Single-RNA counting reveals alternative modes of gene expression in yeast

Zenklusen, Daniel; Larson, Daniel R.; Singer, Robert H.

doi:10.1038/nsmb.1514

Cited by 696 publications

(798 citation statements)

References 60 publications

(91 reference statements)

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“…Note that the Sc estimates are virtually identical to ours, although we used a different labeling technique (4tU instead of 4sU) and had spiked-in Sp controls in the sample. a Please note that we previously used in our calculations a total number of transcripts per cell of 15,000 according to an old estimate (Hereford and Rosbash 1977), whereas we now used a recent estimate of 60,000 (Zenklusen et al 2008). If the same number of transcripts is used, the median synthesis rate obtained by DTA would be 72, comparable to our new estimate obtained by cDTA, despite the difference in media and cell cycle time (Miller et al 2011).…”

Section: Impaired Mrna Synthesis Is Compensated By Decreased Degradationmentioning

confidence: 64%

“…RNA halflives that were recently determined by 4tU pulse-chase labeling in Sc are 1.5-fold longer (Munchel et al 2011), likely because a very long labeling time was used that allowed for thionucleotide reincorporation after mRNA decay. We calculated mRNA synthesis rates as the number of complete transcripts made per cell and per 90 min (the cell cycle time for wild-type Sc), using a new estimate of 60,000 transcripts per yeast cell (Zenklusen et al 2008) instead of the previously used, older, and fourfold lower estimate (Hereford and Rosbash 1977). For Sp, we estimated the number of transcripts from the observed 2.51-fold cumulative total RNA level to be 150,801.…”

Section: Rate Extraction From Cdta Datamentioning

confidence: 99%

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Comparative dynamic transcriptome analysis (cDTA) reveals mutual feedback between mRNA synthesis and degradation

Sun

Schwalb²,

Schulz³

et al. 2012

Genome Res.

288

377

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To monitor eukaryotic mRNA metabolism, we developed comparative dynamic transcriptome analysis (cDTA). cDTA provides absolute rates of mRNA synthesis and decay in Saccharomyces cerevisiae (Sc) cells with the use of Schizosaccharomyces pombe (Sp) as an internal standard. cDTA uses nonperturbing metabolic labeling that supersedes conventional methods for mRNA turnover analysis. cDTA reveals that Sc and Sp transcripts that encode orthologous proteins have similar synthesis rates, whereas decay rates are fivefold lower in Sp, resulting in similar mRNA concentrations despite the larger Sp cell volume. cDTA of Sc mutants reveals that a eukaryote can buffer mRNA levels. Impairing transcription with a point mutation in RNA polymerase (Pol) II causes decreased mRNA synthesis rates as expected, but also decreased decay rates. Impairing mRNA degradation by deleting deadenylase subunits of the Ccr4-Not complex causes decreased decay rates as expected, but also decreased synthesis rates. Extended kinetic modeling reveals mutual feedback between mRNA synthesis and degradation that may be achieved by a factor that inhibits synthesis and enhances degradation.

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Section: Impaired Mrna Synthesis Is Compensated By Decreased Degradationmentioning

confidence: 64%

Section: Rate Extraction From Cdta Datamentioning

confidence: 99%

Comparative dynamic transcriptome analysis (cDTA) reveals mutual feedback between mRNA synthesis and degradation

Sun

Schwalb²,

Schulz³

et al. 2012

Genome Res.

288

377

View full text Add to dashboard Cite

show abstract

“…Note that burst size, b, accounts for all the transcription-translation processes following the main stochastic event (burst initiation), integrating the number of mRNA molecules produced per burst and the number of protein molecules made per each mRNA molecule. Upon a perturbation, the noise-mean relationship may change, depending on whether burst size or burst frequency were modulated (Pedraza and Paulsson 2008;Zenklusen et al 2008;Tan and van Oudenaarden 2010).…”

mentioning

confidence: 99%

Noise–mean relationship in mutated promoters

Hornung¹,

Bar‐Ziv²,

Rosin³

et al. 2012

Genome Res.

