Daniela Ristova

Nitrogen economics of root foraging: Transitive closure of the nitrate–cytokinin relay and distinct systemic signaling for N supply vs. demand

As sessile organisms, root plasticity enables plants to forage for and acquire nutrients in a fluctuating underground environment. Here, we use genetic and genomic approaches in a “split-root” framework—in which physically isolated root systems of the same plant are challenged with different nitrogen (N) environments—to investigate how systemic signaling affects genome-wide reprogramming and root development. The integration of transcriptome and root phenotypes enables us to identify distinct mechanisms underlying “N economy” (i.e., N supply and demand) of plants as a system. Under nitrate-limited conditions, plant roots adopt an “active-foraging strategy”, characterized by lateral root outgrowth and a shared pattern of transcriptome reprogramming, in response to either local or distal nitrate deprivation. By contrast, in nitrate-replete conditions, plant roots adopt a “dormant strategy”, characterized by a repression of lateral root outgrowth and a shared pattern of transcriptome reprogramming, in response to either local or distal nitrate supply. Sentinel genes responding to systemic N signaling identified by genome-wide comparisons of heterogeneous vs. homogeneous split-root N treatments were used to probe systemic N responses in Arabidopsis mutants impaired in nitrate reduction and hormone synthesis and also in decapitated plants. This combined analysis identified genetically distinct systemic signaling underlying plant N economy: (i) N supply, corresponding to a long-distance systemic signaling triggered by nitrate sensing; and (ii) N demand, experimental support for the transitive closure of a previously inferred nitrate–cytokinin shoot–root relay system that reports the nitrate demand of the whole plant, promoting a compensatory root growth in nitrate-rich patches of heterogeneous soil.

Integration of responses within and across Arabidopsis natural accessions uncovers loci controlling root systems architecture

Significance Species display a range of plastic phenotypes that presumably have evolved as a result of adaptation to heterogeneous environments. We asked whether the genetic mechanisms that underlie adaptation across populations also determine the response of an individual plant to environmental cues in Arabidopsis. Using an integrative root phenotyping approach, genes that underlie natural variation in root architecture across populations were shown to control plasticity responses within an individual. Together, our results uncover a genetic mechanism underlying the phenotypic plasticity of an individual and phenotypic diversity across natural variants. Phenotypic plasticity is presumed to be involved in adaptive change toward species diversification. We thus examined how candidate genes underlying natural variation across populations might also mediate plasticity within an individual. Our implementation of an integrative “plasticity space” approach revealed that the root plasticity of a single Arabidopsis accession exposed to distinct environments broadly recapitulates the natural variation “space.” Genome-wide association mapping identified the known gene PHOSPHATE 1 (PHO1) and other genes such as Root System Architecture 1 (RSA1) associated with differences in root allometry, a highly plastic trait capturing the distribution of lateral roots along the primary axis. The response of mutants in the Columbia-0 background suggests their involvement in signaling key modulators of root development including auxin, abscisic acid, and nitrate. Moreover, genotype-by-environment interactions for the PHO1 and RSA1 genes in Columbia-0 phenocopy the root allometry of other natural variants. This finding supports a role for plasticity responses in phenotypic evolution in natural environments.

Plasticity regulators modulate specific root traits in discrete nitrogen environments.

Plant development is remarkably plastic but how precisely can the plant customize its form to specific environments? When the plant adjusts its development to different environments, related traits can change in a coordinated fashion, such that two traits co-vary across many genotypes. Alternatively, traits can vary independently, such that a change in one trait has little predictive value for the change in a second trait. To characterize such “tunability” in developmental plasticity, we carried out a detailed phenotypic characterization of complex root traits among 96 accessions of the model Arabidopsis thaliana in two nitrogen environments. The results revealed a surprising level of independence in the control of traits to environment – a highly tunable form of plasticity. We mapped genetic architecture of plasticity using genome-wide association studies and further used gene expression analysis to narrow down gene candidates in mapped regions. Mutants in genes implicated by association and expression analysis showed precise defects in the predicted traits in the predicted environment, corroborating the independent control of plasticity traits. The overall results suggest that there is a pool of genetic variability in plants that controls traits in specific environments, with opportunity to tune crop plants to a given environment.

RootScape: A Landmark-Based System for Rapid Screening of Root Architecture in Arabidopsis

