A systems approach to understand the origin of transcriptional bursting
Lead Research Organisation:
University of Warwick
Department Name: School of Life Sciences
Abstract
Genetically identical cells, in identical environments often behave very differently to each other. This is clearly evident in transcription which often has large variations of mRNA in that are found in individual cells. This transcriptional noise is poorly understood, especially in mammalian cells. Understanding, and controlling this noise is of great interest to synthetic biology as this noise makes synthetic genetic networks unpredictable and unreliable.
Of particular interest is the phenomena of transcriptional bursting, this is when a gene switches between an 'off' state and an 'on' state, where transcription only occurs in the 'on' state. This results in bursts of expression of a gene. My research will address the question - what is the origin of transcriptional bursting?
This research will answer the question by combining imaging, genetic engineering, high throughput sequencing, bioinformatics and model fitting. More specifically; by perturbing interactions between the promotor and the 3' ends of genes and perturbing mediator/RNA polymerase II condensates.
The projected outcomes of this project would be a significant advance in our understanding of transcriptional variability in mammalian cells, in particular how DNA interactions and polymerase condensates influence this. The project will also provide new ways to control biological noise, vital knowledge for synthetic biology applications.
Of particular interest is the phenomena of transcriptional bursting, this is when a gene switches between an 'off' state and an 'on' state, where transcription only occurs in the 'on' state. This results in bursts of expression of a gene. My research will address the question - what is the origin of transcriptional bursting?
This research will answer the question by combining imaging, genetic engineering, high throughput sequencing, bioinformatics and model fitting. More specifically; by perturbing interactions between the promotor and the 3' ends of genes and perturbing mediator/RNA polymerase II condensates.
The projected outcomes of this project would be a significant advance in our understanding of transcriptional variability in mammalian cells, in particular how DNA interactions and polymerase condensates influence this. The project will also provide new ways to control biological noise, vital knowledge for synthetic biology applications.
Organisations
Publications
Davies P
(2021)
Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision.
in Briefings in bioinformatics
Cavallaro M
(2021)
3 '-5 ' crosstalk contributes to transcriptional bursting
in Genome Biology
Winczura K
(2021)
RPRD Proteins Control Transcription in Human Cells
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/M01116X/1 | 01/10/2015 | 31/03/2024 | |||
| 1897782 | Studentship | BB/M01116X/1 | 02/10/2017 | 31/03/2022 | Matthew Jones |
| Description | Background Transcription in mammalian cells is a complex stochastic process involving shuttling of polymerase between genes and phase-separated liquid condensates. It occurs in bursts, which results in vastly different numbers of an mRNA species in isogenic cell populations. Several factors contributing to transcriptional bursting have been identified, usually classified as intrinsic, in other words local to single genes, or extrinsic, relating to the macroscopic state of the cell. However, some possible contributors have not been explored yet. Here, we focus on processes at the 3 ' and 5 ' ends of a gene that enable reinitiation of transcription upon termination. Results Using Bayesian methodology, we measure the transcriptional bursting in inducible transgenes, showing that perturbation of polymerase shuttling typically reduces burst size, increases burst frequency, and thus limits transcriptional noise. Analysis based on paired-end tag sequencing (PolII ChIA-PET) suggests that this effect is genome wide. The observed noise patterns are also reproduced by a generative model that captures major characteristics of the polymerase flux between the ends of a gene and a phase-separated compartment. Conclusions Interactions between the 3 ' and 5 ' ends of a gene, which facilitate polymerase recycling, are major contributors to transcriptional noise. |
| Exploitation Route | This could also have implications in synthetic biology, where the optimisation of gene expression and the control of its noise are desirable features |
| Sectors | Manufacturing, including Industrial Biotechology |