ArticleBMC systems biology2008
A quantitative estimation of the global translational activity in logarithmically growing yeast cells.
Article in BMC systems biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers.
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Who cites it
95 citing papers in PubMed, 175 citations in OpenAlex.
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- A Trizol-Beadbeater RNA extraction method for yeast, and comparison to Novogene RNA extraction.bioRxiv : the preprint server for biology · 2025Article
- Assembling the jigsaw puzzle of life.Trends in biochemical sciences · 2025Article
- Individual yeast cells signal at different levels but each with good precision.Royal Society open science · 2025Article
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- Improvement of ribonucleic acid production in Cyberlindnera jadinii and optimization of fermentation medium.AMB Express · 2024Article
- Three Rounds of Read Correction Significantly Improve Eukaryotic Protein Detection in ONT Reads.Microorganisms · 2024Article
- PARROT: Prediction of enzyme abundances using protein-constrained metabolic models.PLoS computational biology · 2023Article
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- Physical basis of the cell size scaling laws.eLife · 2023Article
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35 more citing papers are in PubMed but not listed here.
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
backgroundTranslation of messenger mRNAs makes significant contributions to the control of gene expression in all eukaryotes. Because translational control often involves fractional changes in translational activity, good quantitative descriptions of translational activity will be required to achieve a comprehensive understanding of this aspect of biology. Data on translational activity are difficult to generate experimentally under physiological conditions, however, translational activity as a parameter is in principle accessible through published genome-wide datasets.
resultsAn examination of the accuracy of genome-wide expression datasets generated for Saccharomyces cerevisiae shows that the available datasets suffer from large random errors within studies as well as systematic shifts in reported values between studies, which make predictions of translational activity at the level of individual genes relatively inaccurate. In contrast, predictions of cell-wide translational activity are possible from such datasets with higher accuracy, and current datasets predict a production rate of about 13,000 proteins per haploid cell per second under fast growth conditions. This prediction is shown to be consistent with independently derived kinetic information on nucleotide exchange reactions that occur during translation, and on the ribosomal content of yeast cells.
conclusionThis study highlights some of the limitations in published genome-wide expression datasets, but also demonstrates a novel use for such datasets in examining global properties of cells. The global translational activity of yeast cells predicted in this study is a useful benchmark against which biochemical data on individual translation factor activities can be interpreted.
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