Chromosomal Position Effects Are Linked to Sir2-Mediated Variation in Transcriptional Burst Size

Batenchuk, Cory; St-Pierre, Simon; Tepliakova, Lioudmila; Adiga, Samyuktha; Szuto, Anna; Kabbani, Nazir; Bell, John C.; Baetz, Kristin; Kærn, Mads

doi:10.1016/j.bpj.2011.04.021

Cited by 29 publications

(32 citation statements)

References 19 publications

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“…Since none of the isolated strains showed multimodal distributions and almost all of our promoters have at least 75% of their reads within a single distribution peak, we do not expect that this filter removed a considerable number of promoters that derive true multimodal expression distribution; however, removing this filter is advised if the tested promoters may produce such distributions. Fifth, since in our method the promoters are integrated into plasmids in a fixed position, we do not measure the effect of the local chromatin structure on the promoter function (Batenchuk et al 2011). It would be interesting to investigate this effect by measuring the function of our set of promoters in various genomic contexts.…”

Section: Dna-encoded Determinants Of Transcription Noisementioning

confidence: 99%

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Probing the effect of promoters on noise in gene expression using thousands of designed sequences

et al. 2014

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Genetically identical cells exhibit large variability (noise) in gene expression, with important consequences for cellular function. Although the amount of noise decreases with and is thus partly determined by the mean expression level, the extent to which different promoter sequences can deviate away from this trend is not fully known. Here, we present a high-throughput method for measuring promoter-driven noise for thousands of designed synthetic promoters in parallel. We use it to investigate how promoters encode different noise levels and find that the noise levels of promoters with similar mean expression levels can vary more than one order of magnitude, with nucleosome-disfavoring sequences resulting in lower noise and more transcription factor binding sites resulting in higher noise. We propose a kinetic model of gene expression that takes into account the nonspecific DNA binding and one-dimensional sliding along the DNA, which occurs when transcription factors search for their target sites. We show that this assumption can improve the prediction of the mean-independent component of expression noise for our designed promoter sequences, suggesting that a transcription factor target search may affect gene expression noise. Consistent with our findings in designed promoters, we find that binding-site multiplicity in native promoters is associated with higher expression noise. Overall, our results demonstrate that small changes in promoter DNA sequence can tune noise levels in a manner that is predictable and partly decoupled from effects on the mean expression levels. These insights may assist in designing promoters with desired noise levels.

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Section: Dna-encoded Determinants Of Transcription Noisementioning

confidence: 99%

“…In addition, the local chromatin structure of the gene may also affect its level of expression noise (Batenchuk et al 2011). One way to isolate this effect is to integrate the tested promoter upstream of a reporter gene and within a fixed genomic context.…”

Section: [Supplemental Materials Is Available For This Article]mentioning

confidence: 99%

Probing the effect of promoters on noise in gene expression using thousands of designed sequences

et al. 2014

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“…The burst frequency from an episodic gene, or the number of bursts of transcription that occur at that gene per cell cycle, reflects the promoter activation rate and may also vary from cell to cell. Recent studies have demonstrated both constitutive and episodic gene expression exist across organisms (14)(15)(16)(17). One emerging theme is that chromosomal context matters.…”

Section: Stochastic Events and Chromatinmentioning

confidence: 99%

“…One emerging theme is that chromosomal context matters. For instance, the site of integration of reporter genes across chromosome III in budding yeast influences the burst size of their transcriptional activity, and this may be modulated by histone deacetylation (16). Less widely explored, however, is how chromatin context and stochastic gene expression intersect to influence cell fate decisions (18).…”

Section: Stochastic Events and Chromatinmentioning

confidence: 99%

Creating memories of transcription

Kirchmaier¹

2013

Proc. Natl. Acad. Sci. U.S.A.

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“…However, it is uncertain how applicable these findings are to bacteria, given their different mechanisms of transcription and translation. Furthermore, bacteria have different chromosome structures (Rocha 2008) and lack histones, which are largely responsible for position effects on gene silencing (Brand et al 1985) and gene expression noise in eukaryotes (Batenchuk et al 2011). Given that gene clustering is common, any effect it has on gene expression could have a major impact on analyses of gene regulation and the construction of synthetic gene circuits.…”

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confidence: 99%

Minimal Effect of Gene Clustering on Expression inEscherichia coli

Liang¹,

Hussein²,

Block

et al. 2013

Genetics

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Genes that interact or function together are often clustered in bacterial genomes, and it has been proposed that this clustering may affect gene expression. In this study, we directly compared gene expression in nonclustered arrangements and in three common clustered arrangements (codirectional, divergent, and operon) using synthetic circuits in Escherichia coli. We found that gene clustering had minimal effects on gene expression. Specifically, gene clustering did not alter constitutive expression levels or stochastic fluctuations in expression ("expression noise"). Remarkably, the expression of two genes that share the same chromosome position with the same promoter (operon) or with separate promoters (codirectional and divergent arrangements) was not significantly more correlated than genes at different chromosome positions (nonclustered arrangements). The only observed effect of clustering was increased transcription factor binding in codirectional and divergent gene arrangements due to DNA looping, but this is not a specific feature of clustering. In summary, we demonstrate that gene clustering is not a general modulator of gene expression, and therefore any effects of clustering are likely to occur only with specific genes or under certain conditions. BACTERIAL genes that have products that interact or function within a common pathway are often adjacent to one another on the chromosome (i.e., the genes are "clustered") (reviewed in Rocha 2008). Genes that are commonly clustered include those that encode proteins in a metabolic pathway or proteins in multi-protein complexes. Regulatory genes that encode transcription factors are also commonly located next to their target genes. Common arrangements of clustered genes are (1) codirectional (//, genes on the same DNA strand with separate promoters); (2) divergent ()/, genes on opposite DNA strands with separate promoters); and (3) operons (/, genes on the same DNA strand with a shared promoter) (Korbel et al. 2004). Clustered genes that are located on opposite DNA strands with convergent transcription (/)) are less common.A common functional explanation for gene clustering is that it results in more correlated gene expression. That is, genes that are next to each other on the chromosome are more likely to be affected in the same way by DNA compaction and supercoiling (Jeong et al. 2004;Kepes 2004;Peter et al. 2004;Allen et al. 2006;Mathelier and Carbone 2010), gene dosage (Cooper and Helmstetter 1968;Chandler and Pritchard 1975;Schmid and Roth 1987;Sousa et al. 1997), and neighboring sequences (De and Babu 2010). Therefore, the expression of clustered genes is expected to be more likely to increase and decrease in synchrony (due to variation in these local chromosome position effects), resulting in more correlated expression than occurs with nonclustered genes. It has been proposed that more correlated gene expression helps maintain the optimal stoichiometry of the gene products, thereby increasing efficiency and/or decreasing the concentration of tox...

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Chromosomal Position Effects Are Linked to Sir2-Mediated Variation in Transcriptional Burst Size

Cited by 29 publications

References 19 publications

Probing the effect of promoters on noise in gene expression using thousands of designed sequences

Probing the effect of promoters on noise in gene expression using thousands of designed sequences

Creating memories of transcription

Minimal Effect of Gene Clustering on Expression inEscherichia coli

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