Differential expression of TLP, ERF1, and R2R3MYB in annual Medicago species under salinity conditions
Bibliographic record
Abstract
The present study was conducted to evaluate the responses of three annual Medicago species (M. truncatula, M. laciniata, and M. polymorpha) to salinity. We analyzed publicly available microarray data in NCBI pertaining to salinity-response genes in M. truncatula. Our data search identified Tubby C2 (TLP) and ethylene responsive transcription factor 1 (ERF1) as genes that potentially respond to salinity. We evaluated morpho-physiological traits and the expression of the genes in three Medicago species that had been maintained under control and saline conditions. The analysis of morpho-physiological traits showed that M. polymorpha and M. laciniata were more tolerant to salinity than M. truncatula, as they had lower reductions in biomass and dry root weight and lower increases in anthocyanin concentration. The saline conditions caused a significant increase (P < 0.01) in the expression of TLP in all Medicago species, but caused a significant decrease in the expression of ERF1. Considerable variation in anthocyanin concentrations was found among the three Medicago species. To investigate the cause of this variation, we examined the expression of R2R3MYB, a gene involved in the biosynthesis of anthocyanins. Our analysis showed that saline conditions induced high over-expression of R2R3MYB in all three Medicago spp. The high efficiency of the primer pairs used in qRT-PCR enabled us to compare the expression levels of each gene in the three species. We concluded that the more salt tolerant species showed higher expression of TLP and R2R3MYB under both control and salinity conditions.
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 | 0.000 |
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".