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Zhong Y, Chen Y, Pan M, Li X, Hebelstrup K, Cai J, Zhou Q, Dai T, Cao W, Jiang D. Transport and spatio-temporal conversion of sugar facilitate the formation of spatial gradients of starch in wheat caryopses. Commun Biol 2024; 7:928. [PMID: 39090206 PMCID: PMC11294588 DOI: 10.1038/s42003-024-06625-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 07/23/2024] [Indexed: 08/04/2024] Open
Abstract
Wheat grain starch content displays large variations within different pearling fractions, which affecting the processing quality of corresponding flour, while the underlying mechanism on starch gradient formation is unclear. Here, we show that wheat caryopses acquire sugar through the transfer of cells (TCs), inner endosperm (IE), outer endosperm (OE), and finally aleurone (AL) via micro positron emission tomography-computed tomography (PET-CT). To obtain integrated information on spatial transcript distributions, developing caryopses are laser microdissected into AL, OE, IE, and TC. Most genes encoding carbohydrate transporters are upregulated or specifically expressed, and sugar metabolites are more highly enriched in the TC group than in the AL group, in line with the PET-CT results. Genes encoding enzymes in sucrose metabolism, such as sucrose synthase, beta-fructofuranosidase, glucose-1-phosphate adenylyltransferase show significantly lower expression in AL than in OE and IE, indicating that substrate supply is crucial for the formation of starch gradients. Furthermore, the low expressions of gene encoding starch synthase contribute to low starch content in AL. Our results imply that transcriptional regulation represents an important means of impacting starch distribution in wheat grains and suggests breeding targets for enhancing specially pearled wheat with higher quality.
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Affiliation(s)
- Yingxin Zhong
- National Technique Innovation Center for Regional Wheat Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, PR China
| | - Yuhua Chen
- National Technique Innovation Center for Regional Wheat Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, PR China
| | - Mingsheng Pan
- National Technique Innovation Center for Regional Wheat Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, PR China
| | - Xiangnan Li
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Kim Hebelstrup
- Department of Agroecology, Aarhus University, Slagelse, Denmark
| | - Jian Cai
- National Technique Innovation Center for Regional Wheat Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, PR China
| | - Qin Zhou
- National Technique Innovation Center for Regional Wheat Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, PR China
| | - Tingbo Dai
- National Technique Innovation Center for Regional Wheat Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, PR China
| | - Weixing Cao
- National Technique Innovation Center for Regional Wheat Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, PR China
| | - Dong Jiang
- National Technique Innovation Center for Regional Wheat Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, PR China.
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Zhong Y, Chen Y, Pan M, Wang H, Sun J, Chen Y, Cai J, Zhou Q, Wang X, Jiang D. Insights into the Functional Components in Wheat Grain: Spatial Pattern, Underlying Mechanism and Cultivation Regulation. PLANTS (BASEL, SWITZERLAND) 2023; 12:plants12112192. [PMID: 37299171 DOI: 10.3390/plants12112192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/17/2023] [Accepted: 05/29/2023] [Indexed: 06/12/2023]
Abstract
Wheat is a staple crop; its production must achieve both high yield and good quality due to worldwide demands for food security and better quality of life. It has been found that the grain qualities vary greatly within the different layers of wheat kernels. In this paper, the spatial distributions of protein and its components, starch, dietary fiber, and microelements are summarized in detail. The underlying mechanisms regarding the formation of protein and starch, as well as spatial distribution, are discussed from the views of substrate supply and the protein and starch synthesis capacity. The regulating effects of cultivation practices on gradients in composition are identified. Finally, breakthrough solutions for exploring the underlying mechanisms of the spatial gradients of functional components are presented. This paper will provide research perspectives for producing wheat that is both high in yield and of good quality.
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Affiliation(s)
- Yingxin Zhong
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Yuhua Chen
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Mingsheng Pan
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Hengtong Wang
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Jiayu Sun
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Yang Chen
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Jian Cai
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Qin Zhou
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Xiao Wang
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Dong Jiang
- College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
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3
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Tao H, Xu S, Tian Y, Li Z, Ge Y, Zhang J, Wang Y, Zhou G, Deng X, Zhang Z, Ding Y, Jiang D, Guo Q, Jin S. Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives. PLANT COMMUNICATIONS 2022; 3:100344. [PMID: 35655429 PMCID: PMC9700174 DOI: 10.1016/j.xplc.2022.100344] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/08/2022] [Accepted: 05/27/2022] [Indexed: 06/01/2023]
Abstract
Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and precise cultivation. High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits. Proximal and remote sensing (PRS) techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis. Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications. This progress covers most aspects of PRS application in PP, including patterns of global spatial distribution and temporal dynamics, specific PRS technologies, phenotypic research fields, working environments, species, and traits. Subsequently, we demonstrate how to link PRS to multi-omics studies, including how to achieve multi-dimensional PRS data acquisition and processing, how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance, and how to link PP to multi-omics association analysis. Finally, we identify three future perspectives for PRS-based PP: (1) strengthening the spatial and temporal consistency of PRS data, (2) exploring novel phenotypic traits, and (3) facilitating multi-omics communication.
