Xavier Draye

Meta-analysis of Polyploid Cotton QTL Shows Unequal Contributions of Subgenomes to a Complex Network of Genes and Gene Clusters Implicated in Lint Fiber Development

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks.

A Novel Image-Analysis Toolbox Enabling Quantitative Analysis of Root System Architecture

We present in this paper a novel, semiautomated image-analysis software to streamline the quantitative analysis of root growth and architecture of complex root systems. The software combines a vectorial representation of root objects with a powerful tracing algorithm that accommodates a wide range of image sources and quality. The root system is treated as a collection of roots (possibly connected) that are individually represented as parsimonious sets of connected segments. Pixel coordinates and gray level are therefore turned into intuitive biological attributes such as segment diameter and orientation as well as distance to any other segment or topological position. As a consequence, user interaction and data analysis directly operate on biological entities (roots) and are not hampered by the spatially discrete, pixel-based nature of the original image. The software supports a sampling-based analysis of root system images, in which detailed information is collected on a limited number of roots selected by the user according to specific research requirements. The use of the software is illustrated with a time-lapse analysis of cluster root formation in lupin (Lupinus albus) and an architectural analysis of the maize (Zea mays) root system. The software, SmartRoot, is an operating system-independent freeware based on ImageJ and relies on cross-platform standards for communication with data-analysis software.

Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems

This paper presents an original spit-and-combine imaging procedure that enables the complete vectorization of complex root systems grown in rhizotrons. The general principle of the method is to (1) separate the root system into a small number of large pieces to reduce root overlap, (2) scan these pieces one by one, (3) analyze separate images with a root tracing software and (4) combine all tracings into a single vectorized root system. This method generates a rich dataset containing morphological, topological and geometrical information of entire root systems grown in rhizotrons. The utility of the method is illustrated with a detailed architectural analysis of a 20-day old maize root system, coupled with a spatial analysis of water uptake patterns.

Model-assisted integration of physiological and environmental constraints affecting the dynamic and spatial patterns of root water uptake from soils

Due in part to recent progress in root genetics and genomics, increasing attention is being devoted to root system architecture (RSA) for the improvement of drought tolerance. The focus is generally set on deep roots, expected to improve access to soil water resources during water deficit episodes. Surprisingly, our quantitative understanding of the role of RSA in the uptake of soil water remains extremely limited, which is mainly due to the inherent complexity of the soil-plant continuum. Evidently, there is a need for plant biologists and hydrologists to develop together their understanding of water movement in the soil-plant system. Using recent quantitative models coupling the hydraulic behaviour of soil and roots in an explicit 3D framework, this paper illustrates that the contribution of RSA to root water uptake is hardly separable from the hydraulic properties of the roots and of the soil. It is also argued that the traditional view that either the plant or the soil should be dominating the patterns of water extraction is not generally appropriate for crops growing with a sub-optimal water supply. Hopefully, in silico experiments using this type of model will help explore how water fluxes driven by soil and plant processes affect soil water availability and uptake throughout a growth cycle and will embed the study of RSA within the domains of root hydraulic architecture and sub-surface hydrology.

The expression pattern of plasma membrane aquaporins in maize leaf highlights their role in hydraulic regulation.

Leaves are key organs for evaporation and photosynthesis and play a crucial role in plant growth and development. In order to function properly, they need to maintain a balanced water content. Water movement through a leaf occurs by a combination of different pathways: water can follow an apoplastic route through the cell wall or a cell-to-cell route via the symplastic and transcellular paths. As aquaporins (AQPs) play an important role in regulating transcellular water flow and CO2 conductance, studies on AQP mRNA and protein expression in leaves are essential to better understand their role in these physiological processes. Here, we quantified and localized the expression of Zea mays plasma membrane aquaporins (ZmPIPs, plasma membrane intrinsic proteins) in the leaf using quantitative RT-PCR and immunodetection. All ZmPIP genes except ZmPIP2;7 were expressed in leaves. Expression was found to be dependent on the developmental stage of the leaf tissue, with, in general, an increase in expression at the end of the elongation zone and a decrease in mature leaf tissue. These data correlated with the cell water permeability, as determined using a protoplast swelling assay. The diurnal expression of ZmPIPs was also investigated and expression was found to be higher during the first hours of the light period than at night. Immunocytochemical localization of four ZmPIP isoforms indicated that they are involved in leaf radial water movement, in particular in vascular bundles and the mesophyll.

