Unraveling the role of MADS transcription factor complexes in apple tree dormancy
Bibliographic record
Abstract
A group of MADS transcription factors (TFs) are believed to control temperature-mediated bud dormancy. These TFs, called DORMANCY-ASSOCIATED MADS-BOX (DAM), are encoded by genes similar to SHORT VEGETATIVE PHASE (SVP) from Arabidopsis. MADS proteins form transcriptional complexes whose combinatory composition defines their molecular function. However, how MADS multimeric complexes control the dormancy cycle in trees is unclear. Apple MdDAM and other dormancy-related MADS proteins form complexes with MdSVPa, which is essential for the ability of transcriptional complexes to bind to DNA. Sequential DNA-affinity purification sequencing (seq-DAP-seq) was performed to identify the genome-wide binding sites of apple MADS TF complexes. Target genes associated with the binding sites were identified by combining seq-DAP-seq data with transcriptomics datasets obtained using a glucocorticoid receptor fusion system, and RNA-seq data related to apple dormancy. We describe a gene regulatory network (GRN) formed by MdSVPa-containing complexes, which regulate the dormancy cycle in response to environmental cues and hormonal signaling pathways. Additionally, novel molecular evidence regarding the evolutionary functional segregation between DAM and SVP proteins in the Rosaceae is presented. MdSVPa sequentially forms complexes with the MADS TFs that predominate at each dormancy phase, altering its DNA-binding specificity and, therefore, the transcriptional regulation of its target genes.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".