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Affiliation(s)
- Haiyu Tao
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China
| | - Shan Xu
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China
| | - Yongchao Tian
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China
| | - Zhaofeng Li
- The Key Laboratory of Oasis Eco-agriculture, Xinjiang Production and Construction Corps, Agriculture College, Shihezi University, Shihezi 832003, China
| | - Yan Ge
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China
| | - Jiaoping Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Nanjing Agricultural University, Nanjing 210095, China
| | - Yu Wang
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China
| | - Guodong Zhou
- Sanya Research Institute of Nanjing Agriculture University, Sanya 572024, China
| | - Xiong Deng
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
| | - Ze Zhang
- The Key Laboratory of Oasis Eco-agriculture, Xinjiang Production and Construction Corps, Agriculture College, Shihezi University, Shihezi 832003, China
| | - Yanfeng Ding
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China; Hainan Yazhou Bay Seed Laboratory, Sanya 572025, China; Sanya Research Institute of Nanjing Agriculture University, Sanya 572024, China
| | - Dong Jiang
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China; Hainan Yazhou Bay Seed Laboratory, Sanya 572025, China; Sanya Research Institute of Nanjing Agriculture University, Sanya 572024, China
| | - Qinghua Guo
- Institute of Ecology, College of Urban and Environmental Science, Peking University, Beijing 100871, China
| | - Shichao Jin
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, National Engineering and Technology Center for Information Agriculture, Collaborative Innovation Centre for Modern Crop Production co-sponsored by Province and Ministry, Nanjing Agricultural University, Address: No. 1 Weigang, Xuanwu District, Nanjing 210095, China; Hainan Yazhou Bay Seed Laboratory, Sanya 572025, China; Sanya Research Institute of Nanjing Agriculture University, Sanya 572024, China; Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China.
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D'Ascenzo N, Xie Q, Antonecchia E, Ciardiello M, Pagnani G, Pisante M. Kinetically Consistent Data Assimilation for Plant PET Sparse Time Activity Curve Signals. FRONTIERS IN PLANT SCIENCE 2022; 13:882382. [PMID: 35941942 PMCID: PMC9356293 DOI: 10.3389/fpls.2022.882382] [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: 03/04/2022] [Accepted: 06/10/2022] [Indexed: 06/15/2023]
Abstract
Time activity curve (TAC) signal processing in plant positron emission tomography (PET) is a frontier nuclear science technique to bring out the quantitative fluid dynamic (FD) flow parameters of the plant vascular system and generate knowledge on crops and their sustainable management, facing the accelerating global climate change. The sparse space-time sampling of the TAC signal impairs the extraction of the FD variables, which can be determined only as averaged values with existing techniques. A data-driven approach based on a reliable FD model has never been formulated. A novel sparse data assimilation digital signal processing method is proposed, with the unique capability of a direct computation of the dynamic evolution of noise correlations between estimated and measured variables, by taking into explicit account the numerical diffusion due to the sparse sampling. The sequential time-stepping procedure estimates the spatial profile of the velocity, the diffusion coefficient and the compartmental exchange rates along the plant stem from the TAC signals. To illustrate the performance of the method, we report an example of the measurement of transport mechanisms in zucchini sprouts.
