Genome-Wide Association Study Identified One Major Quantitative Trait Locus Associated with Resistance to <i>Fusarium proliferatum</i> in Soybean ( <i>Glycine max</i> )
Why this work is in the frame
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Bibliographic record
Abstract
Fusarium root rot is a yield-limiting disease of soybean ( Glycine max L.) in the United States and Canada (Ontario). Among the species of Fusarium causing root rot, F. proliferatum is a virulent pathogen. Sources of resistance to F. proliferatum have been identified; however, additional screening of soybean accessions is necessary to identify quantitative trait loci (QTLs) associated with resistance to F. proliferatum. The objective of this study was to evaluate 268 soybean accessions obtained from the USDA Germplasm Collection belonging to maturity groups 000 to IX for resistance to a single isolate of F. proliferatum under greenhouse conditions. Additionally, the study sought to identify QTLs, single-nucleotide polymorphism (SNP) markers, and candidate genes associated with the F. proliferatum resistance through a genome-wide association study (GWAS). The experiment was conducted in a completely randomized design using a layer inoculation method and repeated once. The root rot severity was assessed 21 days postinoculation and expressed as the relative treatment effect (RTE). Fifty-two accessions had a significantly lower RTE compared with the susceptible variety ‘Williams 82’ (ATS = 37.03; df = 7.30; P = 2.47 × 10⁻⁵⁴). GWAS analysis using 36,071 SNP markers identified one major QTL on chromosome 11 that explained 30.95% of the phenotype variance, three strongly associated SNP markers, and three candidate genes that could be involved in resistance to F. proliferatum. This study identified soybean accessions with resistance to F. proliferatum, along with novel SNP markers, which could significantly enhance breeding programs aimed at developing cultivars with resistance to Fusarium root rot. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
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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 | 0.001 |
| 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 it