A landmark-based system quantifies root architecture using holistic trait capture methods. The architecture of plant roots affects essential functions including nutrient and water uptake, soil anchorage, and symbiotic interactions. Root architecture comprises many features that arise from the growth of the primary and lateral roots. These root features are dictated by the genetic background but are also highly responsive to the environment. Thus, root system architecture (RSA) represents an important and complex trait that is highly variable, affected by genotype × environment interactions, and relevant to survival/performance. Quantification of RSA in Arabidopsis (Arabidopsis thaliana) using plate-based tissue culture is a very common and relatively rapid assay, but quantifying RSA represents an experimental bottleneck when it comes to medium- or high-throughput approaches used in mutant or genotype screens. Here, we present RootScape, a landmark-based allometric method for rapid phenotyping of RSA using Arabidopsis as a case study. Using the software AAMToolbox, we created a 20-point landmark model that captures RSA as one integrated trait and used this model to quantify changes in the RSA of Arabidopsis (Columbia) wild-type plants grown under different hormone treatments. Principal component analysis was used to compare RootScape with conventional methods designed to measure root architecture. This analysis showed that RootScape efficiently captured nearly all the variation in root architecture detected by measuring individual root traits and is 5 to 10 times faster than conventional scoring. We validated RootScape by quantifying the plasticity of RSA in several mutant lines affected in hormone signaling. The RootScape analysis recapitulated previous results that described complex phenotypes in the mutants and identified novel gene × environment interactions.

Underground tuning: quantitative regulation of root growth

Plants display a high degree of phenotypic plasticity that allows them to tune their form and function to changing environments. The plant root system has evolved mechanisms to anchor the plant and to efficiently explore soils to forage for soil resources. Key to this is an enormous capacity for plasticity of multiple traits that shape the distribution of roots in the soil. Such root system architecture-related traits are determined by root growth rates, root growth direction, and root branching. In this review, we describe how the root system is constituted, and which mechanisms, pathways, and genes mainly regulate plasticity of the root system in response to environmental variation.

Natural Variation of Root Traits: From Development to Nutrient Uptake

Natural variation of root growth informs on processes that govern root development, responses to nutrient availability, and ion uptake and homeostasis. The root system has a crucial role for plant growth and productivity. Due to the challenges of heterogeneous soil environments, diverse environmental signals are integrated into root developmental decisions. While root growth and growth responses are genetically determined, there is substantial natural variation for these traits. Studying the genetic basis of the natural variation of root growth traits can not only shed light on their evolution and ecological relevance but also can be used to map the genes and their alleles responsible for the regulation of these traits. Analysis of root phenotypes has revealed growth strategies and root growth responses to a variety of environmental stimuli, as well as the extent of natural variation of a variety of root traits including ion content, cellular properties, and root system architectures. Linkage and association mapping approaches have uncovered causal genes underlying the variation of these traits.

Genetic control of root growth: from genes to networks

BACKGROUND Roots are essential organs for higher plants. They provide the plant with nutrients and water, anchor the plant in the soil, and can serve as energy storage organs. One remarkable feature of roots is that they are able to adjust their growth to changing environments. This adjustment is possible through mechanisms that modulate a diverse set of root traits such as growth rate, diameter, growth direction and lateral root formation. The basis of these traits and their modulation are at the cellular level, where a multitude of genes and gene networks precisely regulate development in time and space and tune it to environmental conditions. SCOPE This review first describes the root system and then presents fundamental work that has shed light on the basic regulatory principles of root growth and development. It then considers emerging complexities and how they have been addressed using systems-biology approaches, and then describes and argues for a systems-genetics approach. For reasons of simplicity and conciseness, this review is mostly limited to work from the model plant Arabidopsis thaliana, in which much of the research in root growth regulation at the molecular level has been conducted. CONCLUSIONS While forward genetic approaches have identified key regulators and genetic pathways, systems-biology approaches have been successful in shedding light on complex biological processes, for instance molecular mechanisms involving the quantitative interaction of several molecular components, or the interaction of large numbers of genes. However, there are significant limitations in many of these methods for capturing dynamic processes, as well as relating these processes to genotypic and phenotypic variation. The emerging field of systems genetics promises to overcome some of these limitations by linking genotypes to complex phenotypic and molecular data using approaches from different fields, such as genetics, genomics, systems biology and phenomics.

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

Multivariate analysis reveals a hormone- and nutrient-regulated network that shapes root architecture. 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. 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.

Representing Roots on the Basis of Reeb Graphs in Plant Phenotyping

This paper presents a new representation for root images based on Reeb graphs. The representation proposed captures lengths and distances in root structures as well as locations of branches, numbers of lateral roots and the locations of the root tips. An analysis of root images using Reeb graphs is presented and results are compared to ground truth measurements. This paper shows, that the Reeb graph based approach not only captures the characteristics needed for phenotyping of plants, but it also provides a solution to the problem of overlapping roots in the images. Using a Reeb graph based representation, such overlaps can be directly detected without further analysis, during the computation of the graph.

Genome-Wide Association Mapping of Root Traits in the Context of Plant Hormone Research

Genome-wide association (GWA) mapping is a powerful method for the identification of alleles that underlie quantitative traits. It enables one to understand how genetic variation translates into phenotypic variation. In particular, plant hormone signaling pathways play a key role in shaping phenotypes. This chapter presents a protocol for genome-wide association mapping of root traits of Arabidopsis thaliana in the context of hormone research. We describe a specific protocol for acquiring primary and lateral root trait data that is appropriate for GWA studies using FIJI (ImageJ), and subsequent GWA mapping using a user-friendly Internet application.