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

Autor: Dennis Shasha, José M. Alvarez, Jacopo Cirrone, Matthew D. Brooks, Gabriel Krouk, Angelo Pasquino, Joseph Swift, Che Lun Juang, Gloria M. Coruzzi, Rodrigo A. Gutiérrez, Shipra Mittal, Kranthi Varala
Přispěvatelé: Center for Genomics and Systems Biology, Department of Biology [New York], New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU)-New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU), Courant Institute of Mathematical Sciences [New York] (CIMS), Purdue University [West Lafayette], Departamento de Genética Molecular y Microbiología (FONDAP), Pontificia Universidad Católica de Chile (UC), Biochimie et Physiologie Moléculaire des Plantes (BPMP), Université de Montpellier (UM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Equipe Hormones, Nutriments et Développement (HoNuDe) (HONUDE), Université de Montpellier (UM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
0301 basic medicine
Nitrogen
Science
Arabidopsis
Gene regulatory network
General Physics and Astronomy
Repressor
02 engineering and technology
Computational biology
Biology
Genome
Article
General Biochemistry
Genetics and Molecular Biology
03 medical and health sciences
Gene Expression Regulation
Plant
[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry
Molecular Biology/Genomics [q-bio.GN]
Directionality
Gene Regulatory Networks
lcsh:Science
Gene
Transcription factor
Regulation of gene expression
Multidisciplinary
Arabidopsis Proteins
General Chemistry
[SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics
021001 nanoscience & nanotechnology
biology.organism_classification
Basic-Leucine Zipper Transcription Factors
030104 developmental biology
lcsh:Q
0210 nano-technology
Transcription Factors
Zdroj: Nature Communications, Vol 10, Iss 1, Pp 1-13 (2019)
Nature Communications
Nature Communications, Nature Publishing Group, 2019, 10, pp.1569. ⟨10.1038/s41467-019-09522-1⟩
ISSN: 2041-1723
DOI: 10.1038/s41467-019-09522-1
Popis: 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 TF1-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 TF2 targets, which in turn regulate 76% and 87% of TF1 indirect targets in planta, respectively. These results have implications for N-use and the approach can reveal temporal networks for any biological system.
Temporal control of transcriptional networks enables organisms to adapt to changing environment. Here, the authors use a scaled-up cell-based assay to identify direct targets of nitrogen-early responsive transcription factors and validate a network path mediating dynamic nitrogen signaling in Arabidopsis.
Databáze: OpenAIRE
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