Transcriptional bursting in eukaryotic gene regulation : molecular basis and functional consequences

Transcription of mRNA appears to occur in random, intermittent bursts in a large variety of organisms. The statistics of mRNA expression can be described by two parameters: the frequency at which bursts occur (burst frequency) and the average number of mRNA produced within each burst (burst size). The mean steady-state abundance of mRNA is the product of the burst size and burst frequency. Although the experimental evidence for bursty gene transcription is abundant, little is known about its origins and consequences. We utilize single-molecule mRNA imaging and simple stochastic kinetic models to probe and understand both the mechanistic details and functional responses of transcriptional bursting in budding yeast. At the molecular level, we show that gene-specific activators can control both burst size and burst frequency by differentially utilizing kinetically distinct promoter elements. We also recognize the importance of activator residence time and nucleosome positioning on bursting. This investigation exemplifies how we can exploit spontaneous fluctuations in gene expression to uncover the molecular mechanisms and kinetic pathways of transcriptional regulation. At the network level, we demonstrate the important phenotypic consequences of transcriptional bursting by showing how noise itself can generate a bimodal, all-or-none gene expression profile that switches spontaneously between the low and high expression states in a transcriptional positive-feedback loop. Such bimodality is a hallmark in decision-making circuitry within metabolic, developmental, and synthetic gene regulatory networks. Importantly, we prove that the bimodal responses observed in our system are not due to deterministic bistability, which is an often-stated necessary condition for allor- none responses in positive-feedback loops. By clarifying a common misconception, this investigation provides unique biological insights into the molecular components, pathways and mechanisms controlling a measured phenotype.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Chemical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• To, Tsz-Leung

Advisor dc:contributor.advisor

• Narendra Maheshri.

• Chemical Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/62062

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/62062