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Long L, Lv L, Qiu J, Sun D, Wei S, Wan X, Gao C. Comprehensive evaluation of fruit quality for premium Wangmo Castanea mollissima plants. PLoS One 2023; 18:e0295691. [PMID: 38085713 PMCID: PMC10715654 DOI: 10.1371/journal.pone.0295691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 11/23/2023] [Indexed: 12/18/2023] Open
Abstract
In this study, the fruit phenotype and quality of 32 superior Wangmo Castanea mollissima plants (designated GM1 to GM32) were examined to identify the trait characteristics of different cluster groups and germplasms with excellent comprehensive performance. The goal was to provide a theoretical basis and research foundation for collecting high-quality germplasm resources and breeding superior cultivars of Wangmo C. mollissima. Ten fruit phenotypic traits and 13 quality traits were measured and analyzed in these 32 superior Wangmo C. mollissima plants. Cluster analysis and principal component analysis (PCA) were used to perform a comprehensive evaluation. Extremely significant positive correlations (P<0.01) were observed for 15 pairs of fruit phenotypic and quality traits, and significant positive correlations (P<0.05) were observed for 16 pairs of traits. Highly significant negative correlations (P<0.01) were observed for 4 pairs of fruit phenotypic and quality traits, and significant negative correlations (P<0.05) were observed for 15 pairs. The plants were divided into three groups by cluster analysis: the first group had large fruits and good fruit quality, the second group had small fruits and poor fruit quality, and the third group had medium-sized fruits with a high starch content. Four principal components were extracted from the 23 traits by PCA, contributing 76.23% of the variance. The ten plants with the highest comprehensive quality were GM32, GM31, GM29, GM1, GM8, GM17, GM10, GM30, GM3 and GM28. The results of this study provide a reference for the development and utilization of Wangmo C. mollissima germplasm resources.
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Affiliation(s)
- Li Long
- Institute for Forest Resources and Environment of Guizhou, Key Laboratory of Forest Cultivation in Plateau Mountain of Guizhou Province, College of Forestry, Guizhou University, Guiyang, 550025, China
| | - Lingling Lv
- Institute for Forest Resources and Environment of Guizhou, Key Laboratory of Forest Cultivation in Plateau Mountain of Guizhou Province, College of Forestry, Guizhou University, Guiyang, 550025, China
| | - Jie Qiu
- Institute for Forest Resources and Environment of Guizhou, Key Laboratory of Forest Cultivation in Plateau Mountain of Guizhou Province, College of Forestry, Guizhou University, Guiyang, 550025, China
| | - Dongchan Sun
- Institute for Forest Resources and Environment of Guizhou, Key Laboratory of Forest Cultivation in Plateau Mountain of Guizhou Province, College of Forestry, Guizhou University, Guiyang, 550025, China
| | - Shangfeng Wei
- Institute for Forest Resources and Environment of Guizhou, Key Laboratory of Forest Cultivation in Plateau Mountain of Guizhou Province, College of Forestry, Guizhou University, Guiyang, 550025, China
| | - Xianqin Wan
- Institute for Forest Resources and Environment of Guizhou, Key Laboratory of Forest Cultivation in Plateau Mountain of Guizhou Province, College of Forestry, Guizhou University, Guiyang, 550025, China
| | - Chao Gao
- Institute for Forest Resources and Environment of Guizhou, Key Laboratory of Forest Cultivation in Plateau Mountain of Guizhou Province, College of Forestry, Guizhou University, Guiyang, 550025, China
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Chen W, Yan J, Zheng S, Suo J, Lou H, Song L, Wu J. Integrated Metabolomics, Transcriptome and Functional Analysis Reveal Key Genes Are Involved in Tree Age-Induced Amino Acid Accumulation in Torreya grandis Nuts. Int J Mol Sci 2023; 24:17025. [PMID: 38069348 PMCID: PMC10706915 DOI: 10.3390/ijms242317025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 11/14/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
Torreya grandis is native Chinese tree species of economic significance, renowned for its long lifespan and the rich nutritional value of its nuts. In this study, we analyzed the morphological characteristics, metabolites, associated gene expressions, and regulatory mechanism in nuts from young (10 years old) and old (1000 years old) T. grandis trees. We observed that the length, width, and weight of nuts from older trees were considerably greater than those from younger trees. Metabolomic analysis revealed that the concentrations of 18 amino acids and derivatives (including histidine and serine) in nuts from older trees were markedly higher than those in nuts from younger trees. Transcriptome and metabolomic correlation analysis identified 16 genes, including TgPK (pyruvate kinase), TgGAPDH (glyceraldehyde 3-phosphate dehydrogenase), and others, which exhibit higher expression levels in older trees compared to younger trees, as confirmed by qRT-PCR. These genes are associated with the biosynthesis of histidine, glutamic acid, tryptophan, and serine. Transient expression of TgPK in tobacco led to increased pyruvate kinase activity and amino acid content (histidine, tryptophan, and serine). Additionally, dual-luciferase assays and yeast one-hybrid results demonstrated that TgWRKY21 positively regulates TgPK expression by directly binding to the TgPK promoter. These findings not only demonstrate the nutritional differences between nuts from young and old trees but also offer fresh insights into the development of nutritional sources and functional components based on nuts from old trees, enriching our understanding of the potential benefits of utilizing nuts from older trees.
