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Wei Q, Yin Y, Tong Q, Gong Z, Shi Y. Multi-omics analysis of excessive nitrogen fertilizer application: Assessing environmental damage and solutions in potato farming. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 284:116916. [PMID: 39181078 DOI: 10.1016/j.ecoenv.2024.116916] [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: 03/04/2024] [Revised: 08/15/2024] [Accepted: 08/20/2024] [Indexed: 08/27/2024]
Abstract
Potatoes (Solanum tuberosum L.) are the third largest food crop globally and are pivotal for global food security. Widespread N fertilizer waste in potato cultivation has caused diverse environmental issues. This study employed microbial metagenomic sequencing to analyze the causes behind the declining N use efficiency (NUE) and escalating greenhouse gas emissions resulting from excessive N fertilizer application. Addressing N fertilizer inefficiency through breeding has emerged as a viable solution for mitigating overuse in potato cultivation. In this study, transcriptome and metabolome analyses were applied to identify N fertilizer-responsive genes. Metagenomic sequencing revealed that excessive N fertilizer application triggered alterations in the population dynamics of 11 major bacterial phyla, consequently affecting soil microbial functions, particularly N metabolism pathways and bacterial secretion systems. Notably, the enzyme levels associated with NO3- increased, and those associated with NO and N2O increased. Furthermore, excessive N fertilizer application enhanced soil virulence factors and increased potato susceptibility to diseases. Transcriptome and metabolome sequencing revealed significant impacts of excessive N fertilizer use on lipid and amino acid metabolism pathways. Weighted gene co‑expression network analysis (WGCNA) was adopted to identify two genes associated with N fertilizer response: PGSC0003DMG400021157 and PGSC0003DMG400009544.
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Affiliation(s)
- Qiaorong Wei
- College of Agriculture, Northeast Agricultural University, Harbin, China; National Key Laboratory of Smart Farm Technologies and Systems, Harbin, China; Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Ministry of Education, Harbin, China
| | - Yanbin Yin
- College of Agriculture, Northeast Agricultural University, Harbin, China; National Key Laboratory of Smart Farm Technologies and Systems, Harbin, China
| | - Qingsong Tong
- College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Zhenping Gong
- College of Agriculture, Northeast Agricultural University, Harbin, China.
| | - Ying Shi
- College of Agriculture, Northeast Agricultural University, Harbin, China; Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Ministry of Education, Harbin, China.
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Mishra S, Duarte GT, Horemans N, Ruytinx J, Gudkov D, Danchenko M. Complexity of responses to ionizing radiation in plants, and the impact on interacting biotic factors. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 924:171567. [PMID: 38460702 DOI: 10.1016/j.scitotenv.2024.171567] [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: 12/01/2023] [Revised: 02/20/2024] [Accepted: 03/06/2024] [Indexed: 03/11/2024]
Abstract
In nature, plants are simultaneously exposed to different abiotic (e.g., heat, drought, and salinity) and biotic (e.g., bacteria, fungi, and insects) stresses. Climate change and anthropogenic pressure are expected to intensify the frequency of stress factors. Although plants are well equipped with unique and common defense systems protecting against stressors, they may compromise their growth and development for survival in such challenging environments. Ionizing radiation is a peculiar stress factor capable of causing clustered damage. Radionuclides are both naturally present on the planet and produced by human activities. Natural and artificial radioactivity affects plants on molecular, biochemical, cellular, physiological, populational, and transgenerational levels. Moreover, the fitness of pests, pathogens, and symbionts is concomitantly challenged in radiologically contaminated areas. Plant responses to artificial acute ionizing radiation exposure and laboratory-simulated or field chronic exposure are often discordant. Acute or chronic ionizing radiation exposure may occasionally prime the defense system of plants to better tolerate the biotic stress or could often exhaust their metabolic reserves, making plants more susceptible to pests and pathogens. Currently, these alternatives are only marginally explored. Our review summarizes the available literature on the responses of host plants, biotic factors, and their interaction to ionizing radiation exposure. Such systematic analysis contributes to improved risk assessment in radiologically contaminated areas.
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Affiliation(s)
- Shubhi Mishra
- Institute of Plant Genetics and Biotechnology, Plant Science and Biodiversity Centre, Slovak Academy of Sciences, 950 07 Nitra, Slovakia
| | - Gustavo Turqueto Duarte
- Unit for Biosphere Impact Studies, Belgian Nuclear Research Centre SCK CEN, 2400 Mol, Belgium
| | - Nele Horemans
- Unit for Biosphere Impact Studies, Belgian Nuclear Research Centre SCK CEN, 2400 Mol, Belgium; Centre for Environmental Sciences, Hasselt University, 3590 Diepenbeek, Belgium
| | - Joske Ruytinx
- Department of Bio-engineering Sciences, Vrije Universiteit Brussel, 1050 Brussels, Belgium
| | - Dmitri Gudkov
- Institute of Hydrobiology, National Academy of Sciences of Ukraine, 04210 Kyiv, Ukraine
| | - Maksym Danchenko
- Institute of Plant Genetics and Biotechnology, Plant Science and Biodiversity Centre, Slovak Academy of Sciences, 950 07 Nitra, Slovakia.
