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ABSTRACT: soil of panax ginseng in china

PROVIDER: PRJNA1122861 | ENA |

REPOSITORIES: ENA

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Dataset's files

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			Action	DRS
	SRR29366027.fastq.gz	Fastqsanger.gz
	SRR29366028.fastq.gz	Fastqsanger.gz
	SRR29366029.fastq.gz	Fastqsanger.gz
	SRR29366030.fastq.gz	Fastqsanger.gz
	SRR29366031.fastq.gz	Fastqsanger.gz

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Label-free Quantitative Proteomic analysis of drought-responsive proteins in Panax ginseng Meyer

Project description:Korean ginseng (Panax ginseng Meyer) has long been cultivated as an important medicinal plant. Drought results from the moderate water loss, which primarily impairs the growth of ginseng and reduction of yield loss. However, basis of biological clues to understanding the accurate mechanisms related to drought stress in proteome level are still elusive. Therefore, we carried out label-free quantitative proteomic analysis using ginseng roots subjected to drought stress which was grown at less than 10% soil moisture for two weeks, compared with normal ginseng which was grown at 25% soil moisture. The acquired proteins were carried out label-free proteomic analysis using LC-MS/MS. This approach led to the identification of total 2,471 proteins, and out of 195 proteins showed significant modulation. Functional classification revealed that proteins related to secondary metabolites, calcium signaling, and photosynthesis were enriched in control sample (cluster_1), while proteins associated with stress responsive, redox, electron transport, and protein synthesis were mainly dominated in cluster_2 (drought stress condition). Taken together, our results provided an overview of the drought-induced proteomic changes in ginseng root, and it is correlated with physiological changes, contributing to reveal potential marker at proteome level in ginseng.

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Transcriptional profiling by high throughput sequencing of Panax ginseng C.A. Meyer leaf and stem transcriptomes during the leaf-expansion period.

Project description:In order to research the ginseng leaf-stem gene expression profiles of and dig out its function genes in the leaf-expansion period, the transcriptomic sequencing technology was set up the first time for five years the transcription of the Panax ginseng leaf-stem in the leaf-expansion period.

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Project description:The breast cancer incidence has been increasing in China, with the earlier age of onset compared with Western countries. Traditional Chinese medicine has been provided as one of the major source of anti-cancer drugs. Ginseng is one of the most common traditional medicines in China. Ginsenosides, the saponins in the plant Panax (ginseng) are the major active components responsible for their chemopreventive effects from cancer. However, the mechanisms by which ginsenosides exert their anti-cancer effect remain elusive. By combining TMT-based quantitation with TiO2-based phosphopeptide enrichment, we performed a quantitative analysis of the changes of the phosphoproteomes in ginsenoside Rg3-treated breast cancer MDA-MB-231 cells. We were able to quantitate 5,140 phosphorylation sites on 2,041 phosphoproteins. Our data show that the phosphorylation status of 13 sites was changed in MDA-MB-231 cells upon Rg3 treatment. The perturbed phosphoproteins are CPSF7, EEF2, HIRIP3, MAGED2, MPRIP, MYCBP2, PAWR, PPP1R12A, RANBP2, SEPT9, TMPO, and UFL1. These proteins are involved in various biological processes, including protein synthesis, cell division, and inhibition of NF-κB signaling. Our study revealed that Rg3 exerts its anti-cancer effects through a combination of different signaling pathways.

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Transcript profiles of the flowering period Panax ginseng C.A. Meyer root and analysis the gene function

Project description:Panax ginseng C.A. Meyer is one of the most popular medicinal herbs. In order to research the genes that related to the flowering period of ginseng, and find out the antifungal proteins and transcription factors that combat various biotic and abiotic stress, a cDNA sample was prepared from the flowering period ginseng root of a five-year-old plant and sequenced using the Illumina sequencing platform. In this study, we produced nearly 40 million sequencing reads. These reads were assembled into 134,045 contigs using Trinity software (mean size: 282 bp). Based on a similarity search with known proteins, we identified 79,307 sequences with a cut-off E-value of 10-5. Assembled sequences were then annotated using gene ontology (GO) terms, clusters of orthologous group (COG) classifications and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways respectively.

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