Literature DB >> 26522167

Estimation of kinetic parameters of transcription from temporal single-RNA measurements.

Christoph Zimmer1, Antti Häkkinen2, Andre S Ribeiro2.   

Abstract

Gene expression dynamics in prokaryotes is largely controlled by the multi-step process of transcription initiation whose kinetics is subject to regulation. Since the number and duration of these steps cannot be currently measured in vivo, we propose a novel method for estimating them from time series of RNA numbers in individual cells. We demonstrate the method's applicability on measurements of fluorescence-tagged RNA molecules in Escherichia coli cells, and compare with a previous method. We show that the results of the two methods agree for equal data. We also show that, when incorporating additional data, the new method produces significantly different estimates, which are in closer agreement with qPCR measurements. Unlike the previous method, the new method requires no preprocessing of the RNA numbers, using maximal information from the RNA time series. In addition, it can use data outside of the observed RNA productions. Overall, the new method characterizes the transcription initiation process with enhanced detail.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Parameter estimation; Single-RNA measurements; Stochastic modeling; Transcription dynamics

Mesh:

Substances:

Year:  2015        PMID: 26522167     DOI: 10.1016/j.mbs.2015.10.001

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  1 in total

1.  Using average transcription level to understand the regulation of stochastic gene activation.

Authors:  Liang Chen; Genghong Lin; Feng Jiao
Journal:  R Soc Open Sci       Date:  2022-02-16       Impact factor: 2.963

  1 in total

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