Randy T. Clark

Three-Dimensional Root Phenotyping with a Novel Imaging and Software Platform

A novel imaging and software platform was developed for the high-throughput phenotyping of three-dimensional root traits during seedling development. To demonstrate the platform’s capacity, plants of two rice (Oryza sativa) genotypes, Azucena and IR64, were grown in a transparent gellan gum system and imaged daily for 10 d. Rotational image sequences consisting of 40 two-dimensional images were captured using an optically corrected digital imaging system. Three-dimensional root reconstructions were generated and analyzed using a custom-designed software, RootReader3D. Using the automated and interactive capabilities of RootReader3D, five rice root types were classified and 27 phenotypic root traits were measured to characterize these two genotypes. Where possible, measurements from the three-dimensional platform were validated and were highly correlated with conventional two-dimensional measurements. When comparing gellan gum-grown plants with those grown under hydroponic and sand culture, significant differences were detected in morphological root traits (P < 0.05). This highly flexible platform provides the capacity to measure root traits with a high degree of spatial and temporal resolution and will facilitate novel investigations into the development of entire root systems or selected components of root systems. In combination with the extensive genetic resources that are now available, this platform will be a powerful resource to further explore the molecular and genetic determinants of root system architecture.

Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement

More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.

Genetic Architecture of Aluminum Tolerance in Rice (Oryza sativa) Determined through Genome-Wide Association Analysis and QTL Mapping

Aluminum (Al) toxicity is a primary limitation to crop productivity on acid soils, and rice has been demonstrated to be significantly more Al tolerant than other cereal crops. However, the mechanisms of rice Al tolerance are largely unknown, and no genes underlying natural variation have been reported. We screened 383 diverse rice accessions, conducted a genome-wide association (GWA) study, and conducted QTL mapping in two bi-parental populations using three estimates of Al tolerance based on root growth. Subpopulation structure explained 57% of the phenotypic variation, and the mean Al tolerance in Japonica was twice that of Indica. Forty-eight regions associated with Al tolerance were identified by GWA analysis, most of which were subpopulation-specific. Four of these regions co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified QTLs. Three regions corresponding to induced Al-sensitive rice mutants (ART1, STAR2, Nrat1) were identified through bi-parental QTL mapping or GWA to be involved in natural variation for Al tolerance. Haplotype analysis around the Nrat1 gene identified susceptible and tolerant haplotypes explaining 40% of the Al tolerance variation within the aus subpopulation, and sequence analysis of Nrat1 identified a trio of non-synonymous mutations predictive of Al sensitivity in our diversity panel. GWA analysis discovered more phenotype–genotype associations and provided higher resolution, but QTL mapping identified critical rare and/or subpopulation-specific alleles not detected by GWA analysis. Mapping using Indica/Japonica populations identified QTLs associated with transgressive variation where alleles from a susceptible aus or indica parent enhanced Al tolerance in a tolerant Japonica background. This work supports the hypothesis that selectively introgressing alleles across subpopulations is an efficient approach for trait enhancement in plant breeding programs and demonstrates the fundamental importance of subpopulation in interpreting and manipulating the genetics of complex traits in rice.

GEOCHEM-EZ: a chemical speciation program with greater power and flexibility

GEOCHEM-EZ is a multi-functional chemical speciation program, designed to replace GEOCHEM-PC, which can only be used on DOS consoles. Chemical speciation programs, such as GEOCHEM and GEOCHEM-PC, have been excellent tools for scientists designing appropriate solutions for their experiments. GEOCHEM-PC is widely used in plant nutrition and soil and environmental chemistry research to perform equilibrium speciation computations, allowing the user to estimate solution ion activities and to consider simple complexes and solid phases. As helpful as GEOCHEM-PC has been to scientists, the consensus was that the program was not very user friendly, was difficult to learn and to troubleshoot, and suffered from several functional weaknesses. To enhance the usability and to address the problems found in GEOCHEM-PC, we upgraded the program with a Java graphical interface, added Help files, and improved its power and function, allowing it to run on any computer that supports Windows XP, Vista or Windows 7.

Development of a Novel Aluminum Tolerance Phenotyping Platform Used for Comparisons of Cereal Aluminum Tolerance and Investigations into Rice Aluminum Tolerance Mechanisms

The genetic and physiological mechanisms of aluminum (Al) tolerance have been well studied in certain cereal crops, and Al tolerance genes have been identified in sorghum (Sorghum bicolor) and wheat (Triticum aestivum). Rice (Oryza sativa) has been reported to be highly Al tolerant; however, a direct comparison of rice and other cereals has not been reported, and the mechanisms of rice Al tolerance are poorly understood. To facilitate Al tolerance phenotyping in rice, a high-throughput imaging system and root quantification computer program was developed, permitting quantification of the entire root system, rather than just the longest root. Additionally, a novel hydroponic solution was developed and optimized for Al tolerance screening in rice and compared with the Yoshidas rice solution commonly used for rice Al tolerance studies. To gain a better understanding of Al tolerance in cereals, comparisons of Al tolerance across cereal species were conducted at four Al concentrations using seven to nine genetically diverse genotypes of wheat, maize (Zea mays), sorghum, and rice. Rice was significantly more tolerant than maize, wheat, and sorghum at all Al concentrations, with the mean Al tolerance level for rice found to be 2- to 6-fold greater than that in maize, wheat, and sorghum. Physiological experiments were conducted on a genetically diverse panel of more than 20 rice genotypes spanning the range of rice Al tolerance and compared with two maize genotypes to determine if rice utilizes the well-described Al tolerance mechanism of root tip Al exclusion mediated by organic acid exudation. These results clearly demonstrate that the extremely high levels of rice Al tolerance are mediated by a novel mechanism, which is independent of root tip Al exclusion.

