Author response: Spatially coordinated dynamic gene transcription in living pituitary tissue

Featherstone, Karen; Hey, Kirsty; Momiji, Hiroshi; McNamara, A.; Patist, Amanda L.; Woodburn, Joanna; Spiller, David G.; Christian, Helen; McNeilly, Alan S.; Mullins, John J.; Finkenstädt, Bärbel; Rand, D.A.J.; White, Michael R. H.; Davis, Julian

doi:10.7554/elife.08494.026

Cited by 3 publications

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“…The analysis presented in the main paper has been calculated from the set of all possible transcriptional profiles, weighted by their probability of occurrence. Data of d2EGFP fluorescence measured in single cells and subsequent stochastic switch modelling of transcription activity have been deposited in the Dryad data repository ( Featherstone et al, 2015 )…”

Section: Methodsmentioning

confidence: 99%

Spatially coordinated dynamic gene transcription in living pituitary tissue

Featherstone

Hey

Momiji

et al. 2016

eLife

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Transcription at individual genes in single cells is often pulsatile and stochastic. A key question emerges regarding how this behaviour contributes to tissue phenotype, but it has been a challenge to quantitatively analyse this in living cells over time, as opposed to studying snap-shots of gene expression state. We have used imaging of reporter gene expression to track transcription in living pituitary tissue. We integrated live-cell imaging data with statistical modelling for quantitative real-time estimation of the timing of switching between transcriptional states across a whole tissue. Multiple levels of transcription rate were identified, indicating that gene expression is not a simple binary ‘on-off’ process. Immature tissue displayed shorter durations of high-expressing states than the adult. In adult pituitary tissue, direct cell contacts involving gap junctions allowed local spatial coordination of prolactin gene expression. Our findings identify how heterogeneous transcriptional dynamics of single cells may contribute to overall tissue behaviour.DOI: http://dx.doi.org/10.7554/eLife.08494.001

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Section: Methodsmentioning

confidence: 99%

Spatially coordinated dynamic gene transcription in living pituitary tissue

Featherstone

Hey

Momiji

et al. 2016

eLife

Self Cite

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“…In the last several years, developmental studies have also shown that the level of cell-to-cell transcriptional variability among tissues is controlled by cellular interactions. [56][57][58][59] The constraints that canalize cells towards their stable phenotypic state appear to be in large part direct or long-range cellular interactions. Signaling from receptors at the cell surface is probably at the origin of the chromatin stabiliza-tion process via post-translational modifications of proteins interacting with DNA.…”

Section: Cellular Stochasticity Decreases During Differentiationmentioning

confidence: 99%

Tissue‐disruption‐induced cellular stochasticity and epigenetic drift: Common origins of aging and cancer?

Capp

Thomas

2020

BioEssays

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Age-related and cancer-related epigenomic modifications have been associated with enhanced cell-to-cell gene expression variability that characterizes increased cellular stochasticity. Since gene expression variability appears to be highly reduced byand epigenetic and phenotypic stability acquired through-direct or long-range cellular interactions during cell differentiation, we propose a common origin for aging and cancer in the failure to control cellular stochasticity by cell-cell interactions. Tissuedisruption-induced cellular stochasticity associated with epigenetic drift would be at the origin of organ dysfunction because of an increase in phenotypic variation among cells, ultimately leading to cell death and organ failure through a loss of coordination in cellular functions, and eventually to cancerization. We propose mechanistic research perspectives to corroborate this hypothesis and explore its evolutionary consequences, highlighting a positive correlation between the median age of mass loss onset (a proxy for the onset of organ aging) and the median age at cancer diagnosis.

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Transcriptional bursting dynamics in gene expression

Zhang,

Cao,

Wang

et al. 2024

Front. Genet.

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Gene transcription is a stochastic process that occurs in all organisms. Transcriptional bursting, a critical molecular dynamics mechanism, creates significant heterogeneity in mRNA and protein levels. This heterogeneity drives cellular phenotypic diversity. Currently, the lack of a comprehensive quantitative model limits the research on transcriptional bursting. This review examines various gene expression models and compares their strengths and weaknesses to guide researchers in selecting the most suitable model for their research context. We also provide a detailed summary of the key metrics related to transcriptional bursting. We compared the temporal dynamics of transcriptional bursting across species and the molecular mechanisms influencing these bursts, and highlighted the spatiotemporal patterns of gene expression differences by utilizing metrics such as burst size and burst frequency. We summarized the strategies for modeling gene expression from both biostatistical and biochemical reaction network perspectives. Single-cell sequencing data and integrated multiomics approaches drive our exploration of cutting-edge trends in transcriptional bursting mechanisms. Moreover, we examined classical methods for parameter estimation that help capture dynamic parameters in gene expression data, assessing their merits and limitations to facilitate optimal parameter estimation. Our comprehensive summary and review of the current transcriptional burst dynamics theories provide deeper insights for promoting research on the nature of cell processes, cell fate determination, and cancer diagnosis.

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Author response: Spatially coordinated dynamic gene transcription in living pituitary tissue

Cited by 3 publications

References 0 publications

Spatially coordinated dynamic gene transcription in living pituitary tissue

Spatially coordinated dynamic gene transcription in living pituitary tissue

Tissue‐disruption‐induced cellular stochasticity and epigenetic drift: Common origins of aging and cancer?

Transcriptional bursting dynamics in gene expression

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