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Wang Z, Yung WS, Gao Y, Huang C, Zhao X, Chen Y, Li MW, Lam HM. From phenotyping to genetic mapping: identifying water-stress adaptations in legume root traits. BMC PLANT BIOLOGY 2024; 24:749. [PMID: 39103780 DOI: 10.1186/s12870-024-05477-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 08/01/2024] [Indexed: 08/07/2024]
Abstract
BACKGROUND Climate change induces perturbation in the global water cycle, profoundly impacting water availability for agriculture and therefore global food security. Water stress encompasses both drought (i.e. water scarcity) that causes the drying of soil and subsequent plant desiccation, and flooding, which results in excess soil water and hypoxia for plant roots. Terrestrial plants have evolved diverse mechanisms to cope with soil water stress, with the root system serving as the first line of defense. The responses of roots to water stress can involve both structural and physiological changes, and their plasticity is a vital feature of these adaptations. Genetic methodologies have been extensively employed to identify numerous genetic loci linked to water stress-responsive root traits. This knowledge is immensely important for developing crops with optimal root systems that enhance yield and guarantee food security under water stress conditions. RESULTS This review focused on the latest insights into modifications in the root system architecture and anatomical features of legume roots in response to drought and flooding stresses. Special attention was given to recent breakthroughs in understanding the genetic underpinnings of legume root development under water stress. The review also described various root phenotyping techniques and examples of their applications in different legume species. Finally, the prevailing challenges and prospective research avenues in this dynamic field as well as the potential for using root system architecture as a breeding target are discussed. CONCLUSIONS This review integrated the latest knowledge of the genetic components governing the adaptability of legume roots to water stress, providing a reference for using root traits as the new crop breeding targets.
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Affiliation(s)
- Zhili Wang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China
| | - Wai-Shing Yung
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China
| | - Yamin Gao
- College of Resources and Environment, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Cheng Huang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
- Key Laboratory of the Ministry of Education for Crop Physiology and Molecular Biology, College of Agronomy, Hunan Agricultural University, Changsha, 410128, China
| | - Xusheng Zhao
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Yinglong Chen
- The UWA Institute of Agriculture, & School of Agriculture and Environment, The University of Western Australia, Perth, WA, 6001, Australia
| | - Man-Wah Li
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China
| | - Hon-Ming Lam
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China.
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.
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Alrajhi A, Alharbi S, Beecham S, Alotaibi F. Regulation of root growth and elongation in wheat. FRONTIERS IN PLANT SCIENCE 2024; 15:1397337. [PMID: 38835859 PMCID: PMC11148372 DOI: 10.3389/fpls.2024.1397337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 05/06/2024] [Indexed: 06/06/2024]
Abstract
Currently, the control of rhizosphere selection on farms has been applied to achieve enhancements in phenotype, extending from improvements in single root characteristics to the dynamic nature of entire crop systems. Several specific signals, regulatory elements, and mechanisms that regulate the initiation, morphogenesis, and growth of new lateral or adventitious root species have been identified, but much more work remains. Today, phenotyping technology drives the development of root traits. Available models for simulation can support all phenotyping decisions (root trait improvement). The detection and use of markers for quantitative trait loci (QTLs) are effective for enhancing selection efficiency and increasing reproductive genetic gains. Furthermore, QTLs may help wheat breeders select the appropriate roots for efficient nutrient acquisition. Single-nucleotide polymorphisms (SNPs) or alignment of sequences can only be helpful when they are associated with phenotypic variation for root development and elongation. Here, we focus on major root development processes and detail important new insights recently generated regarding the wheat genome. The first part of this review paper discusses the root morphology, apical meristem, transcriptional control, auxin distribution, phenotyping of the root system, and simulation models. In the second part, the molecular genetics of the wheat root system, SNPs, TFs, and QTLs related to root development as well as genome editing (GE) techniques for the improvement of root traits in wheat are discussed. Finally, we address the effect of omics strategies on root biomass production and summarize existing knowledge of the main molecular mechanisms involved in wheat root development and elongation.
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Affiliation(s)
- Abdullah Alrajhi
- King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- Sustainable Infrastructure and Resource Management, University of South Australia, University of South Australia Science, Technology, Engineering, and Mathematics (UniSA STEM), Mawson Lakes, SA, Australia
| | - Saif Alharbi
- The National Research and Development Center for Sustainable Agriculture (Estidamah), Riyadh, Saudi Arabia
| | - Simon Beecham
- Sustainable Infrastructure and Resource Management, University of South Australia, University of South Australia Science, Technology, Engineering, and Mathematics (UniSA STEM), Mawson Lakes, SA, Australia
| | - Fahad Alotaibi
- King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
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Nguyen HA, Martre P, Collet C, Draye X, Salon C, Jeudy C, Rincent R, Muller B. Are high-throughput root phenotyping platforms suitable for informing root system architecture models with genotype-specific parameters? An evaluation based on the root model ArchiSimple and a small panel of wheat cultivars. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:2510-2526. [PMID: 38520390 DOI: 10.1093/jxb/erae009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 03/21/2024] [Indexed: 03/25/2024]
Abstract
Given the difficulties in accessing plant roots in situ, high-throughput root phenotyping (HTRP) platforms under controlled conditions have been developed to meet the growing demand for characterizing root system architecture (RSA) for genetic analyses. However, a proper evaluation of their capacity to provide the same estimates for strictly identical root traits across platforms has never been achieved. In this study, we performed such an evaluation based on six major parameters of the RSA model ArchiSimple, using a diversity panel of 14 bread wheat cultivars in two HTRP platforms that had different growth media and non-destructive imaging systems together with a conventional set-up that had a solid growth medium and destructive sampling. Significant effects of the experimental set-up were found for all the parameters and no significant correlations across the diversity panel among the three set-ups could be detected. Differences in temperature, irradiance, and/or the medium in which the plants were growing might partly explain both the differences in the parameter values across the experiments as well as the genotype × set-up interactions. Furthermore, the values and the rankings across genotypes of only a subset of parameters were conserved between contrasting growth stages. As the parameters chosen for our analysis are root traits that have strong impacts on RSA and are close to parameters used in a majority of RSA models, our results highlight the need to carefully consider both developmental and environmental drivers in root phenomics studies.
