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Teasing Apart Translational and Transcriptional Components of Stochastic Variations in Eukaryotic Gene Expression

Overview of attention for article published in PLoS Computational Biology, August 2012
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Title
Teasing Apart Translational and Transcriptional Components of Stochastic Variations in Eukaryotic Gene Expression
Published in
PLoS Computational Biology, August 2012
DOI 10.1371/journal.pcbi.1002644
Pubmed ID
Authors

Raheleh Salari, Damian Wojtowicz, Jie Zheng, David Levens, Yitzhak Pilpel, Teresa M. Przytycka

Abstract

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.

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Geographical breakdown

Country Count As %
United States 7 7%
Portugal 2 2%
Italy 2 2%
United Kingdom 2 2%
Switzerland 1 <1%
Spain 1 <1%
Iran, Islamic Republic of 1 <1%
Unknown 87 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 38 37%
Student > Ph. D. Student 18 17%
Student > Master 11 11%
Professor 7 7%
Professor > Associate Professor 6 6%
Other 19 18%
Unknown 4 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 49%
Biochemistry, Genetics and Molecular Biology 20 19%
Computer Science 5 5%
Physics and Astronomy 3 3%
Medicine and Dentistry 3 3%
Other 13 13%
Unknown 9 9%