Genome survey sequencing provides clues into glucosinolate biosynthesis and flowering pathway evolution in allotetrapolyploid Brassica juncea
Bibliographic record
Abstract
BACKGROUND: Brassica juncea is an economically important vegetable crop in China, oil crop in India, condiment crop in Europe and selected for canola quality recently in Canada and Australia. B. juncea (2n = 36, AABB) is an allotetraploid derived from interspecific hybridization between B. rapa (2n = 20, AA) and B. nigra (2n = 16, BB), followed by spontaneous chromosome doubling. RESULTS: Comparative genome analysis by genome survey sequence (GSS) of allopolyploid B. juncea with B. rapa was carried out based on high-throughput sequencing approaches. Over 28.35 Gb of GSS data were used for comparative analysis of B. juncea and B. rapa, producing 45.93% reads mapping to the B. rapa genome with a high ratio of single-end reads. Mapping data suggested more structure variation (SV) in the B. juncea genome than in B. rapa. We detected 2,921,310 single nucleotide polymorphisms (SNPs) with high heterozygosity and 113,368 SVs, including 1-3 bp Indels, between B. juncea and B. rapa. Non-synonymous polymorphisms in glucosinolate biosynthesis genes may account for differences in glucosinolate biosynthesis and glucosinolate components between B. juncea and B. rapa. Furthermore, we identified distinctive vernalization-dependent and photoperiod-dependent flowering pathways coexisting in allopolyploid B. juncea, suggesting contribution of these pathways to adaptation for survival during polyploidization. CONCLUSIONS: Taken together, we proposed that polyploidization has allowed for accelerated evolution of the glucosinolate biosynthesis and flowering pathways in B. juncea that likely permit the phenotypic variation observed in the crop.
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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".