Integrative analyses of metabolome and transcriptome reveals metabolomic variations and candidate genes involved in sweet cherry (Prunus avium L.) fruit quality during development and ripening
Sweet cherry (Prunus avium L.), one of the most appreciated and most important commercial temperate fruits, has high sensory quality and nutritional value. Investigating its metabolic variations provides valuable information on the formation of fruit quality. In this study, widely targeted LC-MS/MS...
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| Autores principales: | , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
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Public Library of Science (PLoS)
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/32935819a74c4b30acb3bbd46ba2c3cd |
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| Sumario: | Sweet cherry (Prunus avium L.), one of the most appreciated and most important commercial temperate fruits, has high sensory quality and nutritional value. Investigating its metabolic variations provides valuable information on the formation of fruit quality. In this study, widely targeted LC-MS/MS based metabolomics was used to identify and quantify metabolic changes during ‘Black Pearl’ sweet cherry development and ripening. A total of 263 significant differentially expressed metabolites (DEMs) were detected during the four fruit-development stages. Significant differences were observed in the composition and content of compounds in the four stages of cherry development, especially sugars, organic acids, and flavonoids. Moreover, transcriptome analysis provided a molecular basis for metabolic variations during fruit development. A total of 6724 significant differentially expressed genes (DEGs) were identified. Further correlation analysis of major DEMs and DEGs showed that 19 key DEGs were involved in sugar metabolism, 23 key DEGs in organic acid metabolism, and 13 key DEGs in flavonoid metabolism. The upregulated genes involved in the flavonoid pathway probably play an important role in regulating the rapid increase of anthocyanin content during fruit development. These comprehensive analysis data provide a better understanding to improve fruit quality traits based on molecular and metabolic levels. |
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