Accounting for Experimental Noise Reveals That mRNA Levels, Amplified by Post-Transcriptional Processes, Largely Determine Steady-State Protein Levels in Yeast

被引:125
作者
Csardi, Gabor [1 ]
Franks, Alexander [1 ]
Choi, David S. [1 ]
Airoldi, Edoardo M. [1 ,2 ]
Drummond, D. Allan [3 ,4 ]
机构
[1] Harvard Univ, Dept Stat, Cambridge, MA 02138 USA
[2] Broad Inst Harvard & MIT, Cambridge, MA USA
[3] Univ Chicago, Dept Biochem & Mol Biol, Chicago, IL 60637 USA
[4] Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA
来源
PLOS GENETICS | 2015年 / 11卷 / 05期
基金
美国国家科学基金会;
关键词
GENE-EXPRESSION; SACCHAROMYCES-CEREVISIAE; PROFILING REVEALS; ABUNDANCE; QUANTIFICATION; TRANSCRIPTOME; TRANSLATION; SELECTION; SCALE; REGRESSION;
D O I
10.1371/journal.pgen.1005206
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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.
引用
收藏
页数:32
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