Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate

Here we use time-series transcriptome data to decipher gene relationships and consequently to build core regulatory networks involved in Arabidopsis root adaptation to nitrate provision. The experimental approach has been to monitor genome-wide responses to nitrate at 3, 6, 9, 12, 15 and 20 minutes using Affymetrix ATH1 gene chips. This high-resolution time course analysis demonstrated that the previously known primary nitrate response is actually preceded by a very fast gene expression modulation, involving genes and functions needed to prepare plants to use or reduce nitrate. A state-space model inferred from this microarray time-series data successfully predicts gene behavior in unlearnt conditions.The experiments and methods allow us to propose a temporal working model for nitrate-driven gene networks. This network model is tested both in silico and experimentally. For example, the over-expression of a predicted gene hub encoding a transcription factor induced early in the cascade indeed leads to the modification of the kinetic nitrate response of sentinel genes such as NIR, NIA2, and NRT1.1, and several other transcription factors. The potential nitrate/hormone connections implicated by this time-series data are also evaluated.Higher plants, which constitute a main entry of nitrogen in to the food chain, acquire nitrogen mainly as nitrate (NO3-). Soil concentrations of this mineral ion can fluctuate dramatically in the rhizosphere, often resulting in limited growth and yield [1]. Thus, understanding plant adaptation to fluctuating nitrogen levels in the soil is a challenging task with potential consequences for health, the environment, and economies [2-4].The first genomic studies on NO3- responses in plants were published 10 years ago [5]. To date, data monitoring gene expression in response to NO3- provision from more than 100 Affymetrix ATH1 chips have been published [5-12]. Meta-analysis of microarray data sets from several different labs demonstrated that