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Affiliation(s)
| | | | | | | | | | - Lili Song
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China; (W.C.); (J.Y.); (H.L.)
| | - Jiasheng Wu
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China; (W.C.); (J.Y.); (H.L.)
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Zhou P, Jiang Y, Adeel M, Shakoor N, Zhao W, Liu Y, Li Y, Li M, Azeem I, Rui Y, Tan Z, White JC, Guo Z, Lynch I, Zhang P. Nickel Oxide Nanoparticles Improve Soybean Yield and Enhance Nitrogen Assimilation. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:7547-7558. [PMID: 37134233 DOI: 10.1021/acs.est.3c00959] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Nickel (Ni) is a trace element beneficial for plant growth and development and could improve crop yield by stimulating urea decomposition and nitrogen-fixing enzyme activity. A full life cycle study was conducted to compare the long-term effects of soil-applied NiO nanoparticles (n-NiO), NiO bulk (b-NiO), and NiSO4 at 10-200 mg kg-1 on plant growth and nutritional content of soybean. n-NiO at 50 mg kg-1 significantly promoted the seed yield by 39%. Only 50 mg kg-1 n-NiO promoted total fatty acid content and starch content by 28 and 19%, respectively. The increased yield and nutrition could be attributed to the regulatory effects of n-NiO, including photosynthesis, mineral homeostasis, phytohormone, and nitrogen metabolism. Furthermore, n-NiO maintained a Ni2+ supply for more extended periods than NiSO4, reducing potential phytotoxicity concerns. Single-particle inductively coupled plasma mass spectrometry (sp-ICP-MS) for the first time confirmed that the majority of the Ni in seeds is in ionic form, with only 28-34% as n-NiO. These findings deepen our understanding of the potential of nanoscale and non-nanoscale Ni to accumulate and translocate in soybean, as well as the long-term fate of these materials in agricultural soils as a strategy for nanoenabled agriculture.
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Affiliation(s)
- Pingfan Zhou
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
- Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Yaqi Jiang
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Muhammad Adeel
- BNU-HKUST Laboratory of Green Innovation, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai 519087, China
| | - Noman Shakoor
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Weichen Zhao
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Yanwanjing Liu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yuanbo Li
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Mingshu Li
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Imran Azeem
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Yukui Rui
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Zhiqiang Tan
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Jason C White
- The Connecticut Agricultural Experiment Station, New Haven, Connecticut 06511, United States
| | - Zhiling Guo
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K
| | - Peng Zhang
- Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K
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Bai X, Zhang S, Wang W, Chen Y, Zhao Y, Shi F, Zhu C. Genetic Relationships of 118 Castanea Specific Germplasms and Construction of Their Molecular ID Based on Morphological Characteristics and SSR Markers. PLANTS (BASEL, SWITZERLAND) 2023; 12:1438. [PMID: 37050064 PMCID: PMC10096943 DOI: 10.3390/plants12071438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/13/2023] [Accepted: 03/17/2023] [Indexed: 06/19/2023]
Abstract
To understand the genetic relationships of Castanea species, 16 phenotypic traits were measured, simple sequence repeat (SSR) markers were analyzed, and molecular identity cards (IDs) were constructed for 118 Castanea materials using fluorescent capillary electrophoresis. The coefficient of variation values of the 16 morphological traits of the test materials ranged from 11.11% to 60.38%. A total of 58 alleles were detected using six pairs of SSR core primers, with an average number of 9.7 alleles per locus. The average number of valid alleles per locus was 3.9419 and the proportion of valid alleles was 40.78%. A total of 105 genotypes were detected, and the number of genotypic species that could be amplified per primer pair ranged from 8 to 26. The mean value of the observed heterozygosity was 0.4986. The variation in the He, H, and PIC values was similar; the size of I value was approximately 2.21 times larger, and its mean number of variations was 0.7390, 0.7359, 0.6985, and 1.6015, respectively. The classification of 118 Castanea species was performed using three analytical methods: structure analysis, neighbor-joining (NJ) cluster analysis, and principal coordinate analysis (PCoA), and the results of the three methods were in high agreement. Six pairs of SSR core primers with high polymorphism and strong discriminatory properties were used to identify 118 Castanea plants, and a unique molecular ID card was constructed for each material. These results provide insight into the genetic diversity and population structure of Castanea plants and a theoretical basis for improving the phenomenon of mixed varieties and substandard plants in the Castanea plant market.
