Dynamic Landscapes of Four Histone Modifications during Deetiolation in<i>Arabidopsis</i>
Bibliographic record
Abstract
Although landscapes of several histone marks are now available for Arabidopsis thaliana and Oryza sativa, such profiles remain static and do not provide information about dynamic changes of plant epigenomes in response to developmental or environmental cues. Here, we analyzed the effects of light on four histone modifications (acetylation and trimethylation of lysines 9 and 27 on histone H3: H3K9ac, H3K9me3, H3K27ac, and H3K27me3, respectively). Our genome-wide profiling of H3K9ac and H3K27ac revealed that these modifications are nontransposable element gene-specific. By contrast, we found that H3K9me3 and H3K27me3 target nontransposable element genes, but also intergenic regions and transposable elements. Specific light conditions affected the number of modified regions as well as the overall correlation strength between the presence of specific modifications and transcription. Furthermore, we observed that acetylation marks not only ELONGATED HYPOCOTYL5 and HY5-HOMOLOG upon deetiolation, but also their downstream targets. We found that the activation of photosynthetic genes correlates with dynamic acetylation changes in response to light, while H3K27ac and H3K27me3 potentially contribute to light regulation of the gibberellin metabolism. Thus, this work provides a dynamic portrait of the variations in histone modifications in response to the plant's changing light environment and strengthens the concept that histone modifications represent an additional layer of control for light-regulated genes involved in photomorphogenesis.
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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 | 0.000 | 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) | 0.001 | 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".