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The Potential Role of Plastome Copy Number as a Quality Biomarker for Plant Products using Real-time Quantitative Polymerase Chain Reaction
Background: Plastids are plant-specific semi-autonomous self-replicating organelles, containing circular DNA molecules called plastomes. Plastids perform crucial functions, including photosynthesis, stress perception and response, synthesis of metabolites, and storage. The plastome and plastid numbe...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bentham Science Publishers
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9875542/ https://www.ncbi.nlm.nih.gov/pubmed/36777877 http://dx.doi.org/10.2174/1389202923666220513111643 |
Sumario: | Background: Plastids are plant-specific semi-autonomous self-replicating organelles, containing circular DNA molecules called plastomes. Plastids perform crucial functions, including photosynthesis, stress perception and response, synthesis of metabolites, and storage. The plastome and plastid numbers have been shown to be modulated by developmental stage and environmental stimuli and have been used as a biomarker (identification of plant species) and biosensor (an indicator of abiotic and biotic stresses). However, the determination of plastome sequence and plastid number is a laborious process requiring sophisticated equipment. Methods: This study proposes using plastome copy number (PCN), which can be determined rapidly by real-time quantitative polymerase chain reaction (RT-qPCR) as a plant product quality biomarker. This study shows that the PCN log(10) and range PCN log(10) values calculated from RT-qPCR data, which was obtained for two years from leaves and lint samples of cotton and seed samples of cotton, rice, soybean, maize, and sesame can be used for assessing the quality of the samples. Results: Observation of lower range PCN log(10) values for CS (0.31) and CR (0.58) indicated that the PCN showed little variance from the mean PCN log(10) values for CS (3.81) and CR (3.85), suggesting that these samples might have encountered ambient environmental conditions during growth and/ or post-harvest storage and processing. This conclusion was further supported by observation of higher range PCN log(10) values for RS (3.09) versus RP (0.05), where rice seeds in the RP group had protective hull covering compared to broken hull-less seeds in the RS group. To further support that PCN is affected by external factors, rice seeds treated with high temperatures and pathogens exhibited lower PCN values when compared to untreated seeds. Furthermore, the range PCN log(10) values were found to be high for cotton leaf (CL) and lint (Clt) sample groups, 4.11 and 3.63, respectively, where leaf and lint samples were of different sizes, indicating that leaf samples might be of different developmental stage and lint samples might have been processed differently, supporting that the PCN is affected by both internal and external factors, respectively. Moreover, PCN log(10) values were found to be plant specific, with oil containing seeds such as SeS (6.49) and MS (5.05) exhibiting high PCN log(10) values compared to non-oil seeds such as SS (1.96). Conclusion: In conclusion, it was observed that PCN log(10) values calculated from RT-qPCR assays were specific to plant species and the range of PCN log(10) values can be directly correlated to the internal and external factors and, therefore might be used as a potential biomarker for assessing the quality of plant products. |
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