Association Mapping of Endosperm Colour in Durum Wheat (Triticum turgidum L. var. durum).
Bibliographic record
Abstract
Association mapping (AM), based on linkage disequilibrium, is a complementary strategy to traditional quantitative trait loci (QTL) mapping for describing associations between genotypes and phenotypes in crop plants. Yellow endosperm colour, an important quality trait in durum wheat (Triticum turgidum L. var. durum), was studied to determine the potential of AM to (1) identify previously reported QTL using a genome wide scan and (2) to determine allelic association of the phytoene synthase 1 (Psy1) gene using a candidate gene analysis. At present, a number of QTL for endosperm colour have been identified, and phytoene synthase, the initial enzyme of the carotenoid biosynthetic pathway, has been associated with QTL on the group 7 chromosomes which are considered to play a significant role in expression of yellow pigment concentration. CIE 1976 b*, a light reflectance measurement, and water-saturated butanol extracted pigments were assessed on a collection of 93 elite accessions from a variety of geographic origins, and genotyped with 245 markers. Population structure was assessed using genetic distance and Bayesian model based approaches, identifying five sub-populations consistent with breeding origin and pedigree. Association analysis identified significant associations with yellow endosperm colour on all chromosomes, including several previously identified QTL as well as new regions for genomic dissection. Pairwise LD mapping of Psy1-B1 and Psy1-A1 located the genes to chromosomes 7B and 7A respectively, to regions which have previously been identified for yellow pigment concentration QTL. The results of this study indicate that AM can be used to complement traditional QTL mapping techniques, and identify novel QTL for further study.
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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".