System wide analyses have underestimated protein abundances and the importance of transcription in mammals

Journal Article · Wed Jan 01 00:00:00 EST 2014 · PeerJ

DOI:https://doi.org/10.7717/peerj.270· OSTI ID:1628928

Li, Jingyi Jessica ^[1]; Bickel, Peter J. ^[2]; Biggin, Mark D. ^[3]

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1. Univ. of California, Berkeley, CA (United States). Dept. of Statistics; Univ. of California, Los Angeles, CA (United States). Depts. of Statistics and Human Genetics; DOE/OSTI
2. Univ. of California, Berkeley, CA (United States). Dept. of Statistics
3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Genomics Division

Large scale surveys in mammalian tissue culture cells suggest that the protein expressed at the median abundance is present at 8000–16 000 molecules per cell and that differences in mRNA expression between genes explain only 10–40% of the differences in protein levels. We find, however, that these surveys have significantly underestimated protein abundances and the relative importance of transcription. Using individual measurements for 61 housekeeping proteins to rescale whole proteome data from Schwanhausser et al. (2011), we find that the median protein detected is expressed at 170 000 molecules per cell and that our corrected protein abundance estimates show a higher correlation with mRNA abundances than do the uncorrected protein data. In addition, we estimated the impact of further errors in mRNA and protein abundances using direct experimental measurements of these errors. The resulting analysis suggests that mRNA levels explain at least 56% of the differences in protein abundance for the 4212 genes detected by Schwanhausser et al. (2011), though because one major source of error could not be estimated the true percent contribution should be higher. We also employed a second, independent strategy to determine the contribution of mRNA levels to protein expression. We show that the variance in translation rates directly measured by ribosome profiling is only 12% of that inferred by Schwanhausser et al. (2011), and that the measured and inferred translation rates correlate poorly (R2 = 0.13). Based on this, our second strategy suggests that mRNA levels explain ~81% of the variance in protein levels. We also determined the percent contributions of transcription, RNA degradation, translation and protein degradation to the variance in protein abundances using both of our strategies. While the magnitudes of the two estimates vary, they both suggest that transcription plays a more important role than the earlier studies implied and translation a much smaller role. Finally, the above estimates only apply to those genes whose mRNA and protein expression was detected. Based on a detailed analysis by Hebenstreit et al. (2012), we estimate that approximately 40% of genes in a given cell within a population express no mRNA. Since there can be no translation in the absence of mRNA, we argue that differences in translation rates can play no role in determining the expression levels for the ~40% of genes that are non-expressed.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 1628928
• Journal Information: PeerJ, Journal Name: PeerJ Vol. 2; ISSN 2167-8359
• Publisher: PeerJ Inc.
• Country of Publication: United States
• Language: English

Related Subjects

59 BASIC BIOLOGICAL SCIENCES
97 MATHEMATICS AND COMPUTING
Bioinformatics
Computational Biology
Gene expression
Mass spectrometry
Protein abundance
Science & Technology - Other Topics
Transcription
Translation