High‐throughput two‐dimensional root system phenotyping platform facilitates genetic analysis of root growth and development

High-throughput phenotyping of root systems requires a combination of specialized techniques and adaptable plant growth, root imaging and software tools. A custom phenotyping platform was designed to capture images of whole root systems, and novel software tools were developed to process and analyse these images. The platform and its components are adaptable to a wide range root phenotyping studies using diverse growth systems (hydroponics, paper pouches, gel and soil) involving several plant species, including, but not limited to, rice, maize, sorghum, tomato and Arabidopsis. The RootReader2D software tool is free and publicly available and was designed with both user-guided and automated features that increase flexibility and enhance efficiency when measuring root growth traits from specific roots or entire root systems during large-scale phenotyping studies. To demonstrate the unique capabilities and high-throughput capacity of this phenotyping platform for studying root systems, genome-wide association studies on rice (Oryza sativa) and maize (Zea mays) root growth were performed and root traits related to aluminium (Al) tolerance were analysed on the parents of the maize nested association mapping (NAM) population.

Genotypic recognition and spatial responses by rice roots

Root system growth and development is highly plastic and is influenced by the surrounding environment. Roots frequently grow in heterogeneous environments that include interactions from neighboring plants and physical impediments in the rhizosphere. To investigate how planting density and physical objects affect root system growth, we grew rice in a transparent gel system in close proximity with another plant or a physical object. Root systems were imaged and reconstructed in three dimensions. Root–root interaction strength was calculated using quantitative metrics that characterize the extent to which the reconstructed root systems overlap each other. Surprisingly, we found the overlap of root systems of the same genotype was significantly higher than that of root systems of different genotypes. Root systems of the same genotype tended to grow toward each other but those of different genotypes appeared to avoid each other. Shoot separation experiments excluded the possibility of aerial interactions, suggesting root communication. Staggered plantings indicated that interactions likely occur at root tips in close proximity. Recognition of obstacles also occurred through root tips, but through physical contact in a size-dependent manner. These results indicate that root systems use two different forms of communication to recognize objects and alter root architecture: root-root recognition, possibly mediated through root exudates, and root-object recognition mediated by physical contact at the root tips. This finding suggests that root tips act as local sensors that integrate rhizosphere information into global root architectural changes.

A role for root morphology and related candidate genes in P acquisition efficiency in maize

Phosphorus (P) is an essential nutrient for plants and is acquired from the rhizosphere solution as inorganic phosphate. P is one of the least available mineral nutrients, particularly in highly weathered, tropical soils, and can substantially limit plant growth. The aim of this work was to study a possible effect of root morphology and the expression pattern of related candidate genes on P efficiency in maize. Our field phenotyping results under low and high P conditions enabled us to identify two contrasting genotypes for P acquisition efficiency that were used for the root traits studies. Root morphology was assessed in a paper pouch system to investigate root traits that could be involved in P acquisition efficiency. The genes, Rtcs, Bk2 and Rth3, which are known to be involved in root morphology, showed higher expression in the P efficient line relative to the P inefficient line. Overall, root traits showed high heritability and a low coefficient of variation. Principal component analysis revealed that out of the 24 root traits analysed, only four root traits were needed to adequately represent the diversity among genotypes. The information generated by this study will be useful for establishing early selection strategies for P efficiency in maize, which are needed to support subsequent molecular and physiological studies.

3D Quantification of Plant Root Architecture In Situ

Root systems play important roles in plant nutrient and water uptake. The spatial distribution and structure of root systems can affect many physiological functions, carbon distribution, and plant anchorage. The accurate measurement of root systems is necessary for better understanding of plant growth and responses to biotic and abiotic stress. Due to their underground growth habitat, root systems are usually excavated from the soil before root measurements are taken. This process can destroy the root system architecture and result in the lose of fine root structures, and consequently, many devices and technologies have been developed to nondestructively capture and measure root systems in situ in 2D or 3D, such as WinRhizo, minirhizotrons, X-ray computed tomography, and magnetic resonance imaging.

High-throughput 2D root system phenotyping platform facilitates genetic analysis of root growth and development

High-throughput phenotyping of root systems requires a combination of specialized techniques and adaptable plant growth, root imaging and software tools. A custom phenotyping platform was designed to capture images of whole root systems, and novel software tools were developed to process and analyse these images. The platform and its components are adaptable to a wide range root phenotyping studies using diverse growth systems (hydroponics, paper pouches, gel and soil) involving several plant species, including, but not limited to, rice, maize, sorghum, tomato and Arabidopsis. The RootReader2D software tool is free and publicly available and was designed with both user-guided and automated features that increase flexibility and enhance efficiency when measuring root growth traits from specific roots or entire root systems during large-scale phenotyping studies. To demonstrate the unique capabilities and high-throughput capacity of this phenotyping platform for studying root systems, genome-wide association studies on rice (Oryza sativa) and maize (Zea mays) root growth were performed and root traits related to aluminium (Al) tolerance were analysed on the parents of the maize nested association mapping (NAM) population.