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Liu X, Gao Y, Zhao X, Zhang X, Ben L, Li Z, Dong G, Zhou J, Huang J, Yao Y. Validation of Novel Reference Genes in Different Rice Plant Tissues through Mining RNA-Seq Datasets. PLANTS (BASEL, SWITZERLAND) 2023; 12:3946. [PMID: 38068583 PMCID: PMC10708173 DOI: 10.3390/plants12233946] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 11/20/2023] [Accepted: 11/22/2023] [Indexed: 09/12/2024]
Abstract
Reverse transcription quantitative real-time PCR (RT-qPCR) is arguably the most prevalent and accurate quantitative gene expression analysis. However, selection of reliable reference genes for RT-qPCR in rice (Oryza sativa) is still limited, especially for a specific tissue type or growth condition. In this study, we took the advantage of our RNA-seq datasets encompassing data from five rice varieties with diverse treatment conditions, identified 12 novel candidate reference genes, and conducted rigorous evaluations of their suitability across typical rice tissues. Comprehensive analysis of the leaves, shoots, and roots of two rice seedlings subjected to salt (30 mmol/L NaCl) and drought (air-dry) stresses have revealed that OsMED7, OsACT1, and OsOS-9 were the robust reference genes for leaf samples, while OsACT1, OsZOS3-23, and OsGDCP were recommended for shoots and OsMED7, OsOS-9, and OsGDCP were the most reliable reference genes for roots. Comparison results produced by different sets of reference genes revealed that all these newly recommended reference genes displayed less variation than previous commonly used references genes under the experiment conditions. Thus, selecting appropriate reference genes from RNA-seq datasets leads to identification of reference genes suitable for respective rice tissues under drought and salt stress. The findings offer valuable insights for refining the screening of candidate reference genes under diverse conditions through the RNA-seq database. This refinement serves to improve the accuracy of gene expression in rice under similar conditions.
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Affiliation(s)
- Xin Liu
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.L.); (Y.G.); (X.Z.); (L.B.); (Z.L.); (G.D.); (J.Z.)
| | - Yingbo Gao
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.L.); (Y.G.); (X.Z.); (L.B.); (Z.L.); (G.D.); (J.Z.)
| | - Xinyi Zhao
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.L.); (Y.G.); (X.Z.); (L.B.); (Z.L.); (G.D.); (J.Z.)
| | - Xiaoxiang Zhang
- Lixiahe Agricultural Research Institute of Jiangsu Province, Yangzhou 225007, China;
| | - Linli Ben
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.L.); (Y.G.); (X.Z.); (L.B.); (Z.L.); (G.D.); (J.Z.)
| | - Zongliang Li
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.L.); (Y.G.); (X.Z.); (L.B.); (Z.L.); (G.D.); (J.Z.)
| | - Guichun Dong
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.L.); (Y.G.); (X.Z.); (L.B.); (Z.L.); (G.D.); (J.Z.)
| | - Juan Zhou
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.L.); (Y.G.); (X.Z.); (L.B.); (Z.L.); (G.D.); (J.Z.)
| | - Jianye Huang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.L.); (Y.G.); (X.Z.); (L.B.); (Z.L.); (G.D.); (J.Z.)
| | - Youli Yao
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.L.); (Y.G.); (X.Z.); (L.B.); (Z.L.); (G.D.); (J.Z.)
