Evidence map›Paper›PMID 26828110›Full record

ArticleeLife2016

Spatially coordinated dynamic gene transcription in living pituitary tissue.

Karen Featherstone, Kirsty Hey, Hiroshi Momiji, Anne V McNamara, Amanda L Patist, Joanna Woodburn, David G Spiller, Helen C Christian, Alan S McNeilly, John J Mullins and 4 more

Abstract read
In one paragraph

Article in eLife, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

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  13. Multimodal transcriptional control of pattern formation in embryonic development.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Karen FeatherstoneCentre for Endocrinology and Diabetes, University of Manchester, Manchester, United Kingdom.
Kirsty HeyDepartment of Statistics, University of Warwick, Coventry, United Kingdom.
Hiroshi MomijiWarwick Systems Biology, University of Warwick, Coventry, United Kingdom.
Anne V McNamaraSystems Biology Centre, University of Manchester, Manchester, United Kingdom.
Amanda L PatistCentre for Endocrinology and Diabetes, University of Manchester, Manchester, United Kingdom.
Joanna WoodburnCentre for Endocrinology and Diabetes, University of Manchester, Manchester, United Kingdom.
David G SpillerSystems Biology Centre, University of Manchester, Manchester, United Kingdom.
Helen C ChristianDepartment of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom.
Alan S McNeillyMRC Centre for Reproductive Health, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom.
John J MullinsThe Molecular Physiology Group, Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom.
Bärbel F FinkenstädtDepartment of Statistics, University of Warwick, Coventry, United Kingdom.
David A RandWarwick Systems Biology, University of Warwick, Coventry, United Kingdom.
Michael R H WhiteSystems Biology Centre, University of Manchester, Manchester, United Kingdom.
Julian R E DavisCentre for Endocrinology and Diabetes, University of Manchester, Manchester, United Kingdom.

Funding

Biotechnology and Biological Sciences Research Council BB/K003097/1British Heart FoundationMedical Research Council MR/K015885/1Medical Research Council MR/M008908/1Wellcome Trust
6 · The paper itself

Abstract

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.

Indexed as

Gene Expression RegulationTranscription, GeneticAnimalsGene Expression ProfilingGenes, ReporterOptical ImagingPituitary GlandRats, Inbred F344Spatio-Temporal Analysiscell biologycomputational biologyLive-Cell MicroscopyPituitaryratSpatial OrganisationStochastic Modellingsystems biologyTranscription Dynamics

Identifiers

PMID26828110
PMCPMC4749562

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.