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Affiliation(s)
- Hong Anh Nguyen
- LEPSE, Université de Montpellier, INRAE, Institut Agro Montpellier, Montpellier, France
| | - Pierre Martre
- LEPSE, Université de Montpellier, INRAE, Institut Agro Montpellier, Montpellier, France
| | - Clothilde Collet
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Xavier Draye
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Christophe Salon
- Agroécologie, AgroSup Dijon, INRAE, Université Bourgogne Franche-Comté, Dijon, France
| | - Christian Jeudy
- Agroécologie, AgroSup Dijon, INRAE, Université Bourgogne Franche-Comté, Dijon, France
| | - Renaud Rincent
- GDEC, Université Clermont-Auvergne, INRAE, Clermont-Ferrand, France
| | - Bertrand Muller
- LEPSE, Université de Montpellier, INRAE, Institut Agro Montpellier, Montpellier, France
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4
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Parasurama S, Banan D, Yun K, Doty S, Kim SH. Bridging Time-series Image Phenotyping and Functional-Structural Plant Modeling to Predict Adventitious Root System Architecture. PLANT PHENOMICS (WASHINGTON, D.C.) 2023; 5:0127. [PMID: 38143722 PMCID: PMC10739341 DOI: 10.34133/plantphenomics.0127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 11/21/2023] [Indexed: 12/26/2023]
Abstract
Root system architecture (RSA) is an important measure of how plants navigate and interact with the soil environment. However, current methods in studying RSA must make tradeoffs between precision of data and proximity to natural conditions, with root growth in germination papers providing accessibility and high data resolution. Functional-structural plant models (FSPMs) can overcome this tradeoff, though parameterization and evaluation of FSPMs are traditionally based in manual measurements and visual comparison. Here, we applied a germination paper system to study the adventitious RSA and root phenology of Populus trichocarpa stem cuttings using time-series image-based phenotyping augmented by FSPM. We found a significant correlation between timing of root initiation and thermal time at cutting collection (P value = 0.0061, R2 = 0.875), but little correlation with RSA. We also present a use of RhizoVision [1] for automatically extracting FSPM parameters from time series images and evaluating FSPM simulations. A high accuracy of the parameterization was achieved in predicting 2D growth with a sensitivity rate of 83.5%. This accuracy was lost when predicting 3D growth with sensitivity rates of 38.5% to 48.7%, while overall accuracy varied with phenotyping methods. Despite this loss in accuracy, the new method is amenable to high throughput FSPM parameterization and bridges the gap between advances in time-series phenotyping and FSPMs.
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Affiliation(s)
- Sriram Parasurama
- School of Environmental and Forest Sciences,
University of Washington, Seattle, USA
- School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA
| | - Darshi Banan
- School of Environmental and Forest Sciences,
University of Washington, Seattle, USA
| | - Kyungdahm Yun
- Department of Smart Farm,
Jeonbuk National University, Jeonju, Korea
| | - Sharon Doty
- School of Environmental and Forest Sciences,
University of Washington, Seattle, USA
| | - Soo-Hyung Kim
- School of Environmental and Forest Sciences,
University of Washington, Seattle, USA
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5
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Zhang P, Huang J, Ma Y, Wang X, Kang M, Song Y. Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery. PLANT PHENOMICS (WASHINGTON, D.C.) 2023; 5:0091. [PMID: 37780969 PMCID: PMC10538623 DOI: 10.34133/plantphenomics.0091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 08/26/2023] [Indexed: 10/03/2023]
Abstract
Observable morphological traits are widely employed in plant phenotyping for breeding use, which are often the external phenotypes driven by a chain of functional actions in plants. Identifying and phenotyping inherently functional traits for crop improvement toward high yields or adaptation to harsh environments remains a major challenge. Prediction of whole-plant performance in functional-structural plant models (FSPMs) is driven by plant growth algorithms based on organ scale wrapped up with micro-environments. In particular, the models are flexible for scaling down or up through specific functions at the organ nexus, allowing the prediction of crop system behaviors from the genome to the field. As such, by virtue of FSPMs, model parameters that determine organogenesis, development, biomass production, allocation, and morphogenesis from a molecular to the whole plant level can be profiled systematically and made readily available for phenotyping. FSPMs can provide rich functional traits representing biological regulatory mechanisms at various scales in a dynamic system, e.g., Rubisco carboxylation rate, mesophyll conductance, specific leaf nitrogen, radiation use efficiency, and source-sink ratio apart from morphological traits. High-throughput phenotyping such traits is also discussed, which provides an unprecedented opportunity to evolve FSPMs. This will accelerate the co-evolution of FSPMs and plant phenomics, and thus improving breeding efficiency. To expand the great promise of FSPMs in crop science, FSPMs still need more effort in multiscale, mechanistic, reproductive organ, and root system modeling. In summary, this study demonstrates that FSPMs are invaluable tools in guiding functional trait phenotyping at various scales and can thus provide abundant functional targets for phenotyping toward crop improvement.
