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

Varala, K., Marshall-Colon, A., Cirrone, J., Brooks, M. D., Pasquino, A. V., Leran, S., Mittal, S., Rock, T. M., Edwards, M. B., Kim, G. J., Ruffel, S., McCombie, W. R., Shasha, D., Coruzzi, G. M. (May 2018) Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants. Proc Natl Acad Sci U S A. ISSN 0027-8424

URL: https://www.ncbi.nlm.nih.gov/pubmed/29769331
DOI: 10.1073/pnas.1721487115

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 (15)NO3(-) 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.

Item Type: Paper
Uncontrolled Keywords: network inference nitrogen assimilation plant biology systems biology transcriptional dynamics
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > transcription
organism description > plant
CSHL Authors:
Communities: CSHL labs > McCombie lab
Depositing User: Matt Covey
Date: 16 May 2018
Date Deposited: 21 May 2018 21:04
Last Modified: 21 May 2018 21:04
Related URLs:
URI: http://repository.cshl.edu/id/eprint/36587

Actions (login required)

Administrator's edit/view item Administrator's edit/view item
CSHL HomeAbout CSHLResearchEducationNews & FeaturesCampus & Public EventsCareersGiving