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Affiliation(s)
- Nicola D'Ascenzo
- School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo, Istituto di Ricovero e Cura a Carattere Scientifico, Pozzilli, Italy
| | - Qingguo Xie
- School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo, Istituto di Ricovero e Cura a Carattere Scientifico, Pozzilli, Italy
- Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Emanuele Antonecchia
- School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo, Istituto di Ricovero e Cura a Carattere Scientifico, Pozzilli, Italy
| | - Mariachiara Ciardiello
- Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo, Istituto di Ricovero e Cura a Carattere Scientifico, Pozzilli, Italy
| | - Giancarlo Pagnani
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy
| | - Michele Pisante
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy
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Antonecchia E, Bäcker M, Cafolla D, Ciardiello M, Kühl C, Pagnani G, Wang J, Wang S, Zhou F, D'Ascenzo N, Gialanella L, Pisante M, Rose G, Xie Q. Design Study of a Novel Positron Emission Tomography System for Plant Imaging. FRONTIERS IN PLANT SCIENCE 2022; 12:736221. [PMID: 35116047 PMCID: PMC8805640 DOI: 10.3389/fpls.2021.736221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 12/06/2021] [Indexed: 06/14/2023]
Abstract
Positron Emission Tomography is a non-disruptive and high-sensitive digital imaging technique which allows to measure in-vivo and non invasively the changes of metabolic and transport mechanisms in plants. When it comes to the early assessment of stress-induced alterations of plant functions, plant PET has the potential of a major breakthrough. The development of dedicated plant PET systems faces a series of technological and experimental difficulties, which make conventional clinical and preclinical PET systems not fully suitable to agronomy. First, the functional and metabolic mechanisms of plants depend on environmental conditions, which can be controlled during the experiment if the scanner is transported into the growing chamber. Second, plants need to be imaged vertically, thus requiring a proper Field Of View. Third, the transverse Field of View needs to adapt to the different plant shapes, according to the species and the experimental protocols. In this paper, we perform a simulation study, proposing a novel design of dedicated plant PET scanners specifically conceived to address these agronomic issues. We estimate their expected sensitivity, count rate performance and spatial resolution, and we identify these specific features, which need to be investigated when realizing a plant PET scanner. Finally, we propose a novel approach to the measurement and verification of the performance of plant PET systems, including the design of dedicated plant phantoms, in order to provide a standard evaluation procedure for this emerging digital imaging agronomic technology.
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Affiliation(s)
- Emanuele Antonecchia
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China
- Istituto Neurologico Mediterraneo, NEUROMED I.R.C.C.S, Pozzilli, Italy
| | - Markus Bäcker
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany
| | - Daniele Cafolla
- Istituto Neurologico Mediterraneo, NEUROMED I.R.C.C.S, Pozzilli, Italy
| | | | - Charlotte Kühl
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany
| | - Giancarlo Pagnani
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy
| | - Jiale Wang
- School of Information and Communication Engineering, University of Electronics Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute of University of Science and Technology of China, Quzhou, China
| | - Shuai Wang
- School of Information and Communication Engineering, University of Electronics Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute of University of Science and Technology of China, Quzhou, China
| | - Feng Zhou
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China
| | - Nicola D'Ascenzo
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China
- Istituto Neurologico Mediterraneo, NEUROMED I.R.C.C.S, Pozzilli, Italy
| | - Lucio Gialanella
- Department of Mathematics and Physics, University of Campania L. Vanvitelli, Caserta, Italy
| | - Michele Pisante
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy
| | - Georg Rose
- Institute for Medical Engineering and Research Campus STIMULATE, University of Magdeburg, Magdeburg, Germany
| | - Qingguo Xie
- Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China
- Istituto Neurologico Mediterraneo, NEUROMED I.R.C.C.S, Pozzilli, Italy
- Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
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Schmidt MP, Mamet SD, Ferrieri RA, Peak D, Siciliano SD. From the Outside in: An Overview of Positron Imaging of Plant and Soil Processes. Mol Imaging 2020; 19:1536012120966405. [PMID: 33119419 PMCID: PMC7605056 DOI: 10.1177/1536012120966405] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Positron-emitting nuclides have long been used as imaging agents in medical science to spatially trace processes non-invasively, allowing for real-time molecular imaging using low tracer concentrations. This ability to non-destructively visualize processes in real time also makes positron imaging uniquely suitable for probing various processes in plants and porous environmental media, such as soils and sediments. Here, we provide an overview of historical and current applications of positron imaging in environmental research. We highlight plant physiological research, where positron imaging has been used extensively to image dynamics of macronutrients, signalling molecules, trace elements, and contaminant metals under various conditions and perturbations. We describe how positron imaging is used in porous soils and sediments to visualize transport, flow, and microbial metabolic processes. We also address the interface between positron imaging and other imaging approaches, and present accompanying chemical analysis of labelled compounds for reviewed topics, highlighting the bridge between positron imaging and complementary techniques across scales. Finally, we discuss possible future applications of positron imaging and its potential as a nexus of interdisciplinary biogeochemical research.
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Affiliation(s)
- Michael P Schmidt
- Department of Soil Science, College of Agriculture and Bioresources, 7235University of Saskatchewan, Saskatoon, Canada
| | - Steven D Mamet
- Department of Soil Science, College of Agriculture and Bioresources, 7235University of Saskatchewan, Saskatoon, Canada
| | - Richard A Ferrieri
- Interdisciplinary Plant Group, Division of Plant Sciences, Department of Chemistry, Missouri Research Reactor Center, 14716University of Missouri, Columbia, MO, USA
| | - Derek Peak
- Department of Soil Science, College of Agriculture and Bioresources, 7235University of Saskatchewan, Saskatoon, Canada
| | - Steven D Siciliano
- Department of Soil Science, College of Agriculture and Bioresources, 7235University of Saskatchewan, Saskatoon, Canada
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