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Affiliation(s)
- Pengpeng Zhang
- School of Agronomy, Anhui Agricultural University, Hefei, Anhui Province 230036, China
| | - Jingyao Huang
- School of Agronomy, Anhui Agricultural University, Hefei, Anhui Province 230036, China
| | - Yuntao Ma
- College of Land Science and Technology, China Agricultural University, Beijing 100094, China
| | - Xiujuan Wang
- The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Mengzhen Kang
- The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Youhong Song
- School of Agronomy, Anhui Agricultural University, Hefei, Anhui Province 230036, China
- Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD 4350, Australia
- Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD 4350, Australia
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6
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Peeples J, Xu W, Gloaguen R, Rowland D, Zare A, Brym Z. Spatial and Texture Analysis of Root System distribution with Earth mover's Distance (STARSEED). PLANT METHODS 2023; 19:2. [PMID: 36604751 PMCID: PMC9814335 DOI: 10.1186/s13007-022-00974-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
PURPOSE Root system architectures are complex and challenging to characterize effectively for agronomic and ecological discovery. METHODS We propose a new method, Spatial and Texture Analysis of Root SystEm distribution with Earth mover's Distance (STARSEED), for comparing root system distributions that incorporates spatial information through a novel application of the Earth Mover's Distance (EMD). RESULTS We illustrate that the approach captures the response of sesame root systems for different genotypes and soil moisture levels. STARSEED provides quantitative and visual insights into changes that occur in root architectures across experimental treatments. CONCLUSION STARSEED can be generalized to other plants and provides insight into root system architecture development and response to varying growth conditions not captured by existing root architecture metrics and models. The code and data for our experiments are publicly available: https://github.com/GatorSense/STARSEED .
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Affiliation(s)
- Joshua Peeples
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, 77845 USA
| | - Weihuang Xu
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, 32611 USA
| | | | - Diane Rowland
- College of Natural Sciences, Forestry, and Agriculture, University of Maine, Orono, 04469 USA
| | - Alina Zare
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, 32611 USA
| | - Zachary Brym
- Tropical Research and Education Center, University of Florida, Gainesville, 33031 USA
- Department of Agronomy, University of Florida, Gainesville, 32611 USA
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7
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Deja-Muylle A, Opdenacker D, Parizot B, Motte H, Lobet G, Storme V, Clauw P, Njo M, Beeckman T. Genetic Variability of Arabidopsis thaliana Mature Root System Architecture and Genome-Wide Association Study. FRONTIERS IN PLANT SCIENCE 2022; 12:814110. [PMID: 35154211 PMCID: PMC8831901 DOI: 10.3389/fpls.2021.814110] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 12/15/2021] [Indexed: 06/14/2023]
Abstract
Root system architecture (RSA) has a direct influence on the efficiency of nutrient uptake and plant growth, but the genetics of RSA are often studied only at the seedling stage. To get an insight into the genetic blueprint of a more mature RSA, we exploited natural variation and performed a detailed in vitro study of 241 Arabidopsis thaliana accessions using large petri dishes. A comprehensive analysis of 17 RSA traits showed high variability among the different accessions, unveiling correlations between traits and conditions of the natural habitat of the plants. A sub-selection of these accessions was grown in water-limiting conditions in a rhizotron set-up, which revealed that especially the spatial distribution showed a high consistency between in vitro and ex vitro conditions, while in particular, a large root area in the lower zone favored drought tolerance. The collected RSA phenotype data were used to perform genome-wide association studies (GWAS), which stands out from the previous studies by its exhaustive measurements of RSA traits on more mature Arabidopsis accessions used for GWAS. As a result, we found not only several genes involved in the lateral root (LR) development or auxin signaling pathways to be associated with RSA traits but also new candidate genes that are potentially involved in the adaptation to the natural habitats.
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Affiliation(s)
- Agnieszka Deja-Muylle
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Davy Opdenacker
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Boris Parizot
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Hans Motte
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Guillaume Lobet
- Forschungszentrum Jülich GmbH, Agrosphere (IBG-3), Jülich, Germany
| | - Veronique Storme
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Pieter Clauw
- Gregor Mendel Institute of Molecular Plant Biology, Vienna, Austria
| | - Maria Njo
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Tom Beeckman
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
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8
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Kim KS, Kim SH, Kim J, Tripathi P, Lee JD, Chung YS, Kim Y. A Large Root Phenome Dataset Wide-Opened the Potential for Underground Breeding in Soybean. FRONTIERS IN PLANT SCIENCE 2021; 12:704239. [PMID: 34421953 PMCID: PMC8374737 DOI: 10.3389/fpls.2021.704239] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 07/14/2021] [Indexed: 06/02/2023]
Abstract
The root is the most critical plant organ for water and nutrient acquisition. Although the root is vital for water and nutrient uptake, the diverse root characters of soybean still need to be identified owing to the difficulty of root sampling. In this study, we used 150 wild and 50 cultivated soybean varieties to collect root image samples. We analyzed root morphological traits using acquired-image. Except for the main total length (MTL), the root morphological traits for most cultivated and wild plants were significantly different. According to correlation analysis, the wild and cultivated plants showed a significant correlation among total root length (TRL), projected area (PA), forks, total lateral length (TLL), link average diameter, and MTL. In particular, TRL was highly correlated with PA in both cultivated (0.92) and wild (0.82) plants compared with between MTL (0.43 for cultivated and 0.27 for wild) and TLL (0.82 for cultivated and 0.52 for wild). According to principal component analysis results, both plants could be separated; however, there was some overlap of the traits among the wild and cultivated individuals from some regions. Nevertheless, variation among the cultivated plants was higher than that found in the wild plants. Furthermore, three groups, including MTL, TLL, and the remaining traits, could explain all the variances.
