Unique features of the m<sup>6</sup>A methylome and its response to drought stress in sea buckthorn (<i>Hippophae rhamnoides</i> Linn.)
Bibliographic record
Abstract
In plants, recent studies have revealed that N6-methyladenosine (m6A) methylation of mRNA has potential regulatory functions of this mRNA modification in many biological processes. m6A methyltransferase, m6A demethylase and m6A-binding proteins can cause differential phenotypes, indicating that m6A may have critical roles in the plant. In this study, we depicted the m6A map of sea buckthorn (Hippophae rhamnoides Linn.) transcriptome. Similar to A. thaliana, m6A sites of sea buckthorn transcriptome is significantly enriched around the stop codon and within 3ʹ-untranslated regions (3ʹUTR). Gene ontology analysis shows that the m6A modification genes are associated with metabolic biosynthesis. In addition, we identified 13,287 different m6A peaks (DMPs) between leaf under drought (TR) and control (CK) treatment. It reveals that m6A has a high level of conservation and has a positive correlation with mRNA abundance in plants. GO and KEGG enrichment results showed that DMP modification DEGs in TR were particularly associated with ABA biosynthesis. Interestingly, our results showed three m6A demethylase (HrALKBH10B, HrALKBH10C and HrALKBH10D) genes were significantly increased following drought stress, which indicated that it may contributed the decreased m6A levels. This exhaustive m6A map provides a basis and resource for the further functional study of mRNA m6A modification in abiotic stress.
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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".