details are provided in Supplementary Section S4. See Supplementary Figure S14 for a different feature grouping. Source data is available for this figure at www.nature.com/msb.
Figure 4
Figure 4
Concordance of mRNA and protein expression regulation. The figure shows the correlation coefficients for features listed in Table I. All correlations are listed in the Supplementary information; x axis: Spearman's rank correlation between the respective feature, and the mRNA concentration, which is the combined outcome of transcription and mRNA decay; y axis: partial Spearman's rank correlation between the respective feature and the protein concentration, fixing variation in mRNA concentration, which describes the combined outcome of translation and protein degradation.
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