National Center for Biotechnology Information, National Library of Medicine, Bethesda, Maryland, USA.
PLoS Comput Biol. 2012;8(8):e1002644. doi: 10.1371/journal.pcbi.1002644. Epub 2012 Aug 30.
The intrinsic stochasticity of gene expression leads to cell-to-cell variations, noise, in protein abundance. Several processes, including transcription, translation, and degradation of mRNA and proteins, can contribute to these variations. Recent single cell analyses of gene expression in yeast have uncovered a general trend where expression noise scales with protein abundance. This trend is consistent with a stochastic model of gene expression where mRNA copy number follows the random birth and death process. However, some deviations from this basic trend have also been observed, prompting questions about the contribution of gene-specific features to such deviations. For example, recent studies have pointed to the TATA box as a sequence feature that can influence expression noise by facilitating expression bursts. Transcription-originated noise can be potentially further amplified in translation. Therefore, we asked the question of to what extent sequence features known or postulated to accompany translation efficiency can also be associated with increase in noise strength and, on average, how such increase compares to the amplification associated with the TATA box. Untangling different components of expression noise is highly nontrivial, as they may be gene or gene-module specific. In particular, focusing on codon usage as one of the sequence features associated with efficient translation, we found that ribosomal genes display a different relationship between expression noise and codon usage as compared to other genes. Within nonribosomal genes we found that sequence high codon usage is correlated with increased noise relative to the average noise of proteins with the same abundance. Interestingly, by projecting the data on a theoretical model of gene expression, we found that the amplification of noise strength associated with codon usage is comparable to that of the TATA box, suggesting that the effect of translation on noise in eukaryotic gene expression might be more prominent than previously appreciated.
基因表达的固有随机性导致了细胞间蛋白质丰度的变化,即噪声。包括转录、mRNA 和蛋白质的翻译和降解在内的几个过程都可能导致这些变化。最近对酵母中基因表达的单细胞分析揭示了一个普遍趋势,即表达噪声与蛋白质丰度成比例。这一趋势与 mRNA 拷贝数遵循随机出生和死亡过程的基因表达随机模型一致。然而,也观察到了一些偏离这一基本趋势的情况,这引发了关于基因特异性特征对这些偏差的贡献的问题。例如,最近的研究指出 TATA 盒作为一种序列特征,可以通过促进表达爆发来影响表达噪声。起源于转录的噪声可以在翻译中进一步放大。因此,我们提出了一个问题,即已知或假设与翻译效率相关的序列特征在多大程度上也可以与噪声强度的增加相关,以及平均而言,这种增加与 TATA 盒相关的放大相比如何。解析表达噪声的不同成分是非常复杂的,因为它们可能是基因或基因模块特异性的。特别是,我们关注密码子使用作为与高效翻译相关的序列特征之一,发现与其他基因相比,核糖体基因的表达噪声与密码子使用之间的关系不同。在非核糖体基因中,我们发现高密码子使用与噪声增加相关,相对于具有相同丰度的蛋白质的平均噪声。有趣的是,通过将数据投影到基因表达的理论模型上,我们发现与密码子使用相关的噪声强度的放大与 TATA 盒相当,这表明翻译对真核基因表达中噪声的影响可能比以前认为的更为显著。