Small RNA regulation of ovule development in the cotton plant, G. hirsutum L
Bibliographic record
Abstract
BACKGROUND: The involvement of small RNAs in cotton fiber development is under explored. The objective of this work was to directly clone, annotate, and analyze small RNAs of developing ovules to reveal the candidate small interfering RNA/microRNAs involved in cotton ovule and fiber development. RESULTS: We cloned small RNA sequences from 0-10 days post anthesis (DPA) developing cotton ovules. A total of 6691 individual colonies were sequenced from 11 ovule small RNA libraries that yielded 2482 candidate small RNAs with a total of 583 unique sequence signatures. The majority (362, 62.1%) of these 583 sequences were 24 nt long with an additional 145 sequences (24.9%) in the 21 nt to 23 nt size range. Among all small RNA sequence signatures only three mirBase-confirmed plant microRNAs (miR172, miR390 and ath-miR853-like) were identified and only two miRNA-containing clones were recovered beyond 4 DPA. Further, among all of the small RNA sequences obtained from the small RNA pools in developing ovules, only 15 groups of sequences were observed in more than one DPA period. Of these, only five were present in more than two DPA periods. Two of these were miR-172 and miR-390 and a third was identified as 5.8S rRNA sequence. Thus, the vast majority of sequence signatures were expressed in only one DPA period and this included nearly all of the 24 nt sequences. Finally, we observed a distinct DPA-specific expression pattern among our clones based upon sequence abundance. Sequences occurring only once were far more likely to be seen in the 0 to 2 DPA periods while those occurring five or more times were the majority in later periods. CONCLUSION: This initial survey of small RNA sequences present in developing ovules in cotton indicates that fiber development is under complex small RNA regulation. Taken together, the results of this initial small RNA screen of developing cotton ovules is most consistent with a model, proposed by Baulcombe, that there are networks of small RNAs that are induced in a cascade fashion by the action of miRNAs and that the nature of these cascades can change from tissue to tissue and developmental stage to developmental stage.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".