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Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions

Charting a temporal path in gene networks requires linking early transcription factor (TF)-triggered events to downstream effects. We scale-up a cell-based TF-perturbation assay to identify direct regulated targets of 33 nitrogen (N)-early response TFs encompassing 88% of N-responsive Arabidopsis ge...

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Autores principales: Brooks, Matthew D., Cirrone, Jacopo, Pasquino, Angelo V., Alvarez, Jose M., Swift, Joseph, Mittal, Shipra, Juang, Che-Lun, Varala, Kranthi, Gutiérrez, Rodrigo A., Krouk, Gabriel, Shasha, Dennis, Coruzzi, Gloria M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451032/
https://www.ncbi.nlm.nih.gov/pubmed/30952851
http://dx.doi.org/10.1038/s41467-019-09522-1
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author Brooks, Matthew D.
Cirrone, Jacopo
Pasquino, Angelo V.
Alvarez, Jose M.
Swift, Joseph
Mittal, Shipra
Juang, Che-Lun
Varala, Kranthi
Gutiérrez, Rodrigo A.
Krouk, Gabriel
Shasha, Dennis
Coruzzi, Gloria M.
author_facet Brooks, Matthew D.
Cirrone, Jacopo
Pasquino, Angelo V.
Alvarez, Jose M.
Swift, Joseph
Mittal, Shipra
Juang, Che-Lun
Varala, Kranthi
Gutiérrez, Rodrigo A.
Krouk, Gabriel
Shasha, Dennis
Coruzzi, Gloria M.
author_sort Brooks, Matthew D.
collection PubMed
description Charting a temporal path in gene networks requires linking early transcription factor (TF)-triggered events to downstream effects. We scale-up a cell-based TF-perturbation assay to identify direct regulated targets of 33 nitrogen (N)-early response TFs encompassing 88% of N-responsive Arabidopsis genes. We uncover a duality where each TF is an inducer and repressor, and in vitro cis-motifs are typically specific to regulation directionality. Validated TF-targets (71,836) are used to refine precision of a time-inferred root network, connecting 145 N-responsive TFs and 311 targets. These data are used to chart network paths from direct TF(1)-regulated targets identified in cells to indirect targets responding only in planta via Network Walking. We uncover network paths from TGA1 and CRF4 to direct TF(2) targets, which in turn regulate 76% and 87% of TF(1) indirect targets in planta, respectively. These results have implications for N-use and the approach can reveal temporal networks for any biological system.
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spelling pubmed-64510322019-04-08 Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions Brooks, Matthew D. Cirrone, Jacopo Pasquino, Angelo V. Alvarez, Jose M. Swift, Joseph Mittal, Shipra Juang, Che-Lun Varala, Kranthi Gutiérrez, Rodrigo A. Krouk, Gabriel Shasha, Dennis Coruzzi, Gloria M. Nat Commun Article Charting a temporal path in gene networks requires linking early transcription factor (TF)-triggered events to downstream effects. We scale-up a cell-based TF-perturbation assay to identify direct regulated targets of 33 nitrogen (N)-early response TFs encompassing 88% of N-responsive Arabidopsis genes. We uncover a duality where each TF is an inducer and repressor, and in vitro cis-motifs are typically specific to regulation directionality. Validated TF-targets (71,836) are used to refine precision of a time-inferred root network, connecting 145 N-responsive TFs and 311 targets. These data are used to chart network paths from direct TF(1)-regulated targets identified in cells to indirect targets responding only in planta via Network Walking. We uncover network paths from TGA1 and CRF4 to direct TF(2) targets, which in turn regulate 76% and 87% of TF(1) indirect targets in planta, respectively. These results have implications for N-use and the approach can reveal temporal networks for any biological system. Nature Publishing Group UK 2019-04-05 /pmc/articles/PMC6451032/ /pubmed/30952851 http://dx.doi.org/10.1038/s41467-019-09522-1 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Brooks, Matthew D.
Cirrone, Jacopo
Pasquino, Angelo V.
Alvarez, Jose M.
Swift, Joseph
Mittal, Shipra
Juang, Che-Lun
Varala, Kranthi
Gutiérrez, Rodrigo A.
Krouk, Gabriel
Shasha, Dennis
Coruzzi, Gloria M.
Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
title Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
title_full Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
title_fullStr Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
title_full_unstemmed Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
title_short Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
title_sort network walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6451032/
https://www.ncbi.nlm.nih.gov/pubmed/30952851
http://dx.doi.org/10.1038/s41467-019-09522-1
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