Global identification and analysis of microRNAs involved in salt stress responses in two alfalfa (<i>Medicago sativa</i> ‘Millennium’) lines
Bibliographic record
Abstract
Alfalfa is an important economic crop; a mutant (M) strain was identified during planting and production. M plants consistently had better relative water content and relative electrical conductivity under higher salt conditions compared with the wild type (WT) plants, suggesting that M plants have higher tolerance for salt. To understand the microRNAs (miRNAs) involved in salt stress response in alfalfa, 128 miRNAs were identified from the WT and M alfalfa plants under normal and saline conditions. Of the 128 miRNAs, 29 and 23 differentially expressed miRNAs were identified in the M vs. WT control (M-CK vs. WT-CK) and salt-stressed M vs. WT (M-salt vs. WT-salt) comparison, respectively. These miRNAs responded to salt stress and showed different expression patterns after salt treatment. Their potential target genes were predicted and further analysed by GO classification and KEGG pathway analysis, where the majority of target genes were associated with plant growth and development, and exhibited significant changes in WT and M plants. In addition, compared with the WT plants, miR172-CNGC, miR319-CAX2, miR408-NHX and miR2590-CHX14/15 showed significant upregulation in M alfalfa plants, suggesting that M plants have higher ion transport levels. The differential expression profiles of miRNAs and putative target genes were further validated by quantitative real-time polymerase chain reaction. It is speculated that these miRNAs are involved in the increased salt tolerance of the M alfalfa plants.
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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".