Ontology highlight
ABSTRACT:
PROVIDER: PRJNA842855 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19427103_1.fastq.gz | Fastqsanger.gz | |||
| SRR19427103_2.fastq.gz | Fastqsanger.gz |
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Project description:micro RNA identification of tea plant
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Project description:Background: Lysine succinylation of proteins has potential impacts on protein structure and function, which occurred on post-translation level. However, the information about the lysine succinylation of proteins in tea plants is limited. In the present study, the significant signal of succinylation in tea plants was found by western blot. Subsequently, we performed qualitative analyses to globally identify lysine succinylation substrates by using high accuracy nano LC-MS/MS combined with affinity purification. Results: As a result, a total of 142 lysine succinylation sites were identified in 86 proteins. The identified succinylated proteins are involved in various biological processes and a large proportion of the succinylation sites are present on proteins in the primary metabolism pathway, including glyoxylate and dicarboxylate metabolism, the tricarboxylic acid (TCA) cycle and glycine, serine and threonine metabolism. Moreover, 10 new succinylated sites on histones were detected in tea plants either. Conclusions: These results suggested that succinylated proteins in tea plants might play critical regulatory roles in biological processes, especially in the primary metabolism. This study not only globally analysed the functional annotation of lysine succinylation in tea plants, but also provided valuable information for further investigating the functions of lysine succinylation in tea plants.
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Project description:Tea (Camellia sinensis (L.) O. Kuntze) is an important non-alcoholic commercial beverage crop. Tea tree is a perennial plant, and winter dormancy is its part of biological adaptation to environmental changes. We recently discovered a novel tea tree cultivar that can generate tender shoots in winter, but the regulatory mechanism of this ever-growing tender shoot development in winter is not clear. In this study, we conducted a proteomic analysis for identification of key genes and proteins differentially expressed between the winter and spring tender shoots, to explore the putative regulatory mechanisms and physiological basis of its ever-growing character during winter.
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Project description:BACKGROUND: Evaluation of the airway transcriptome may reveal patterns of gene expression that are associated with clinical phenotypes of asthma. To define transcriptomic endotypes of asthma (TEA) we analyzed gene expression in induced sputum that correlate with phenotypes of disease. METHODS: Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation. RESULTS: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower pre-bronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04), compared to the other TEA clusters. TEA cluster 2, the smallest cluster had the most subjects that were hospitalized for asthma (P = 0.04). Subjects in TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 x 10-06) and hospitalization (P = 0.01), respectively. CONCLUSIONS: Patterns of gene expression in the sputum and blood reveal TEA clusters that are associated with severe asthma phenotypes in children and adults. Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation.
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