ShootRawCounts

Raw counts of total RNA-Seq reads aligned to each gene model in the Arabidopsis thaliana genome (TAIR10 version). These counts are from the RNA-Seq libraries constructed from shoot samples

RootRawCounts

Raw counts of total RNA-Seq reads aligned to each gene model in the Arabidopsis thaliana genome (TAIR10 version). These counts are from the RNA-Seq libraries constructed from root samples

Root_NxTime_genePlots

Gene expression plots of all N-responsive genes in Root

Plotting DEgenes

R script to create gene expression plots from the normalized counts

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

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. External links: 1. DFG: http://cs.nyu.edu/~mirowski/pub/GRN_Krouk_Mirowski_GenomeBiology.zip, 2. GEO dataset: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9750

Shoot_NxTime_genePlots

Gene expression plots for all N-responsive genes in shoots

Plot Data

Data files needed to generate the gene expression plots

DE_Spline

R script for identifying differential gene expression in response to N-supply