Repetitive DNA and Plant Domestication: Variation in Copy Number and Proximity to Genes of LTR-Retrotransposons among Wild and Cultivated Sunflower (<i>Helianthus annuus</i>) Genotypes
Bibliographic record
Abstract
The sunflower (Helianthus annuus) genome contains a very large proportion of transposable elements, especially long terminal repeat retrotransposons. However, knowledge on the retrotransposon-related variability within this species is still limited. We used next-generation sequencing (NGS) technologies to perform a quantitative and qualitative survey of intraspecific variation of the retrotransposon fraction of the genome across 15 genotypes--7 wild accessions and 8 cultivars--of H. annuus. By mapping the Illumina reads of the 15 genotypes onto a library of sunflower long terminal repeat retrotransposons, we observed considerable variability in redundancy among genotypes, at both superfamily and family levels. In another analysis, we mapped Illumina paired reads to two sets of sequences, that is, long terminal repeat retrotransposons and protein-encoding sequences, and evaluated the extent of retrotransposon proximity to genes in the sunflower genome by counting the number of paired reads in which one read mapped to a retrotransposon and the other to a gene. Large variability among genotypes was also ascertained for retrotransposon proximity to genes. Both long terminal repeat retrotransposon redundancy and proximity to genes varied among retrotransposon families and also between cultivated and wild genotypes. Such differences are discussed in relation to the possible role of long terminal repeat retrotransposons in the domestication of sunflower.
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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 | 0.000 | 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".