Improved transcriptional activators and their use in mis‐expression traps in Arabidopsis
Bibliographic record
Abstract
The synthetic transcription factor LhG4 has been used in numerous mis-expression studies in plants. We show that the sequence encoding the LhG4 activation domain, derived from Saccharomyces cerevisiae GAL4, contains several cryptic polyadenylation signals in Arabidopsis. The GAL4-derived sequence was modified according to preferred Arabidopsis codon usage, generating LhG4AtO which was faithfully transcribed in Arabidopsis plants. In protoplasts, LhG4AtO achieved maximum transactivation of the pOp promoter with 10-fold less input DNA than LhG4. The same methods were used to compare 10 other LhG4 derivatives that carried alternative natural or synthetic activation domains. Lh214 and Lh314, which contain synthetic activation domains comprising trimers of a core acidic activation domain, directed threefold more GUS expression from the pOp promoter with 20-fold less input DNA than LhG4. In contrast, when expressed from the CaMV 35S promoter in transgenic plants carrying a pOp-GUS reporter, Lh214 and Lh314 yielded transformants with substantially lower GUS activities than other constructs including LhG4AtO and LhG4 which performed similarly. When incorporated into an enhancer-trapping vector, however, LhG4AtO and Lh314 yielded enhancer traps with approximately twice the frequency of LhG4, suggesting that the modified activation domains offer improved performance when expressed from weaker transcription signals. To increase the number of LhG4 patterns available for mis-expression studies, we describe a population of enhancer-trap lines obtained with LhG4AtO in a pOp-GUS background. We show that enhancer-trap lines can transactivate an unlinked pOp-green fluorescent protein (pOp-GFP) reporter in the pattern predicted by staining for GUS activity.
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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".