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Cui J, Li J, Dai C, Li L. Transcriptome and Metabolome Analyses Revealed the Response Mechanism of Sugar Beet to Salt Stress of Different Durations. Int J Mol Sci 2022; 23:ijms23179599. [PMID: 36076993 PMCID: PMC9455719 DOI: 10.3390/ijms23179599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 08/17/2022] [Accepted: 08/22/2022] [Indexed: 11/16/2022] Open
Abstract
Salinity is one of the most serious threats to agriculture worldwide. Sugar beet is an important sugar-yielding crop and has a certain tolerance to salt; however, the genome-wide dynamic response to salt stress remains largely unknown in sugar beet. In the present study, physiological and transcriptome analyses of sugar beet leaves and roots were compared under salt stress at five time points. The results showed that different salt stresses influenced phenotypic characteristics, leaf relative water content and root activity in sugar beet. The contents of chlorophyll, malondialdehyde (MDA), the activities of peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT) were also affected by different salt stresses. Compared with control plants, there were 7391 and 8729 differentially expressed genes (DEGs) in leaves and roots under salt stress, respectively. A total of 41 hub genes related to salt stress were identified by weighted gene co-expression network analysis (WGCNA) from DEGs, and a transcriptional regulatory network based on these genes was constructed. The expression pattern of hub genes under salt stress was confirmed by qRT-PCR. In addition, the metabolite of sugar beet was compared under salt stress for 24 h. A total of 157 and 157 differentially accumulated metabolites (DAMs) were identified in leaves and roots, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis further indicated that DEGs and DAMs act on the starch and sucrose metabolism, alpha-linolenic acid metabolism, phenylpropanoid biosynthesis and plant hormone signal transduction pathway. In this study, RNA-seq, WGCNA analysis and untargeted metabolomics were combined to investigate the transcriptional and metabolic changes of sugar beet during salt stress. The results provided new insights into the molecular mechanism of sugar beet response to salt stress, and also provided candidate genes for sugar beet improvement.
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Affiliation(s)
- Jie Cui
- School of Medicine and Health, Harbin Institute of Technology, Harbin 150086, China
- Correspondence: ; Tel.: +86-0451-86622017
| | - Junliang Li
- College of Life and Environmental Science, Wenzhou University, Wenzhou 325035, China
- College of Life Science, Northeast Forestry University, Harbin 150040, China
| | - Cuihong Dai
- School of Medicine and Health, Harbin Institute of Technology, Harbin 150086, China
| | - Liping Li
- School of Medicine and Health, Harbin Institute of Technology, Harbin 150086, China
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Guo H, Pu X, Jia H, Zhou Y, Ye G, Yang Y, Na T, Wang J. Transcriptome analysis reveals multiple effects of nitrogen accumulation and metabolism in the roots, shoots, and leaves of potato (Solanum tuberosum L.). BMC PLANT BIOLOGY 2022; 22:282. [PMID: 35676629 PMCID: PMC9178895 DOI: 10.1186/s12870-022-03652-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 05/16/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Nitrogen (N) is a major element and fundamental constituent of grain yield. N fertilizer plays an essential role in the roots, shoots, and leaves of crop plants. Here, we obtained two N-sensitive potato cultivars. RESULTS The plants were cultivated in the pots using N-deficient and N-sufficient conditions. Crop height, leaf chlorophyll content, dry matter, and N-accumulation significantly decreased under N-deficient conditions. Furthermore, we performed a comprehensive analysis of the phenotype and transcriptome, GO terms, and KEGG pathways. We used WGCNA of co-expressed genes, and 116 differentially expressed hub genes involved in photosynthesis, nitrogen metabolism, and secondary metabolites to generate 23 modules. Among those modules, six NRT gene families, four pigment genes, two auxin-related genes, and two energy-related genes were selected for qRT-PCR validation. CONCLUSIONS Overall, our study demonstrates the co-expressed genes and potential pathways associated with N transport and accumulation in potato cultivars' roots, shoots, and leaves under N-deficient conditions. Therefore, this study provides new ideas to conduct further research on improving nitrogen use efficiency in potatoes.
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Affiliation(s)
- Heng Guo
- Qinghai University/Qinghai Academy of Agriculture and Forestry Sciences/Northwest potato Engineering Research Center of Ministry of Education/Key Laboratory of Qinghai-Tibetan Plateau Biotechnology of Ministry of Education, Xining, 810016 Qinghai China
| | - Xiuqin Pu
- Qinghai University/Qinghai Academy of Agriculture and Forestry Sciences/Northwest potato Engineering Research Center of Ministry of Education/Key Laboratory of Qinghai-Tibetan Plateau Biotechnology of Ministry of Education, Xining, 810016 Qinghai China
| | - Hao Jia
- Qinghai University/Qinghai Academy of Agriculture and Forestry Sciences/Northwest potato Engineering Research Center of Ministry of Education/Key Laboratory of Qinghai-Tibetan Plateau Biotechnology of Ministry of Education, Xining, 810016 Qinghai China
| | - Yun Zhou
