Identification of novel miRNAs and miRNA expression profiling in embryogenic tissues of Picea balfouriana treated by 6-benzylaminopurine
Bibliographic record
Abstract
Here, we compared miRNA expression profiles in embryonic cell cultures of the conifer Picea balfouriana following application of the synthetic cytokinin 6-benzylaminopurine (6-BAP). We used next-generation sequencing to analyze three libraries of small RNAs from the treated embryogenic cell cultures and generated 24,000,000 raw reads from each of the libraries. Over 70 differentially regulated micro RNA (miRNA) families (≥2 fold change in expression) were identified between pairs of treatments. A quantitative analysis showed that miR3633 and miR1026 were upregulated in tissues with the highest embryogenic ability. These two miRNAs were predicted to target genes encoding receptor-like protein kinase and GAMYB transcription factors, respectively. In one library, miR1160, miR5638, miR1315, and miR5225 were downregulated. These four miRNAs were predicted to target genes encoding APETALA2, calmodulin-binding protein, and calcium-dependent protein kinase transcription factors. The expression patterns of the miRNAs and their targets were negatively correlated. Approximately 181 potentially novel P. balfouriana miRNAs were predicted from the three libraries, and seven were validated during the quantitative analysis. This study is the first report of differential miRNA regulation in tissues treated with 6-BAP during somatic embryogenesis. The differentially expressed miRNAs will be of value for investigating the mechanisms of embryogenic processes that are responsive to 6-BAP in P. balfouriana.
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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) | 0.000 | 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 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".