MsNF-YC4 positively regulates root branching and drought resistance in alfalfa by activating MsARF8
Bibliographic record
Abstract
The objective of this study was to identify functional genes regulating root branching and drought resistance that could be used in developing drought-tolerant alfalfa ( Medicago sativa L.) cultivars. Heterologously expression of an Arabidopsis orphan gene QQS was found to enhance root branching and drought tolerance in alfalfa. By yeast two-hybid (Y2H) and luciferase complementation imaging (LCI) assay, a transcription factor MsNF-YC4 was confirmed as an endogenous interactor of QQS. We speculated it could play a positive role in regulating alfalfa root branching and drought tolerance. Transgenic alfalfa plants overexpressing MsNF-YC4 were generated by Agrobacterium-mediated transformation. Through RNA sequencing (RNA-seq), we noticed that the abscisic acid and auxin signaling pathways were affected in the MsNF-YC4 overexpressing plants. Consistently, exogenous application of indoleacetic acid also enhanced root branching and drought tolerance of alfalfa seedlings. Further, MsNF-YC4 was found to activate the transcription of MsARF8 by yeast one-hybrid (Y1H) and dual-luciferase (LUC) reporter Assay. Silencing of MsARF8 by antisense oligonucleotide (as-ODN) method suppressed both root branching and drought tolerance of alfalfa seedlings. Collectively, we prove that an endogenous transcription factor MsNF-YC4 interacts with foreign protein QQS, and by activating MsARF8 to regulate alfalfa root branching and drought resilience. Our study also provides a regulatory pathway for drought tolerant alfalfa breeding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".