Mapping tightly linked genes controlling potyvirus infection at the <i>Rsv1</i> and <i>Rpv1</i> region in soybean
Bibliographic record
Abstract
Soybean mosaic virus (SMV) and peanut mottle virus (PMV) are two potyviruses that cause yield losses and reduce seed quality in infested soybean (Glycine max (L.) Merr.) fields throughout the world. Rsv1 and Rpv1 are genes that provide soybean with resistance to SMV and PMV, respectively. Isolating and characterizing Rsv1 and Rpv1 are instrumental in providing insight into the molecular mechanism of potyvirus recognition in soybean. A population of 1056 F2 individuals from a cross between SMV- and PMV-resistant line PI 96983 (Rsv1 and Rpv1) and the susceptible cultivar 'Lee 68' (rsv1 and rpv1) was used in this study. Disease reaction and molecular-marker data were collected to determine the linkage relationship between Rsv1, Rpv1, and markers that target candidate disease-resistance genes. F2 lines showing a recombination between two of three Rsv1-flanking microsatellite markers were selected for fine mapping. Over 20 RFLP, RAPD, and microsatellite markers were used to map 38 loci at high-resolution to a 6.8-cM region around Rsv1 and Rpv1. This study demonstrates that Rsv1 and Rpv1 are tightly linked at a distance of 1.1 cM. In addition, resistance-gene candidate sequences were mapped to positions flanking and cosegregating with these resistance loci. Based on comparisons of genetic markers and disease reactions, it appears likely that several tightly linked genes are conditioning a resistance response to SMV. We discuss the specifics of these findings and investigate the utility of two disease resistance related probes for the screening of SMV or PMV resistance in soybean.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".