Association Analysis of Resistance to Soybean Mosaic Virus and Variation in Resistance Allelic Excavation
Bibliographic record
Abstract
Soybean Mosaic Virus (SMV) is one of the most important soybean diseases in the world, and it seriously affects soybean yield and quality. In this paper, 405 SSR molecular markers were used in genome-wide scan to analysis 327 soybean varieties in the North of China. The purpose was to search the genetic loci and excellent resistance genes related to SMV1 and SMV3, and to reveal the differences between the genetic models of varieties. The results confirmed that the genetic differences among the tested varieties were large. Through the association analysis of the population genome-wide association (GWA) and linkage group association (LGA), 14 highly significant sites related to SN1 and SN3 were found. There are three sites related to SN1 (Sat-297, sat-296, sat-154) which are coincident with or adjacent to the resistance sites found by predecessors; while there are two at SN3 (Sat-154 and sat-726) which are coincident with previous studies, and sat-154 is a resistance site shared by SN1 and SN3. 7 genes related to resistance were obtained, of which Glyma13g25420 and Glycma13g25440, Glyma14g08700 and Glyma14g08710 has resistance genes on the NBS-LRR domain; Glyma14g08900, Glyma14g08910, and Glyma14g08920 have PLP2 (Patation-like Protein) resistance genes. This study provides an important reference for SMV resistance research and technical support for soybean resistance breeding.
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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".