Transposable Elements in Zea: Their Role in Genetic Diversity and Evolution
Bibliographic record
Abstract
Transposable elements (TEs) are significant contributors to genetic diversity and evolutionary processes in Zea mays (maize). These mobile genetic elements can move within the genome, inducing mutations, structural variations, and changes in gene expression, which collectively enhance genetic variability and adaptability. TEs are maintained in a delicate balance within the genome, as they can be both deleterious and beneficial. In maize, TEs have been shown to play crucial roles in genome evolution, including the generation of allelic diversity and the regulation of gene expression. The maize genome is particularly rich in TEs, with recent advancements in annotation methods revealing a higher abundance and diversity of TEs than previously recognized. Moreover, the interplay between TEs and epigenetic mechanisms, such as RNA N6-methyladenosine modification, further underscores their role in the adaptive evolution of maize. This study synthesizes current knowledge on the impact of TEs on the genetic diversity and evolutionary dynamics of maize, highlighting their dual role as both genomic parasites and symbionts. The findings underscore the importance of TEs in shaping the maize genome and their potential in driving adaptive responses to environmental challenges.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".