Characterizing resistance to soybean cyst nematode in PI 494182, an early maturing soybean accession
Bibliographic record
Abstract
Abstract The soybean cyst nematode (SCN) ( Heterodera glycines Ichinohe) generates more damage to soybean [ Glycine max (L.) Merr.] than any other parasite in most soybean‐producing countries. The use of SCN‐resistant cultivars remains the most effective method to limit losses caused by SCN. The SCN‐resistant accession PI 88788 has been used almost exclusively to control SCN over the past decades, inducing a shift in nematode virulence to overcome the resistance. Furthermore, PI 88788 and other sources of resistance characterized to date belong to maturity groups (MGs) III and higher, making them less attractive to develop early maturing soybean varieties (MGs 0‐000). In this work, we performed a quantitative trait loci (QTL) analysis of the SCN‐resistant soybean accession PI 494182 (MG 0). A recombinant inbred lines (RILs) population (‘Costaud’ × PI 494182) segregating for SCN resistance was challenged with SCN ( H. glycines [HG] type 0) and genotyped via genotyping‐by‐sequencing (GBS) to produce a genetic map. Six resistance QTL were identified, including a potentially new resistance locus on chromosome 07. A subset of the RIL population was confronted to a HG type 2.5.7 SCN population and some of these exhibited resistance toward this type. Whole‐genome sequencing of PI 494182 and Costaud allowed us to determine the alleles and their copy number for three candidate genes: GmSNAP11 , GmSNAP18 ( Rhg1 ), and GmSHMT08 ( Rhg4 ). Finally, we determined that selecting for PI 494182 alleles at some SCN‐resistance QTL could entail linkage drag (decrease in protein concentration and 100‐seed weight, increase in oil concentration). This work provides useful markers for introgressing SCN resistance in early maturing soybean varieties.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".