Tung Tree ( <i>Vernicia Fordii</i> ) Genome Provides A Resource for Understanding Genome Evolution and Improved Oil Production
Bibliographic record
Abstract
Tung tree (Vernicia fordii) is an economically important woody oil plant that produces tung oil rich in eleostearic acid. Here, we report a high-quality chromosome-scale genome sequence of tung tree. The genome sequence was assembled by combining Illumina short reads, Pacific Biosciences single-molecule real-time long reads, and Hi-C sequencing data. The size of tung tree genome is 1.12 Gb, with 28,422 predicted genes and over 73% repeat sequences. The V. fordii underwent an ancient genome triplication event shared by core eudicots but no further whole-genome duplication in the subsequent ca. 34.55 million years of evolutionary history of the tung tree lineage. Insertion time analysis revealed that repeat-driven genome expansion might have arisen as a result of long-standing long terminal repeat retrotransposon bursts and lack of efficient DNA deletion mechanisms. The genome harbors 88 resistance genes encoding nucleotide-binding sites; 17 of these genes may be involved in early-infection stage of Fusarium wilt resistance. Further, 651 oil-related genes were identified, 88 of which are predicted to be directly involved in tung oil biosynthesis. Relatively few phosphoenolpyruvate carboxykinase genes, and synergistic effects between transcription factors and oil biosynthesis-related genes might contribute to the high oil content of tung seed. The tung tree genome constitutes a valuable resource for understanding genome evolution, as well as for molecular breeding and genetic improvements for oil production.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".