Abstract Drought is a significant factor in agricultural losses, making it imperative to understand how root system architecture and function (RSA) adapts to environmental conditions such as water deficit. HydroRoot is a functional-structural plant model (FSPM) aimed at analyzing and simulating root system hydraulic and solute transport. The model provides a static hydraulic solver, a coupled water-solute transport solver, a statistical generator of RSA based on the Markov model, and a dynamic hydraulic model accounting for root growth. This paper presents the model, mathematical description of solver formalisms, and use cases with their associated tutorials. Four use cases illustrate the capabilities of HydroRoot, which has been successfully used for phenotyping root hydraulics across various species including Arabidopsis, maize, and pearl millet. The model-driven phenotyping method "Cut and Flow" is presented to characterize root axial and radial conductivities on a given genotype. Finally, three step-by-step tutorials provide a structured way to learn how to use HydroRoot 1) to simulate hydraulics of a given root architecture, 2) to simulate water and solute transport in a maize root, and 3) to simulate hydraulics on two pearl millet genotypes in varying soil conditions. HydroRoot is an open-source package of the OpenAlea platform, with the code publicly available on Github. A comprehensive documentation is available with a reproducible gallery of examples.

Root water transport has been viewed as primarily limited by the radial component, with the axial pathway considered highly conductive and non-limiting. This is supported by theoretical estimates of axial conductance using the Hagen-Poiseuille equation. However, increasing evidence indicates that actual axial conductance is often nearly an order of magnitude lower than predicted, challenging assumptions that it does not limit water uptake. In this review, we discuss how recent model inversion approaches, guided by root hydraulic conductance measurements, have revealed that water transport can be co-limited by radial and axial conductance. We explore possible explanations for this co-limitation, with particular attention to root topology. Finally, we highlight how drought-induced adjustments in xylem vessel traits can reduce axial conductance, contributing to water conservation and cavitation resistance, thereby supporting drought adaptation strategies. Leveraging this overlooked limitation opens new avenues for breeding crops with improved water-use efficiency and resilience to drought .

Pearl millet is a key food security grain crop in the world's drylands due to its tolerance to abiotic stresses. However, its yield remains low and is negatively impacted by climate change. Root phenes are potential targets to improve crop productivity and resilience to environmental stress. However, the sheer number of combinations resulting from interactions of multiple phenes is a challenge for empirical research. In silico approaches are a plausible alternative to assess the utility of different phene combinations in varying states over diverse environmental contexts. Here, we developed an implementation of the functional-structural plant/soil model – OpenSimRoot, for pearl millet in typical sub-Sahelian soil and environmental conditions. Root architectural, anatomical, and physiological parameters were measured using a popular pearl millet variety (Souna 3) and implemented in the model. The above-ground biomass and root length density predicted by the model were similar to data from field trials. The utility of different root phenes was then evaluated for improved phosphorus uptake and plant growth in P deficient soils. Doubled root hair length and density, shallower root angle (-15°) and doubled long lateral root density were found to improve plant growth by 76%, 33% and 33% respectively under low P conditions. Moreover, these phenes showed synergism when combined in silico and led to optimal biomass production in low P supply conditions that resulted in a 75% loss of biomass in the reference variety. Our study suggests that these phenotypes could be targeted to improve biomass production in pearl millet and consequently its yield in low-P availability conditions.

Abstract Lateral root organogenesis is a key process in the development of a plant’s root system and its adaptation to the environment. During lateral root formation, an early phase of cell proliferation first produces a four-cell-layered primordium, and only from this stage onwards is a root meristem-like structure, expressing root stem cell niche marker genes, being established in the developing organ. Previous studies reported that the gene regulatory network controlling lateral root formation is organized into two subnetworks whose mutual inhibition may contribute to organ patterning. PUCHI encodes an AP2/ERF transcription factor expressed early during lateral root primordium development and required for correct lateral root formation. To dissect the molecular events occurring during this early phase, we generated time-series transcriptomic datasets profiling lateral root development in puchi-1 mutants and wild types. Transcriptomic and reporter analyses revealed that meristem-related genes were expressed ectopically at early stages of lateral root formation in puchi-1 mutants. We conclude that, consistent with the inhibition of genetic modules contributing to lateral root development, PUCHI represses ectopic establishment of meristematic cell identities at early stages of organ development. These findings shed light on gene network properties that orchestrate correct timing and patterning during lateral root formation.

Over the last few decades, many genes have been functionally characterized and shown to be involved in various metabolic, developmental, and signaling pathways. However it still remains unclear how all these genes and pathways integrate into a unique regulatory network to coordinate the development and the growth, or the response to the environment. This is why unraveling the topology of gene regulatory networks (GRN) has become central to our understanding of all these processes. The recent advancement of high-throughput methods has provided enormous amount of -omics data. These data can now be exploited for rapid network reconstruction with statistical inference methods. We recently published a new GRN inference algorithm called TDCor which reconstructs GRN from time-series transcriptomic data. The algorithm has been released in the form of an R package. Here, I describe into details how to install and use the package.

Systems biology is the study of biological interactions. These interactions exist between biological entities at every scale, from genes to population, and create incredibly complex networks of feedbacks responsible for emerging behaviors. To study these behaviors, biologists can use models based on mathematical and computational formalisms grounded on vast existing corpus of theoretical work. This chapter develops an overview of this process of plant systems biology study from the point of view of a teaching course, and introduces the methods and studies presented in this second edition of the "Plant Systems Biology" book series.

Plant systems biology is currently facing several important challenges, whose nature depend on the considered frame of reference and associated scale. This review covers some of the issues associated respectively with the molecular, tissue, and whole-plant scales, as well as discusses the potential for latest advances in synthetic biology and machine-learning methods to be of use in the future of plant systems biology.

