Tissue-Specific GAL4 Expression Patterns as a Resource Enabling Targeted Gene Expression, Cell Type-Specific Transcript Profiling and Gene Function Characterization in the Arabidopsis Vascular System
Bibliographic record
Abstract
Cell type-specific fluorescent gene expression markers are a prerequisite for various strategies in functional genomics and developmental biology. To increase the resolution of vascular tissue analysis and to identify more genes expressed in the vasculature, we searched for expression in vascular tissues within a new collection of transactivated enhancer trap lines. Among 33 lines with vascular expression, we identified five lines with expression profiles marking procambial or procambium-associated cell states. In stem cross-sections we identified one line with phloem- and four with xylem-specific expression, as well as nine lines with expression in both phloem and xylem and two with cambial expression. For all lines, we also report the expression patterns in different organs and developmental stages. Special features of expression patterns include a line with auxin-dependent expression domains. We determined the flanking sequences of 21 enhancer trap insertions, 16 of which are found in, or in close proximity to, annotated genes and thus may reflect the expression patterns of natural promoters. Finally, we analyzed the loss-of-function phenotypes of 14 putatively affected genes. Remarkably, mutations in a gene encoding a putative F-box protein were associated with an auxin-hypersensitive hypocotyl elongation response. Our compendium provides a diverse selection of markers for different vascular cell states, which can be used for targeted gene expression, cell type-specific transcript profiling and gene function assignment in the plant vascular system.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".