Genomic investigation of oat quality
Bibliographic record
Abstract
Both structural genomic and functional genomic approaches increase our understanding of the genetics of quality traits in oats, thereby providing knowledge and tools that accelerate breeding for oat improvement. Initially, we employed the structural genomic approaches of recombination mapping and quantitative trait locus (QTL) analysis to investigate the genetics of a number of quality traits in a Terra x Marion (TM) recombinant inbred population (DeKoeyer et al. 2004). Bi-plot analyses gave complementary insight. These identified genomic regions that play a major role in controlling oil, beta-glucan, and protein content. Comparative marker and QTL mapping with other oat populations increased our understanding of the number and organization of the genes involved and further validated the TM QTLs. Extension to additional elite populations contrasting for these traits helped to complete the analysis. Markers flanking the TM oil and beta-glucan QTLs were converted to sequence characterized amplified region (SCAR) markers (Orr and Molnar 2004). These polymerase chain reaction (PCR)-based markers are robust, rapid, and cost efficient and, therefore, suitable for markerassisted breeding. Recently, functional genomic approaches have been employed to isolate candidate genes in the biochemical pathways for oil and protein content, to study expression level polymorphisms, and to associate both of these with QTLs in mapping populations (Lybaert 2004). These approaches promise to advance our understanding of the involvement of key enzymes in oil and protein biosynthesis and their regulators. DeKoeyer, D., et al. 2004, Theoretical and Applied Genetics 108:(in press); Lybaert, A. 2004, PhD Thesis (in preparation), McGill University; Orr, W. & Molnar, S.J. 2004, (submitted).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".