Suppr超能文献

考虑到实验噪声后发现,经转录后过程放大的mRNA水平在很大程度上决定了酵母中的稳态蛋白质水平。

Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast.

作者信息

Csárdi Gábor, Franks Alexander, Choi David S, Airoldi Edoardo M, Drummond D Allan

机构信息

Dept. of Statistics, Harvard University, Cambridge, Massachusetts, United States of America.

Dept. of Statistics, Harvard University, Cambridge, Massachusetts, United States of America,; The Broad Institute of Harvard & MIT, Cambridge, Massachusetts, United States of America.

出版信息

PLoS Genet. 2015 May 7;11(5):e1005206. doi: 10.1371/journal.pgen.1005206. eCollection 2015 May.

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.

摘要

细胞通过mRNA转录和转录后控制来调节蛋白质水平,从而对其环境做出反应。观察到的全局稳态mRNA与蛋白质测量值之间适度的相关性被解释为mRNA水平大致决定了40%蛋白质水平变化的证据,这表明转录后效应占主导地位。然而,这些结论所依据的技术,如相关性和回归分析,在数据存在噪声、系统性缺失和共线性时(mRNA和蛋白质测量的特性)会产生有偏差的结果,这促使我们重新审视这个问题。对24项芽殖酵母研究进行的噪声稳健分析表明,mRNA水平解释了稳态蛋白质水平超过85%的变化。蛋白质水平与mRNA水平不成正比,而是上升得更快。翻译调控足以解释这种非线性效应,揭示了转录信号的转录后放大而非竞争。这些结果大幅修正了广泛认可的蛋白质水平调控模型,并引入了多种噪声感知方法,这些方法对于正确分析许多生物学现象至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e65/4423881/f6e21c351208/pgen.1005206.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验