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Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants

Varala Kranthi, Marshall-Colón Amy, Cirrone Jacopo, Brooks Matthew D., Pasquino Angelo V., Leran Sophie, Mittal Shipra, Rock Tara M., Edwards Molly B., Kim Grace J., Ruffel Sandrine, McCombie Richard, Shasha Dennis, Coruzzi Gloria M.. 2018. Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants. Proceedings of the National Academy of Sciences of the United States of America, 115 (25) : pp. 6494-6499.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
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Url - jeu de données : https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE97500

Quartile : Outlier, Sujet : MULTIDISCIPLINARY SCIENCES

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Economie-gestion; Psychologie-éthologie-ergonomie

Abstract : This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our “just-in-time” analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to “prune” the network to 155 TFs and 608 targets. This network precision was reconfirmed using genome-wide TF-target regulation data for four additional TFs (TGA1, HHO5/6, and PHL1) not used in network pruning. These higher-confidence edges in the GRN were further filtered by independent TF-target binding data, used to calculate a TF “N-specificity” index. This refined GRN identifies the temporal relationship of known/validated regulators of N signaling (NLP7/8, TGA1/4, NAC4, HRS1, and LBD37/38/39) and 146 additional regulators. Six TFs—CRF4, SNZ, CDF1, HHO5/6, and PHL1—validated herein regulate a significant number of genes in the dynamic N response, targeting 54% of N-uptake/assimilation pathway genes. Phenotypically, inducible overexpression of CRF4 in planta regulates genes resulting in altered biomass, root development, and 15NO3− uptake, specifically under low-N conditions. This dynamic N-signaling GRN now provides the temporal “transcriptional logic” for 155 candidate TFs to improve nitrogen use efficiency with potential agricultural applications. Broadly, these time-based approaches can uncover the temporal transcriptional logic for any biological response system in biology, agriculture, or medicine.

Mots-clés Agrovoc : Nutrition des plantes, Azote, gene regulatory networks [EN], Assimilation des nitrates, Transcription génique, Analyse de réseau, Intelligence artificielle

Mots-clés complémentaires : pangénomique

Mots-clés libres : System biology, Plant biology, Nitrogen assimilation, Transcriptional dynamics, Network inference

Classification Agris : F30 - Plant genetics and breeding
F60 - Plant physiology and biochemistry

Champ stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

  • Varala Kranthi, Purdue University (USA)
  • Marshall-Colón Amy, University of Illinois (USA)
  • Cirrone Jacopo, State University of New York (USA)
  • Brooks Matthew D., State University of New York (USA)
  • Pasquino Angelo V., State University of New York (USA)
  • Leran Sophie, CIRAD-BIOS-UMR IPME (FRA)
  • Mittal Shipra, State University of New York (USA)
  • Rock Tara M., State University of New York (USA)
  • Edwards Molly B., State University of New York (USA)
  • Kim Grace J., State University of New York (USA)
  • Ruffel Sandrine, Université de Montpellier (FRA)
  • McCombie Richard, Cold Spring Harbor (USA)
  • Shasha Dennis, University of New-York (USA)
  • Coruzzi Gloria M., State University of New York (USA) - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/594989/)

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