Multifaceted roles of transcription factors during plant embryogenesis
Bibliographic record
Abstract
Transcription factors (TFs) are diverse groups of regulatory proteins. Through their specific binding domains, TFs bind to their target genes and regulate their expression, therefore TFs play important roles in various growth and developmental processes. Plant embryogenesis is a highly regulated and intricate process during which embryos arise from various sources and undergo development; it can be further divided into zygotic embryogenesis (ZE) and somatic embryogenesis (SE). TFs play a crucial role in the process of plant embryogenesis with a number of them acting as master regulators in both ZE and SE. In this review, we focus on the master TFs involved in embryogenesis such as BABY BOOM (BBM) from the APETALA2 / Ethylene-Responsive Factor (AP2/ERF) family, WUSCHEL and WUSCHEL-related homeobox (WOX) from the homeobox family, LEAFY COTYLEDON 2 (LEC2) from the B3 family, AGAMOUS-Like 15 (AGL15) from the MADS family and LEAFY COTYLEDON 1 (LEC1) from the Nuclear Factor Y (NF-Y) family. We aim to present the recent progress pertaining to the diverse roles these master TFs play in both ZE and SE in Arabidopsis, as well as other plant species including crops. We also discuss future perspectives in this context.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".