Characterization of a second secologanin synthase isoform producing both secologanin and secoxyloganin allows enhanced de novo assembly of a Catharanthus roseus transcriptome
Bibliographic record
Abstract
BACKGROUND: Transcriptome sequencing offers a great resource for the study of non-model plants such as Catharanthus roseus, which produces valuable monoterpenoid indole alkaloids (MIAs) via a complex biosynthetic pathway whose characterization is still undergoing. Transcriptome databases dedicated to this plant were recently developed by several consortia to uncover new biosynthetic genes. However, the identification of missing steps in MIA biosynthesis based on these large datasets may be limited by the erroneous assembly of close transcripts and isoforms, even with the multiple available transcriptomes. RESULTS: Secologanin synthases (SLS) are P450 enzymes that catalyze an unusual ring-opening reaction of loganin in the biosynthesis of the MIA precursor secologanin. We report here the identification and characterization in C. roseus of a new isoform of SLS, SLS2, sharing 97 % nucleotide sequence identity with the previously characterized SLS1. We also discovered that both isoforms further oxidize secologanin into secoxyloganin. SLS2 had however a different expression profile, being the major isoform in aerial organs that constitute the main site of MIA accumulation. Unfortunately, we were unable to find a current C. roseus transcriptome database containing simultaneously well reconstructed sequences of SLS isoforms and accurate expression levels. After a pair of close mRNA encoding tabersonine 16-hydroxylase (T16H1 and T16H2), this is the second example of improperly assembled transcripts from the MIA pathway in the public transcriptome databases. To construct a more complete transcriptome resource for C. roseus, we re-processed previously published transcriptome data by combining new single assemblies. Care was particularly taken during clustering and filtering steps to remove redundant contigs but not transcripts encoding potential isoforms by monitoring quality reconstruction of MIA genes and specific SLS and T16H isoforms. The new consensus transcriptome allowed a precise estimation of abundance of SLS and T16H isoforms, similar to qPCR measurements. CONCLUSIONS: The C. roseus consensus transcriptome can now be used for characterization of new genes of the MIA pathway. Furthermore, additional isoforms of genes encoding distinct MIA biosynthetic enzymes isoforms could be predicted suggesting the existence of a higher level of complexity in the synthesis of MIA, raising the question of the evolutionary events behind what seems like redundancy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".