Cargando…

Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules

Deciphering how the regulatory DNA sequence of a gene dictates its expression in response to intra and extracellular cues is one of the leading challenges in modern genomics. The development of novel single-cell sequencing and imaging techniques, as well as a better exploitation of currently availab...

Descripción completa

Detalles Bibliográficos
Autores principales: Choubey, Sandeep, Kondev, Jane, Sanchez, Alvaro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636183/
https://www.ncbi.nlm.nih.gov/pubmed/26544860
http://dx.doi.org/10.1371/journal.pcbi.1004345
_version_ 1782399614358388736
author Choubey, Sandeep
Kondev, Jane
Sanchez, Alvaro
author_facet Choubey, Sandeep
Kondev, Jane
Sanchez, Alvaro
author_sort Choubey, Sandeep
collection PubMed
description Deciphering how the regulatory DNA sequence of a gene dictates its expression in response to intra and extracellular cues is one of the leading challenges in modern genomics. The development of novel single-cell sequencing and imaging techniques, as well as a better exploitation of currently available single-molecule imaging techniques, provides an avenue to interrogate the process of transcription and its dynamics in cells by quantifying the number of RNA polymerases engaged in the transcription of a gene (or equivalently the number of nascent RNAs) at a given moment in time. In this paper, we propose that measurements of the cell-to-cell variability in the number of nascent RNAs provide a mostly unexplored method for deciphering mechanisms of transcription initiation in cells. We propose a simple kinetic model of transcription initiation and elongation from which we calculate nascent RNA copy-number fluctuations. To demonstrate the usefulness of this approach, we test our theory against published nascent RNA data for twelve constitutively expressed yeast genes. Rather than transcription being initiated through a single rate limiting step, as it had been previously proposed, our single-cell analysis reveals the presence of at least two rate limiting steps. Surprisingly, half of the genes analyzed have nearly identical rates of transcription initiation, suggesting a common mechanism. Our analytical framework can be used to extract quantitative information about dynamics of transcription from single-cell sequencing data, as well as from single-molecule imaging and electron micrographs of fixed cells, and provides the mathematical means to exploit the quantitative power of these technologies.
format Online
Article
Text
id pubmed-4636183
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-46361832015-11-13 Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules Choubey, Sandeep Kondev, Jane Sanchez, Alvaro PLoS Comput Biol Research Article Deciphering how the regulatory DNA sequence of a gene dictates its expression in response to intra and extracellular cues is one of the leading challenges in modern genomics. The development of novel single-cell sequencing and imaging techniques, as well as a better exploitation of currently available single-molecule imaging techniques, provides an avenue to interrogate the process of transcription and its dynamics in cells by quantifying the number of RNA polymerases engaged in the transcription of a gene (or equivalently the number of nascent RNAs) at a given moment in time. In this paper, we propose that measurements of the cell-to-cell variability in the number of nascent RNAs provide a mostly unexplored method for deciphering mechanisms of transcription initiation in cells. We propose a simple kinetic model of transcription initiation and elongation from which we calculate nascent RNA copy-number fluctuations. To demonstrate the usefulness of this approach, we test our theory against published nascent RNA data for twelve constitutively expressed yeast genes. Rather than transcription being initiated through a single rate limiting step, as it had been previously proposed, our single-cell analysis reveals the presence of at least two rate limiting steps. Surprisingly, half of the genes analyzed have nearly identical rates of transcription initiation, suggesting a common mechanism. Our analytical framework can be used to extract quantitative information about dynamics of transcription from single-cell sequencing data, as well as from single-molecule imaging and electron micrographs of fixed cells, and provides the mathematical means to exploit the quantitative power of these technologies. Public Library of Science 2015-11-06 /pmc/articles/PMC4636183/ /pubmed/26544860 http://dx.doi.org/10.1371/journal.pcbi.1004345 Text en © 2015 Choubey et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Choubey, Sandeep
Kondev, Jane
Sanchez, Alvaro
Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules
title Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules
title_full Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules
title_fullStr Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules
title_full_unstemmed Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules
title_short Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules
title_sort deciphering transcriptional dynamics in vivo by counting nascent rna molecules
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636183/
https://www.ncbi.nlm.nih.gov/pubmed/26544860
http://dx.doi.org/10.1371/journal.pcbi.1004345
work_keys_str_mv AT choubeysandeep decipheringtranscriptionaldynamicsinvivobycountingnascentrnamolecules
AT kondevjane decipheringtranscriptionaldynamicsinvivobycountingnascentrnamolecules
AT sanchezalvaro decipheringtranscriptionaldynamicsinvivobycountingnascentrnamolecules