Combining quantitative trait locus and co-expression analysis allowed identification of new candidates for oil accumulation in rapeseed
Bibliographic record
Abstract
In crops there are quantitative trait loci (QTLs) in which some of the causal quantitative trait genes (QTGs) have not been functionally characterized even in the model plant Arabidopsis. We propose an approach to delineate QTGs in rapeseed by coordinating expression of genes located within QTLs and known orthologs related to traits from Arabidopsis. Using this method in developing siliques 15 d after pollination in 71 lines of rapeseed, we established an acyl-lipid metabolism co-expression network with 21 modules composed of 270 known acyl-lipid genes and 3503 new genes. The core module harbored 76 known genes involved in fatty acid and triacylglycerol biosynthesis and 671 new genes involved in sucrose transport, carbon metabolism, amino acid metabolism, seed storage protein processes, seed maturation, and phytohormone metabolism. Moreover, the core module closely associated with the modules of photosynthesis and carbon metabolism. From the co-expression network, we selected 12 hub genes to identify their putative Arabidopsis orthologs. These putative orthologs were functionally analysed using Arabidopsis knockout and overexpression lines. Four knockout mutants exhibited lower seed oil content, while the seed oil content in 10 overexpression lines was significantly increased. Therefore, combining gene co-expression network analysis and QTL mapping, this study provides new insights into the detection of QTGs and into acyl-lipid metabolism in rapeseed.
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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 | 0.000 |
| 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".