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Affiliation(s)
- Ki-Seung Kim
- Department of Innovative Technology, FarmHannong, Ltd., Nonsan, South Korea
| | - Se-Hun Kim
- Department of Applied Biosciences, Kyungpook National University, Daegu, South Korea
| | - Jaeyoung Kim
- Department of Plant Resources and Environment, Jeju National University, Jeju, South Korea
| | - Pooja Tripathi
- Department of Applied Biosciences, Kyungpook National University, Daegu, South Korea
| | - Jeong-Dong Lee
- Department of Applied Biosciences, Kyungpook National University, Daegu, South Korea
| | - Yong Suk Chung
- Department of Plant Resources and Environment, Jeju National University, Jeju, South Korea
| | - Yoonha Kim
- Department of Applied Biosciences, Kyungpook National University, Daegu, South Korea
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Pandey AK, Rubiales D, Wang Y, Fang P, Sun T, Liu N, Xu P. Omics resources and omics-enabled approaches for achieving high productivity and improved quality in pea (Pisum sativum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:755-776. [PMID: 33433637 DOI: 10.1007/s00122-020-03751-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Accepted: 12/10/2020] [Indexed: 05/09/2023]
Abstract
Pea (Pisum sativum L.), a cool-season legume crop grown in more than 85 countries, is the second most important grain legume and one of the major green vegetables in the world. While pea was historically studied as the genetic model leading to the discovery of the laws of genetics, pea research has lagged behind that of other major legumes in the genomics era, due to its large and complex genome. The evolving climate change and growing population have posed grand challenges to the objective of feeding the world, making it essential to invest research efforts to develop multi-omics resources and advanced breeding tools to support fast and continuous development of improved pea varieties. Recently, the pea researchers have achieved key milestones in omics and molecular breeding. The present review provides an overview of the recent important progress including the development of genetic resource databases, high-throughput genotyping assays, reference genome, genes/QTLs responsible for important traits, transcriptomic, proteomic, and phenomic atlases of various tissues under different conditions. These multi-faceted resources have enabled the successful implementation of various markers for monitoring early-generation populations as in marker-assisted backcrossing breeding programs. The emerging new breeding approaches such as CRISPR, speed breeding, and genomic selection are starting to change the paradigm of pea breeding. Collectively, the rich omics resources and omics-enable breeding approaches will enhance genetic gain in pea breeding and accelerate the release of novel pea varieties to meet the elevating demands on productivity and quality.
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Affiliation(s)
- Arun K Pandey
- College of Life Sciences, China Jiliang University, Hangzhou, 310018, China
| | - Diego Rubiales
- Institute for Sustainable Agriculture, CSIC, 14004, Córdoba, Spain
| | - Yonggang Wang
- College of Life Sciences, China Jiliang University, Hangzhou, 310018, China
| | - Pingping Fang
- College of Life Sciences, China Jiliang University, Hangzhou, 310018, China
| | - Ting Sun
- College of Life Sciences, China Jiliang University, Hangzhou, 310018, China
| | - Na Liu
- Institute of Vegetables, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Pei Xu
- College of Life Sciences, China Jiliang University, Hangzhou, 310018, China.
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10
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Nagel KA, Lenz H, Kastenholz B, Gilmer F, Averesch A, Putz A, Heinz K, Fischbach A, Scharr H, Fiorani F, Walter A, Schurr U. The platform GrowScreen- Agar enables identification of phenotypic diversity in root and shoot growth traits of agar grown plants. PLANT METHODS 2020; 16:89. [PMID: 32582364 PMCID: PMC7310412 DOI: 10.1186/s13007-020-00631-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 06/15/2020] [Indexed: 05/24/2023]
Abstract
BACKGROUND Root system architecture and especially its plasticity in acclimation to variable environments play a crucial role in the ability of plants to explore and acquire efficiently soil resources and ensure plant productivity. Non-destructive measurement methods are indispensable to quantify dynamic growth traits. For closing the phenotyping gap, we have developed an automated phenotyping platform, GrowScreen-Agar, for non-destructive characterization of root and shoot traits of plants grown in transparent agar medium. RESULTS The phenotyping system is capable to phenotype root systems and correlate them to whole plant development of up to 280 Arabidopsis plants within 15 min. The potential of the platform has been demonstrated by quantifying phenotypic differences within 78 Arabidopsis accessions from the 1001 genomes project. The chosen concept 'plant-to-sensor' is based on transporting plants to the imaging position, which allows for flexible experimental size and design. As transporting causes mechanical vibrations of plants, we have validated that daily imaging, and consequently, moving plants has negligible influence on plant development. Plants are cultivated in square Petri dishes modified to allow the shoot to grow in the ambient air while the roots grow inside the Petri dish filled with agar. Because it is common practice in the scientific community to grow Arabidopsis plants completely enclosed in Petri dishes, we compared development of plants that had the shoot inside with that of plants that had the shoot outside the plate. Roots of plants grown completely inside the Petri dish grew 58% slower, produced a 1.8 times higher lateral root density and showed an etiolated shoot whereas plants whose shoot grew outside the plate formed a rosette. In addition, the setup with the shoot growing outside the plate offers the unique option to accurately measure both, leaf and root traits, non-destructively, and treat roots and shoots separately. CONCLUSIONS Because the GrowScreen-Agar system can be moved from one growth chamber to another, plants can be phenotyped under a wide range of environmental conditions including future climate scenarios. In combination with a measurement throughput enabling phenotyping a large set of mutants or accessions, the platform will contribute to the identification of key genes.
