Genome-Wide Association Studies for Grain Micronutrient Concentration in Spring Wheat (Triticum aestivum L.)
Bibliographic record
Abstract
The micronutrient content is a major aspect of food quality and has been under threat after a gain in production post-green revolution. Calcium (Ca) and magnesium (Mg) are the micronutrients that are cofactors for many enzymes and play a critical role in human physiology. Deciphering the accumulation of these micronutrients in wheat and the identification of QTLs associated with these elements is very significant for cutting the risk of malnutrition in humans. Here, a genome-wide association study (GWAS) of 105 lines from an elite panel of the Wheat Association Mapping Initiative (WAMI) was performed for the two cropping seasons of 2021-2022 and 2022-2023 for the grain calcium and magnesium content (GCaC and GMgC). Notably, two marker trait associations (MTAs), wsnp_Ex_c2718_5038582, Kukri_c11327_977, and RAC875_c9984_1003, were found for the GCaC, and similarly three MTAs (Tdurum_contig28802_213, wsnp_Ex_c34597_42879693, and RFL_Contig6053_3082) were identified for the GMgC in both the cropping seasons, proving their utility and non-redundancy. An MTA associated with a SNP marker (wsnp_Ex_c34597_42879718) was also identified in the two seasons and was significant for both the GCaC and GMgC. Candidate gene analysis showed the association of these MTAs with some of the very vital genes associated with activities where Ca and Mg play significant roles. Our study widens the insights on the genetic control of Ca and Mg accumulation in wheat and the utilization of this information for future breeding programs, wherein wheat improvement with enhanced Ca and Mg may be designed and conducted.
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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".