Genome-wide association study for agronomic and yield-related traits in spring wheat (Triticum aestivum L.) germplasm
Bibliographic record
Abstract
BACKGROUND: Common wheat (Triticum aestivum L.) is one of the most widely grown and consumed cereal crops, but its complicated genome makes it difficult to study how genes affect important agronomic and yield-related traits. Genome-wide association study (GWAS) is a useful method for finding specific loci that control complex agronomic and yield-related traits. RESULTS: ) for all traits ranged from 0.50 to 0.71 (Env1; 2021-2022) and 0.53 to 0.81 (Env2; 2022-2023). Using two environments' phenotypic data, and high-throughput single-nucleotide polymorphisms (SNPs) genotypic data of 20,996 markers, we discovered 114 grain-yield-related quantitative trait loci (QTLs) and 300 associated SNP markers. Eighty-five of the identified markers were stable, consistently detected across environments (Env1 and Env2) and combined environment (CE) data, and showed a significant association with 32 different QTLs. The trait with the most associated QTLs (28) was the number of fertile tillers (NFT), with 70 markers. This was followed by 20 QTLs for each, spike length (SL) and spikelet number per spike (SPS), with 69 and 82 SNPs, respectively. Conversely, six SNPs that exhibited association with multiple traits were also identified. Twenty-nine of the total 114 identified QTLs were located in chromosomal positions where at least one marker-trait association had been previously identified. CONCLUSION: This study has found new SNPs, and useful QTLs that may help us to understand the biological processes behind each studied trait. Further validation in various genetic backgrounds and environments is necessary to confirm the potential utility of the significant alleles found in this study for breeding wheat varieties with improved agronomic and yield-related traits.
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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".