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Affiliation(s)
- Xiaoqian Bai
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences (Nanjing Botanical Garden Mem. Sun Yat-Sen), Nanjing 210014, China
| | - Shijie Zhang
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences (Nanjing Botanical Garden Mem. Sun Yat-Sen), Nanjing 210014, China
| | - Wu Wang
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences (Nanjing Botanical Garden Mem. Sun Yat-Sen), Nanjing 210014, China
| | - Yu Chen
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences (Nanjing Botanical Garden Mem. Sun Yat-Sen), Nanjing 210014, China
| | - Yuqiang Zhao
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences (Nanjing Botanical Garden Mem. Sun Yat-Sen), Nanjing 210014, China
| | - Fenghou Shi
- College of Forestry, Nanjing Forestry University, Nanjing 210037, China
| | - Cancan Zhu
- Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences (Nanjing Botanical Garden Mem. Sun Yat-Sen), Nanjing 210014, China
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Jiang Y, Zhou P, Ma T, Adeel M, Shakoor N, Li Y, Li M, Guo M, Rui Y. Effects of two Mn-based nanomaterials on soybean antioxidant system and mineral element homeostasis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:18880-18889. [PMID: 36219299 DOI: 10.1007/s11356-022-23559-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 10/06/2022] [Indexed: 05/22/2023]
Abstract
Since less attention has been paid to the physiological effects of manganese-based nanomaterials (Mn-based NMs) on plants, it is necessary to explore the application of Mn-based NMs in improving crop yield and the concentration range of Mn-based NMs that produce toxicity. The results showed that soil application of 100 mg/kg manganese oxide (MnO2) and manganese tetroxide (Mn3O4) NMs could increase the shoot height of soybean by 51.8% and 31.8%, respectively, compared with the control. In addition, 100 mg/kg MnO2 NMs increased catalase (CAT) activity in roots by 62.2%, and 50 mg/kg Mn3O4 NMs increased CAT activity in roots by 200%, thereby increasing the stress resistance of soybean. However, at the highest concentration of 500 mg/kg, Mn-based NMs increased the Mn content in soybean extremely so that the absorption of mineral elements such as potassium, phosphorus, and calcium in the root was inhibited. This research lays the foundation for the safe application of Mn-based NMs in agriculture, benefiting the development of nanotechnology and agriculture globally.
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Affiliation(s)
- Yaqi Jiang
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Pingfan Zhou
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Tengtao Ma
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Muhammad Adeel
- BNU-HKUST Laboratory of Green Innovation, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai, 519087, China
| | - Noman Shakoor
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Yuanbo Li
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Mingshu Li
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Manlin Guo
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Yukui Rui
- Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China.
- China Agricultural University Professor's Workstation of Yuhuangmiao Town, Shanghe County, Jinan, Shandong, China.
- China Agricultural University Professor's Workstation of Sunji Town, Shanghe County, Jinan, Shandong, China.
