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,
Bärbel F Finkenstädt,
David A Rand,
Michael RH White,
Julian RE Davis
Affiliations
Karen Featherstone
Centre for Endocrinology and Diabetes, University of Manchester, Manchester, United Kingdom
Kirsty Hey
Department of Statistics, University of Warwick, Coventry, United Kingdom
Hiroshi Momiji
Warwick Systems Biology, University of Warwick, Coventry, United Kingdom
Anne V McNamara
Systems Biology Centre, University of Manchester, Manchester, United Kingdom
Amanda L Patist
Centre for Endocrinology and Diabetes, University of Manchester, Manchester, United Kingdom
Joanna Woodburn
Centre for Endocrinology and Diabetes, University of Manchester, Manchester, United Kingdom
David G Spiller
Systems Biology Centre, University of Manchester, Manchester, United Kingdom
Helen C Christian
Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
Alan S McNeilly
MRC Centre for Reproductive Health, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
John J Mullins
The Molecular Physiology Group, Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
Bärbel F Finkenstädt
Department of Statistics, University of Warwick, Coventry, United Kingdom
David A Rand
Warwick Systems Biology, University of Warwick, Coventry, United Kingdom
Michael RH White
Systems Biology Centre, University of Manchester, Manchester, United Kingdom
Julian RE Davis
Centre for Endocrinology and Diabetes, University of Manchester, Manchester, United Kingdom
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.