This chapter compiles a list of useful references for aspiring plant systems biologists. It is structured in four sections focusing on systems biology books, reviews for the different types of models and resources at each plant scale, online resources, and plant systems biology communities.

Abstract Water uptake by roots is a key adaptation of plants to aerial life. Water uptake depends on root system architecture (RSA) and tissue hydraulic properties that, together, shape the root hydraulic architecture. This work investigates how the interplay between conductivities along radial (e.g. aquaporins) and axial (e.g. xylem vessels) pathways determines the water transport properties of highly branched RSAs as found in adult Arabidopsis (Arabidopsis thaliana) plants. A hydraulic model named HydroRoot was developed, based on multi-scale tree graph representations of RSAs. Root water flow was measured by the pressure chamber technique after successive cuts of a same root system from the tip toward the base. HydroRoot model inversion in corresponding RSAs allowed us to concomitantly determine radial and axial conductivities, providing evidence that the latter is often overestimated by classical evaluation based on the Hagen–Poiseuille law. Organizing principles of Arabidopsis primary and lateral root growth and branching were determined and used to apply the HydroRoot model to an extended set of simulated RSAs. Sensitivity analyses revealed that water transport can be co-limited by radial and axial conductances throughout the whole RSA. The number of roots that can be sectioned (intercepted) at a given distance from the base was defined as an accessible and informative indicator of RSA. The overall set of experimental and theoretical procedures was applied to plants mutated in ESKIMO1 and previously shown to have xylem collapse. This approach will be instrumental to dissect the root water transport phenotype of plants with intricate alterations in root growth or transport functions.

F.B., and M.L. contributed equally but not as first authors. Y.B. contributed to model coding, developed the cut-and-flow and root intercept approaches, and contributed to phenotyping characterizations. C.P. supervised the coding of the HydroRoot model and contributed to data analyses. F

Postembryonic organogenesis is a critical component in plant root and shoot development and its adaptation to the environment. Decades of scientific analyses have yielded a wealth of experimental data about the cellular and molecular processes orchestrating the postembryonic formation of new shoot and root organs. Among these, distribution and signaling of the plant hormone auxin play a prominent role. Systems biology approaches are now particularly interesting to study the emerging properties of such complex and dynamic regulatory networks. To fully explore the precise kinetics of these organogenesis processes, efficient protocols for the synchronized induction of shoot and root organogenesis are extremely valuable. Two protocols for shoot and root organ induction are detailed.

Crown roots constitute the main part of the rice root system. Several key genes involved in crown root initiation and development have been identified by functional genomics approaches. Nevertheless, these approaches are impaired by functional redundancy and mutant lethality. To overcome these limitations, organ targeted transcriptome analysis can help to identify genes involved in crown root formation and early development. In this study, we generated an atlas of genes expressed in developing crown root primordia in comparison with adjacent stem cortical tissue at three different developmental stages before emergence, using laser capture microdissection. We identified 3975 genes differentially expressed in crown root primordia. About 30% of them were expressed at the three developmental stages, whereas 10.5%, 19.5% and 12.8% were specifically expressed at the early, intermediate and late stages, respectively. Sorting them by functional ontology highlighted an active transcriptional switch during the process of crown root primordia formation. Cross-analysis with other rice root development-related datasets revealed genes encoding transcription factors, chromatin remodeling factors, peptide growth factors, and cell wall remodeling enzymes that are likely to play a key role during crown root primordia formation. This atlas constitutes an open primary data resource for further studies on the regulation of crown root initiation and development.

Pearl millet is able to withstand dry and hot conditions and plays an important role for food security in arid and semi-arid areas of Africa and India. However, low soil fertility and drought constrain pearl millet yield. One target to address these constraints through agricultural practices or breeding is root system architecture. In this study, in order to easily phenotype the root system in field conditions, we developed a model to predict root length density (RLD) of pearl millet plants from root intersection densities (RID) counted on a trench profile in field conditions. We identified root orientation as an important parameter to improve the relationship between RID and RLD. Root orientation was notably found to depend on soil depth and to differ between thick roots (more anisotropic with depth) and fine roots (isotropic at all depths). We used our model to study pearl millet root system response to drought and showed that pearl millet reorients its root growth toward deeper soil layers that retain more water in these conditions. Overall, this model opens ways for the characterization of the impact of environmental factors and management practices on pearl millet root system development.

SummaryCrown roots (CRs) are essential components of the rice root system. Several genes involved in CR initiation or development have been identified but our knowledge about how they organize to form a gene regulatory network (GRN) is still limited. To characterize the regulatory cascades acting during CR formation, we used a systems biology approach to infer the GRN controlling CR formation downstream of CROWN ROOTLESS 1 (CRL1), coding for an ASL (asymmetric leaves‐2‐like)/LBD (LOB domain) transcription factor necessary for CR initiation. A time‐series transcriptomic dataset was generated after synchronized induction of CR formation by dexamethasone‐mediated expression of CRL1 expression in a crl1 mutant background. This time series revealed three different genome expression phases during the early steps of CR formation and was further exploited to infer a GRN using a dedicated algorithm. The predicted GRN was confronted with experimental data and 72% of the inferred links were validated. Interestingly, this network revealed a regulatory cascade linking CRL1 to other genes involved in CR initiation, root meristem specification and maintenance, such as QUIESCENT‐CENTER-SPECIFIC HOMEOBOX, and in auxin signalling. This predicted regulatory cascade was validated in vivo using transient activation assays. Thus, the CRL1‐dependant GRN reflects major gene regulation events at play during CR formation and constitutes a valuable source of discovery to better understand this developmental process.