1. Real-time single-cell characterization of the eukaryotic transcription cycle reveals correlations between RNA initiation, elongation, and cleavage
- Author
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Simon Alamos, Donald Hansen, Hernan G. Garcia, Elizabeth Eck, Jonathan Liu, Yang Joon Kim, and Meghan A Turner
- Subjects
Embryology ,Transcription, Genetic ,Statistical methods ,Cell ,Gene Expression ,Biochemistry ,chemistry.chemical_compound ,Signal Initiation ,Transcription (biology) ,RNA polymerase ,Biology (General) ,Ecology ,Hydrolysis ,Transcriptional Control ,Messenger RNA ,Drosophila Melanogaster ,Mechanisms of Signal Transduction ,Statistics ,Eukaryota ,Animal Models ,Nucleic acids ,Monte Carlo method ,Physical sciences ,Insects ,medicine.anatomical_structure ,Experimental Organism Systems ,Computational Theory and Mathematics ,Modeling and Simulation ,Drosophila ,Single-Cell Analysis ,Research Article ,Signal Transduction ,Arthropoda ,QH301-705.5 ,DNA transcription ,Computational biology ,Cleavage (embryo) ,Cellular and Molecular Neuroscience ,Model Organisms ,Gene Types ,Genetics ,medicine ,Animals ,Gene Regulation ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Reporter gene ,Embryos ,Eukaryotic transcription ,Organisms ,Biology and Life Sciences ,RNA ,Cell Biology ,Invertebrates ,Research and analysis methods ,chemistry ,Animal Studies ,Mathematical and statistical techniques ,RNA Cleavage ,Zoology ,Entomology ,Mathematics ,Transcription Factors ,Developmental Biology ,Reporter Genes - Abstract
The eukaryotic transcription cycle consists of three main steps: initiation, elongation, and cleavage of the nascent RNA transcript. Although each of these steps can be regulated as well as coupled with each other, their in vivo dissection has remained challenging because available experimental readouts lack sufficient spatiotemporal resolution to separate the contributions from each of these steps. Here, we describe a novel application of Bayesian inference techniques to simultaneously infer the effective parameters of the transcription cycle in real time and at the single-cell level using a two-color MS2/PP7 reporter gene and the developing fruit fly embryo as a case study. Our method enables detailed investigations into cell-to-cell variability in transcription-cycle parameters as well as single-cell correlations between these parameters. These measurements, combined with theoretical modeling, suggest a substantial variability in the elongation rate of individual RNA polymerase molecules. We further illustrate the power of this technique by uncovering a novel mechanistic connection between RNA polymerase density and nascent RNA cleavage efficiency. Thus, our approach makes it possible to shed light on the regulatory mechanisms in play during each step of the transcription cycle in individual, living cells at high spatiotemporal resolution., Author summary Live cell imaging using fluorescence microscopy provides an exciting way to visualize the transcription cycle in living organisms with great amounts of precision. However, the output of these technologies is often complex and can be hard to interpret. We have developed a computational framework for analyzing the transcription cycle that quantifies rates of RNA initiation, elongation, and cleavage, given input datasets from live cell imaging. Using the developing fruit fly embryo as a case study, we demonstrate that our methodology can quantitatively describe the whole transcription cycle at single-cell resolution. These results allow us to investigate a plethora of avenues, from couplings between different aspects of the transcription cycle at the single-cell level to comparisons with theoretical predictions of distributions of elongation rates across cells. We envision our methodology to provide a unified computational framework for the analysis of transcriptional data obtained from live cell imaging.
- Published
- 2021