Genome-Wide Association Mapping for Agronomic and Seed Quality Traits of Field Pea (Pisum sativum L.)
Why this work is in the frame
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Bibliographic record
Abstract
Genome-wide association study (GWAS) was completed to identify loci associated with agronomic (days to flowering, days to maturity, plant height, seed yield and seed weight), seed morphology (shape and dimpling) and seed quality (protein, starch and fibre concentrations) traits of field pea (Pisum sativum L.). A collection of 135 pea accessions from 23 different breeding programs in Africa (Ethiopia), Asia (India), Australia, Europe (Belarus, Czech Republic, Denmark, France, Lithuania, Netherlands, Russia, Sweden, Ukraine and United Kingdom) and North America (Canada and USA), was used for the GWAS. The accessions were genotyped using genotyping-by-sequencing (GBS). After filtering for a minimum read depth of five, and minor allele frequency of 0.05, 16,877 high quality SNPs were selected to determine marker-trait associations (MTA). The LD decay (LD1/2max, 90) across the chromosomes varied from 20 to 80 kb. Population structure analysis grouped the accessions into nine subpopulations. The accessions were evaluated in multi-year, multi-location trials in Olomouc (Czech Republic), Fargo, North Dakota (USA), and Rosthern and Saskatoon, Saskatchewan (Canada) from 2013 to 2017. Each trait was phenotyped in at least five location-years. MTAs that were consistent across multiple trials were identified. Chr5LG3_566189651 and Chr5LG3_572899434 for plant height, Chr2LG1_409403647 for lodging resistance, Chr1LG6_57305683 and Chr1LG6_366513463 for grain yield, Chr1LG6_176606388, Chr2LG1_457185, Chr3LG5_234519042 and Chr7LG7_8229439 for seed starch concentration, and Chr3LG5_194530376 for seed protein concentration were identified from different locations and years. This research identified SNP markers associated with important traits in pea that are potential for marker-assisted selection towards rapid cultivar improvement.
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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 | 0.001 | 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 it