Ontology highlight
ABSTRACT:
PROVIDER: PRJNA436830 | ENA |
REPOSITORIES: ENA
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Project description:Background：Taxol is an efficient anticancer drug; however, the accumulation of taxoids can vary hugely among Taxus species. The mechanism underlying differential accumulation of taxoids are largely unknown. Thus, the comparative analysis of the transcriptomes in three Taxus species, including T. media, T. mairei and T. cuspidata, was performed. Results:KEGG enrichment analysis revealed that the diterpenoid biosynthesis and cytochrome P450 pathways were significantly enriched in the differential expressed genes. Dynamic expressions of the taxol biosynthesis related genes might be a potential explanation for the interspecific differential accumulation of taxol and its derivatives. Besides, the sequences of several key enzymes were re-assembled based on independent transcriptomes from different Taxus species. Our data showed that sequence diversity may be another factor that determines the variations in taxoids. Furthermore, five jasmonic acid (JA) metabolism-related GO terms were analyzed. The differential expression of these JA-related transcription factors suggested distinct responses to exogenous MeJA applications in the three Taxus species. Conclusions:Our results revealed the comprehensive variations in the expression pattern and sequence similarity of the key genes involved in the metabolism of taxoids among different Taxus species. The data give us an opportunity to reveal the mechanism underlying the variations in the taxoid contents and to select the highest-yielding Taxus species.
2018-10-20 | GSE121523 | GEO
Project description:This model was reconstructed from single-nucleus RNA-seq (snRNA-seq) data of human postmortem brain and curated using published metabolomics data from human iPSC-derived neurons and cerebrospinal fluid (CSF), together with gene expression data from the Human Protein Atlas. It more accurately simulates human neuronal metabolic flux in neurodegenerative conditions such as Alzheimer's disease (AD).
2026-06-27 | MODEL2606170001 | BioModels