Transgenerational Response to Heat Stress in the Form of Differential Expression of Noncoding RNA Fragments in <i>Brassica rapa</i> Plants
Why this work is in the frame
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Bibliographic record
Abstract
Epigenetic regulations in the form of changes in differential expression of noncoding RNAs (ncRNAs) are an essential mechanism of stress response in plants. Previously we showed that heat treatment in L. results in the differential processing and accumulation of ncRNA fragments (ncRFs) stemming from transfer RNAs (tRNAs), ribosomal RNAs (rRNAs), small nuclear RNAs (snRNAs), and small nucleolar RNAs (snoRNAs). In this work, we analyzed whether ncRFs are differentially expressed in the progeny of heat-stressed plants. We found significant changes in the size of tRF reads and a significant decrease in the percentage of tRFs mapping to tRNA-Ala, tRNA-Arg, and tRNA-Tyr and an increase in tRFs mapping to tRNA-Asp. The enrichment analysis showed significant differences in processing of tRFs from tRNA, tRNA, tRNA, tRNA, tRNA, and tRNA isoacceptors. Analysis of potential targets of tRFs showed that they regulate brassinosteroid metabolism, the proton pump ATPase activity, the antiporter activity, the mRNA decay activity as well as nucleosome positioning and the epigenetic regulation of transgenerational response. Gene ontology term analysis of potential targets demonstrated a significant enrichment in tRFs that potentially targeted a cellular component endoplasmic reticulum (ER) and in small nucleolar RNA fragments (snoRFs), the molecular function protein binding. To summarize, our work demonstrated that the progeny of heat-stressed plants exhibit changes in the expression of tRFs and snoRFs but not of small nuclear RNA fragments (snRFs) or ribosomal RNA fragments (rRFs) and these changes likely better prepare the progeny of stressed plants to future stress encounters.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it