Time to build on good design: Resolving the temporal dynamics of gene regulatory networks

The increasing availability of -omics data is driving the development of computational methods for integrating these datasets to connect the underlying molecular mechanisms to phenotypes. Building gene regulatory networks (GRNs) from transcriptomic studies often results in a static view of gene expression, which can make it difficult to disentangle pathway structure. Increasing the temporal resolution of any experimental design provides the opportunity to model the dynamic nature of a regulatory pathway response to a stimulus. Many transient intermediate states can separate the initial prestimulus state from the final poststimulus state; time-series analyses permit the detection and integration of these intermediate steps into the pathway. The difficulty is to incorporate these time-dependent changes to determine causal relationships within the GRN, such as which transcription factor (TF) regulates which target genes. In PNAS, Varala et al. (1) address this challenge by integrating time into their GRN to unravel the temporal cascade of nitrogen signaling. Their time-based analysis offers a potent and general approach to uncover the temporal transcriptional logic for any plant or animal response system. Nitrogen (N) commonly limits plant production and the widespread application of mineral N fertilizer has greatly increased crop yields (2). Unfortunately, the production of mineral N fertilizer is expensive in terms of fossil energy. Furthermore, plant assimilation of applied N is inefficient; for example, cereals such as maize, rice, and wheat take up less than 40% of the applied N (3). The remaining N is lost to the environment through processes including denitrification and volatilization, releasing greenhouse gases, leaching, contaminating groundwater, and surface runoff, causing eutrophication of fresh and estuarine waters (4). Therefore, the excessive use of N fertilizer both increases the cost of crop production and causes environmental pollution. One might expect that, consequently, plant N use efficiency (NUE) would represent a major target for … [↵][1]1To whom correspondence should be addressed. Email: c.robertson.mcclung{at}Dartmouth.edu. [1]: #xref-corresp-1-1