The haplotype-resolved telomere-to-telomere genome and OMICS analyses reveal genetic responses to tapping in rubber tree
Bibliographic record
Abstract
Rubber tree (Hevea brasiliensis) is the primary source of natural rubber and economically important. We present the haplotype-resolved, telomere-to-telomere, gap-free genome assembly of the cultivar CATAS 7-33–97, with both haplotypes containing complete telomeric and centromeric regions. Structural variations, including a 32.71 Mb inversion on chromosome 8, are identified. The fully assembled 36 chromosomes enable comprehensive identification of rubber biosynthesis genes and their allele-specific expression. By integrating transcriptomic and metabolomic data, we reconstruct the rubber biosynthesis pathway and confirm the mevalonate (MVA) pathway as the major carbon source for rapid latex regeneration during tapping. Jasmonic acid (JA) plays a key role in promoting rubber yield by enhancing biosynthetic activity in response to mechanical wounding. We propose a model where JA-induced myelocytomatosis proteins 2 activate mevalonate kinase 1 expression, boosting MVA synthesis and rubber production. These findings provide insights into rubber tree genomics and its molecular response to tapping. Authors report the assembly of the haplotype-resolved and telomere-to-telomere genome of a key rubber tree variety and uncover major structural variations. It is also revealed that jasmonic acid enhances rubber yield by activating the mevalonate pathway during tapping.
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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".