Identification of Quantitative Trait Loci Associated with Seed Protein Concentration in a Pea Recombinant Inbred Line Population
Bibliographic record
Abstract
This research aimed to identify quantitative trait loci (QTLs) associated with seed protein concentration in a recombinant inbred line (RIL) population of pea and aimed to validate the identified QTLs using chromosome segment-introgressed lines developed by recurrent backcrossing. PR-25, an RIL population consisting of 108 F7 bulked lines derived from a cross between CDC Amarillo (yellow cotyledon) and CDC Limerick (green cotyledon), was used in this research. The RIL population was genotyped using an Axiom 90K SNP array. A total of 10,553 polymorphic markers were used for linkage map construction, after filtering for segregation distortion and missing values. The linkage map represents 901 unique loci on 11 linkage groups which covered a map distance of 855.3 Centimorgans. Protein concentration was assessed using near-infrared (NIR) spectroscopy of seeds harvested from field trials in seven station-years in Saskatchewan, Canada, during the 2019-2021 field seasons. Three QTLs located on chromosomes 2, 3 and 5 were identified to be associated with seed protein concentration. These QTLs explained 22%, 11% and 17% of the variation for protein concentration, respectively. The identified QTLs were validated by introgression lines, developed by marker-assisted selection of backcross lines for introgression of corresponding chromosome segments (~1/4 chromosome) harboring the QTL regions. Introgression line PR-28-7, not carrying any protein-related QTLs identified in this study, was 4.7% lower in protein concentration than CDC Amarillo, the lower protein parent of PR-25 which carried one identified protein-related QTL. The SNP markers located at the peak of the three identified QTLs will be converted into breeder-friendly KASP assays, which will be used for the selection of high-protein lines from segregating populations.
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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".