Molecular regulatory mechanisms underlying the adaptability of polyploid plants
Bibliographic record
Abstract
ABSTRACT Polyploidization influences the genetic composition and gene expression of an organism. This multi‐level genetic change allows the formation of new regulatory pathways leading to increased adaptability. Although both forms of polyploidization provide advantages, autopolyploids were long thought to have little impact on plant divergence compared to allopolyploids due to their formation through genome duplication only, rather than in combination with hybridization. Recent advances have begun to clarify the molecular regulatory mechanisms such as microRNAs, alternative splicing, RNA‐binding proteins, histone modifications, chromatin remodelling, DNA methylation, and N 6 ‐methyladenosine (m6A) RNA methylation underlying the evolutionary success of polyploids. Such research is expanding our understanding of the evolutionary adaptability of polyploids and the regulatory pathways that allow adaptive plasticity in a variety of plant species. Herein we review the roles of individual molecular regulatory mechanisms and their potential synergistic pathways underlying plant evolution and adaptation. Notably, increasing interest in m6A methylation has provided a new component in potential mechanistic coordination that is still predominantly unexplored. Future research should attempt to identify and functionally characterize the evolutionary impact of both individual and synergistic pathways in polyploid plant species.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".