Description
This work uses a time series in order to decipher gene relationships and consequently to build core regulatory networks involved in Arabidopsis root adaptation to NO3- provision. The experimental approach has been to monitor genome response to NO3- at 3, 6, 9, 12, 15 and 20 min, using ATH1 chips. This high-resolution time course analysis demonstrated that the previously known primary nitrate response is actually preceded by very fast (within 3 min) gene expression modulation, involving genes/functions needed to prepare plants to use/reduce NO3-. State-space modeling (a machine learning approach) has been used to successfully predict gene behavior in unlearnt conditions.