Transposable Element Populations Shed Light on the Evolutionary History of Wheat and the Complex Co‐Evolution of Autonomous and Non‐Autonomous Retrotransposons
Bibliographic record
Abstract
Wheat has one of the largest and most repetitive genomes among major crop plants, containing over 85% transposable elements (TEs). TEs populate genomes much in the way that individuals populate ecosystems, diversifying into different lineages, sub-families and sub-populations. The recent availability of high-quality, chromosome-scale genome sequences from ten wheat lines enables a detailed analysis how TEs evolved in allohexaploid wheat, its diploids progenitors, and in various chromosomal haplotype segments. LTR retrotransposon families evolved into distinct sub-populations and sub-families that were active in waves lasting several hundred thousand years. Furthermore, It is shown that different retrotransposon sub-families were active in the three wheat sub-genomes, making them useful markers to study and date polyploidization events and chromosomal rearrangements. Additionally, haplotype-specific TE sub-families are used to characterize chromosomal introgressions in different wheat lines. Additionally, populations of non-autonomous TEs co-evolved over millions of years with their autonomous partners, leading to complex systems with multiple types of autonomous, semi-autonomous and non-autonomous elements. Phylogenetic and TE population analyses revealed the relationships between non-autonomous elements and their mobilizing autonomous partners. TE population analysis provided insights into genome evolution of allohexaploid wheat and genetic diversity of species, and may have implication for future crop breeding.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".