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Yu L, Hui C, Huang R, Wang D, Fei C, Guo C, Zhang J. Genome-wide identification, evolution and transcriptome analysis of GRAS gene family in Chinese chestnut ( Castanea mollissima). Front Genet 2023; 13:1080759. [PMID: 36685835 PMCID: PMC9845266 DOI: 10.3389/fgene.2022.1080759] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 12/06/2022] [Indexed: 01/05/2023] Open
Abstract
GRAS transcription factors play an important role in regulating various biological processes in plant growth and development. However, their characterization and potential function are still vague in Chinese chestnut (Castanea mollissima), an important nut with rich nutrition and high economic value. In this study, 48 CmGRAS genes were identified in Chinese chestnut genome and phylogenetic analysis divided CmGRAS genes into nine subfamilies, and each of them has distinct conserved structure domain and features. Genomic organization revealed that CmGRAS tend to have a representative GRAS domain and fewer introns. Tandem duplication had the greatest contribution for the CmGRAS expansion based on the comparative genome analysis, and CmGRAS genes experienced strong purifying selection pressure based on the Ka/Ks. Gene expression analysis revealed some CmGRAS members with potential functions in bud development and ovule fertility. CmGRAS genes with more homologous relationships with reference species had more cis-acting elements and higher expression levels. Notably, the lack of DELLA domain in members of the DELLA subfamily may cause de functionalization, and the differences between the three-dimensional structures of them were exhibited. This comprehensive study provides theoretical and practical basis for future research on the evolution and function of GRAS gene family.
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Affiliation(s)
- Liyang Yu
- Engineering Research Center of Chestnut Industry Technology, Ministry of Education, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, China,Hebei Collaborative Innovation Center of Chestnut Industry, Qinhuangdao, Hebei, China
| | - Cai Hui
- The Office of Scientific Research, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, China
| | - Ruimin Huang
- Engineering Research Center of Chestnut Industry Technology, Ministry of Education, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, China,Hebei Collaborative Innovation Center of Chestnut Industry, Qinhuangdao, Hebei, China
| | - Dongsheng Wang
- Engineering Research Center of Chestnut Industry Technology, Ministry of Education, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, China,Hebei Collaborative Innovation Center of Chestnut Industry, Qinhuangdao, Hebei, China
| | - Cao Fei
- Hebei Collaborative Innovation Center of Chestnut Industry, Qinhuangdao, Hebei, China,Hebei Key Laboratory of Horticultural Germplasm Excavation and Innovative Utilization, Qinhuangdao, Hebei, China
| | - Chunlei Guo
- Engineering Research Center of Chestnut Industry Technology, Ministry of Education, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, China,Hebei Collaborative Innovation Center of Chestnut Industry, Qinhuangdao, Hebei, China
| | - Jingzheng Zhang
- Engineering Research Center of Chestnut Industry Technology, Ministry of Education, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, China,Hebei Collaborative Innovation Center of Chestnut Industry, Qinhuangdao, Hebei, China,Hebei Key Laboratory of Horticultural Germplasm Excavation and Innovative Utilization, Qinhuangdao, Hebei, China,*Correspondence: Jingzheng Zhang,
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Phytochemical and Nutritional Profile Composition in Fruits of Different Sweet Chestnut (Castanea sativa Mill.) Cultivars Grown in Romania. SEPARATIONS 2022. [DOI: 10.3390/separations9030066] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Chestnut (Castanea sativa Mill.), a valuable fruit crop, is cultivated in small areas in Romania, mostly in the west, where the moderate continental climate has a slight Mediterranean influence. This work aims to investigate the bioactive characteristics (total polyphenols, total flavonoids and antioxidant activity), individual polyphenolic composition, phytochemical and nutritional HRMS screening profiles, sugar and mineral composition of six sweet chestnut cultivars, namely ‘Marsol’, ‘Maraval’, ‘Bournette’, ‘Précoce Migoule’ and ‘Marissard’ grown at Fruit Growing Research—Extension Station (SCDP) Vâlcea, in Northern Oltenia, Romania. Fruit samples were collected in two consecutive years, in order to study the impact of genetic variability between cultivars and the influence of the different climatic conditions corresponding to different cultivation years. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) allow the discrimination between the sweet chestnut fruits harvested in different years and different sweet chestnut cultivars. Analytical investigations revealed that sweet chestnut cultivars grown in Romania show similar bioactive, phytochemical and nutritional composition to cultivars grown in the large European chestnut-producing countries, indicating the high adaptation potential of the chestnut in the temperate continental zone with small Mediterranean influences characteristic of the southwestern area of Romania.
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