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• W2139708137 startingPage "e1005206" @default.
• W2139708137 abstract "Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena." @default.
• W2139708137 created "2016-06-24" @default.
• W2139708137 creator A5011032570 @default.
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• W2139708137 creator A5081449151 @default.
• W2139708137 date "2015-05-07" @default.
• W2139708137 modified "2023-09-28" @default.
• W2139708137 title "Accounting for Experimental Noise Reveals That mRNA Levels, Amplified by Post-Transcriptional Processes, Largely Determine Steady-State Protein Levels in Yeast" @default.
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• W2139708137 doi "https://doi.org/10.1371/journal.pgen.1005206" @default.
• W2139708137 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4423881" @default.
• W2139708137 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25950722" @default.
• W2139708137 hasPublicationYear "2015" @default.
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