Sequence-Based Analysis of Structural Organization and Composition of the Cultivated Sunflower (Helianthus annuus L.) Genome
Bibliographic record
Abstract
Sunflower is an important oilseed crop, as well as a model system for evolutionary studies, but its 3.6 gigabase genome has proven difficult to assemble, in part because of the high repeat content of its genome. Here we report on the sequencing, assembly, and analyses of 96 randomly chosen BACs from sunflower to provide additional information on the repeat content of the sunflower genome, assess how repetitive elements in the sunflower genome are organized relative to genes, and compare the genomic distribution of these repeats to that found in other food crops and model species. We also examine the expression of transposable element-related transcripts in EST databases for sunflower to determine the representation of repeats in the transcriptome and to measure their transcriptional activity. Our data confirm previous reports in suggesting that the sunflower genome is >78% repetitive. Sunflower repeats share very little similarity to other plant repeats such as those of Arabidopsis, rice, maize and wheat; overall 28% of repeats are "novel" to sunflower. The repetitive sequences appear to be randomly distributed within the sequenced BACs. Assuming the 96 BACs are representative of the genome as a whole, then approximately 5.2% of the sunflower genome comprises non TE-related genic sequence, with an average gene density of 18kbp/gene. Expression levels of these transposable elements indicate tissue specificity and differential expression in vegetative and reproductive tissues, suggesting that expressed TEs might contribute to sunflower development. The assembled BACs will also be useful for assessing the quality of several different draft assemblies of the sunflower genome and for annotating the reference sequence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".