Characterization of three terpenoid glycosyltransferase genes in ‘Valencia’ sweet orange (<i>Citrus sinensis</i> L. Osbeck)
Bibliographic record
Abstract
Three putative terpenoid UDP-glycosyltransferase (UGT) genes, designated CsUGT1, CsUGT2, and CsUGT3, were isolated and characterized in 'Valencia' sweet orange (Citrus sinensis L. Osbeck). CsUGT1 consisted of 1493 nucleotides with an open reading frame encoding 492 amino acids, CsUGT2 consisted of 1727 nucleotides encoding 504 amino acids, and CsUGT3 consisted of 1705 nucleotides encoding 468 amino acids. CsUGT3 had a 145 bp intron at 730-874, whereas CsUGT1 and CsUGT2 had none. The three deduced glycosyltransferase proteins had a highly conserved plant secondary product glycosyltransferase motif in the C terminus. Phylogenetic analysis showed that CsUGT1 and CsUGT3 were classified into group L of glycosyltransferase family 1, and CsUGT2 was classified into group D. Through Southern blotting analysis, CsUGT1 was found to have two copies in the sweet orange genome, whereas CsUGT2 and CsUGT3 had at least seven and nine copies, respectively. CsUGT1, CsUGT2, and CsUGT3 were constitutively expressed in leaf, flower, and fruit tissues. The results facilitate further investigation of the function of terpenoid glycosyltransferases in citrus and the biosynthesis of terpenoid glycosides in vitro.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".