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Summary Root hair (RH) cells can elongate to several hundred times their initial size, and are an ideal model system for investigating cell size control. Their development is influenced by both endogenous and external signals, which are combined to form an integrative response. Surprisingly, a low‐temperature condition of 10°C causes increased RH growth inArabidopsisand in several monocots, even when the development of the rest of the plant is halted.Previously, we demonstrated a strong correlation between RH growth response and a significant decrease in nutrient availability in the growth medium under low‐temperature conditions. However, the molecular basis responsible for receiving and transmitting signals related to the availability of nutrients in the soil, and their relation to plant development, remain largely unknown.We have discovered two antagonic gene regulatory networks (GRNs) controlling RH early transcriptome responses to low temperature. One GNR enhances RH growth and it is commanded by the transcription factors (TFs)ROOT HAIR DEFECTIVE 6(RHD6),HAIR DEFECTIVE 6‐LIKE 2 and 4(RSL2‐RSL4) and a member of the homeodomain leucine zipper (HD‐Zip I) group I 16 (AtHB16). On the other hand, a second GRN was identified as a negative regulator of RH growth at low temperature and it is composed by the trihelix TFGT2‐LIKE1(GTL1) and the associated DF1, a previously unidentified MYB‐like TF (AT2G01060) and several members of HD‐Zip I group (AtHB3, AtHB13, AtHB20, AtHB23).Functional analysis of both GRNs highlights a complex regulation of RH growth response to low temperature, and more importantly, these discoveries enhance our comprehension of how plants synchronize RH growth in response to variations in temperature at the cellular level. 

Ru(ii) 1,2-azolylamidino-DMSO complexes are herein described. Their electrochemical behavior in CO₂media is consistent with CO₂electrocatalyzed reduction, whereas photocatalytic CO₂reduction experiments lead to CO and trace amounts of formate. 

All aspects of transcription and its regulation involve dynamic events. However, capturing these dynamic events in gene regulatory networks (GRNs) offers both a promise and a challenge. The promise is that capturing and modeling the dynamic changes in GRNs will allow us to understand how organisms adapt to a changing environment. The ability to mount a rapid transcriptional response to environmental changes is especially important in nonmotile organisms such as plants. The challenge is to capture these dynamic, genome-wide events and model them in GRNs. In this review, we cover recent progress in capturing dynamic interactions of transcription factors with their targets—at both the local and genome-wide levels—and using them to learn how GRNs operate as a function of time. We also discuss recent advances that employ time-based machine learning approaches to forecast gene expression at future time points, a key goal of systems biology. Expected final online publication date for the Annual Review of Plant Biology, Volume 72 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

An increase in nutrient dose leads to proportional increases in crop biomass and agricultural yield. However, the molecular underpinnings of this nutrient dose–response are largely unknown. To investigate, we assayed changes in the Arabidopsis root transcriptome to different doses of nitrogen (N)—a key plant nutrient—as a function of time. By these means, we found that rate changes of genome-wide transcript levels in response to N-dose could be explained by a simple kinetic principle: the Michaelis–Menten (MM) model. Fitting the MM model allowed us to estimate the maximum rate of transcript change ( V max ), as well as the N-dose at which one-half of V max was achieved ( K m ) for 1,153 N-dose–responsive genes. Since transcription factors (TFs) can act in part as the catalytic agents that determine the rates of transcript change, we investigated their role in regulating N-dose–responsive MM-modeled genes. We found that altering the abundance of TGA1, an early N-responsive TF, perturbed the maximum rates of N-dose transcriptomic responses ( V max ), K m , as well as the rate of N-dose–responsive plant growth. We experimentally validated that MM-modeled N-dose–responsive genes included both direct and indirect TGA1 targets, using a root cell TF assay to detect TF binding and/or TF regulation genome-wide. Taken together, our results support a molecular mechanism of transcriptional control that allows an increase in N-dose to lead to a proportional change in the rate of genome-wide expression and plant growth. 

Abstract Nitrogen (N) and water (W) are crucial inputs for plant survival as well as costly resources for agriculture. Given their importance, the molecular mechanisms that plants rely on to signal changes in either N or W status have been under intense scrutiny. However, how plants sense and respond to the combination of N and W signals at the molecular level has received scant attention. The purpose of this review is to shed light on what is currently known about how plant responses to N are impacted by W status. We review classic studies which detail how N and W combinations have both synergistic and antagonistic effects on key plant traits, such as root architecture and stomatal aperture. Recent molecular studies of N and W interactions show that mutations in genes involved in N metabolism affect drought responses, and vice versa. Specifically, perturbing key N signaling genes may lead to changes in drought-responsive gene expression programs, which is supported by a meta-analysis we conduct on available transcriptomic data. Additionally, we cite studies that show how combinatorial transcriptional responses to N and W status might drive crop phenotypes. Through these insights, we suggest research strategies that could help to develop crops adapted to marginal soils depleted in both N and W, an important task in the face of climate change.