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Affiliation(s)
- Kerstin A Nagel
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Henning Lenz
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Bernd Kastenholz
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Frank Gilmer
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
- Present Address: BASF SE, 67117 Limburgerhof, Germany
| | - Andreas Averesch
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Alexander Putz
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Kathrin Heinz
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Andreas Fischbach
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Hanno Scharr
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Fabio Fiorani
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Achim Walter
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
- Present Address: Institute of Agricultural Sciences, ETH Zürich, Universitätstrasse 2, 8092 Zurich, Switzerland
| | - Ulrich Schurr
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
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11
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Watt M, Fiorani F, Usadel B, Rascher U, Muller O, Schurr U. Phenotyping: New Windows into the Plant for Breeders. ANNUAL REVIEW OF PLANT BIOLOGY 2020; 71:689-712. [PMID: 32097567 DOI: 10.1146/annurev-arplant-042916-041124] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Plant phenotyping enables noninvasive quantification of plant structure and function and interactions with environments. High-capacity phenotyping reaches hitherto inaccessible phenotypic characteristics. Diverse, challenging, and valuable applications of phenotyping have originated among scientists, prebreeders, and breeders as they study the phenotypic diversity of genetic resources and apply increasingly complex traits to crop improvement. Noninvasive technologies are used to analyze experimental and breeding populations. We cover the most recent research in controlled-environment and field phenotyping for seed, shoot, and root traits. Select field phenotyping technologies have become state of the art and show promise for speeding up the breeding process in early generations. We highlight the technologies behind the rapid advances in proximal and remote sensing of plants in fields. We conclude by discussing the new disciplines working with the phenotyping community: data science, to address the challenge of generating FAIR (findable, accessible, interoperable, and reusable) data, and robotics, to apply phenotyping directly on farms.
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Affiliation(s)
- Michelle Watt
- IBG-2: Plant Sciences, Institute of Bio- and Geosciences, Forschungszentrum Jülich, 52425 Jülich, Germany; ,
| | - Fabio Fiorani
- IBG-2: Plant Sciences, Institute of Bio- and Geosciences, Forschungszentrum Jülich, 52425 Jülich, Germany; ,
| | - Björn Usadel
- IBG-2: Plant Sciences, Institute of Bio- and Geosciences, Forschungszentrum Jülich, 52425 Jülich, Germany; ,
- Institute for Botany and Molecular Genetics, BioSC, RWTH Aachen University, 52074 Aachen, Germany
| | - Uwe Rascher
- IBG-2: Plant Sciences, Institute of Bio- and Geosciences, Forschungszentrum Jülich, 52425 Jülich, Germany; ,
| | - Onno Muller
- IBG-2: Plant Sciences, Institute of Bio- and Geosciences, Forschungszentrum Jülich, 52425 Jülich, Germany; ,
| | - Ulrich Schurr
- IBG-2: Plant Sciences, Institute of Bio- and Geosciences, Forschungszentrum Jülich, 52425 Jülich, Germany; ,
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12
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Kim Y, Chung YS, Lee E, Tripathi P, Heo S, Kim KH. Root Response to Drought Stress in Rice ( Oryza sativa L .). Int J Mol Sci 2020; 21:E1513. [PMID: 32098434 PMCID: PMC7073213 DOI: 10.3390/ijms21041513] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 02/21/2020] [Accepted: 02/21/2020] [Indexed: 01/24/2023] Open
Abstract
The current unpredictable climate changes are causing frequent and severe droughts. Such circumstances emphasize the need to understand the response of plants to drought stress, especially in rice, one of the most important grain crops. Knowledge of the drought stress response components is especially important in plant roots, the major organ for the absorption of water and nutrients from the soil. Thus, this article reviews the root response to drought stress in rice. It is presented to provide readers with information of use for their own research and breeding program for tolerance to drought stress in rice.
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Affiliation(s)
- Yoonha Kim
- School of Applied Biosciences, Kyungpook National University, Daegu 41566, Korea; (Y.K.); (P.T.)
| | - Yong Suk Chung
- Faculty of Bioscience and Industry, College of Applied Life Science, SARI, Jeju National University, Jeju 63243, Korea;
| | - Eungyeong Lee
- National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Korea;
| | - Pooja Tripathi
- School of Applied Biosciences, Kyungpook National University, Daegu 41566, Korea; (Y.K.); (P.T.)
| | - Seong Heo
- Ganghwa Agricultural Technology Service Center, Incheon 23038, Korea;
| | - Kyung-Hwan Kim
- National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Korea;
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13
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Tracy SR, Nagel KA, Postma JA, Fassbender H, Wasson A, Watt M. Crop Improvement from Phenotyping Roots: Highlights Reveal Expanding Opportunities. TRENDS IN PLANT SCIENCE 2020; 25:105-118. [PMID: 31806535 DOI: 10.1016/j.tplants.2019.10.015] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 10/30/2019] [Accepted: 10/31/2019] [Indexed: 05/21/2023]
Abstract
Root systems determine the water and nutrients for photosynthesis and harvested products, underpinning agricultural productivity. We highlight 11 programs that integrated root traits into germplasm for breeding, relying on phenotyping. Progress was successful but slow. Today's phenotyping technologies will speed up root trait improvement. They combine multiple new alleles in germplasm for target environments, in parallel. Roots and shoots are detected simultaneously and nondestructively, seed to seed measures are automated, and field and laboratory technologies are increasingly linked. Available simulation models can aid all phenotyping decisions. This century will see a shift from single root traits to rhizosphere selections that can be managed dynamically on farms and a shift to phenotype-based improvement to accommodate the dynamic complexity of whole crop systems.
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Affiliation(s)
- Saoirse R Tracy
- School of Agriculture & Food Science, University College Dublin, Dublin, Ireland
| | - Kerstin A Nagel
- Institute for Bio and Geosciences-2, Plant Sciences, Forschungszentrum Juelich GmbH, 52428 Juelich, Germany
| | - Johannes A Postma
- Institute for Bio and Geosciences-2, Plant Sciences, Forschungszentrum Juelich GmbH, 52428 Juelich, Germany
| | - Heike Fassbender
- Institute for Bio and Geosciences-2, Plant Sciences, Forschungszentrum Juelich GmbH, 52428 Juelich, Germany
| | - Anton Wasson
- CSIRO Agriculture and Food, Canberra, Australian Capital Territory, Australia
| | - Michelle Watt
- Institute for Bio and Geosciences-2, Plant Sciences, Forschungszentrum Juelich GmbH, 52428 Juelich, Germany.
