The sunflower (<i>Helianthus annuus</i> L.) genome reflects a recent history of biased accumulation of transposable elements
Bibliographic record
Abstract
Aside from polyploidy, transposable elements are the major drivers of genome size increases in plants. Thus, understanding the diversity and evolutionary dynamics of transposable elements in sunflower (Helianthus annuus L.), especially given its large genome size (∼3.5 Gb) and the well-documented cases of amplification of certain transposons within the genus, is of considerable importance for understanding the evolutionary history of this emerging model species. By analyzing approximately 25% of the sunflower genome from random sequence reads and assembled bacterial artificial chromosome (BAC) clones, we show that it is composed of over 81% transposable elements, 77% of which are long terminal repeat (LTR) retrotransposons. Moreover, the LTR retrotransposon fraction in BAC clones harboring genes is disproportionately composed of chromodomain-containing Gypsy LTR retrotransposons ('chromoviruses'), and the majority of the intact chromoviruses contain tandem chromodomain duplications. We show that there is a bias in the efficacy of homologous recombination in removing LTR retrotransposon DNA, thereby providing insight into the mechanisms associated with transposable element (TE) composition in the sunflower genome. We also show that the vast majority of observed LTR retrotransposon insertions have likely occurred since the origin of this species, providing further evidence that biased LTR retrotransposon activity has played a major role in shaping the chromatin and DNA landscape of the sunflower genome. Although our findings on LTR retrotransposon age and structure could be influenced by the selection of the BAC clones analyzed, a global analysis of random sequence reads indicates that the evolutionary patterns described herein apply to the sunflower genome as a whole.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".