An online database for plant image analysis software tools

BackgroundRecent years have seen an increase in methods for plant phenotyping using image analyses. These methods require new software solutions for data extraction and treatment. These solutions are instrumental in supporting various research pipelines, ranging from the localisation of cellular compounds to the quantification of tree canopies. However, due to the variety of existing tools and the lack of central repository, it is challenging for researchers to identify the software that is best suited for their research.ResultsWe present an online, manually curated, database referencing more than 90 plant image analysis software solutions. The website, plant-image-analysis.org, presents each software in a uniform and concise manner enabling users to identify the available solutions for their experimental needs. The website also enables user feedback, evaluations and new software submissions.ConclusionsThe plant-image-analysis.org database provides an overview of existing plant image analysis software. The aim of such a toolbox is to help users to find solutions, and to provide developers a way to exchange and communicate about their work.

DART: a software to analyse root system architecture and development from captured images

Image analysis is used in numerous studies of root system architecture (RSA). To date, fully automatic procedures have not been good enough to completely replace alternative manual methods. DART (Data Analysis of Root Tracings) is freeware based on human vision to identify roots, particularly across time-series. Each root is described by a series of ordered links encapsulating specific information and is connected to other roots. The population of links constitutes the RSA. DART creates a comprehensive dataset ready for individual or global analyses and this can display root growth sequences along time. We exemplify here individual tomato root growth response to shortfall in solar radiation and we analyse the global distribution of the inter-root branching distances. DART helps in studying RSA and in producing structured and flexible datasets of individual root growth parameters. It is written in JAVA and relies on manual procedures to minimize the risks of errors and biases in datasets.

Post-embryonic root organogenesis in cereals: branching out from model plants.

The root architecture of higher plants is amazingly diverse. In this review, we compare the lateral root developmental programme in cereals and Arabidopsis thaliana. In cereals, cells in the endodermis are recruited to form the new root cap and overlying cortical cells divide to facilitate the emergence of the lateral root primordium. The TIR1/ABF2 auxin receptors and the AUX/IAA, ARF, and LBD transcriptional regulatory proteins are conserved in cereals and Arabidopsis. Several elements of this regulatory network are common to lateral and crown roots in cereals. Also, the ground meristem from which crown roots differentiate shows similarities with the root pericycle. Studies in cereals promise to give complementary insights into the mechanisms regulating the development of post-embryonic roots in plants.

Plant Water Uptake in Drying Soils

Integrative soil-plant system approaches are needed to understand plant water uptake dynamics. Over the last decade, investigations on root water uptake have evolved toward a deeper integration of the soil and roots compartment properties, with the goal of improving our understanding of water acquisition from drying soils. This evolution parallels the increasing attention of agronomists to suboptimal crop production environments. Recent results have led to the description of root system architectures that might contribute to deep-water extraction or to water-saving strategies. In addition, the manipulation of root hydraulic properties would provide further opportunities to improve water uptake. However, modeling studies highlight the role of soil hydraulics in the control of water uptake in drying soil and call for integrative soil-plant system approaches.

The Emerging Role of Reactive Oxygen Species Signaling during Lateral Root Development

ROS signaling is crucial for lateral root emergence and root growth, and it regulates distinct sets of genes in these processes. Overall root architecture is the combined result of primary and lateral root growth and is influenced by both intrinsic genetic programs and external signals. One of the main questions for root biologists is how plants control the number of lateral root primordia and their emergence through the main root. We recently identified S-phase kinase-associated protein2 (SKP2B) as a new early marker for lateral root development. Here, we took advantage of its specific expression pattern in Arabidopsis (Arabidopsis thaliana) in a cell-sorting and transcriptomic approach to generate a lateral root-specific cell sorting SKP2B data set that represents the endogenous genetic developmental program. We first validated this data set by showing that many of the identified genes have a function during root growth or lateral root development. Importantly, genes encoding peroxidases were highly represented in our data set. Thus, we next focused on this class of enzymes and showed, using genetic and chemical inhibitor studies, that peroxidase activity and reactive oxygen species signaling are specifically required during lateral root emergence but, intriguingly, not for primordium specification itself.