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Castro-Camba R, Neves M, Correia S, Canhoto J, Vielba JM, Sánchez C. Ethylene Action Inhibition Improves Adventitious Root Induction in Adult Chestnut Tissues. PLANTS (BASEL, SWITZERLAND) 2024; 13:738. [PMID: 38475584 DOI: 10.3390/plants13050738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 03/02/2024] [Accepted: 03/04/2024] [Indexed: 03/14/2024]
Abstract
Phase change refers to the process of maturation and transition from the juvenile to the adult stage. In response to this shift, certain species like chestnut lose the ability to form adventitious roots, thereby hindering the successful micropropagation of adult plants. While auxin is the main hormone involved in adventitious root formation, other hormones, such as ethylene, are also thought to play a role in its induction and development. In this study, experiments were carried out to determine the effects of ethylene on the induction and growth of adventitious roots. The analysis was performed in two types of chestnut microshoots derived from the same tree, a juvenile-like line with a high rooting ability derived from basal shoots (P2BS) and a line derived from crown branches (P2CR) with low rooting responses. By means of the application of compounds to modify ethylene content or inhibit its signalling, the potential involvement of this hormone in the induction of adventitious roots was analysed. Our results show that ethylene can modify the rooting competence of mature shoots, while the response in juvenile material was barely affected. To further characterise the molecular reasons underlying this maturation-derived shift in behaviour, specific gene expression analyses were developed. The findings suggest that several mechanisms, including ethylene signalling, auxin transport and epigenetic modifications, relate to the modulation of the rooting ability of mature chestnut microshoots and their recalcitrant behaviour.
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Affiliation(s)
- Ricardo Castro-Camba
- Department of Plant Production, Misión Biológica de Galicia, CSIC, Avda de Vigo s/n, 15705 Santiago de Compostela, Spain
| | - Mariana Neves
- Centre for Functional Ecology, TERRA Associate Laboratory, Department of Life Sciences, University of Coimbra, Calçada Martim de Freitas, 3000-456 Coimbra, Portugal
| | - Sandra Correia
- Centre for Functional Ecology, TERRA Associate Laboratory, Department of Life Sciences, University of Coimbra, Calçada Martim de Freitas, 3000-456 Coimbra, Portugal
- InnovPlantProtect CoLab, Estrada de Gil Vaz, 7350-478 Elvas, Portugal
| | - Jorge Canhoto
- Centre for Functional Ecology, TERRA Associate Laboratory, Department of Life Sciences, University of Coimbra, Calçada Martim de Freitas, 3000-456 Coimbra, Portugal
| | - Jesús M Vielba
- Department of Plant Production, Misión Biológica de Galicia, CSIC, Avda de Vigo s/n, 15705 Santiago de Compostela, Spain
| | - Conchi Sánchez
- Department of Plant Production, Misión Biológica de Galicia, CSIC, Avda de Vigo s/n, 15705 Santiago de Compostela, Spain
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Türkoğlu A, Haliloğlu K, Demirel F, Aydin M, Çiçek S, Yiğider E, Demirel S, Piekutowska M, Szulc P, Niedbała G. Machine Learning Analysis of the Impact of Silver Nitrate and Silver Nanoparticles on Wheat ( Triticum aestivum L.): Callus Induction, Plant Regeneration, and DNA Methylation. PLANTS (BASEL, SWITZERLAND) 2023; 12:4151. [PMID: 38140479 PMCID: PMC10747064 DOI: 10.3390/plants12244151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 11/28/2023] [Accepted: 11/29/2023] [Indexed: 12/24/2023]
Abstract
The objective of this study was to comprehend the efficiency of wheat regeneration, callus induction, and DNA methylation through the application of mathematical frameworks and artificial intelligence (AI)-based models. This research aimed to explore the impact of treatments with AgNO3 and Ag-NPs on various parameters. The study specifically concentrated on analyzing RAPD profiles and modeling regeneration parameters. The treatments and molecular findings served as input variables in the modeling process. It included the use of AgNO3 and Ag-NPs at different concentrations (0, 2, 4, 6, and 8 mg L-1). The in vitro and epigenetic characteristics were analyzed using several machine learning (ML) methods, including support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), k-nearest neighbor classifier (KNN), and Gaussian processes classifier (GP) methods. This study's results revealed that the highest values for callus induction (CI%) and embryogenic callus induction (EC%) occurred at a concentration of 2 mg L-1 of Ag-NPs. Additionally, the regeneration efficiency (RE) parameter reached its peak at a concentration of 8 mg L-1 of AgNO3. Taking an epigenetic approach, AgNO3 at a concentration of 2 mg L-1 demonstrated the highest levels of genomic template stability (GTS), at 79.3%. There was a positive correlation seen between increased levels of AgNO3 and DNA hypermethylation. Conversely, elevated levels of Ag-NPs were associated with DNA hypomethylation. The models were used to estimate the relationships between the input elements, including treatments, concentration, GTS rates, and Msp I and Hpa II polymorphism, and the in vitro output parameters. The findings suggested that the XGBoost model exhibited superior performance scores for callus induction (CI), as evidenced by an R2 score of 51.5%, which explained the variances. Additionally, the RF model explained 71.9% of the total variance and showed superior efficacy in terms of EC%. Furthermore, the GP model, which provided the most robust statistics for RE, yielded an R2 value of 52.5%, signifying its ability to account for a substantial portion of the total variance present in the data. This study exemplifies the application of various machine learning models in the cultivation of mature wheat embryos under the influence of treatments and concentrations involving AgNO3 and Ag-NPs.
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Affiliation(s)
- Aras Türkoğlu
- Department of Field Crops, Faculty of Agriculture, Necmettin Erbakan University, Konya 42310, Türkiye
| | - Kamil Haliloğlu
- Department of Field Crops, Faculty of Agriculture, Ataturk University, Erzurum 25240, Türkiye;
| | - Fatih Demirel
- Department of Agricultural Biotechnology, Faculty of Agriculture, Igdır University, Igdir 76000, Türkiye;
| | - Murat Aydin
- Department of Agricultural Biotechnology, Faculty of Agriculture, Ataturk University, Erzurum 25240, Türkiye; (M.A.); (S.Ç.); (E.Y.)
| | - Semra Çiçek
- Department of Agricultural Biotechnology, Faculty of Agriculture, Ataturk University, Erzurum 25240, Türkiye; (M.A.); (S.Ç.); (E.Y.)
| | - Esma Yiğider
- Department of Agricultural Biotechnology, Faculty of Agriculture, Ataturk University, Erzurum 25240, Türkiye; (M.A.); (S.Ç.); (E.Y.)
| | - Serap Demirel
- Department of Molecular Biology and Genetics, Faculty of Science, Van Yüzüncü Yıl University, Van 65080, Türkiye;
| | - Magdalena Piekutowska
- Department of Geoecology and Geoinformation, Institute of Biology and Earth Sciences, Pomeranian University in Słupsk, 27 Partyzantów St., 76-200 Słupsk, Poland;
| | - Piotr Szulc
- Department of Agronomy, Poznań University of Life Sciences, Dojazd 11, 60-632 Poznań, Poland;
| | - Gniewko Niedbała
- Department of Biosystems Engineering, Faculty of Environmental and Mechanical Engineering, Poznań University of Life Sciences, Wojska Polskiego 50, 60-627 Poznań, Poland
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