A mathematical model for synergistic eukaryotic gene activation 1 1Edited by F. E. Cohen

Wang, Jin; Ellwood, Katharine; Lehman, Alison M.; Carey, Michael; She, Zhen‐Su

doi:10.1006/jmbi.1998.2489

Cited by 38 publications

(43 citation statements)

References 30 publications

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“…The presence of at least two sequential steps that are regulated by activators readily explains transcriptional synergy (35,36). It is widely known that transcriptional synergy occurs even with a single type of activator such as GAL4-VP16 if bound multiply on a promoter (37,38), at which each activator is presumed to contact a different target within each PIC and to stimulate a distinct step of the transcriptional pathway (1,39,40).…”

Section: Discussionmentioning

confidence: 99%

The regulatory role for the ERCC3 helicase of general transcription factor TFIIH during promoter escape in transcriptional activation

Fukuda

Nogi²,

Hisatake³

2002

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

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Eukaryotic transcriptional activators have been proposed to function, for the most part, by promoting the assembly of preinitiation complex through the recruitment of the RNA polymerase II transcriptional machinery to the promoter. Previous studies have shown that transcriptional activation is critically dependent on transcription factor IIH (TFIIH), which functions during promoter opening and promoter escape, the steps following preinitiation complex assembly. Here we have analyzed the role of TFIIH in transcriptional activation and show that the excision repair crosscomplementing (ERCC) 3 helicase activity of TFIIH plays a regulatory role to stimulate promoter escape in activated transcription. The stimulatory effect of the ERCC3 helicase is observed until Ϸ10-nt RNA is synthesized, and the helicase seems to act throughout the entire course of promoter escape. Analyses of the early phase of transcription show that a majority of the initiated complexes abort transcription and fail to escape the promoter; however, the proportion of productive complexes that escape the promoter apparently increases in response to activation. Our results establish that promoter escape is an important regulatory step stimulated by the ERCC3 helicase activity in response to activation and reveal a possible mechanism of transcriptional synergy.

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Section: Discussionmentioning

confidence: 99%

The regulatory role for the ERCC3 helicase of general transcription factor TFIIH during promoter escape in transcriptional activation

Fukuda

Nogi²,

Hisatake³

2002

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

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“…The regulation of gene expression in eukaryotes can be modeled using laws of statistical thermodynamics and Boltzmann's factor (e.g., Gibson 1996;Wang et al 1999). Our model includes variables sufficient to capture the qualitative behavior of gene expression regulation: the concentration of the transcription factor regulating the gene of interest (x, molar); its binding affinity for the cis-regulatory elements of the gene it regulates, expressed as free energy DG tf (kilocalories per mole); the strength of cooperativity among the transcription-factor molecules, also expressed in terms of free energy (DG co, kilocalories per mole); and the number of binding sites for the transcription factor upstream of the gene of interest (n).…”

Section: Appendix-model Of Gene Expression Regulationmentioning

confidence: 99%

Compensatory cis-trans Evolution and the Dysregulation of Gene Expression in Interspecific Hybrids of Drosophila

et al. 2005

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Hybrids between species are often characterized by novel gene-expression patterns. A recent study on allele-specific gene expression in hybrids between species of Drosophila revealed cases in which cis-and transregulatory elements within species had coevolved in such a way that changes in cis-regulatory elements are compensated by changes in trans-regulatory elements. We hypothesized that such coevolution should often lead to gene misexpression in the hybrid. To test this hypothesis, we estimated allele-specific expression and overall expression levels for 31 genes in D. melanogaster, D. simulans, and their F 1 hybrid. We found that 13 genes with cis-trans compensatory evolution are in fact misexpressed in the hybrid. These represent candidate genes whose dysregulation might be the consequence of coevolution of cis-and trans-regulatory elements within species. Using a mathematical model for the regulation of gene expression, we explored the conditions under which cis-trans compensatory evolution can lead to misexpression in interspecific hybrids.

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“…Thus, we distinguish two cell states, active or inactive, and refer to these two states as macrostates. Thermostatistical approaches to determine transcriptional activity are based on the assumption that a cell with a promoter at which RNAP is bound is engaged in transcriptional initiation [5][6][7][8][9][10][11]. The higher the probability is that cells have an active promoter (i.e., exhibiting a RNAP molecule bound at the promoter), the higher is the transcriptional activity of the cell population.…”

Section: Micro- Meso-and Macrolevels Of the Thermostatistical Modelimentioning

confidence: 99%

“…The transcriptional activity r is assumed to be proportional to the probability P [5][6][7][8][9][10][11] …”

Section: Micro- Meso-and Macrolevels Of the Thermostatistical Modelimentioning

confidence: 99%

“…In order to derive S(P) from the transcriptional activity r measured at different time points or concentrations, we need a fit to the predicted graph r that provides us with values of the basal activity r 0 and the saturation activity r(sat) and we need to know the proportionality factor occurring in Eq. (9). Then, we will be able to identify the relationship between S(P)/S max and r/r(sat) because P can be calculated from r like ) sat ( (max) r P r P (35) From Figure 4A it follows that there are three possible cases.…”

Section: Thermostatistics-based Metric Of Cell-to-cell Variabilitymentioning

confidence: 99%

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Catching transcriptional regulation by thermostatistical modeling

et al. 2012

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Gene expression is frequently regulated by multiple transcription factors (TFs). Thermostatistical methods allow for a quantitative description of interactions between TFs, RNA polymerase, and DNA, and their impact on the transcription rates. We illustrate three different scales of the thermostatistical approach: the microscale of TF molecules, the mesoscale of promoter energy levels, and the macroscale of transcriptionally active and inactive cells in a cell population. We demonstrate versatility of combinatorial transcriptional activation by exemplifying logic functions, such as AND and OR gates. We discuss a metric for cell-to-cell transcriptional activation variability known as Fermi entropy. Suitability of thermostatistical modeling is illustrated by describing the experimental data on transcriptional induction of NF B and the c-Fos protein.2

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A mathematical model for synergistic eukaryotic gene activation 1 1Edited by F. E. Cohen

Cited by 38 publications

References 30 publications

The regulatory role for the ERCC3 helicase of general transcription factor TFIIH during promoter escape in transcriptional activation

The regulatory role for the ERCC3 helicase of general transcription factor TFIIH during promoter escape in transcriptional activation

Compensatory cis-trans Evolution and the Dysregulation of Gene Expression in Interspecific Hybrids of Drosophila

Catching transcriptional regulation by thermostatistical modeling

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