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

Kranthi Varala, Amy Marshall-Colón, Jacopo Cirrone, Matthew D. Brooks, Angelo V. Pasquino, Sophie Léran, Shipra Mittal, Tara M. Rock, Molly B. Edwards, Grace J. Kim, Sandrine Ruffel, W. Richard McCombie, Dennis Shasha, Gloria M. Coruzzi

Research output: Contribution to journalArticlepeer-review

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, and15NO3 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.

Original languageEnglish (US)
Pages (from-to)6494-6499
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume115
Issue number25
DOIs
StatePublished - Jun 19 2018

Keywords

  • Network inference
  • Nitrogen assimilation
  • Plant biology
  • Systems biology
  • Transcriptional dynamics

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants'. Together they form a unique fingerprint.

Cite this