Revealing a law of transcriptional bursting by absolute quantification of nascent RNA in live Drosophila embryos

Abstract

Transcriptional bursting has been observed as a common regulatory strategy for controlling gene outputs in various organisms, from bacteria to yeast, from developing Drosophila embryos to human cells. The search of the molecular determinants of bursting has been an active field of research over the past 15 years. Experimental designs that dissect transcriptional regulation process into its smaller parts has helped us identify many molecular processes associated with the modulation of bursting parameters under various physiological conditions, such as enhancer regulation, transcription factor regulation, epigenetics modifications, etc. However, these reductionist insights have not yet been successful in adding up to a coherent biophysical model that links molecular mechanisms to the observed bursting regulation. In this thesis work, I aim to provide a unified perspective on this problem, using an improved live imaging module with Drosophila embryos as a model. Specifically, in Chapter 1, I briefly discuss our current state of knowledge on bursting regulation, and point out the conundrum we are facing. I argue early Drosophila embryos could be a good model to address some aspects of the problems. In Chapter 2, I design a highly quantitative two-photon laser scanning microscope and develop a scheme to characterize its performance. My goal is to quantify the transcriptional activity in live Drosophila embryos with single RNA detection sensitivity. In Chapter 3, we extensively analyze the dynamic promoter activity of four gap genes with our quantitative live imaging data. We reveal a unified regulatory strategy shared among gap genes that demonstrate surprising constraints on the regulation of bursting parameters. In Chapter 4, we further test this regulatory strategy in mutants. The results suggest the confined bursting regulation could be linked to some core biophysical properties of the evolutionarily conserved eukaryotic transcriptional machinery. We also demonstrate the transcription activity is correlated between two alleles.