Mapping Quantitative Trait Loci for Carotenoid Concentration in Three F <sub>2</sub> Populations of Chickpea
Bibliographic record
Abstract
Core Ideas Quantitative trait locus (QTL) analyses for carotenoids in chickpea were completed for three F 2 populations. A moderate number of QTLs and candidate genes associated with carotenoid concentration in chickpea seeds were identified. Green cotyledon color is positively associated with provitamin A carotenoids. Three F 2 populations derived from crosses between cultivars with green and yellow cotyledon colors were used to identify quantitative trait loci (QTLs) associated with carotenoid components in chickpea ( Cicer arietinum L.) seeds developed by the Crop Development Centre (CDC). Carotenoids including violaxanthin, lutein, zeaxanthin, β‐cryptoxanthin, and β‐carotene were assessed in the F 2:3 seeds via high‐performance liquid chromatography (HPLC). In the ‘CDC Jade’ × ‘CDC Frontier’ population, 1068 bin markers derived from the 50K Axiom CicerSNP array were mapped onto eight linkage groups (LGs). Eight QTLs, including two each for β‐carotene and zeaxanthin and one each for total carotenoids, β‐cryptoxanthin, β‐carotene, and violaxanthin were identified in this population. In the ‘CDC Cory’ × ‘CDC Jade’ population, 694 bin markers were mapped onto eight LGs and one partial LG. Quantitative trait loci for β‐cryptoxanthin, β‐carotene, violaxanthin, lutein, and total carotenoids were identified on LG8. A map with eight LGs was developed from 581 bin markers in the third population derived from the ‘ICC4475’ × ‘CDC Jade’ cross. One QTL for β‐carotene and four QTLs, one each for β‐cryptoxanthin, β‐carotene, lutein, and total carotenoids, were identified in this population. The highest phenotypic variation explained by the QTLs was for β‐carotene, which ranged from 58 to 70% in all three populations. A major gene for cotyledon color was mapped on LG8 in each population. A significant positive correlation between cotyledon color and carotenoid concentration was observed. Potential candidate genes associated with carotenoid components were obtained and their locations on the chickpea genome are presented.
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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 | 0.000 |
| 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) | 0.001 | 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".