169

210

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Gene expression depends on the frequency of transcription events (burst frequency) and on the number of mRNA molecules made per event (burst size). Both processes are encoded in promoter sequence, yet their dependence on mutations is poorly understood. Theory suggests that burst size and frequency can be distinguished by monitoring the stochastic variation (noise) in gene expression: Increasing burst size will increase mean expression without changing noise, while increasing burst frequency will increase mean expression and decrease noise. To reveal principles by which promoter sequence regulates burst size and frequency, we randomly mutated 22 yeast promoters chosen to span a range of expression and noise levels, generating libraries of hundreds of sequence variants. In each library, mean expression (m) and noise (coefficient of variation, h) varied together, defining a scaling curve: h 2 = b/m + h ext 2 . This relation is expected if sequence mutations modulate burst frequency primarily. The estimated burst size (b) differed between promoters, being higher in promoter containing a TATA box and lacking a nucleosome-free region. The rare variants that significantly decreased b were explained by mutations in TATA, or by an insertion of an out-of-frame translation start site. The decrease in burst size due to mutations in TATA was promoter-dependent, but independent of other mutations. These TATA box mutations also modulated the responsiveness of gene expression to changing conditions. Our results suggest that burst size is a promoter-specific property that is relatively robust to sequence mutations but is strongly dependent on the interaction between the TATA box and promoter nucleosomes.

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“…The importance of rigorous quantification of gene expression in arriving at this conclusion has to be emphasized. In this regard, it should be noted that smRNA FISH offered a better approach than immunostaining because the signals are discrete and can be expressed as counts instead of as relative intensity levels [49]. In addition, by measuring RNA levels, smRNA FISH provided a more immediate read-out of the transcriptional changes that occurs early in differentiation.…”

Section: Discussionmentioning

confidence: 99%

Single Cell Analysis Reveals Concomitant Transcription of Pluripotent and Lineage Markers During the Early Steps of Differentiation of Embryonic Stem Cells

Lanctôt

2015

Stem Cells

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The differentiation of embryonic stem cells is associated with extensive changes in gene expression. It is not yet clear whether these changes are the result of binary switch-like mechanisms or that of continuous and progressive variation. Here, I have used immunostaining and single molecule RNA fluorescence in situ hybridization (FISH) to assess changes in the expression of the well-known pluripotency-associated gene Pou5f1 (also known as Oct4) and early differentiation markers Sox1 and T-brachyury in single cells during the early steps of differentiation of mouse embryonic stem cells. I found extensive overlap between the expression of Pou5f1/Sox1 or Pou5f1/T-brachyury shortly after the initiation of differentiation towards either the neuronal or the mesendodermal lineage, but no evidence of correlation between their respective expression levels. Quantitative analysis of transcriptional output at the sites of nascent transcription revealed that Pou5f1 and Sox1 were transcribed in pulses and that embryonic stem cell differentiation was accompanied by changes in pulsing frequencies. The progressive induction of Sox1 was further associated with an increase in the average size of individual transcriptional bursts. Surprisingly, single cells that actively and simultaneously transcribe both the pluripotency-and the lineage-associated genes could easily be found in the differentiating population. The results presented here show for the first time that lineage priming can occur in cells that are actively transcribing a pluripotent marker. Furthermore, they suggest that this process is associated with changes in transcriptional dynamics. STEM CELLS 2015;33:2949-2960 SIGNIFICANCE STATEMENTEmbryonic stem cells can differentiate into various cell types. The results presented here show that this process is characterized by the existence of a transient stage at which pluripotent and lineage markers appear to be expressed in an uncorrelated fashion. This lack of correlation extends to nascent transcription, as evidenced by the detection of cells that transcribe a stem cell marker alongside a lineage one. These observations highlight the plasticity of the early differentiation process, a property which could eventually be exploited to influence the fate chosen by embryonic stem cells.

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Single-RNA counting reveals alternative modes of gene expression in yeast

Cited by 696 publications

References 60 publications

Comparative dynamic transcriptome analysis (cDTA) reveals mutual feedback between mRNA synthesis and degradation

Comparative dynamic transcriptome analysis (cDTA) reveals mutual feedback between mRNA synthesis and degradation

Noise–mean relationship in mutated promoters

Single Cell Analysis Reveals Concomitant Transcription of Pluripotent and Lineage Markers During the Early Steps of Differentiation of Embryonic Stem Cells

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