Research ResourcePlant biology

Combinatorial interaction network of transcriptomic and phenotypic responses to nitrogen and hormones in the Arabidopsis thaliana root

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Sci. Signal.  25 Oct 2016:
Vol. 9, Issue 451, pp. rs13
DOI: 10.1126/scisignal.aaf2768

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A nitrogen-hormone interaction network in plants

Both intrinsic factors, such as hormones, and extrinsic factors, such as water and nutrient availability, shape plant development. Ristova et al. evaluated the short-term transcriptional responses and the long-term developmental responses of Arabidopsis thaliana roots to the nitrogen-containing nutrients nitrate and ammonium and the hormones auxin, cytokinin, and abscisic acid. The authors identified genes that were stimulated or inhibited in response to each single factor and to all possible combinations of these three hormones and two nitrogen sources. By combining these transcriptomic data with quantification of changes in root architecture after each treatment, the authors built a multivariate network model of the interaction between nitrogen and hormones that may predict changes in the architecture response of the Arabidopsis root. These data will be useful for future studies on the molecular mechanisms that mediate these interactions and may help identify combinations of nutrients and hormones that improve plant growth under specific environmental conditions.

Abstract

Plants form the basis of the food webs that sustain animal life. Exogenous factors, such as nutrients and sunlight, and endogenous factors, such as hormones, cooperate to control both the growth and the development of plants. We assessed how Arabidopsis thaliana integrated nutrient and hormone signaling pathways to control root growth and development by investigating the effects of combinatorial treatment with the nutrients nitrate and ammonium; the hormones auxin, cytokinin, and abscisic acid; and all binary combinations of these factors. We monitored and integrated short-term genome-wide changes in gene expression over hours and long-term effects on root development and architecture over several days. Our analysis revealed trends in nutrient and hormonal signal crosstalk and feedback, including responses that exhibited logic gate behavior, which means that they were triggered only when specific combinations of signals were present. From the data, we developed a multivariate network model comprising the signaling molecules, the early gene expression modulation, and the subsequent changes in root phenotypes. This multivariate network model pinpoints several genes that play key roles in the control of root development and may help understand how eukaryotes manage multifactorial signaling inputs.

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