Exploring the gene expression patterns of plant ACYL LIPID THIOESTERASEs (ALTs) through various analyses
Bibliographic record
Abstract
ACYL-LIPID THIOESTERASE (ALT) enzymes are found across all plant taxa and produce medium-chain fatty acids, methylketone precursors, and 3-hydroxy fatty acids.While the products produced by many ALTs from diverse plant taxa are known, the biological roles of the enzymes themselves are not.The aim of this thesis was to infer the biological roles of some ALTs through their tissue specific expression patterns or their responsiveness to environmental cues.Histochemical β-glucuronidase (GUS) reporter gene staining of Arabidopsis thaliana transgenic lines demonstrated that ALT3 from A. thaliana (AtALT3) is widely expressed in nearly all aerial and root tissues.Additionally, cis-regulatory elements outside of the AtALT3 upstream region were reported to be important for AtALT3 gene expression.By examining AtALT3 transcript abundance using qRT-PCR analysis in response to wounding or methyl jasmonate application, I provided insight and further considerations for future transcript analysis involving ALTs.Publicly available transcriptomic data sets were analyzed to reveal that ALT gene expression in various plant species could be related to germination, submergence stress, or insect and pathogen attack.Taking into consideration both the ALT gene expression patterns and corresponding ALT products, I suggest that ALTs have diverse roles, but mostly related to seed germination and defense against biotic stressors.The findings presented in this thesis will help direct future research to determine the potentially diverse functions of ALT enzymes. Appendix B -Agarose gel demonstrating successful insertion of T-DNA containingAtALT3p::GUS ....
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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) | 0.000 | 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 | 0.000 | 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".