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Record W2154109695 · doi:10.1186/1471-2164-11-262

De novo sequencing and analysis of the American ginseng root transcriptome using a GS FLX Titanium platform to discover putative genes involved in ginsenoside biosynthesis

2010· article· en· W2154109695 on OpenAlexaff
Chao Sun, Ying Li, Qiong Wu, Hongmei Luo, Yongzhen Sun, Jingyuan Song, Edmund MK. Lui, Shilin Chen

Bibliographic record

VenueBMC Genomics · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGinseng Biological Effects and Applications
Canadian institutionsWestern University
FundersNational Natural Science Foundation of China
KeywordsGinsenosideBiologyKEGGMethyl jasmonateTranscriptomeGinsengContigMetabolic pathwayGeneDNA microarrayExpressed sequence tagComputational biologyBiosynthesisGenomeGeneticsGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: American ginseng (Panax quinquefolius L.) is one of the most widely used herbal remedies in the world. Its major bioactive constituents are the triterpene saponins known as ginsenosides. However, little is known about ginsenoside biosynthesis in American ginseng, especially the late steps of the pathway. RESULTS: In this study, a one-quarter 454 sequencing run produced 209,747 high-quality reads with an average sequence length of 427 bases. De novo assembly generated 31,088 unique sequences containing 16,592 contigs and 14,496 singletons. About 93.1% of the high-quality reads were assembled into contigs with an average 8-fold coverage. A total of 21,684 (69.8%) unique sequences were annotated by a BLAST similarity search against four public sequence databases, and 4,097 of the unique sequences were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes. Based on the bioinformatic analysis described above, we found all of the known enzymes involved in ginsenoside backbone synthesis, starting from acetyl-CoA via the isoprenoid pathway. Additionally, a total of 150 cytochrome P450 (CYP450) and 235 glycosyltransferase unique sequences were found in the 454 cDNA library, some of which encode enzymes responsible for the conversion of the ginsenoside backbone into the various ginsenosides. Finally, one CYP450 and four UDP-glycosyltransferases were selected as the candidates most likely to be involved in ginsenoside biosynthesis through a methyl jasmonate (MeJA) inducibility experiment and tissue-specific expression pattern analysis based on a real-time PCR assay. CONCLUSIONS: We demonstrated, with the assistance of the MeJA inducibility experiment and tissue-specific expression pattern analysis, that transcriptome analysis based on 454 pyrosequencing is a powerful tool for determining the genes encoding enzymes responsible for the biosynthesis of secondary metabolites in non-model plants. Additionally, the expressed sequence tags (ESTs) and unique sequences from this study provide an important resource for the scientific community that is interested in the molecular genetics and functional genomics of American ginseng.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.272
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations295
Published2010
Admission routes1
Has abstractyes

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