Analysis of the Root System Architecture of Arabidopsis Provides a Quantitative Readout of Crosstalk between Nutritional Signals  . Issue 4 (1st April 2014)

• Record Type: Journal Article
• Authors: Kellermeier, Fabian; Armengaud, Patrick; Seditas, Triona J.; Danku, John; Salt, David E.; Amtmann, Anna
• Is Part Of: The Plant Cell. Volume 26:Issue 4(2014)
• Page Start: 1480
• Page End: 1496
• Publication Date: 2014-04-01
• DOI: 10.1105/tpc.113.122101
• Languages: English
• ISSNs: 1040-4651

Abstract

Abstract : Root architectures of Arabidopsis thaliana were quantified in multiple combinations of N, P, K, S, and light to understand how plants integrate multiple nutritional signals. Combined with mutant phenotypes, transcriptional profiles, and shoot ion contents, the comprehensive data set facilitates the dissection of the nutrient signaling network and identifies roles for receptor-transporters. Abstract: As plant roots forage the soil for food and water, they translate a multifactorial input of environmental stimuli into a multifactorial developmental output that manifests itself as root system architecture (RSA ). Our current understanding of the underlying regulatory network is limited because root responses have traditionally been studied separately for individual nutrient deficiencies. In this study, we quantified 13 RSA parameters of Arabidopsis thaliana in 32 binary combinations of N, P, K, S, and light. Analysis of variance showed that each RSA parameter was determined by a typical pattern of environmental signals and their interactions. P caused the most important single-nutrient effects, while N-effects were strongly light dependent. Effects of K and S occurred mostly through nutrient interactions in paired or multiple combinations. Several RSA parameters were selected for further analysis through mutant phenotyping, which revealed combinations of transporters, receptors, and kinases acting as signaling modules in K–N interactions. Furthermore, nutrient response profiles of individual RSA features across NPK combinations could be assigned to transcriptionally coregulated clusters of nutrient-responsive genes in the roots and to ionome patterns in the shoots. The obtained data set provides a quantitative basis for understanding how plants integrate multiple nutritional stimuli into complex developmental programs.