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Temporal dynamics and transcriptional control using single-cell gene expression analysis

BACKGROUND: Changes in environmental conditions lead to expression variation that manifest at the level of gene regulatory networks. Despite a strong understanding of the role noise plays in synthetic biological systems, it remains unclear how propagation of expression heterogeneity in an endogenous...

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Autores principales: Kouno, Tsukasa, de Hoon, Michiel, Mar, Jessica C, Tomaru, Yasuhiro, Kawano, Mitsuoki, Carninci, Piero, Suzuki, Harukazu, Hayashizaki, Yoshihide, Shin, Jay W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015031/
https://www.ncbi.nlm.nih.gov/pubmed/24156252
http://dx.doi.org/10.1186/gb-2013-14-10-r118
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author Kouno, Tsukasa
de Hoon, Michiel
Mar, Jessica C
Tomaru, Yasuhiro
Kawano, Mitsuoki
Carninci, Piero
Suzuki, Harukazu
Hayashizaki, Yoshihide
Shin, Jay W
author_facet Kouno, Tsukasa
de Hoon, Michiel
Mar, Jessica C
Tomaru, Yasuhiro
Kawano, Mitsuoki
Carninci, Piero
Suzuki, Harukazu
Hayashizaki, Yoshihide
Shin, Jay W
author_sort Kouno, Tsukasa
collection PubMed
description BACKGROUND: Changes in environmental conditions lead to expression variation that manifest at the level of gene regulatory networks. Despite a strong understanding of the role noise plays in synthetic biological systems, it remains unclear how propagation of expression heterogeneity in an endogenous regulatory network is distributed and utilized by cells transitioning through a key developmental event. RESULTS: Here we investigate the temporal dynamics of a single-cell transcriptional network of 45 transcription factors in THP-1 human myeloid monocytic leukemia cells undergoing differentiation to macrophages. We systematically measure temporal regulation of expression and variation by profiling 120 single cells at eight distinct time points, and infer highly controlled regulatory modules through which signaling operates with stochastic effects. This reveals dynamic and specific rewiring as a cellular strategy for differentiation. The integration of both positive and negative co-expression networks further identifies the proto-oncogene MYB as a network hinge to modulate both the pro- and anti-differentiation pathways. CONCLUSIONS: Compared to averaged cell populations, temporal single-cell expression profiling provides a much more powerful technique to probe for mechanistic insights underlying cellular differentiation. We believe that our approach will form the basis of novel strategies to study the regulation of transcription at a single-cell level.
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spelling pubmed-40150312014-05-10 Temporal dynamics and transcriptional control using single-cell gene expression analysis Kouno, Tsukasa de Hoon, Michiel Mar, Jessica C Tomaru, Yasuhiro Kawano, Mitsuoki Carninci, Piero Suzuki, Harukazu Hayashizaki, Yoshihide Shin, Jay W Genome Biol Research BACKGROUND: Changes in environmental conditions lead to expression variation that manifest at the level of gene regulatory networks. Despite a strong understanding of the role noise plays in synthetic biological systems, it remains unclear how propagation of expression heterogeneity in an endogenous regulatory network is distributed and utilized by cells transitioning through a key developmental event. RESULTS: Here we investigate the temporal dynamics of a single-cell transcriptional network of 45 transcription factors in THP-1 human myeloid monocytic leukemia cells undergoing differentiation to macrophages. We systematically measure temporal regulation of expression and variation by profiling 120 single cells at eight distinct time points, and infer highly controlled regulatory modules through which signaling operates with stochastic effects. This reveals dynamic and specific rewiring as a cellular strategy for differentiation. The integration of both positive and negative co-expression networks further identifies the proto-oncogene MYB as a network hinge to modulate both the pro- and anti-differentiation pathways. CONCLUSIONS: Compared to averaged cell populations, temporal single-cell expression profiling provides a much more powerful technique to probe for mechanistic insights underlying cellular differentiation. We believe that our approach will form the basis of novel strategies to study the regulation of transcription at a single-cell level. BioMed Central 2013 2013-10-24 /pmc/articles/PMC4015031/ /pubmed/24156252 http://dx.doi.org/10.1186/gb-2013-14-10-r118 Text en Copyright © 2013 Kouno et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Kouno, Tsukasa
de Hoon, Michiel
Mar, Jessica C
Tomaru, Yasuhiro
Kawano, Mitsuoki
Carninci, Piero
Suzuki, Harukazu
Hayashizaki, Yoshihide
Shin, Jay W
Temporal dynamics and transcriptional control using single-cell gene expression analysis
title Temporal dynamics and transcriptional control using single-cell gene expression analysis
title_full Temporal dynamics and transcriptional control using single-cell gene expression analysis
title_fullStr Temporal dynamics and transcriptional control using single-cell gene expression analysis
title_full_unstemmed Temporal dynamics and transcriptional control using single-cell gene expression analysis
title_short Temporal dynamics and transcriptional control using single-cell gene expression analysis
title_sort temporal dynamics and transcriptional control using single-cell gene expression analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015031/
https://www.ncbi.nlm.nih.gov/pubmed/24156252
http://dx.doi.org/10.1186/gb-2013-14-10-r118
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