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Can we predict protein from mRNA levels?

Nature volume 547, pages E19–E20 (2017)Cite this article

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Arising from M. Wilhelm et al. Nature 509, 582–587 (2014); doi:10.1038/nature13319

Prediction of protein levels from mRNA levels has long been fraught with unreliability and a lack of precision. However, Wilhelm et al.1 claimed that using estimated gene-specific translation rates together with mRNA levels accurately predicts protein levels in any given tissue, reporting correlations of approximately 0.9 between predictions and measurements across genes. Here we show that these correlations greatly overestimate the accuracy of per-gene predictions. Using simple and standard statistical evaluation methods, we demonstrate that the gene-specific translation rates estimated by Wilhelm et al. are, in general, not useful to predict protein levels from mRNA levels, with a median correlation of 0.21. There is a Reply to this Comment by Wilhelm, M. et al. Nature 547, 10.1038/nature22294 (2017).

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Figure 1: Across-genes correlations versus within-genes correlations between observed and predicted protein levels.

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Author information

Authors and Affiliations

  1. Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British, Columbia, Canada

    Nikolaus Fortelny & Christopher M. Overall

  2. Michael Smith Laboratories, University of British Columbia, Vancouver, British, Columbia, Canada

    Nikolaus Fortelny & Paul Pavlidis

  3. Centre for Blood Research, University of British Columbia, Vancouver, British, Columbia, Canada

    Nikolaus Fortelny & Christopher M. Overall

  4. Department of Oral Biological and Medical Sciences, University of British Columbia, Vancouver, British, Columbia, Canada

    Christopher M. Overall

  5. Department of Psychiatry, University of British Columbia, Vancouver, British, Columbia, Canada

    Paul Pavlidis

  6. Department of Statistics, University of British Columbia, Vancouver, British, Columbia, Canada

    Gabriela V. Cohen Freue

Authors
  1. Nikolaus Fortelny
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  2. Christopher M. Overall
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  3. Paul Pavlidis
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  4. Gabriela V. Cohen Freue
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Contributions

N.F. and G.V.C.F. designed the research project. C.M.O. and P.P. contributed to the design of the project and provided funding. N.F. designed the manuscript and analysed the data. P.P. and G.V.C.F. wrote the paper. G.V.C.F. supervised the research project. All authors contributed to extensive discussions and revisions of all drafts of the paper.

Corresponding author

Correspondence to Gabriela V. Cohen Freue.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Relation between gene-specific protein predictions and observed protein levels.

a, mRNA and protein in simulated data for three genes (colours) in five tissues. The data points for one tissue are highlighted and the error from the ratio-based prediction is indicated. b, Predicted and observed protein in simulated data for three genes (colours) in one tissue from a. The error in the prediction is indicated by the distance from the point to the 45° line. c, mRNA (open symbols) and predicted protein (solid symbols) on the x-axis and observed protein on the y-axis. The plot shows real data for four example genes. Data points from one tissue and their modification by the prediction of Wilhelm et al.1 are indicated by an error.

Extended Data Figure 2 mRNA contribution to protein prediction.

mRNA and protein in simulated data for three genes (A, B, and C, colours) in five tissues. a, Three gene-specific models (grey lines) to predict protein levels from mRNA levels as in Wilhelm et al. b, Three gene-specific models (grey lines) to predict protein levels without using mRNA.

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Fortelny, N., Overall, C., Pavlidis, P. et al. Can we predict protein from mRNA levels?. Nature 547, E19–E20 (2017). https://doi.org/10.1038/nature22293

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