Transcriptome analysis of reproductive-stage <i>Arabidopsis</i> plants exposed gamma-ray irradiation at various doses
Bibliographic record
Abstract
Purpose: Gamma rays (GR) induce significant changes in the structure and expression of genes involved in the regulation of diverse biochemical and physiological processes. Arabidopsis plants exhibit different growth and development patterns in response to exposure to GR. The effects on gene expression of different radiation doses of GR (100 and 800 Gy) administered to Arabidopsis plants were examined at the reproductive stage. Materials and methods: We irradiated 26-day-old plants with three replications [developmental stages 5.1–6.0, according to Boyes et al. (2001)] using a GR irradiator (60 Co, ca. 150 TBq capacity, Atomic Energy of Canada Limited, Ontario, Canada) at the Korea Atomic Energy Research Institute. Plants were treated with 100, 200, 300, 400, 800, 1200, 1600, or 2000 Gy, and the doses were made from varying the distance to the source. Results: We conducted a high-throughput screening analysis and detected 883 GR-responsive genes that showed significant changes; these were involved in several putative metabolic pathways related to biotic stress. Additionally, five overrepresented cis-regulatory elements were identified in the 1-kb upstream regions of GR-responsive genes by using motif enrichment analysis. We also detected three GR-responsive genes associated with stamen development and confirmed their co-regulation with functionally interacting genes. Conclusions: This finding suggests that a network-based analysis is a viable approach to identify significant GR-responsive genes associated with the reproductive stage of Arabidopsis. Our results provide further insights into the complex biological systems involved in the response to different doses of GR in plants.
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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 | 0.001 |
| 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 | 0.001 |
| 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 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".