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14
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Chung YS, Lee U, Heo S, Silva RR, Na CI, Kim Y. Image-Based Machine Learning Characterizes Root Nodule in Soybean Exposed to Silicon. FRONTIERS IN PLANT SCIENCE 2020; 11:520161. [PMID: 33193467 PMCID: PMC7655541 DOI: 10.3389/fpls.2020.520161] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Accepted: 10/06/2020] [Indexed: 05/07/2023]
Abstract
Silicon promotes nodule formation in legume roots which is crucial for nitrogen fixation. However, it is very time-consuming and laborious to count the number of nodules and to measure nodule size manually, which led nodule characterization not to be study as much as other agronomical characters. Thus, the current study incorporated various techniques including machine learning to determine the number and size of root nodules and identify various root phenotypes from root images that may be associated with nodule formation with and without silicon treatment. Among those techniques, the machine learning for characterizing nodule is the first attempt, which enabled us to find high correlations among root phenotypes including root length, number of forks, and average link angles, and nodule characters such as number of nodules and nodule size with silicon treatments. The methods here could greatly accelerate further investigation such as delineating the optimal concentration of silicon for nodule formation.
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Affiliation(s)
- Yong Suk Chung
- Department of Plant Resources and Environment, Jeju National University, Jeju-si, South Korea
| | - Unseok Lee
- Smart Farm Research Center, Korea Institute of Science and Technology, Gangneung-si, South Korea
| | - Seong Heo
- Department of Horticulture, Kongju National University, Yesan, South Korea
| | | | - Chae-In Na
- Department of Agronomy, Gyeongsang National University, Jinju-si, South Korea
| | - Yoonha Kim
- School of Applied Life Science, Kyungpook National University, Daegu, South Korea
- *Correspondence: Yoonha Kim, ;
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15
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Li S, Peng F, Xiao Y, Gong Q, Bao Z, Li Y, Wu X. Mechanisms of High Concentration Valine-Mediated Inhibition of Peach Tree Shoot Growth. FRONTIERS IN PLANT SCIENCE 2020; 11:603067. [PMID: 33193558 PMCID: PMC7658097 DOI: 10.3389/fpls.2020.603067] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Accepted: 10/09/2020] [Indexed: 05/10/2023]
Abstract
The vigorous growth of the new shoots of the peach tree was not beneficial to high quality and efficient cultivation. High concentration of amino acids can inhibit plant growth, but the mechanism is not clear. In this study, we explored the regulatory effects of seven amino acids (phenylalanine, valine, leucine, isoleucine, serine, D-alanine, and proline) (10 g⋅L-1) on the growth of peach trees. The results showed that phenylalanine, valine, and proline inhibited peach seedling growth and valine has the most significant effect and it can promote the root growth of peach seedlings. Compared with paclobutrazol, valine treatment improves net photosynthetic rate and fruit quality without reducing shoot diameter or puncture strength, and it does not affect leaf morphology. Valine enhanced the expression of PpSnRK1 (sucrose non-fermenting-1-related protein kinase) and inhibited the expression of PpTOR (Target of Rapamycin) and PpS6K (Ribosomal S6 kinase). The gibberellin content was significantly reduced in the valine treatment group. The endogenous valine content of peach seedlings was increased, acetohydroxyacid synthase (AHAS, E.C. 2.2.1.6) activity was inhibited by feedback, isoleucine synthesis was decreased, the relative amounts of branched chain amino acids were unbalanced, and growth was inhibited. However, isoleucine spraying after valine treatment could increase the content of isoleucine and alleviate the inhibition of valine on the shoot growth. In conclusion, valine is environmentally friendly to inhibit the growth of new shoots of peach trees by regulating the balance of PpSnRK1 and PpTOR and the synthesis of isoleucine.
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Affiliation(s)
- Suhong Li
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai’an, China
| | - Futian Peng
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai’an, China
- *Correspondence: Futian Peng,
| | - Yuansong Xiao
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai’an, China
- Yuansong Xiao,
| | | | - Ziyi Bao
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai’an, China
| | - Yanyan Li
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai’an, China
| | - Xuelian Wu
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai’an, China
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16
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Bodner G, Loiskandl W, Hartl W, Erhart E, Sobotik M. Characterization of Cover Crop Rooting Types from Integration of Rhizobox Imaging and Root Atlas Information. PLANTS (BASEL, SWITZERLAND) 2019; 8:E514. [PMID: 31744188 PMCID: PMC6918168 DOI: 10.3390/plants8110514] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 11/06/2019] [Accepted: 11/15/2019] [Indexed: 11/24/2022]
Abstract
Plant root systems are essential for sustainable agriculture, conveying resource-efficient genotypes and species with benefits to soil ecosystem functions. Targeted selection of species/genotypes depends on available root system information. Currently there is no standardized approach for comprehensive root system characterization, suggesting the need for data integration across methods and sources. Here, we combine field measured root descriptors from the classical Root Atlas series with traits from controlled-environment root imaging for 10 cover crop species to (i) detect descriptors scaling between distant experimental methods, (ii) provide traits for species classification, and (iii) discuss implications for cover crop ecosystem functions. Results revealed relation of single axes measures from root imaging (convex hull, primary-lateral length ratio) to Root Atlas field descriptors (depth, branching order). Using composite root variables (principal components) for branching, morphology, and assimilate investment traits, cover crops were classified into species with (i) topsoil-allocated large diameter rooting type, (ii) low-branched primary/shoot-born axes-dominated rooting type, and (iii) highly branched dense rooting type, with classification trait-dependent distinction according to depth distribution. Data integration facilitated identification of root classification variables to derive root-related cover crop distinction, indicating their agro-ecological functions.
