Conservation and divergence of regulatory architecture in nitrate-responsive plant gene circuits

Author:

Bian CORCID,Demirer GSORCID,Oz MTORCID,Cai YORCID,Witham SSORCID,Mason GAORCID,Shen R,Gaudinier AORCID,Brady SM,Patron NJORCID

Abstract

ABSTRACTNitrogen is an essential element for all life processes in plants. As such, plant roots dynamically respond to nitrogen availability below-ground by executing a signaling and transcriptional cascade resulting in altered plant growth, optimized for nutrient uptake. The NIN-LIKE PROTEIN 7 (NLP7) transcription factor senses nitrogen and along with its closely related paralog NLP6, partially coordinates these transcriptional responses. Here, we dissect a sub-circuit of the Arabidopsis nitrogen transcriptional network comprising AUXIN RESPONSE FACTOR 18 (ARF18), ARF9, DEHYDRATION RESPONSE ELEMENT BINDING-PROTEIN 26 (DREB26), A NAC-DOMAIN CONTAINING PROTEIN 32 (ANAC032), NLP6 and NLP7 transcription factors and their regulation of NITRATE REDUCTASE 1 (NIR1). Thecis-regulatory architecture of these factors are defined as is direct transcriptional regulation resulting in a network with multiple multi-node feedforward loops. Conservation and divergence of this network is similarly assessed inSolanum lycopersicum. The resulting models are validated by measuring the transcriptional output of the network with the syntheticNITRATE-REGULATED PROMOTERin varying concentrations of available nitrate revealing rewiring of nitrogen regulation across distinct plant lineages.Significance StatementNitrogen is a critical nutrient for plant growth and yield. While external N has facilitated modern agriculture, over-application of N-containing fertilizers has drastic ecological and environmental consequences. Here, we focus on a regulatory circuit acting upstream of the criticalNIN-LIKE PROTEIN7transcription factor and its conservation and divergence between Arabidopsis and tomato. Differences in gene membership, repressors, feedforward, and multinode loops exist between these species. The resulting network models provide a framework for targeted engineering to increase plant nitrogen use efficiency.

Publisher

Cold Spring Harbor Laboratory

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