- Qinghai University/Qinghai Academy of Agriculture and Forestry Sciences/Northwest potato Engineering Research Center of Ministry of Education/Key Laboratory of Qinghai-Tibetan Plateau Biotechnology of Ministry of Education, Xining, 810016 Qinghai China
| | - Guangji Ye
- Qinghai University/Qinghai Academy of Agriculture and Forestry Sciences/Northwest potato Engineering Research Center of Ministry of Education/Key Laboratory of Qinghai-Tibetan Plateau Biotechnology of Ministry of Education, Xining, 810016 Qinghai China
| | - Yongzhi Yang
- Qinghai University/Qinghai Academy of Agriculture and Forestry Sciences/Northwest potato Engineering Research Center of Ministry of Education/Key Laboratory of Qinghai-Tibetan Plateau Biotechnology of Ministry of Education, Xining, 810016 Qinghai China
| | - Tiancang Na
- Qinghai University/Qinghai Academy of Agriculture and Forestry Sciences/Northwest potato Engineering Research Center of Ministry of Education/Key Laboratory of Qinghai-Tibetan Plateau Biotechnology of Ministry of Education, Xining, 810016 Qinghai China
| | - Jian Wang
- Qinghai University/Qinghai Academy of Agriculture and Forestry Sciences/Northwest potato Engineering Research Center of Ministry of Education/Key Laboratory of Qinghai-Tibetan Plateau Biotechnology of Ministry of Education, Xining, 810016 Qinghai China
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Zhang X, Zhou J, Huang N, Mo L, Lv M, Gao Y, Chen C, Yin S, Ju J, Dong G, Zhou Y, Yang Z, Li A, Wang Y, Huang J, Yao Y. Transcriptomic and Co-Expression Network Profiling of Shoot Apical Meristem Reveal Contrasting Response to Nitrogen Rate between Indica and Japonica Rice Subspecies. Int J Mol Sci 2019; 20:E5922. [PMID: 31775351 PMCID: PMC6928681 DOI: 10.3390/ijms20235922] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Revised: 11/22/2019] [Accepted: 11/23/2019] [Indexed: 12/17/2022] Open
Abstract
Reducing nitrogen (N) input is a key measure to achieve a sustainable rice production in China, especially in Jiangsu Province. Tiller is the basis for achieving panicle number that plays as a major factor in the yield determination. In actual production, excessive N is often applied in order to produce enough tillers in the early stages. Understanding how N regulates tillering in rice plants is critical to generate an integrative management to reduce N use and reaching tiller number target. Aiming at this objective, we utilized RNA sequencing and weighted gene co-expression network analysis (WGCNA) to compare the transcriptomes surrounding the shoot apical meristem of indica (Yangdao6, YD6) and japonica (Nipponbare, NPB) rice subspecies. Our results showed that N rate influenced tiller number in a different pattern between the two varieties, with NPB being more sensitive to N enrichment, and YD6 being more tolerant to high N rate. Tiller number was positively related to N content in leaf, culm and root tissue, but negatively related to the soluble carbohydrate content, regardless of variety. Transcriptomic comparisons revealed that for YD6 when N rate enrichment from low (LN) to medium (MN), it caused 115 DEGs (LN vs. MN), from MN to high level (HN) triggered 162 DEGs (MN vs. HN), but direct comparison of low with high N rate showed a 511 DEGs (LN vs. HN). These numbers of DEG in NPB were 87 (LN vs. MN), 40 (MN vs. HN), and 148 (LN vs. HN). These differences indicate that continual N enrichment led to a bumpy change at the transcription level. For the reported sixty-five genes which affect tillering, thirty-six showed decent expression in SAM at tiller starting phase, among them only nineteen being significantly influenced by N level, and two genes showed significant interaction between N rate and variety. Gene ontology analysis revealed that the majority of the common DEGs are involved in general stress responses, stimulus responses, and hormonal signaling process. WGCNA network identified twenty-two co-expressing gene modules and ten candidate hubgenes for each module. Several genes associated with tillering and N rate fall on the related modules. These indicate that there are more genes participating in tillering regulation in response to N enrichment.
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Affiliation(s)
- Xiaoxiang Zhang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
- Lixiahe Agricultural Research Institute of Jiangsu Province, Yangzhou 225007, China; (N.H.); (A.L.)
| | - Juan Zhou
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Niansheng Huang
- Lixiahe Agricultural Research Institute of Jiangsu Province, Yangzhou 225007, China; (N.H.); (A.L.)
| | - Lanjing Mo
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Minjia Lv
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Yingbo Gao
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Chen Chen
- Zhenjiang Agricultural Research Institute of Jiangsu Province, Jurong 212400, China;
| | - Shuangyi Yin
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Jing Ju
- College of Environmental Science and Engineering, Yangzhou University, Yangzhou 225000, China;
| | - Guichun Dong
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Yong Zhou
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Zefeng Yang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Aihong Li
- Lixiahe Agricultural Research Institute of Jiangsu Province, Yangzhou 225007, China; (N.H.); (A.L.)
| | - Yulong Wang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Jianye Huang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
| | - Youli Yao
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China; (X.Z.); (J.Z.); (L.M.); (M.L.); (Y.G.); (S.Y.); (G.D.); (Y.Z.); (Z.Y.); (Y.W.)
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