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Affiliation(s)
- Gernot Bodner
- Institute of Agronomy, Department of Crop Sciences, University of Natural Resources and Life Sciences, Konrad-Lorenz-Straße 24, A-3430 Tulln, Austria
- Austrian Society of Root Research, Muthgasse 18, A-1190 Vienna, Austria; (W.L.); (W.H.); (E.E.); (M.S.)
| | - Willibald Loiskandl
- Austrian Society of Root Research, Muthgasse 18, A-1190 Vienna, Austria; (W.L.); (W.H.); (E.E.); (M.S.)
- Institute for Soil Physics and Rural Water Management, University of Natural Resources and Life Sciences, Muthgasse 18, A-1190 Vienna, Austria
| | - Wilfried Hartl
- Austrian Society of Root Research, Muthgasse 18, A-1190 Vienna, Austria; (W.L.); (W.H.); (E.E.); (M.S.)
- Bioforschung Austria, Esslinger Hauptstrasse 132-134, A-1220 Vienna, Austria
| | - Eva Erhart
- Austrian Society of Root Research, Muthgasse 18, A-1190 Vienna, Austria; (W.L.); (W.H.); (E.E.); (M.S.)
- Bioforschung Austria, Esslinger Hauptstrasse 132-134, A-1220 Vienna, Austria
| | - Monika Sobotik
- Austrian Society of Root Research, Muthgasse 18, A-1190 Vienna, Austria; (W.L.); (W.H.); (E.E.); (M.S.)
- Pflanzensoziologisches Institut, Pichlern 9, A-4822 Bad Goisern, Austria
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17
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Jiang N, Floro E, Bray AL, Laws B, Duncan KE, Topp CN. Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures. THE PLANT CELL 2019; 31:1708-1722. [PMID: 31123089 PMCID: PMC6713302 DOI: 10.1105/tpc.19.00015] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 05/08/2019] [Accepted: 07/01/2019] [Indexed: 05/22/2023]
Abstract
Understanding how an organism's phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology. Root systems are one of the most important but poorly understood aspects of plants, largely due to the three-dimensional (3D), dynamic, and multiscale phenotyping challenge they pose. A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize (Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.
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Affiliation(s)
- Ni Jiang
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
| | - Eric Floro
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
| | - Adam L Bray
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
- Division of Plant Sciences, University of Missouri, Columbia, Missouri 65211
| | - Benjamin Laws
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
| | - Keith E Duncan
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
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18
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Jiang N, Floro E, Bray AL, Laws B, Duncan KE, Topp CN. Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures. THE PLANT CELL 2019; 31:1708-1722. [PMID: 31123089 DOI: 10.1101/381046] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 05/08/2019] [Accepted: 07/01/2019] [Indexed: 05/28/2023]
Abstract
Understanding how an organism's phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology. Root systems are one of the most important but poorly understood aspects of plants, largely due to the three-dimensional (3D), dynamic, and multiscale phenotyping challenge they pose. A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize (Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.
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Affiliation(s)
- Ni Jiang
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
| | - Eric Floro
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
| | - Adam L Bray
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
- Division of Plant Sciences, University of Missouri, Columbia, Missouri 65211
| | - Benjamin Laws
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
| | - Keith E Duncan
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132
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19
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Del Bianco M, Kepinski S. Building a future with root architecture. JOURNAL OF EXPERIMENTAL BOTANY 2018; 69:5319-5323. [PMID: 30445468 PMCID: PMC6255693 DOI: 10.1093/jxb/ery390] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Affiliation(s)
- Marta Del Bianco
- Centre for Plant Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Stefan Kepinski
- Centre for Plant Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
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20
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Bodner G, Nakhforoosh A, Arnold T, Leitner D. Hyperspectral imaging: a novel approach for plant root phenotyping. PLANT METHODS 2018; 14:84. [PMID: 30305838 PMCID: PMC6169016 DOI: 10.1186/s13007-018-0352-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 09/24/2018] [Indexed: 05/22/2023]
Abstract
BACKGROUND Root phenotyping aims to characterize root system architecture because of its functional role in resource acquisition. RGB imaging and analysis procedures measure root system traits via colour contrasts between roots and growth media or artificial backgrounds. In the case of plants grown in soil-filled rhizoboxes, where the colour contrast can be poor, it is hypothesized that root imaging based on spectral signatures improves segmentation and provides additional knowledge on physico-chemical root properties. RESULTS Root systems of Triticum durum grown in soil-filled rhizoboxes were scanned in a spectral range of 1000-1700 nm with 222 narrow bands and a spatial resolution of 0.1 mm. A data processing pipeline was developed for automatic root segmentation and analysis of spectral root signatures. Spectral- and RGB-based root segmentation did not significantly differ in accuracy even for a bright soil background. Best spectral segmentation was obtained from log-linearized and asymptotic least squares corrected images via fuzzy clustering and multilevel thresholding. Root axes revealed major spectral distinction between center and border regions. Root decay was captured by an exponential function of the difference spectra between water and structural carbon absorption regions. CONCLUSIONS Fundamentals for root phenotyping using hyperspectral imaging have been established by means of an image processing pipeline for automated segmentation of soil-grown plant roots at a high spatial resolution and for the exploration of spectral signatures encoding physico-chemical root zone properties.
