Genome‐wide association study to identify single nucleotide polymorphisms associated with Fe, Zn, and Se concentration in field pea
Bibliographic record
Abstract
Abstract Micronutrients are an important component of crop quality. With an objective of identification of trait‐associated single nucleotide polymorphism (SNP) markers, a genome‐wide association study (GWAS) panel of 135 diverse pea ( Pisum sativum L.) accessions previously genotyped was assessed for Fe, Zn, and Se concentrations from five location–years (2013 Saskatoon, 2014 Fargo, 2015 Saskatoon, 2016 Saskatoon, and 2016 Rosthern) using atomic absorption spectroscopy (AAS). Accessions differed significantly for Fe and Zn in all location–years but not for Se ( P ≤ .05). Year and location effects were significant for all three micronutrients. Mean concentration in the five location–years combined analysis was 50.70, 29.42, and 0.99, and the concentration (μg g −1 ) ranged from 29.22 to 90.53, 12.83 to 51.47, and 0.22 to 7.82 in the ground whole pea seeds for Fe, Zn, and Se, respectively. In general, pea grain yield was negatively correlated with Fe, Zn, and Se concentration. Of the 16,877 SNP markers used for association analysis, five each were identified for association with Fe and Zn concentrations. In silico validation identified that one Fe‐associated and four Zn‐associated markers were within the genomic regions of major quantitative trait loci (QTL) previously reported for these traits. Fe‐associated marker Chr5LG3_204123886 and Zn‐associated markers Chr5LG3_1921113554, Chr5LG3_197808492, and Sc4026_15361 identified in this study and validated using the previous GWAS and biparental mapping studies can be used for reliable marker‐assisted selection (MAS) in pea breeding programs.
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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 | 0.001 |
| 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) | 0.000 | 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".