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Affiliation(s)
- Gernot Bodner
- Division of Agronomy, Department of Crop Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), Konrad Lorenz-Straße 24, 3430 Tulln an der Donau, Austria
| | - Alireza Nakhforoosh
- Division of Agronomy, Department of Crop Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), Konrad Lorenz-Straße 24, 3430 Tulln an der Donau, Austria
- Agriculture and Agri-Food Canada, Brandon Research and Development Centre, Brandon, MB R7A 5Y3 Canada
| | - Thomas Arnold
- Carinthian Tech Research AG, Europastraße 12, High Tech Campus Villach, 9524 Villach/St. Magdalen, Austria
| | - Daniel Leitner
- Computational Science Center, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
- Simulationswerkstatt, Ortmayrstrasse 20, 4060 Leonding, Austria
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21
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Zhao J, Sykacek P, Bodner G, Rewald B. Root traits of European Vicia faba cultivars-Using machine learning to explore adaptations to agroclimatic conditions. PLANT, CELL & ENVIRONMENT 2018; 41:1984-1996. [PMID: 28857245 DOI: 10.1111/pce.13062] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 08/18/2017] [Accepted: 08/22/2017] [Indexed: 05/23/2023]
Abstract
Faba bean (Vicia faba L.) is an important source of protein, but breeding for increased yield stability and stress tolerance is hampered by the scarcity of phenotyping information. Because comparisons of cultivars adapted to different agroclimatic zones improve our understanding of stress tolerance mechanisms, the root architecture and morphology of 16 European faba bean cultivars were studied at maturity. Different machine learning (ML) approaches were tested in their usefulness to analyse trait variations between cultivars. A supervised, that is, hypothesis-driven, ML approach revealed that cultivars from Portugal feature greater and coarser but less frequent lateral roots at the top of the taproot, potentially enhancing water uptake from deeper soil horizons. Unsupervised clustering revealed that trait differences between northern and southern cultivars are not predominant but that two cultivar groups, independently from major and minor types, differ largely in overall root system size. Methodological guidelines on how to use powerful ML methods such as random forest models for enhancing the phenotypical exploration of plants are given.
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Affiliation(s)
- Jiangsan Zhao
- Department of Forest and Soil Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), 1190, Tulln an der Donau, Austria
| | - Peter Sykacek
- Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna (BOKU), 1190, Tulln an der Donau, Austria
| | - Gernot Bodner
- Division of Agronomy, Department of Crop Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), 3430, Tulln an der Donau, Austria
| | - Boris Rewald
- Department of Forest and Soil Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), 1190, Tulln an der Donau, Austria
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22
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Pagès L, Kervella J. Seeking stable traits to characterize the root system architecture. Study on 60 species located at two sites in natura. ANNALS OF BOTANY 2018; 122:107-115. [PMID: 29697745 PMCID: PMC6025210 DOI: 10.1093/aob/mcy061] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Accepted: 04/06/2018] [Indexed: 05/17/2023]
Abstract
Background and Aims In several disciplines, identifying relevant root traits to characterize the root system architecture of species or genotypes is a crucial step. To address this question, we analysed the inter-specific variations of root architectural traits in two contrasting environments. Methods We sampled 60 species in natura, at two sites, each presenting homogeneous soil conditions. We estimated for each species and site a set of five traits used for the modelling of the root system architecture: extreme tip diameters (Dmin and Dmax), relative diameter range (Drange), mean inter-branch distance (IBD) and dominance slope between the diameters of parent and lateral roots (DlDm). Key Results The five traits presented a highly significant species effect, explaining between 77 and 98 % of the total variation. Dmin, Dmax and Drange were particularly determined by the species, while DlDm and IBD exhibited a higher percentage of environmental variations. These traits make it possible to confirm two main axes of variation: 'fineness-density' (defined by Dmin and IBD) and 'dominance-heterorhizy' (DlDm and Drange), that together accounted for 84 % of the variations observed. Conclusions We confirmed the interest of these traits in the characterization of the root system architecture in ecology and genetics, and suggest using them to enrich the 'root economic spectrum'.
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Affiliation(s)
- Loïc Pagès
- INRA, Centre PACA, UR 1115 PSH, Domaine Saint-Paul, Site Agroparc, Avignon cedex 9, France
| | - Jocelyne Kervella
- INRA, Centre PACA, UR 1052 GAFL, Domaine Saint-Maurice, Montfavet cedex, France
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23
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Ye H, Roorkiwal M, Valliyodan B, Zhou L, Chen P, Varshney RK, Nguyen HT. Genetic diversity of root system architecture in response to drought stress in grain legumes. JOURNAL OF EXPERIMENTAL BOTANY 2018; 69:3267-3277. [PMID: 29522207 DOI: 10.1093/jxb/ery082] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Accepted: 03/05/2018] [Indexed: 05/23/2023]
Abstract
Climate change has increased the occurrence of extreme weather patterns globally, causing significant reductions in crop production, and hence threatening food security. In order to meet the food demand of the growing world population, a faster rate of genetic gains leading to productivity enhancement for major crops is required. Grain legumes are an essential commodity in optimal human diets and animal feed because of their unique nutritional composition. Currently, limited water is a major constraint in grain legume production. Root system architecture (RSA) is an important developmental and agronomic trait, which plays vital roles in plant adaptation and productivity under water-limited environments. A deep and proliferative root system helps extract sufficient water and nutrients under these stress conditions. The integrated genetics and genomics approach to dissect molecular processes from genome to phenome is key to achieve increased water capture and use efficiency through developing better root systems. Success in crop improvement under drought depends on discovery and utilization of genetic variations existing in the germplasm. In this review, we summarize current progress in the genetic diversity in major legume crops, quantitative trait loci (QTLs) associated with RSA, and the importance and applications of recent discoveries associated with the beneficial root traits towards better RSA for enhanced drought tolerance and yield.
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Affiliation(s)
- Heng Ye
- Division of Plant Sciences, University of Missouri, Columbia, MO, USA
| | - Manish Roorkiwal
- Center of Excellence in Genomics & Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India
| | - Babu Valliyodan
- Division of Plant Sciences, University of Missouri, Columbia, MO, USA
| | - Lijuan Zhou
- Division of Plant Sciences, University of Missouri, Columbia, MO, USA
| | - Pengyin Chen
- Division of Plant Sciences, University of Missouri-Fisher Delta Research Center, Portageville, MO, USA
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India
| | - Henry T Nguyen
- Division of Plant Sciences, University of Missouri, Columbia, MO, USA
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